diff --git a/.gitmodules b/.gitmodules index 91a432db..39273b06 100644 --- a/.gitmodules +++ b/.gitmodules @@ -1,3 +1,7 @@ [submodule "docs/_static/docson"] path = docs/_static/docson url = https://github.com/OpenDataServices/docson +[submodule "flatten-tool"] + path = flatten-tool + url = https://github.com/OpenDataServices/flatten-tool/ + branch = sheet-name-length diff --git a/developer_docs.md b/developer_docs.md index 0da48a5c..6a686bd6 100644 --- a/developer_docs.md +++ b/developer_docs.md @@ -17,6 +17,7 @@ This section contains the following how-to guides: * [Deploy changes](#deploy-changes) * [Release a new version](#release-a-new-version) * [Update requirements](#update-requirements) +* [Add an RDLS metadata example](#add-an-rdls-metadata-example) ### Propose changes @@ -47,7 +48,7 @@ cd rdl-standard Subsequent instructions assume that your current working directory is `rdl-standard`, unless otherwise stated. -#### Install submodules +#### Update submodules ```bash git submodule init @@ -106,6 +107,12 @@ pip install --upgrade pip setuptools pip install -r requirements.txt ``` +Install Flatten Tool: + +```bash +pip install ./flatten-tool +``` + ### Resolve check failures #### mdformat @@ -202,6 +209,25 @@ To deploy the `dev` branch to the live documentation site, [create a pull reques ``` 1. Commit your changes. + +## Add an RDLS metadata example + +1. Author your example RDLS metadata in JSON format. You can use either a text editor or the [RDLS spreadsheet template](https://github.com/GFDRR/rdls-spreadsheet-template/) and [Flatten Tool](https://flatten-tool.readthedocs.io/en/latest/). Your example RDLS metadata must be wrapped in an outer `datasets` array, e.g. + +```json +{ + "datasets": [ + { + "id": "1", + "title": "My example RDLS metadata" + } + ] +} +``` +1. Save your example JSON file to `examples/{component}/{title}/example.json` where `{component}` is the risk data component the example relates to (hazard, exposure, loss or vulnerability) and `{title}` is the title of the example. +1. Run `./manage.py pre-commit` to create a CSV version of the example. +1. Add Sphinx directives to the Markdown files in `docs` to render your example in the built documentation. + ## Style guides ### Changelog style guide @@ -258,7 +284,8 @@ Feature branches branch off the `dev` branch, with work merged into the `dev` br - `.tx/`: Transifex configuration (not yet implemented) - `img/`: Images used in the documentation - `locale/`: Translations of the English documentation (not yet implemented) -- `schema/`: schema-related files +- `examples`: Example JSON files, CSV files and figures +- `schema/`: schema- and codelist-related files - `specs/`: TBD - `SteeringCommittee/`: Minutes of steering committee meetings diff --git a/docs/_static/extra.css b/docs/_static/extra.css index 31856b06..d8ae737a 100644 --- a/docs/_static/extra.css +++ b/docs/_static/extra.css @@ -71,4 +71,7 @@ margin-right: 20px; svg[id^="mermaid-"] { width: 100%; max-width: 80em; -} \ No newline at end of file +} +.wy-table-responsive table th { + white-space: pre; +} diff --git a/docs/_static/json-example-format.js b/docs/_static/json-example-format.js new file mode 100644 index 00000000..25fe3a52 --- /dev/null +++ b/docs/_static/json-example-format.js @@ -0,0 +1,36 @@ + $( document ).ready(function() { + $(".expandjson").each(function(){ + classList = $(this).attr("class").split(/\s+/); + expand = [] + $.each(classList, function(index, item) { + if (item.indexOf('expand') === 0) { + expand.push(item.replace('expand-','')) + } + if (item.indexOf('file') === 0) { + filename = item + } + }); + jsontext = $(this).text().trim() + json = JSON.parse(jsontext) + if(json.length) { + json = json[0] + } + $(this).html(renderjson.set_show_to_level(1).set_max_string_length(100).set_default_open(expand)(json)) + if($(this).siblings(".selection-container").length === 0) { // NEED TO FIX THE CODE HERE. MOVE THINGS INTO THE PARENT CLASS CORRECTLY! + id = Math.floor(5 * (Math.random() % 1)); + $(this).wrap("
") + $(this).parent().prepend( + $("") + .change(function(){ + $(this).siblings(".expandjson").hide(); + $(this).siblings("."+ $(this).val()).show(); + })) + $(this).siblings("select").append($("").attr("value",filename).text(filename.replace("file-",""))) + } else { + container = $(this).siblings(".selection-container") + $(this).detach().appendTo(container) + $(this).siblings("select").append($("").attr("value",filename).text(filename.replace("file-",""))) + $(this).hide() + } + }); + }); diff --git a/docs/_static/renderjson.css b/docs/_static/renderjson.css new file mode 100644 index 00000000..0f7b1b61 --- /dev/null +++ b/docs/_static/renderjson.css @@ -0,0 +1,11 @@ +pre.renderjson { overflow: scroll; font-size:smaller; border: 1px solid #e1e4e5; padding: 12px; background-color: #eeffcc;} +.renderjson a { text-decoration: none; } +.renderjson .disclosure { color: grey; font-size: 150%; } +.renderjson .syntax { color: grey; } +.renderjson .string { color: #4070a0; } +.renderjson .number { color: darkcyan; } +.renderjson .boolean { color: blueviolet; } +.renderjson .key { color: #062873; font-weight: bold;} +.renderjson .keyword { color: blue; } +.renderjson .object.syntax { color: grey; } +.renderjson .array.syntax { color: grey; } diff --git a/docs/_static/renderjson.js b/docs/_static/renderjson.js new file mode 100644 index 00000000..03970242 --- /dev/null +++ b/docs/_static/renderjson.js @@ -0,0 +1,194 @@ +// Copyright © 2013-2014 David Caldwell +// +// Permission to use, copy, modify, and/or distribute this software for any +// purpose with or without fee is hereby granted, provided that the above +// copyright notice and this permission notice appear in all copies. +// +// THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES +// WITH REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF +// MERCHANTABILITY AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY +// SPECIAL, DIRECT, INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES +// WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION +// OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF OR IN +// CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE. + +// Usage +// ----- +// The module exports one entry point, the `renderjson()` function. It takes in +// the JSON you want to render as a single argument and returns an HTML +// element. +// +// Options +// ------- +// renderjson.set_icons("+", "-") +// This Allows you to override the disclosure icons. +// +// renderjson.set_show_to_level(level) +// Pass the number of levels to expand when rendering. The default is 0, which +// starts with everything collapsed. As a special case, if level is the string +// "all" then it will start with everything expanded. +// +// renderjson.set_max_string_length(length) +// Strings will be truncated and made expandable if they are longer than +// `length`. As a special case, if `length` is the string "none" then +// there will be no truncation. The default is "none". +// +// renderjson.set_sort_objects(sort_bool) +// Sort objects by key (default: false) +// +// Theming +// ------- +// The HTML output uses a number of classes so that you can theme it the way +// you'd like: +// .disclosure ("⊕", "⊖") +// .syntax (",", ":", "{", "}", "[", "]") +// .string (includes quotes) +// .number +// .boolean +// .key (object key) +// .keyword ("null", "undefined") +// .object.syntax ("{", "}") +// .array.syntax ("[", "]") + +var module; +(module||{}).exports = renderjson = (function() { + var themetext = function(/* [class, text]+ */) { + var spans = []; + while (arguments.length) + spans.push(append(span(Array.prototype.shift.call(arguments)), + text(Array.prototype.shift.call(arguments)))); + return spans; + }; + var append = function(/* el, ... */) { + var el = Array.prototype.shift.call(arguments); + for (var a=0; a 0) + show(); + return el; + + }; + + if (json === null) return themetext(null, my_indent, "keyword", "null"); + if (json === void 0) return themetext(null, my_indent, "keyword", "undefined"); + + if (typeof(json) == "string" && json.length > max_string) + return disclosure('"', json.substr(0,max_string)+" ...", '"', "string", function () { + return append(span("string"), themetext(null, my_indent, "string", JSON.stringify(json))); + }); + + if (typeof(json) != "object") // Strings, numbers and bools + return themetext(null, my_indent, typeof(json), JSON.stringify(json)); + + if (json.constructor == Array) { + if (json.length == 0) return themetext(null, my_indent, "array syntax", "[]"); + + return disclosure("[", " ... ", "]", "array", function () { + var as = append(span("array"), themetext("array syntax", "[", null, "\n")); + for (var i=0; i -1) ? show_level + 1 : show_level - 1 ), max_string, sort_objects), + k != last ? themetext("syntax", ",") : [], + text("\n")); + } + append(os, themetext(null, indent, "object syntax", "}")); + return os; + }); + } + + var renderjson = function renderjson(json) + { + var pre = append(document.createElement("pre"), _renderjson(json, "", false, renderjson.show_to_level, renderjson.max_string_length, renderjson.sort_objects)); + pre.className = "renderjson"; + return pre; + } + renderjson.set_icons = function(show, hide) { renderjson.show = show; + renderjson.hide = hide; + return renderjson; }; + renderjson.set_show_to_level = function(level) { renderjson.show_to_level = typeof level == "string" && + level.toLowerCase() === "all" ? Number.MAX_VALUE + : level; + return renderjson; }; + renderjson.set_max_string_length = function(length) { renderjson.max_string_length = typeof length == "string" && + length.toLowerCase() === "none" ? Number.MAX_VALUE + : length; + return renderjson; }; + renderjson.set_sort_objects = function(sort_bool) { renderjson.sort_objects = sort_bool; + return renderjson; }; + // Backwards compatiblity. Use set_show_to_level() for new code. + renderjson.set_show_by_default = function(show) { renderjson.show_to_level = show ? Number.MAX_VALUE : 0; + return renderjson; }; + + //Added by timgdavies + renderjson.set_default_open = function(node_list) { renderjson.default_open = node_list ? node_list : [] ; return renderjson; }; + + renderjson.set_icons('⊕', '⊖'); + renderjson.set_show_by_default(false); + renderjson.set_sort_objects(false); + renderjson.set_max_string_length("none"); + renderjson.set_default_open([]); + return renderjson; +})(); \ No newline at end of file diff --git a/docs/_templates/layout.html b/docs/_templates/layout.html index 6fceec14..4f0d56e8 100644 --- a/docs/_templates/layout.html +++ b/docs/_templates/layout.html @@ -1,4 +1,4 @@ {% extends "!layout.html" %} -{% set css_files = css_files + ["_static/basic.css"] %} - +{% set css_files = css_files + ["_static/renderjson.css", "_static/jsonschema.css"] %} +{% set script_files = script_files + ["_static/renderjson.js", "_static/json-example-format.js"] %} diff --git a/docs/about/changelog.md b/docs/about/changelog.md index 1de0eb81..ca47386d 100644 --- a/docs/about/changelog.md +++ b/docs/about/changelog.md @@ -102,6 +102,7 @@ This page lists changes to the Risk Data Library Standard. - [#146](https://github.com/GFDRR/rdl-standard/pull/146) - Update introduction to the RDLS reference section. - [#193](https://github.com/GFDRR/rdl-standard/pull/193) - Fix lists of referencing fields for subschemas and codelists. - [#225](https://github.com/GFDRR/rdl-standard/pull/225) - Update high level descriptions of the 4 risk data components. +- [#196](https://github.com/GFDRR/rdl-standard/pull/196) - Add examples to schema reference documentation. ### Non-normative documentation diff --git a/docs/reference/schema.md b/docs/reference/schema.md index 7a71de4d..31268ea4 100644 --- a/docs/reference/schema.md +++ b/docs/reference/schema.md @@ -133,67 +133,154 @@ The hazard component uses hazard_type, process_type and intensity_measure consis } ``` -`````{tab-set} - -````{tab-item} Schema +The `hazard` object has the following properties: ```{jsonschema} ../../docs/_readthedocs/html/rdls_schema.json --- pointer: /properties/hazard -collapse: event_sets/0/hazards,event_sets/0/spatial,event_sets/0/temporal,event_sets/0/events +collapse: + event_sets/0/hazards,event_sets/0/spatial,event_sets/0/temporal,event_sets/0/events addtargets: --- ``` +``````{dropdown} Example: Fathom Global Flood Map +--- +open: +--- +The following example shows RDLS metadata for the [Fathom Global Flood Map](https://www.fathom.global/product/global-flood-map/) in tabular format and JSON format. + +`````{tab-set} + +````{tab-item} Figure + +```{figure} ../../examples/hazard/fathom/figure.png +``` + ```` -````{tab-item} Examples +````{tab-item} Metadata (tabular) -Hazard data are most often represented by geospatial grids (raster); sometimes they are represented by points or polygons. +In tabular format, the metadata consists of several tables. To aid comprehension, the metadata is presented column wise using field titles. -**Flood hazard maps for Kabul** +```{csv-table-no-translate} Datasets +--- +stub-columns: 1 +widths: auto +file: ../../examples/hazard/fathom/datasets.csv +--- -Schema attributes for flood hazard map related to the occurrence probability of a river flood event with a return period of once in 100 years over Kabul, Afghanistan. The hydrological data used for modelling the intensity of floods is derived from observations over the period 1958-2001 (44 years). The hazard intensity is measured as water depth, in meters. These information cover all mandatory fields, and a few optional fields. +``` -![Screenshot](../img/hzd_fl_kabul.jpg) +```{csv-table-no-translate} Resources +--- +stub-columns: 1 +widths: auto +file: ../../examples/hazard/fathom/Resources.csv +--- + +``` -| **Required** | **Attribute** | **Example** | -| :----------: | ----------------------- | --------------- | -| \* | Hazard type | Flood | -| \* | Analysis type | Probabilistic | -| \* | Calculation method | Simulated | -| | Geographic area | Kabul | -| | Frequency type | Return Period | -| | Occurrence probability | 100 years | -| | Occurrence time (start) | 1958 | -| | Occurrence time (end) | 2001 | -| | Occurrence time (span) | 44 years | -| \* | Hazard process | River flood | -| \* | Unit of measure | Water depth (m) | +```{csv-table-no-translate} Event sets +--- +stub-columns: 1 +widths: auto +file: ../../examples/hazard/fathom/Hazard metadata_Event sets.csv +--- + +``` -**Earthquake hazard maps for Afghanistan** +```{csv-table-no-translate} Event set hazards +--- +stub-columns: 1 +widths: auto +file: ../../examples/hazard/fathom/Hazard metadata_Event sets_Hazards.csv +--- -Schema attributes for an earthquake hazard map related to an occurrence probability of an event with return period of once in 1000 years over Afghanistan. The seismic data catalogue behind the calculation of occurrence probability starts from year 800, covering a period of 1200 years. The hazard intensity is measured as Peak Ground Acceleration, expressed in (g). +``` -![Screenshot](../img/hzd_eq_afg.jpg) +```` -| **Required** | **Attribute** | **Example** | -| :----------: | ----------------------- | ------------- | -| \* | Hazard type | Earthquake | -| \* | Analysis type | Probabilistic | -| \* | Calculation method | Simulated | -| | Frequency type | Return Period | -| | Occurrence probability | 1000 years | -| | Occurrence time (start) | 800 | -| | Occurrence time (end) | 2001 | -| | Occurrence time (span) | 1200 years | -| \* | Hazard process | Ground motion | -| \* | Unit of measure | PGA (g) | +````{tab-item} Metadata (JSON) +```{eval-rst} +.. jsoninclude:: ../../examples/hazard/fathom/example.json + :jsonpointer: /datasets/0 + :title: Example +``` ```` ````` +`````` + +``````{dropdown} Example: Aqueduct Floods Hazard Maps + +The following example shows RDLS metadata for the [Aqueduct Floods Hazard Maps](https://www.wri.org/data/aqueduct-floods-hazard-maps) in tabular format and JSON format. + +`````{tab-set} + +````{tab-item} Figure + +```{figure} ../../examples/hazard/aqueduct/figure.png +``` + +```` + +````{tab-item} Metadata (tabular) + +In tabular format, the metadata consists of several tables. To aid comprehension, the metadata is presented column wise using field titles. + +```{csv-table-no-translate} Datasets +--- +stub-columns: 1 +widths: auto +file: ../../examples/hazard/aqueduct/datasets.csv +--- + +``` + +```{csv-table-no-translate} Resources +--- +stub-columns: 1 +widths: auto +file: ../../examples/hazard/aqueduct/Resources.csv +--- + +``` + +```{csv-table-no-translate} Event sets +--- +stub-columns: 1 +widths: auto +file: ../../examples/hazard/aqueduct/Hazard metadata_Event sets.csv +--- + +``` + +```{csv-table-no-translate} Event set hazards +--- +stub-columns: 1 +widths: auto +file: ../../examples/hazard/aqueduct/Hazard metadata_Event sets_Hazards.csv +--- + +``` + +```` + +````{tab-item} Metadata (JSON) + +```{eval-rst} +.. jsoninclude:: ../../examples/hazard/aqueduct/example.json + :jsonpointer: /datasets/0 + :title: Example +``` + +```` + +````` +`````` ## Exposure @@ -221,10 +308,6 @@ The exposure component uses exposure categories consistent with the vulnerabilit } ``` -`````{tab-set} - -````{tab-item} Schema - ```{jsonschema} ../../docs/_readthedocs/html/rdls_schema.json --- pointer: /properties/exposure @@ -233,40 +316,181 @@ addtargets: --- ``` +``````{dropdown} Example: Central Asia projected residential exposure dataset + +The following example shows RDLS metadata for the [Central Asia projected residential exposure dataset](https://datacatalog.worldbank.org/search/dataset/0064254/Central-Asia-exposure-dataset---Projected-residential-exposure) in tabular format and JSON format. + +`````{tab-set} + +````{tab-item} Metadata (tabular) + +In tabular format, the metadata consists of several tables. To aid comprehension, the metadata is presented column wise using field titles. + +```{csv-table-no-translate} Datasets +--- +stub-columns: 1 +widths: auto +file: ../../examples/exposure/central_asia_residential_projected/datasets.csv +--- + +``` + +```{csv-table-no-translate} Resources +--- +stub-columns: 1 +widths: auto +file: ../../examples/exposure/central_asia_residential_projected/Resources.csv +--- + +``` + +```{csv-table-no-translate} Attributions +--- +stub-columns: 1 +widths: auto +file: ../../examples/exposure/central_asia_residential_projected/Attributions.csv +--- + +``` + +```{csv-table-no-translate} Referenced by +--- +stub-columns: 1 +widths: auto +file: ../../examples/exposure/central_asia_residential_projected/Referenced by.csv +--- + +``` + +```{csv-table-no-translate} Sources +--- +stub-columns: 1 +widths: auto +file: ../../examples/exposure/central_asia_residential_projected/Sources.csv +--- + +``` + +```{csv-table-no-translate} Gazetteer entries (spatial coverage) +--- +stub-columns: 1 +widths: auto +file: ../../examples/exposure/central_asia_residential_projected/Spatial coverage_Gazetteer entries.csv +--- + +``` + +```{csv-table-no-translate} Exposure metrics +--- +stub-columns: 1 +widths: auto +file: ../../examples/exposure/central_asia_residential_projected/Exposure metadata_Exposure metrics.csv +--- + +``` + +```` + +````{tab-item} Metadata (JSON) + +```{eval-rst} +.. jsoninclude:: ../../examples/exposure/central_asia_residential_projected/example.json + :jsonpointer: /datasets/0 + :title: Example +``` + ```` -````{tab-item} Examples +````` +`````` + +``````{dropdown} Example: Central Asia current residential exposure dataset + +The following example shows RDLS metadata for the [Central Asia current residential exposure dataset](https://datacatalog.worldbank.org/search/dataset/0064251/Central-Asia-exposure-dataset---Residential-buildings) in tabular format and JSON format. + +`````{tab-set} + +````{tab-item} Metadata (tabular) + +In tabular format, the metadata consists of several tables. To aid comprehension, the metadata is presented column wise using field titles. + +```{csv-table-no-translate} Datasets +--- +stub-columns: 1 +widths: auto +file: ../../examples/exposure/central_asia_residential_current/datasets.csv +--- + +``` + +```{csv-table-no-translate} Resources +--- +stub-columns: 1 +widths: auto +file: ../../examples/exposure/central_asia_residential_current/Resources.csv +--- + +``` + +```{csv-table-no-translate} Attributions +--- +stub-columns: 1 +widths: auto +file: ../../examples/exposure/central_asia_residential_current/Attributions.csv +--- + +``` + +```{csv-table-no-translate} Referenced by +--- +stub-columns: 1 +widths: auto +file: ../../examples/exposure/central_asia_residential_current/Referenced by.csv +--- + +``` -Exposure data can be stored at multiple scales, more often using vectors, namely polygons (e.g. building footprint), points (e.g. asset geolocation) and lines (e.g. transport infrastructures, lifelines), but in same case exposure estimates are aggregated at ADM level or distributed over a raster grid. +```{csv-table-no-translate} Sources +--- +stub-columns: 1 +widths: auto +file: ../../examples/exposure/central_asia_residential_current/Sources.csv +--- -**Exposure map for Kabul** +``` -Two exposure datasets are shown together in the example: building footprints polygons and population density raster at 90 m resolution. +```{csv-table-no-translate} Gazetteer entries (spatial coverage) +--- +stub-columns: 1 +widths: auto +file: ../../examples/exposure/central_asia_residential_current/Spatial coverage_Gazetteer entries.csv +--- -![Exposure example](../img/sample_exp.jpg) +``` -| **Required** | **Attribute** | **Example** | -| :----------: | ------------------- | ----------- | -| \* | Geographic coverage | Afghanistan | -| \* | Exposure category | Buildings | -| \* | Occupancy | Mixed | -| | Taxonomy | OSM | -| \* | Value type | Structure | -| \* | Unit of measure | USD | +```{csv-table-no-translate} Exposure metrics +--- +stub-columns: 1 +widths: auto +file: ../../examples/exposure/central_asia_residential_current/Exposure metadata_Exposure metrics.csv +--- -| **Required** | **Attribute** | **Example** | -| :----------: | ------------------- | ----------- | -| \* | Geographic coverage | Afghanistan | -| \* | Exposure category | Indicators | -| \* | Occupancy | Residential | -| | Period of occupancy | Night | -| \* | Value type | Other | -| \* | Unit of measure | Count | +``` +```` + +````{tab-item} Metadata (JSON) + +```{eval-rst} +.. jsoninclude:: ../../examples/exposure/central_asia_residential_current/example.json + :jsonpointer: /datasets/0 + :title: Example +``` ```` ````` +`````` ## Vulnerability @@ -295,10 +519,6 @@ The vulnerability component uses hazard_type, process_type and intensity_measure } ``` -`````{tab-set} - -````{tab-item} Schema - ```{jsonschema} ../../docs/_readthedocs/html/rdls_schema.json --- pointer: /properties/vulnerability @@ -307,9 +527,83 @@ addtargets: --- ``` +``````{dropdown} Example: Global flood depth-damage functions +--- +open: +--- +The following example shows RDLS metadata for the [Global flood depth-damage functions](https://publications.jrc.ec.europa.eu/repository/handle/JRC105688) in tabular format and JSON format. + +`````{tab-set} + +````{tab-item} Figure + +```{figure} ../../examples/vulnerability/flood_jrc/figure.png +``` +```` + +````{tab-item} Metadata (tabular) + +In tabular format, the metadata consists of several tables. To aid comprehension, the metadata is presented column wise using field titles. + +```{csv-table-no-translate} Datasets +--- +stub-columns: 1 +widths: auto +file: ../../examples/vulnerability/flood_jrc/datasets.csv +--- + +``` + +```{csv-table-no-translate} Resources +--- +stub-columns: 1 +widths: auto +file: ../../examples/vulnerability/flood_jrc/Resources.csv +--- + +``` + +```{csv-table-no-translate} Attributions +--- +stub-columns: 1 +widths: auto +file: ../../examples/vulnerability/flood_jrc/Attributions.csv +--- + +``` + +```{csv-table-no-translate} Referenced by +--- +stub-columns: 1 +widths: auto +file: ../../examples/vulnerability/flood_jrc/Referenced by.csv +--- + +``` + +```{csv-table-no-translate} Asset costs +--- +stub-columns: 1 +widths: auto +file: ../../examples/vulnerability/flood_jrc/Vulnerability metadata_Asset cost.csv +--- + +``` + +```` + +````{tab-item} Metadata (JSON) + +```{eval-rst} +.. jsoninclude:: ../../examples/vulnerability/flood_jrc/example.json + :jsonpointer: /datasets/0 + :title: Example +``` + ```` ````` +`````` ## Loss @@ -345,10 +639,6 @@ Loss datasets can be explicitly linked to the exposure, hazard, and vulnerabilit } ``` -`````{tab-set} - -````{tab-item} Schema - ```{jsonschema} ../../docs/_readthedocs/html/rdls_schema.json --- pointer: /properties/loss @@ -357,70 +647,6 @@ addtargets: --- ``` -```` - -````{tab-item} Examples - -Losses can be represented in many different way: regular raster grids, points, or polygons. Often, the loss data consist of measures aggregated at the administrative unit level. - -**Flood loss scenarios for Afghanistan, 2050** - -Schema attributes for loss map related to future river flood hazard scenarios (2050) over all types of exposure occupancies for Afghanistan. - -![Flood losses in Afghanistan](../img/lss_fl_afg.jpg) - -The losses are higher in the most densely built-up area of Kabul. - -![Flood losses in Kabul](../img/lss_fl_kabul.jpg) - -| **Required** | **Attribute** | **Example** | -| :----------: | ---------------------- | ----------------------------------------------------------------------- | -| \* | Hazard type | Flood | -| | Hazard process | River flood | -| \* | Exposure occupancy | Mixed | -| \* | Exposure category | Buildings | -| \* | Value type | Structure | -| | Hazard link | [Dataset](http://jkan.riskdatalibrary.org/datasets/hzd-afg-fl-baseline) | -| | Exposure link | | -| | Vulnerability link | | -| | Time year | 2050 | -| | Frequency type | Return Period | -| | Occurrence probability | RP 5-1000 years | -| \* | Impact | Direct | -| \* | Loss type | Ground up | -| \* | Metric | Average Annual Losses | -| \* | Unit | USD | - -______________________________________________________________________ - -Losses can be investigated as total or for individual exposed asset and infrastructure elements. - -![Example of data showing exposed roads in Afghanistan](../img/exp_afg_roads.jpg) - -______________________________________________________________________ - -**Observed losses** - -Insert example of recorded empirical losses. - -| **Required** | **Attribute** | **Example** | -| :----------: | ----------------------- | ------------- | -| \* | Hazard type | Earthquake | -| \* | Analysis type | Probabilistic | -| \* | Calculation method | Simulated | -| | Frequency type | Return Period | -| | Occurrence probability | 1000 years | -| | Occurrence time (start) | 800 | -| | Occurrence time (end) | 2001 | -| | Occurrence time (span) | 1200 years | -| \* | Hazard process | Ground motion | -| \* | Unit of measure | PGA (g) | - - -```` - -````` - ## Sub-schemas ### Entity diff --git a/examples/exposure/central_asia_residential_current/Attributions.csv b/examples/exposure/central_asia_residential_current/Attributions.csv new file mode 100644 index 00000000..b7a5ed02 --- /dev/null +++ b/examples/exposure/central_asia_residential_current/Attributions.csv @@ -0,0 +1,7 @@ +Dataset identifier,https://datacatalog.worldbank.org/search/dataset/0064251/Central-Asia-exposure-dataset---Residential-buildings,https://datacatalog.worldbank.org/search/dataset/0064251/Central-Asia-exposure-dataset---Residential-buildings +Attribution identifier,0064251_attr1,0064251_attr2 +"Entity: +Name",Chi-Yun Huang,"OGS, Italy" +"Entity: +Email address",chuang@worldbank.org, +Role,custodian,collaborator diff --git a/examples/exposure/central_asia_residential_current/Exposure metadata_Exposure metrics.csv b/examples/exposure/central_asia_residential_current/Exposure metadata_Exposure metrics.csv new file mode 100644 index 00000000..1ded8ec2 --- /dev/null +++ b/examples/exposure/central_asia_residential_current/Exposure metadata_Exposure metrics.csv @@ -0,0 +1,4 @@ +Dataset identifier,https://datacatalog.worldbank.org/search/dataset/0064251/Central-Asia-exposure-dataset---Residential-buildings +Identifier,0064251_metric1 +Metric dimension,structure +Metric quantity kind,currency diff --git a/examples/exposure/central_asia_residential_current/Links.csv b/examples/exposure/central_asia_residential_current/Links.csv new file mode 100644 index 00000000..a45c40b5 --- /dev/null +++ b/examples/exposure/central_asia_residential_current/Links.csv @@ -0,0 +1,3 @@ +Dataset identifier,https://datacatalog.worldbank.org/search/dataset/0064251/Central-Asia-exposure-dataset---Residential-buildings +Link target,https://raw.githubusercontent.com/GFDRR/rdl-standard/0__2__0/schema/rdls_schema.json +Link relation type,describedby diff --git a/examples/exposure/central_asia_residential_current/Referenced by.csv b/examples/exposure/central_asia_residential_current/Referenced by.csv new file mode 100644 index 00000000..520cb07e --- /dev/null +++ b/examples/exposure/central_asia_residential_current/Referenced by.csv @@ -0,0 +1,4 @@ +Dataset identifier,https://datacatalog.worldbank.org/search/dataset/0064251/Central-Asia-exposure-dataset---Residential-buildings,https://datacatalog.worldbank.org/search/dataset/0064251/Central-Asia-exposure-dataset---Residential-buildings +Related resource identifier,0064251_ref1,0064251_ref2 +Name,Central Asia exposure data development technical report - English version,Central Asia exposure data development technical report - Russian version +URL,https://datacatalogfiles.worldbank.org/ddh-published/0064117/DR0091010/Task4_Exposure_Report_r6_EN.pdf?versionId=2023-07-21T17:33:32.2845222Z,https://datacatalogfiles.worldbank.org/ddh-published/0064117/DR0091011/Task4_Exposure_Report_r6_RU.pdf?versionId=2023-07-21T17:33:26.6527091Z diff --git a/examples/exposure/central_asia_residential_current/Resources.csv b/examples/exposure/central_asia_residential_current/Resources.csv new file mode 100644 index 00000000..5d8fb8f7 --- /dev/null +++ b/examples/exposure/central_asia_residential_current/Resources.csv @@ -0,0 +1,16 @@ +Dataset identifier,https://datacatalog.worldbank.org/search/dataset/0064251/Central-Asia-exposure-dataset---Residential-buildings,https://datacatalog.worldbank.org/search/dataset/0064251/Central-Asia-exposure-dataset---Residential-buildings,https://datacatalog.worldbank.org/search/dataset/0064251/Central-Asia-exposure-dataset---Residential-buildings,https://datacatalog.worldbank.org/search/dataset/0064251/Central-Asia-exposure-dataset---Residential-buildings,https://datacatalog.worldbank.org/search/dataset/0064251/Central-Asia-exposure-dataset---Residential-buildings +Resource identifier,0064251_res1,0064251_res2,0064251_res3,0064251_res4,0064251_res5 +Resource title,Central Asia exposure dataset - Residential buildings - KAZ,Central Asia exposure dataset - Residential buildings - KGZ,Central Asia exposure dataset - Residential buildings - TJK,Central Asia exposure dataset - Residential buildings - TKM,Central Asia exposure dataset - Residential buildings - UZB +Resource description,"Central Asia exposure layers – Residential buildings - KAZ +Files: RESIDENTIAL_[OBLAST].csv, RESIDENTIAL_[OBLAST].shp","Central Asia exposure layers – Residential buildings - KGZ +Files: RESIDENTIAL_[OBLAST].csv, RESIDENTIAL_[OBLAST].shp","Central Asia exposure layers – Residential buildings - TJK +Files: RESIDENTIAL_[OBLAST].csv, RESIDENTIAL_[OBLAST].shp","Central Asia exposure layers – Residential buildings - TKM +Files: RESIDENTIAL_[OBLAST].csv, RESIDENTIAL_[OBLAST].shp","Central Asia exposure layers – Residential buildings - UZB +Files: RESIDENTIAL_[OBLAST].csv, RESIDENTIAL_[OBLAST].shp" +Format,csv,csv,csv,csv,csv +Spatial resolution,500,500,500,500,500 +resources/0/url,https://datacatalogfiles.worldbank.org/ddh-published/0064251/DR0091988/KAZ_residential_exposure.zip?versionId=2023-07-11T15:15:39.6450392Z,https://datacatalogfiles.worldbank.org/ddh-published/0064251/DR0091661/KGZ_residential_exposure.zip?versionId=2023-07-11T15:15:41.4460187Z,https://datacatalogfiles.worldbank.org/ddh-published/0064251/DR0091660/TJK_residential_exposure.zip?versionId=2023-07-11T15:15:37.7301236Z,https://datacatalogfiles.worldbank.org/ddh-published/0064251/DR0091659/TKM_residential_exposure.zip?versionId=2023-07-11T15:15:34.9986705Z,https://datacatalogfiles.worldbank.org/ddh-published/0064251/DR0091989/UZB_residential_exposure.zip?versionId=2023-07-11T15:15:43.2479984Z +"Temporal coverage: +Start",2020,2020,2020,2020,2020 +"Temporal coverage: +End date",2020,2020,2020,2020,2020 diff --git a/examples/exposure/central_asia_residential_current/Sources.csv b/examples/exposure/central_asia_residential_current/Sources.csv new file mode 100644 index 00000000..6d1ec570 --- /dev/null +++ b/examples/exposure/central_asia_residential_current/Sources.csv @@ -0,0 +1,2 @@ +Dataset identifier,https://datacatalog.worldbank.org/search/dataset/0064251/Central-Asia-exposure-dataset---Residential-buildings +Source identifier,0064251_src1 diff --git a/examples/exposure/central_asia_residential_current/Spatial coverage_Gazetteer entries.csv b/examples/exposure/central_asia_residential_current/Spatial coverage_Gazetteer entries.csv new file mode 100644 index 00000000..5c61bbfc --- /dev/null +++ b/examples/exposure/central_asia_residential_current/Spatial coverage_Gazetteer entries.csv @@ -0,0 +1,4 @@ +Dataset identifier,https://datacatalog.worldbank.org/search/dataset/0064251/Central-Asia-exposure-dataset---Residential-buildings +Gazetteer entry identifier,0064251_spatial1 +Scheme,ISO 3166-1 alpha-3 +Description,"Central Asia: KAZ, KGZ, TJK, TKM, UZB" diff --git a/examples/exposure/central_asia_residential_current/datasets.csv b/examples/exposure/central_asia_residential_current/datasets.csv new file mode 100644 index 00000000..f022cc59 --- /dev/null +++ b/examples/exposure/central_asia_residential_current/datasets.csv @@ -0,0 +1,28 @@ +Dataset identifier,https://datacatalog.worldbank.org/search/dataset/0064251/Central-Asia-exposure-dataset---Residential-buildings +Title,Central-Asia-exposure-dataset---Current-residential-exposure +Description,Regional layer of residential buildings in Central Asia +Risk data type,exposure +"Publisher: +Name",World Bank +"Publisher: +Email address",sfraser@worldbank.org +"Publisher: +URL",http://www.worldbank.org +Dataset version,12 +Dataset purpose,"Developed as part of the regional risk assessment, under the Strengthening Financial Resilience and Accelerating Risk Reduction in Central Asia program. (https://www.gfdrr.org/en/program/SFRARR-Central-Asia)" +Project title,Strengthening Financial Resilience and Accelerating Risk Reduction in Central Asia +"Spatial coverage: +Countries",KAZ;KGZ;TJK;TKM;UZB +License,CC-BY-4.0 +"Contact point: +Name",Stuart Fraser +"Contact point: +Email address",sfraser@worldbank.org +"Creator: +Name",Risk Engineering and Development +"Creator: +URL",http://www.redrisk.com +"Exposure metadata: +Exposure category",buildings +"Exposure metadata: +Exposure taxonomy scheme",GED4ALL diff --git a/examples/exposure/central_asia_residential_current/example.json b/examples/exposure/central_asia_residential_current/example.json new file mode 100644 index 00000000..d7bba817 --- /dev/null +++ b/examples/exposure/central_asia_residential_current/example.json @@ -0,0 +1,173 @@ +{ + "datasets": [ + { + "id": "https://datacatalog.worldbank.org/search/dataset/0064251/Central-Asia-exposure-dataset---Residential-buildings", + "title": "Central-Asia-exposure-dataset---Current-residential-exposure", + "description": "Regional layer of residential buildings in Central Asia", + "risk_data_type": [ + "exposure" + ], + "publisher": { + "name": "World Bank", + "email": "sfraser@worldbank.org", + "url": "http://www.worldbank.org" + }, + "version": "12", + "purpose": "Developed as part of the regional risk assessment, under the Strengthening Financial Resilience and Accelerating Risk Reduction in Central Asia program. (https://www.gfdrr.org/en/program/SFRARR-Central-Asia)", + "project": "Strengthening Financial Resilience and Accelerating Risk Reduction in Central Asia ", + "spatial": { + "countries": [ + "KAZ", + "KGZ", + "TJK", + "TKM", + "UZB" + ], + "gazetteerEntries": [ + { + "id": "KAZ", + "scheme": "ISO 3166-1 alpha-3" + }, + { + "id": "KGZ", + "scheme": "ISO 3166-1 alpha-3" + }, + { + "id": "TJK", + "scheme": "ISO 3166-1 alpha-3" + }, + { + "id": "TKM", + "scheme": "ISO 3166-1 alpha-3" + }, + { + "id": "UZB", + "scheme": "ISO 3166-1 alpha-3" + } + ] + }, + "license": "CC-BY-4.0", + "contact_point": { + "name": "Stuart Fraser", + "email": "sfraser@worldbank.org" + }, + "creator": { + "name": "Risk Engineering and Development", + "url": "http://www.redrisk.com " + }, + "exposure": { + "category": "buildings", + "taxonomy": "GED4ALL", + "metrics": [ + { + "id": "0064251_metric1", + "dimension": "structure", + "quantity_kind": "currency" + } + ] + }, + "attributions": [ + { + "id": "0064251_attr1", + "entity": { + "name": "Chi-Yun Huang", + "email": "chuang@worldbank.org" + }, + "role": "custodian" + }, + { + "id": "0064251_attr2", + "entity": { + "name": "OGS, Italy" + }, + "role": "collaborator" + } + ], + "sources": [ + { + "id": "0064251_src1" + } + ], + "referenced_by": [ + { + "id": "0064251_ref1", + "name": "Central Asia exposure data development technical report - English version", + "url": "https://datacatalogfiles.worldbank.org/ddh-published/0064117/DR0091010/Task4_Exposure_Report_r6_EN.pdf?versionId=2023-07-21T17:33:32.2845222Z" + }, + { + "id": "0064251_ref2", + "name": "Central Asia exposure data development technical report - Russian version", + "url": "https://datacatalogfiles.worldbank.org/ddh-published/0064117/DR0091011/Task4_Exposure_Report_r6_RU.pdf?versionId=2023-07-21T17:33:26.6527091Z" + } + ], + "resources": [ + { + "id": "0064251_res1", + "title": "Central Asia exposure dataset - Residential buildings - KAZ", + "description": "Central Asia exposure layers – Residential buildings - KAZ\nFiles: RESIDENTIAL_[OBLAST].csv, RESIDENTIAL_[OBLAST].shp", + "format": "csv", + "spatial_resolution": 500, + "download_url": "https://datacatalogfiles.worldbank.org/ddh-published/0064251/DR0091988/KAZ_residential_exposure.zip?versionId=2023-07-11T15:15:39.6450392Z", + "temporal": { + "start": "2020", + "end": "2020" + } + }, + { + "id": "0064251_res2", + "title": "Central Asia exposure dataset - Residential buildings - KGZ", + "description": "Central Asia exposure layers – Residential buildings - KGZ\nFiles: RESIDENTIAL_[OBLAST].csv, RESIDENTIAL_[OBLAST].shp", + "format": "csv", + "spatial_resolution": 500, + "download_url": "https://datacatalogfiles.worldbank.org/ddh-published/0064251/DR0091661/KGZ_residential_exposure.zip?versionId=2023-07-11T15:15:41.4460187Z", + "temporal": { + "start": "2020", + "end": "2020" + } + }, + { + "id": "0064251_res3", + "title": "Central Asia exposure dataset - Residential buildings - TJK", + "description": "Central Asia exposure layers – Residential buildings - TJK\nFiles: RESIDENTIAL_[OBLAST].csv, RESIDENTIAL_[OBLAST].shp", + "format": "csv", + "spatial_resolution": 500, + "url": "https://datacatalogfiles.worldbank.org/ddh-published/0064251/DR0091660/TJK_residential_exposure.zip?versionId=2023-07-11T15:15:37.7301236Z", + "temporal": { + "start": "2020", + "end": "2020" + } + }, + { + "id": "0064251_res4", + "title": "Central Asia exposure dataset - Residential buildings - TKM", + "description": "Central Asia exposure layers – Residential buildings - TKM\nFiles: RESIDENTIAL_[OBLAST].csv, RESIDENTIAL_[OBLAST].shp", + "format": "csv", + "spatial_resolution": 500, + "download_url": "https://datacatalogfiles.worldbank.org/ddh-published/0064251/DR0091659/TKM_residential_exposure.zip?versionId=2023-07-11T15:15:34.9986705Z", + "temporal": { + "start": "2020", + "end": "2020" + } + }, + { + "id": "0064251_res5", + "title": "Central Asia exposure dataset - Residential buildings - UZB", + "description": "Central Asia exposure layers – Residential buildings - UZB\nFiles: RESIDENTIAL_[OBLAST].csv, RESIDENTIAL_[OBLAST].shp", + "format": "csv", + "spatial_resolution": 500, + "download_url": "https://datacatalogfiles.worldbank.org/ddh-published/0064251/DR0091989/UZB_residential_exposure.zip?versionId=2023-07-11T15:15:43.2479984Z", + "temporal": { + "start": "2020", + "end": "2020" + } + } + ], + "links": [ + { + "href": "https://raw.githubusercontent.com/GFDRR/rdl-standard/0__2__0/schema/rdls_schema.json", + "rel": "describedby" + } + ] + } + ] +} diff --git a/examples/exposure/central_asia_residential_projected/Attributions.csv b/examples/exposure/central_asia_residential_projected/Attributions.csv new file mode 100644 index 00000000..50066cf1 --- /dev/null +++ b/examples/exposure/central_asia_residential_projected/Attributions.csv @@ -0,0 +1,7 @@ +Dataset identifier,https://datacatalog.worldbank.org/search/dataset/0064254/Central-Asia-exposure-dataset---Projected-residential-exposure,https://datacatalog.worldbank.org/search/dataset/0064254/Central-Asia-exposure-dataset---Projected-residential-exposure +Attribution identifier,0064254_attr1,0064254_attr2 +"Entity: +Name",Chi-Yun Huang,"OGS, Italy" +"Entity: +Email address",chuang@worldbank.org, +Role,custodian,collaborator diff --git a/examples/exposure/central_asia_residential_projected/Exposure metadata_Exposure metrics.csv b/examples/exposure/central_asia_residential_projected/Exposure metadata_Exposure metrics.csv new file mode 100644 index 00000000..a120d14e --- /dev/null +++ b/examples/exposure/central_asia_residential_projected/Exposure metadata_Exposure metrics.csv @@ -0,0 +1,4 @@ +Dataset identifier,https://datacatalog.worldbank.org/search/dataset/0064254/Central-Asia-exposure-dataset---Projected-residential-exposure +Identifier,0064254_metric1 +Metric dimension,structure +Metric quantity kind,currency diff --git a/examples/exposure/central_asia_residential_projected/Links.csv b/examples/exposure/central_asia_residential_projected/Links.csv new file mode 100644 index 00000000..92e0bce5 --- /dev/null +++ b/examples/exposure/central_asia_residential_projected/Links.csv @@ -0,0 +1,3 @@ +Dataset identifier,https://datacatalog.worldbank.org/search/dataset/0064254/Central-Asia-exposure-dataset---Projected-residential-exposure +Link target,https://raw.githubusercontent.com/GFDRR/rdl-standard/0__2__0/schema/rdls_schema.json +Link relation type,describedby diff --git a/examples/exposure/central_asia_residential_projected/Referenced by.csv b/examples/exposure/central_asia_residential_projected/Referenced by.csv new file mode 100644 index 00000000..081921fe --- /dev/null +++ b/examples/exposure/central_asia_residential_projected/Referenced by.csv @@ -0,0 +1,4 @@ +Dataset identifier,https://datacatalog.worldbank.org/search/dataset/0064254/Central-Asia-exposure-dataset---Projected-residential-exposure,https://datacatalog.worldbank.org/search/dataset/0064254/Central-Asia-exposure-dataset---Projected-residential-exposure +Related resource identifier,0064254_ref1,0064254_ref2 +Name,Central Asia exposure data development technical report - English version,Central Asia exposure data development technical report - Russian version +URL,https://datacatalogfiles.worldbank.org/ddh-published/0064117/DR0091010/Task4_Exposure_Report_r6_EN.pdf?versionId=2023-07-21T17:33:32.2845222Z,https://datacatalogfiles.worldbank.org/ddh-published/0064117/DR0091011/Task4_Exposure_Report_r6_RU.pdf?versionId=2023-07-21T17:33:26.6527091Z diff --git a/examples/exposure/central_asia_residential_projected/Resources.csv b/examples/exposure/central_asia_residential_projected/Resources.csv new file mode 100644 index 00000000..b155cb2c --- /dev/null +++ b/examples/exposure/central_asia_residential_projected/Resources.csv @@ -0,0 +1,17 @@ +Dataset identifier,https://datacatalog.worldbank.org/search/dataset/0064254/Central-Asia-exposure-dataset---Projected-residential-exposure,https://datacatalog.worldbank.org/search/dataset/0064254/Central-Asia-exposure-dataset---Projected-residential-exposure,https://datacatalog.worldbank.org/search/dataset/0064254/Central-Asia-exposure-dataset---Projected-residential-exposure +Resource identifier,0064254_res1,0064254_res2,0064254_res3 +Resource title,"Central Asia projected (2080) residential exposure - all countries, Oblast level: SSP1","Central Asia projected (2080) residential exposure - all countries, Oblast level: SSP4","Central Asia projected (2080) residential exposure - all countries, Oblast level: SSP5" +Resource description,"Central Asia projected (2080) residential exposure - for all five Central Asia countries included in the analysis, one file per Oblast (ADM1) for SSP1 +Dataset includes projected residneital data for SSP1, SSP4, SSP5 scenarios. +Files: RESIDENTIAL_[OBLAST]._2080_[SSP].csv","Central Asia projected (2080) residential exposure - for all five Central Asia countries included in the analysis, one file per Oblast (ADM1) for SSP4 +Dataset includes projected residneital data for SSP1, SSP4, SSP5 scenarios. +Files: RESIDENTIAL_[OBLAST]._2080_[SSP].csv","Central Asia projected (2080) residential exposure - for all five Central Asia countries included in the analysis, one file per Oblast (ADM1) for SSP5 +Dataset includes projected residneital data for SSP1, SSP4, SSP5 scenarios. +Files: RESIDENTIAL_[OBLAST]._2080_[SSP].csv" +Format,csv,csv,csv +Spatial resolution,500,500,500 +resources/0/url,https://datacatalogfiles.worldbank.org/ddh-published/0064254/DR0091991/P2080_SSP1.zip?versionId=2023-07-11T15:12:01.4656749Z,https://datacatalogfiles.worldbank.org/ddh-published/0064254/DR0091992/P2080_SSP4.zip?versionId=2023-07-11T15:12:06.1470219Z,https://datacatalogfiles.worldbank.org/ddh-published/0064254/DR0091993/P2080_SSP5.zip?versionId=2023-07-11T15:12:03.5145140Z +"Temporal coverage: +Start",2080,2080,2080 +"Temporal coverage: +End date",2080,2080,2080 diff --git a/examples/exposure/central_asia_residential_projected/Sources.csv b/examples/exposure/central_asia_residential_projected/Sources.csv new file mode 100644 index 00000000..7846c4fe --- /dev/null +++ b/examples/exposure/central_asia_residential_projected/Sources.csv @@ -0,0 +1,2 @@ +Dataset identifier,https://datacatalog.worldbank.org/search/dataset/0064254/Central-Asia-exposure-dataset---Projected-residential-exposure +Source identifier,0064254_src1 diff --git a/examples/exposure/central_asia_residential_projected/Spatial coverage_Gazetteer entries.csv b/examples/exposure/central_asia_residential_projected/Spatial coverage_Gazetteer entries.csv new file mode 100644 index 00000000..e7700032 --- /dev/null +++ b/examples/exposure/central_asia_residential_projected/Spatial coverage_Gazetteer entries.csv @@ -0,0 +1,4 @@ +Dataset identifier,https://datacatalog.worldbank.org/search/dataset/0064254/Central-Asia-exposure-dataset---Projected-residential-exposure +Gazetteer entry identifier,0064254_spatial1 +Scheme,ISO 3166-1 alpha-3 +Description,"Central Asia: KAZ, KGZ, TJK, TKM, UZB" diff --git a/examples/exposure/central_asia_residential_projected/datasets.csv b/examples/exposure/central_asia_residential_projected/datasets.csv new file mode 100644 index 00000000..6a732368 --- /dev/null +++ b/examples/exposure/central_asia_residential_projected/datasets.csv @@ -0,0 +1,28 @@ +Dataset identifier,https://datacatalog.worldbank.org/search/dataset/0064254/Central-Asia-exposure-dataset---Projected-residential-exposure +Title,Central-Asia-exposure-dataset---Projected-residential-exposure +Description,"Regional layer of residential buildings in Central Asia, projected to 2080" +Risk data type,exposure +"Publisher: +Name",World Bank +"Publisher: +Email address",sfraser@worldbank.org +"Publisher: +URL",http://www.worldbank.org +Dataset version,12 +Dataset purpose,"Developed as part of the regional risk assessment, under the Strengthening Financial Resilience and Accelerating Risk Reduction in Central Asia program. (https://www.gfdrr.org/en/program/SFRARR-Central-Asia)" +Project title,Strengthening Financial Resilience and Accelerating Risk Reduction in Central Asia +"Spatial coverage: +Countries",KAZ;KGZ;TJK;TKM;UZB +License,CC-BY-4.0 +"Contact point: +Name",Stuart Fraser +"Contact point: +Email address",sfraser@worldbank.org +"Creator: +Name",Risk Engineering and Development +"Creator: +URL",http://www.redrisk.com +"Exposure metadata: +Exposure category",buildings +"Exposure metadata: +Exposure taxonomy scheme",GED4ALL diff --git a/examples/exposure/central_asia_residential_projected/example.json b/examples/exposure/central_asia_residential_projected/example.json new file mode 100644 index 00000000..ffaa4139 --- /dev/null +++ b/examples/exposure/central_asia_residential_projected/example.json @@ -0,0 +1,149 @@ +{ + "datasets": [ + { + "id": "https://datacatalog.worldbank.org/search/dataset/0064254/Central-Asia-exposure-dataset---Projected-residential-exposure", + "title": "Central-Asia-exposure-dataset---Projected-residential-exposure", + "description": "Regional layer of residential buildings in Central Asia, projected to 2080", + "risk_data_type": [ + "exposure" + ], + "publisher": { + "name": "World Bank", + "email": "sfraser@worldbank.org", + "url": "http://www.worldbank.org" + }, + "version": "12", + "purpose": "Developed as part of the regional risk assessment, under the Strengthening Financial Resilience and Accelerating Risk Reduction in Central Asia program. (https://www.gfdrr.org/en/program/SFRARR-Central-Asia)", + "project": "Strengthening Financial Resilience and Accelerating Risk Reduction in Central Asia ", + "spatial": { + "countries": [ + "KAZ", + "KGZ", + "TJK", + "TKM", + "UZB" + ], + "gazetteerEntries": [ + { + "id": "KAZ", + "scheme": "ISO 3166-1 alpha-3" + }, + { + "id": "KGZ", + "scheme": "ISO 3166-1 alpha-3" + }, + { + "id": "TJK", + "scheme": "ISO 3166-1 alpha-3" + }, + { + "id": "TKM", + "scheme": "ISO 3166-1 alpha-3" + }, + { + "id": "UZB", + "scheme": "ISO 3166-1 alpha-3" + } + ] + }, + "license": "CC-BY-4.0", + "contact_point": { + "name": "Stuart Fraser", + "email": "sfraser@worldbank.org" + }, + "creator": { + "name": "Risk Engineering and Development", + "url": "http://www.redrisk.com " + }, + "exposure": { + "category": "buildings", + "taxonomy": "GED4ALL", + "metrics": [ + { + "id": "0064254_metric1", + "dimension": "structure", + "quantity_kind": "currency" + } + ] + }, + "attributions": [ + { + "id": "0064254_attr1", + "entity": { + "name": "Chi-Yun Huang", + "email": "chuang@worldbank.org" + }, + "role": "custodian" + }, + { + "id": "0064254_attr2", + "entity": { + "name": "OGS, Italy" + }, + "role": "collaborator" + } + ], + "sources": [ + { + "id": "0064254_src1" + } + ], + "referenced_by": [ + { + "id": "0064254_ref1", + "name": "Central Asia exposure data development technical report - English version", + "url": "https://datacatalogfiles.worldbank.org/ddh-published/0064117/DR0091010/Task4_Exposure_Report_r6_EN.pdf?versionId=2023-07-21T17:33:32.2845222Z" + }, + { + "id": "0064254_ref2", + "name": "Central Asia exposure data development technical report - Russian version", + "url": "https://datacatalogfiles.worldbank.org/ddh-published/0064117/DR0091011/Task4_Exposure_Report_r6_RU.pdf?versionId=2023-07-21T17:33:26.6527091Z" + } + ], + "resources": [ + { + "id": "0064254_res1", + "title": "Central Asia projected (2080) residential exposure - all countries, Oblast level: SSP1", + "description": "Central Asia projected (2080) residential exposure - for all five Central Asia countries included in the analysis, one file per Oblast (ADM1) for SSP1\nDataset includes projected residneital data for SSP1, SSP4, SSP5 scenarios.\nFiles: RESIDENTIAL_[OBLAST]._2080_[SSP].csv", + "format": "csv", + "spatial_resolution": 500, + "downloadurl": "https://datacatalogfiles.worldbank.org/ddh-published/0064254/DR0091991/P2080_SSP1.zip?versionId=2023-07-11T15:12:01.4656749Z", + "temporal": { + "start": "2080", + "end": "2080" + } + }, + { + "id": "0064254_res2", + "title": "Central Asia projected (2080) residential exposure - all countries, Oblast level: SSP4", + "description": "Central Asia projected (2080) residential exposure - for all five Central Asia countries included in the analysis, one file per Oblast (ADM1) for SSP4\nDataset includes projected residneital data for SSP1, SSP4, SSP5 scenarios.\nFiles: RESIDENTIAL_[OBLAST]._2080_[SSP].csv", + "format": "csv", + "spatial_resolution": 500, + "download_url": "https://datacatalogfiles.worldbank.org/ddh-published/0064254/DR0091992/P2080_SSP4.zip?versionId=2023-07-11T15:12:06.1470219Z", + "temporal": { + "start": "2080", + "end": "2080" + } + }, + { + "id": "0064254_res3", + "title": "Central Asia projected (2080) residential exposure - all countries, Oblast level: SSP5", + "description": "Central Asia projected (2080) residential exposure - for all five Central Asia countries included in the analysis, one file per Oblast (ADM1) for SSP5\nDataset includes projected residneital data for SSP1, SSP4, SSP5 scenarios.\nFiles: RESIDENTIAL_[OBLAST]._2080_[SSP].csv", + "format": "csv", + "spatial_resolution": 500, + "download_url": "https://datacatalogfiles.worldbank.org/ddh-published/0064254/DR0091993/P2080_SSP5.zip?versionId=2023-07-11T15:12:03.5145140Z", + "temporal": { + "start": "2080", + "end": "2080" + } + } + ], + "links": [ + { + "href": "https://raw.githubusercontent.com/GFDRR/rdl-standard/0__2__0/schema/rdls_schema.json", + "rel": "describedby" + } + ] + } + ] +} diff --git a/examples/full/SFRARR_fluvialhazardmaps/Attributions.csv b/examples/full/SFRARR_fluvialhazardmaps/Attributions.csv new file mode 100644 index 00000000..dc3124b4 --- /dev/null +++ b/examples/full/SFRARR_fluvialhazardmaps/Attributions.csv @@ -0,0 +1,9 @@ +Dataset identifier,https://datacatalog.worldbank.org/search/dataset/0064232 +Attribution identifier,0064232_1attr +"Entity: +Name",World Bank +"Entity: +Email address",chuang@worldbank.org +"Entity: +URL",http://www.worldbank.org +Role,custodian diff --git a/examples/full/SFRARR_fluvialhazardmaps/Hazard metadata_Event sets.csv b/examples/full/SFRARR_fluvialhazardmaps/Hazard metadata_Event sets.csv new file mode 100644 index 00000000..6609d787 --- /dev/null +++ b/examples/full/SFRARR_fluvialhazardmaps/Hazard metadata_Event sets.csv @@ -0,0 +1,10 @@ +Dataset identifier,https://datacatalog.worldbank.org/search/dataset/0064232 +Event set identifier,0064232_EventSet1 +Analysis type,probabilistic +Seasonality distribution,uniform +Calculation Method,simulated +Event count,10000 +"Spatial coverage: +Countries",KAZ;KGZ;TJK;TKM;UZB +"Spatial coverage: +Spatial scale",regional diff --git a/examples/full/SFRARR_fluvialhazardmaps/Hazard metadata_Event sets_Events.csv b/examples/full/SFRARR_fluvialhazardmaps/Hazard metadata_Event sets_Events.csv new file mode 100644 index 00000000..02116cd5 --- /dev/null +++ b/examples/full/SFRARR_fluvialhazardmaps/Hazard metadata_Event sets_Events.csv @@ -0,0 +1,16 @@ +Dataset identifier,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232 +Event set identifier,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1 +Event identifier,0064232_EventSet1_KAZ_5,0064232_EventSet1_KAZ_10,0064232_EventSet1_KAZ_20,0064232_EventSet1_KAZ_50,0064232_EventSet1_KAZ_100,0064232_EventSet1_KAZ_200,0064232_EventSet1_KAZ_500,0064232_EventSet1_KAZ_1000,0064232_EventSet1_KGZ_5,0064232_EventSet1_KGZ_10,0064232_EventSet1_KGZ_20,0064232_EventSet1_KGZ_50,0064232_EventSet1_KGZ_100,0064232_EventSet1_KGZ_200,0064232_EventSet1_KGZ_500,0064232_EventSet1_KGZ_1000,0064232_EventSet1_TJK_5,0064232_EventSet1_TJK_10,0064232_EventSet1_TJK_20,0064232_EventSet1_TJK_50,0064232_EventSet1_TJK_100,0064232_EventSet1_TJK_200,0064232_EventSet1_TJK_500,0064232_EventSet1_TJK_1000,0064232_EventSet1_TKM_5,0064232_EventSet1_TKM_10,0064232_EventSet1_TKM_20,0064232_EventSet1_TKM_50,0064232_EventSet1_TKM_100,0064232_EventSet1_TKM_200,0064232_EventSet1_TKM_500,0064232_EventSet1_TKM_1000,0064232_EventSet1_UZB_5,0064232_EventSet1_UZB_10,0064232_EventSet1_UZB_20,0064232_EventSet1_UZB_50,0064232_EventSet1_UZB_100,0064232_EventSet1_UZB_200,0064232_EventSet1_UZB_500,0064232_EventSet1_UZB_1000 +Disaster identifier,n/a,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, +Model calculation method,simulated,simulated,simulated,simulated,simulated,simulated,simulated,simulated,simulated,simulated,simulated,simulated,simulated,simulated,simulated,simulated,simulated,simulated,simulated,simulated,simulated,simulated,simulated,simulated,simulated,simulated,simulated,simulated,simulated,simulated,simulated,simulated,simulated,simulated,simulated,simulated,simulated,simulated,simulated,simulated +"Hazard: +Hazard identifier",0064232_EventSet1_KAZ_5,0064232_EventSet1_KAZ_10,0064232_EventSet1_KAZ_20,0064232_EventSet1_KAZ_50,0064232_EventSet1_KAZ_100,0064232_EventSet1_KAZ_200,0064232_EventSet1_KAZ_500,0064232_EventSet1_KAZ_1000,0064232_EventSet1_KGZ_5,0064232_EventSet1_KGZ_10,0064232_EventSet1_KGZ_20,0064232_EventSet1_KGZ_50,0064232_EventSet1_KGZ_100,0064232_EventSet1_KGZ_200,0064232_EventSet1_KGZ_500,0064232_EventSet1_KGZ_1000,0064232_EventSet1_TJK_5,0064232_EventSet1_TJK_10,0064232_EventSet1_TJK_20,0064232_EventSet1_TJK_50,0064232_EventSet1_TJK_100,0064232_EventSet1_TJK_200,0064232_EventSet1_TJK_500,0064232_EventSet1_TJK_1000,0064232_EventSet1_TKM_5,0064232_EventSet1_TKM_10,0064232_EventSet1_TKM_20,0064232_EventSet1_TKM_50,0064232_EventSet1_TKM_100,0064232_EventSet1_TKM_200,0064232_EventSet1_TKM_500,0064232_EventSet1_TKM_1000,0064232_EventSet1_UZB_5,0064232_EventSet1_UZB_10,0064232_EventSet1_UZB_20,0064232_EventSet1_UZB_50,0064232_EventSet1_UZB_100,0064232_EventSet1_UZB_200,0064232_EventSet1_UZB_500,0064232_EventSet1_UZB_1000 +"Hazard: +Hazard type",flood,flood,flood,flood,flood,flood,flood,flood,flood,flood,flood,flood,flood,flood,flood,flood,flood,flood,flood,flood,flood,flood,flood,flood,flood,flood,flood,flood,flood,flood,flood,flood,flood,flood,flood,flood,flood,flood,flood,flood +"Hazard: +Hazard processes",fluvial_flood,fluvial_flood,fluvial_flood,fluvial_flood,fluvial_flood,fluvial_flood,fluvial_flood,fluvial_flood,fluvial_flood,fluvial_flood,fluvial_flood,fluvial_flood,fluvial_flood,fluvial_flood,fluvial_flood,fluvial_flood,fluvial_flood,fluvial_flood,fluvial_flood,fluvial_flood,fluvial_flood,fluvial_flood,fluvial_flood,fluvial_flood,fluvial_flood,fluvial_flood,fluvial_flood,fluvial_flood,fluvial_flood,fluvial_flood,fluvial_flood,fluvial_flood,fluvial_flood,fluvial_flood,fluvial_flood,fluvial_flood,fluvial_flood,fluvial_flood,fluvial_flood,fluvial_flood +"Hazard: +Intensity measure",fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m +"Occurrence: +Probabilistic frequency: +Return period",5,10,20,50,100,200,500,1000,5,10,20,50,100,200,500,1000,5,10,20,50,100,200,500,1000,5,10,20,50,100,200,500,1000,5,10,20,50,100,200,500,1000 diff --git a/examples/full/SFRARR_fluvialhazardmaps/Hazard metadata_Event sets_Events_Footprints.csv b/examples/full/SFRARR_fluvialhazardmaps/Hazard metadata_Event sets_Events_Footprints.csv new file mode 100644 index 00000000..acd4bbb5 --- /dev/null +++ b/examples/full/SFRARR_fluvialhazardmaps/Hazard metadata_Event sets_Events_Footprints.csv @@ -0,0 +1,5 @@ +Dataset identifier,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232 +Event set identifier,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1 +Event identifier,0064232_EventSet1_KAZ_5,0064232_EventSet1_KAZ_10,0064232_EventSet1_KAZ_20,0064232_EventSet1_KAZ_50,0064232_EventSet1_KAZ_100,0064232_EventSet1_KAZ_200,0064232_EventSet1_KAZ_500,0064232_EventSet1_KAZ_1000,0064232_EventSet1_KGZ_5,0064232_EventSet1_KGZ_10,0064232_EventSet1_KGZ_20,0064232_EventSet1_KGZ_50,0064232_EventSet1_KGZ_100,0064232_EventSet1_KGZ_200,0064232_EventSet1_KGZ_500,0064232_EventSet1_KGZ_1000,0064232_EventSet1_TJK_5,0064232_EventSet1_TJK_10,0064232_EventSet1_TJK_20,0064232_EventSet1_TJK_50,0064232_EventSet1_TJK_100,0064232_EventSet1_TJK_200,0064232_EventSet1_TJK_500,0064232_EventSet1_TJK_1000,0064232_EventSet1_TKM_5,0064232_EventSet1_TKM_10,0064232_EventSet1_TKM_20,0064232_EventSet1_TKM_50,0064232_EventSet1_TKM_100,0064232_EventSet1_TKM_200,0064232_EventSet1_TKM_500,0064232_EventSet1_TKM_1000,0064232_EventSet1_UZB_5,0064232_EventSet1_UZB_10,0064232_EventSet1_UZB_20,0064232_EventSet1_UZB_50,0064232_EventSet1_UZB_100,0064232_EventSet1_UZB_200,0064232_EventSet1_UZB_500,0064232_EventSet1_UZB_1000 +Footprint identifier,0064232_EventSet1_KAZ_5,0064232_EventSet1_KAZ_10,0064232_EventSet1_KAZ_20,0064232_EventSet1_KAZ_50,0064232_EventSet1_KAZ_100,0064232_EventSet1_KAZ_200,0064232_EventSet1_KAZ_500,0064232_EventSet1_KAZ_1000,0064232_EventSet1_KGZ_5,0064232_EventSet1_KGZ_10,0064232_EventSet1_KGZ_20,0064232_EventSet1_KGZ_50,0064232_EventSet1_KGZ_100,0064232_EventSet1_KGZ_200,0064232_EventSet1_KGZ_500,0064232_EventSet1_KGZ_1000,0064232_EventSet1_TJK_5,0064232_EventSet1_TJK_10,0064232_EventSet1_TJK_20,0064232_EventSet1_TJK_50,0064232_EventSet1_TJK_100,0064232_EventSet1_TJK_200,0064232_EventSet1_TJK_500,0064232_EventSet1_TJK_1000,0064232_EventSet1_TKM_5,0064232_EventSet1_TKM_10,0064232_EventSet1_TKM_20,0064232_EventSet1_TKM_50,0064232_EventSet1_TKM_100,0064232_EventSet1_TKM_200,0064232_EventSet1_TKM_500,0064232_EventSet1_TKM_1000,0064232_EventSet1_UZB_5,0064232_EventSet1_UZB_10,0064232_EventSet1_UZB_20,0064232_EventSet1_UZB_50,0064232_EventSet1_UZB_100,0064232_EventSet1_UZB_200,0064232_EventSet1_UZB_500,0064232_EventSet1_UZB_1000 +Hazard intensity measurement,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m,fl_wd:m diff --git a/examples/full/SFRARR_fluvialhazardmaps/Hazard metadata_Event sets_Hazards.csv b/examples/full/SFRARR_fluvialhazardmaps/Hazard metadata_Event sets_Hazards.csv new file mode 100644 index 00000000..dbb986ab --- /dev/null +++ b/examples/full/SFRARR_fluvialhazardmaps/Hazard metadata_Event sets_Hazards.csv @@ -0,0 +1,6 @@ +Dataset identifier,https://datacatalog.worldbank.org/search/dataset/0064232 +Event set identifier,0064232_EventSet1 +Hazard identifier,0064232_EventSet1_FL +Hazard type,flood +Hazard processes,fluvial_flood +Intensity measure,fl_wd:m diff --git a/examples/full/SFRARR_fluvialhazardmaps/Hazard metadata_Event sets_Spatial coverage_Gazetteer entries.csv b/examples/full/SFRARR_fluvialhazardmaps/Hazard metadata_Event sets_Spatial coverage_Gazetteer entries.csv new file mode 100644 index 00000000..9cfde234 --- /dev/null +++ b/examples/full/SFRARR_fluvialhazardmaps/Hazard metadata_Event sets_Spatial coverage_Gazetteer entries.csv @@ -0,0 +1,5 @@ +Dataset identifier,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232 +Event set identifier,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1,0064232_EventSet1 +Gazetteer entry identifier,KAZ,KGZ,TJK,TKM,UZB +Scheme,ISO 3166-1 alpha-3,ISO 3166-1 alpha-3,ISO 3166-1 alpha-3,ISO 3166-1 alpha-3,ISO 3166-1 alpha-3 +Description,Kazakhstan,Kyrgyz Republic,Tajikistan,Turkmenistan,Uzbekistan diff --git a/examples/full/SFRARR_fluvialhazardmaps/Links.csv b/examples/full/SFRARR_fluvialhazardmaps/Links.csv new file mode 100644 index 00000000..74f6da51 --- /dev/null +++ b/examples/full/SFRARR_fluvialhazardmaps/Links.csv @@ -0,0 +1,3 @@ +Dataset identifier,https://datacatalog.worldbank.org/search/dataset/0064232 +Link target,https://raw.githubusercontent.com/GFDRR/rdl-standard/0__2__0/schema/rdls_schema.json +Link relation type,describedby diff --git a/examples/full/SFRARR_fluvialhazardmaps/Referenced by.csv b/examples/full/SFRARR_fluvialhazardmaps/Referenced by.csv new file mode 100644 index 00000000..df274b78 --- /dev/null +++ b/examples/full/SFRARR_fluvialhazardmaps/Referenced by.csv @@ -0,0 +1,6 @@ +Dataset identifier,https://datacatalog.worldbank.org/search/dataset/0064232 +Related resource identifier,0064232_ref1 +Name,Central Asia flood hazard technical report - English version +Author names,Risk Engineering and Development +Publication date,2023-02-09 +URL,https://datacatalogfiles.worldbank.org/ddh-published/0064084/DR0090774/Task3_FloodHazard_Report_r5_EN.pdf?versionId=2023-07-21T17:34:14.1038579Z diff --git a/examples/full/SFRARR_fluvialhazardmaps/Resources.csv b/examples/full/SFRARR_fluvialhazardmaps/Resources.csv new file mode 100644 index 00000000..1d798ccd --- /dev/null +++ b/examples/full/SFRARR_fluvialhazardmaps/Resources.csv @@ -0,0 +1,9 @@ +Dataset identifier,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232,https://datacatalog.worldbank.org/search/dataset/0064232 +Resource identifier,0064232_res1,0064232_res2,0064232_res3,0064232_res4,0064232_res5,0064232_res6 +Resource title,Central Asia fluvial flood hazard maps - defended – KAZ 5-50y RP,Central Asia fluvial flood hazard maps - defended – KAZ 100-1000y RP,Central Asia fluvial flood hazard maps - defended - KGZ,Central Asia fluvial flood hazard maps - defended - TJK,Central Asia fluvial flood hazard maps - defended - TKM,Central Asia fluvial flood hazard maps - defended - UZB +Resource description,"Fluvial flood hazard maps for Central Asia, derived from a regional model. Filenaming: FLU_DEF_XXy_ZZZ.tif (XX= return period, ZZZ= country initials). Cell value gives maximum flood depth (m) expected for the return period of that raster dataset. Due to file size, this is a partial set of data covering 1-in-5-50y return period. See dataset “Central Asia fluvial flood hazard maps - defended – KAZ 100-1000y RP” for the remaining data.","Fluvial flood hazard maps for Central Asia, derived from a regional model. Filenaming: FLU_DEF_XXy_ZZZ.tif (XX= return period, ZZZ= country initials). Cell value gives maximum flood depth (m) expected for the return period of that raster dataset. Due to file size, this is a partial set of data covering 1-in-100-1000y return period. See dataset “Central Asia fluvial flood hazard maps - defended – KaZ 5-50y RP” for the remaining data.","Fluvial flood hazard maps for Central Asia, derived from a regional model. Filenaming: FLU_DEF_XXy_ZZZ.tif (XX= return period, ZZZ= country initials). Cell value gives maximum flood depth (m) expected for the return period of that raster dataset.","Fluvial flood hazard maps for Central Asia, derived from a regional model. Filenaming: FLU_DEF_XXy_ZZZ.tif (XX= return period, ZZZ= country initials). Cell value gives maximum flood depth (m) expected for the return period of that raster dataset.","Fluvial flood hazard maps for Central Asia, derived from a regional model. Filenaming: FLU_DEF_XXy_ZZZ.tif (XX= return period, ZZZ= country initials). Cell value gives maximum flood depth (m) expected for the return period of that raster dataset.","Fluvial flood hazard maps for Central Asia, derived from a regional model. Filenaming: FLU_DEF_XXy_ZZZ.tif (XX= return period, ZZZ= country initials). Cell value gives maximum flood depth (m) expected for the return period of that raster dataset." +Media type,image/tiff,image/tiff,image/tiff,image/tiff,image/tiff,image/tiff +Format,geotiff,geotiff,geotiff,geotiff,geotiff,geotiff +Spatial resolution,90,90,90,90,90,90 +Coordinate reference system,EPSG:4326,EPSG:4326,EPSG:4326,EPSG:4326,EPSG:4326,EPSG:4326 +resources/0/url,https://datacatalogfiles.worldbank.org/ddh-published/0064232/DR0092000/FLU_DEF_KAZ_5-50yRP.zip?versionId=2023-07-11T15:17:06.8346489Z,https://datacatalogfiles.worldbank.org/ddh-published/0064232/DR0092001/FLU_DEF_KAZ_100-1000yRP.zip?versionId=2023-07-11T15:17:09.5061377Z,https://datacatalogfiles.worldbank.org/ddh-published/0064232/DR0091440/FLU_DEF_KGZ.zip?versionId=2023-07-11T15:16:59.0750434Z,https://datacatalogfiles.worldbank.org/ddh-published/0064232/DR0091439/FLU_DEF_TJK.zip?versionId=2023-07-11T15:17:11.4860175Z,https://datacatalogfiles.worldbank.org/ddh-published/0064232/DR0091768/FLU_DEF_TKM.zip?versionId=2023-07-11T15:17:01.5896193Z,https://datacatalogfiles.worldbank.org/ddh-published/0064232/DR0091769/FLU_DEF_UZB.zip?versionId=2023-07-11T15:17:04.1441727Z diff --git a/examples/full/SFRARR_fluvialhazardmaps/Sources.csv b/examples/full/SFRARR_fluvialhazardmaps/Sources.csv new file mode 100644 index 00000000..ac0cfb3a --- /dev/null +++ b/examples/full/SFRARR_fluvialhazardmaps/Sources.csv @@ -0,0 +1,2 @@ +Dataset identifier,https://datacatalog.worldbank.org/search/dataset/0064232 +Source identifier,0064232_1src diff --git a/examples/full/SFRARR_fluvialhazardmaps/Spatial coverage_Gazetteer entries.csv b/examples/full/SFRARR_fluvialhazardmaps/Spatial coverage_Gazetteer entries.csv new file mode 100644 index 00000000..956dd693 --- /dev/null +++ b/examples/full/SFRARR_fluvialhazardmaps/Spatial coverage_Gazetteer entries.csv @@ -0,0 +1,3 @@ +Dataset identifier,https://datacatalog.worldbank.org/search/dataset/0064232 +Gazetteer entry identifier,0064232_gaz1 +Scheme,ISO 3166-1 alpha-3 diff --git a/examples/full/SFRARR_fluvialhazardmaps/datasets.csv b/examples/full/SFRARR_fluvialhazardmaps/datasets.csv new file mode 100644 index 00000000..1553d3dc --- /dev/null +++ b/examples/full/SFRARR_fluvialhazardmaps/datasets.csv @@ -0,0 +1,22 @@ +Dataset identifier,https://datacatalog.worldbank.org/search/dataset/0064232 +Title,Central Asia flood hazard - fluvial flood hazard maps DEFENDED +Description,Simulated fluvial flood hazard maps with the simulated effects of flood protection. +Risk data type,hazard +"Publisher: +Name",World Bank Europe and Central Asia DRM team +"Publisher: +Email address",sfraser@worldbank.org +Dataset version,2 +Dataset purpose,Developed as part of a regional probabilistic flood and earthquake risk assessment under the Strengthening Financial Resilience and Accelerating Risk Reduction in Central Asia program. (https://www.gfdrr.org/en/program/SFRARR-Central-Asia) +Project title,Strengthening Financial Resilience and Accelerating Risk Reduction in Central Asia +"Spatial coverage: +Countries",KAZ;KGZ;TJK;TKM;UZB +"Spatial coverage: +Spatial scale",regional +License,CC-BY-4.0 +"Contact point: +Name",Stuart Fraser +"Contact point: +Email address",sfraser@worldbank.org +"Creator: +Name",Risk Engineering and Development diff --git a/examples/full/SFRARR_fluvialhazardmaps/example.json b/examples/full/SFRARR_fluvialhazardmaps/example.json new file mode 100644 index 00000000..69fae112 --- /dev/null +++ b/examples/full/SFRARR_fluvialhazardmaps/example.json @@ -0,0 +1,1119 @@ +{ + "datasets": [ + { + "id": "https://datacatalog.worldbank.org/search/dataset/0064232", + "title": "Central Asia flood hazard - fluvial flood hazard maps DEFENDED", + "description": "Simulated fluvial flood hazard maps with the simulated effects of flood protection. ", + "risk_data_type": [ + "hazard" + ], + "publisher": { + "name": "World Bank Europe and Central Asia DRM team", + "email": "sfraser@worldbank.org" + }, + "version": "2", + "purpose": "Developed as part of a regional probabilistic flood and earthquake risk assessment under the Strengthening Financial Resilience and Accelerating Risk Reduction in Central Asia program. (https://www.gfdrr.org/en/program/SFRARR-Central-Asia)", + "project": "Strengthening Financial Resilience and Accelerating Risk Reduction in Central Asia ", + "spatial": { + "countries": [ + "KAZ", + "KGZ", + "TJK", + "TKM", + "UZB" + ], + "scale": "regional", + "gazetteerEntries": [ + { + "id": "0064232_gaz1", + "scheme": "ISO 3166-1 alpha-3" + } + ] + }, + "license": "CC-BY-4.0", + "contact_point": { + "name": "Stuart Fraser", + "email": "sfraser@worldbank.org" + }, + "creator": { + "name": "Risk Engineering and Development" + }, + "attributions": [ + { + "id": "0064232_1attr", + "entity": { + "name": "World Bank", + "email": "chuang@worldbank.org", + "url": "http://www.worldbank.org" + }, + "role": "custodian" + } + ], + "sources": [ + { + "id": "0064232_1src" + } + ], + "referenced_by": [ + { + "id": "0064232_ref1", + "name": "Central Asia flood hazard technical report - English version", + "authorNames": [ + "Risk Engineering and Development" + ], + "datePublished": "2023-02-09", + "url": "https://datacatalogfiles.worldbank.org/ddh-published/0064084/DR0090774/Task3_FloodHazard_Report_r5_EN.pdf?versionId=2023-07-21T17:34:14.1038579Z" + } + ], + "resources": [ + { + "id": "0064232_res1", + "title": "Central Asia fluvial flood hazard maps - defended – KAZ 5-50y RP", + "description": "Fluvial flood hazard maps for Central Asia, derived from a regional model. Filenaming: FLU_DEF_XXy_ZZZ.tif (XX= return period, ZZZ= country initials). Cell value gives maximum flood depth (m) expected for the return period of that raster dataset. Due to file size, this is a partial set of data covering 1-in-5-50y return period. See dataset “Central Asia fluvial flood hazard maps - defended – KAZ 100-1000y RP” for the remaining data.", + "media_type": "image/tiff", + "format": "geotiff", + "spatial_resolution": 90, + "coordinate_system": "EPSG:4326", + "download_url": "https://datacatalogfiles.worldbank.org/ddh-published/0064232/DR0092000/FLU_DEF_KAZ_5-50yRP.zip?versionId=2023-07-11T15:17:06.8346489Z" + }, + { + "id": "0064232_res2", + "title": "Central Asia fluvial flood hazard maps - defended – KAZ 100-1000y RP", + "description": "Fluvial flood hazard maps for Central Asia, derived from a regional model. Filenaming: FLU_DEF_XXy_ZZZ.tif (XX= return period, ZZZ= country initials). Cell value gives maximum flood depth (m) expected for the return period of that raster dataset. Due to file size, this is a partial set of data covering 1-in-100-1000y return period. See dataset “Central Asia fluvial flood hazard maps - defended – KaZ 5-50y RP” for the remaining data.", + "media_type": "image/tiff", + "format": "geotiff", + "spatial_resolution": 90, + "coordinate_system": "EPSG:4326", + "download_url": "https://datacatalogfiles.worldbank.org/ddh-published/0064232/DR0092001/FLU_DEF_KAZ_100-1000yRP.zip?versionId=2023-07-11T15:17:09.5061377Z" + }, + { + "id": "0064232_res3", + "title": "Central Asia fluvial flood hazard maps - defended - KGZ", + "description": "Fluvial flood hazard maps for Central Asia, derived from a regional model. Filenaming: FLU_DEF_XXy_ZZZ.tif (XX= return period, ZZZ= country initials). Cell value gives maximum flood depth (m) expected for the return period of that raster dataset.", + "media_type": "image/tiff", + "format": "geotiff", + "spatial_resolution": 90, + "coordinate_system": "EPSG:4326", + "download_url": "https://datacatalogfiles.worldbank.org/ddh-published/0064232/DR0091440/FLU_DEF_KGZ.zip?versionId=2023-07-11T15:16:59.0750434Z" + }, + { + "id": "0064232_res4", + "title": "Central Asia fluvial flood hazard maps - defended - TJK", + "description": "Fluvial flood hazard maps for Central Asia, derived from a regional model. Filenaming: FLU_DEF_XXy_ZZZ.tif (XX= return period, ZZZ= country initials). Cell value gives maximum flood depth (m) expected for the return period of that raster dataset.", + "media_type": "image/tiff", + "format": "geotiff", + "spatial_resolution": 90, + "coordinate_system": "EPSG:4326", + "download_url": "https://datacatalogfiles.worldbank.org/ddh-published/0064232/DR0091439/FLU_DEF_TJK.zip?versionId=2023-07-11T15:17:11.4860175Z" + }, + { + "id": "0064232_res5", + "title": "Central Asia fluvial flood hazard maps - defended - TKM", + "description": "Fluvial flood hazard maps for Central Asia, derived from a regional model. Filenaming: FLU_DEF_XXy_ZZZ.tif (XX= return period, ZZZ= country initials). Cell value gives maximum flood depth (m) expected for the return period of that raster dataset.", + "media_type": "image/tiff", + "format": "geotiff", + "spatial_resolution": 90, + "coordinate_system": "EPSG:4326", + "download_url": "https://datacatalogfiles.worldbank.org/ddh-published/0064232/DR0091768/FLU_DEF_TKM.zip?versionId=2023-07-11T15:17:01.5896193Z" + }, + { + "id": "0064232_res6", + "title": "Central Asia fluvial flood hazard maps - defended - UZB", + "description": "Fluvial flood hazard maps for Central Asia, derived from a regional model. Filenaming: FLU_DEF_XXy_ZZZ.tif (XX= return period, ZZZ= country initials). Cell value gives maximum flood depth (m) expected for the return period of that raster dataset.", + "media_type": "image/tiff", + "format": "geotiff", + "spatial_resolution": 90, + "coordinate_system": "EPSG:4326", + "download_url": "https://datacatalogfiles.worldbank.org/ddh-published/0064232/DR0091769/FLU_DEF_UZB.zip?versionId=2023-07-11T15:17:04.1441727Z" + } + ], + "hazard": { + "event_sets": [ + { + "id": "0064232_EventSet1", + "analysis_type": "probabilistic", + "seasonality": "uniform", + "calculation_method": "simulated", + "event_count": 10000, + "spatial": { + "countries": [ + "KAZ", + "KGZ", + "TJK", + "TKM", + "UZB" + ], + "scale": "regional", + "gazetteerEntries": [ + { + "id": "KAZ", + "scheme": "ISO 3166-1 alpha-3", + "description": "Kazakhstan" + }, + { + "id": "KGZ", + "scheme": "ISO 3166-1 alpha-3", + "description": "Kyrgyz Republic" + }, + { + "id": "TJK", + "scheme": "ISO 3166-1 alpha-3", + "description": "Tajikistan" + }, + { + "id": "TKM", + "scheme": "ISO 3166-1 alpha-3", + "description": "Turkmenistan" + }, + { + "id": "UZB", + "scheme": "ISO 3166-1 alpha-3", + "description": "Uzbekistan" + } + ] + }, + "hazards": [ + { + "id": "0064232_EventSet1_FL", + "type": "flood", + "processes": [ + "fluvial_flood" + ], + "intensity_measure": "fl_wd:m" + } + ], + "events": [ + { + "id": "0064232_EventSet1_KAZ_5", + "disaster_identifier": "n/a", + "calculation_method": "simulated", + "hazard": { + "id": "0064232_EventSet1_KAZ_5", + "type": "flood", + "processes": [ + "fluvial_flood" + ], + "intensity_measure": "fl_wd:m" + }, + "occurrence": { + "probabilistic": { + "return_period": 5 + } + }, + "footprints": [ + { + "id": "0064232_EventSet1_KAZ_5", + "intensity_measure": "fl_wd:m" + } + ] + }, + { + "id": "0064232_EventSet1_KAZ_10", + "calculation_method": "simulated", + "hazard": { + "id": "0064232_EventSet1_KAZ_10", + "type": "flood", + "processes": [ + "fluvial_flood" + ], + "intensity_measure": "fl_wd:m" + }, + "occurrence": { + "probabilistic": { + "return_period": 10 + } + }, + "footprints": [ + { + "id": "0064232_EventSet1_KAZ_10", + "intensity_measure": "fl_wd:m" + } + ] + }, + { + "id": "0064232_EventSet1_KAZ_20", + "calculation_method": "simulated", + "hazard": { + "id": "0064232_EventSet1_KAZ_20", + "type": "flood", + "processes": [ + "fluvial_flood" + ], + "intensity_measure": "fl_wd:m" + }, + "occurrence": { + "probabilistic": { + "return_period": 20 + } + }, + "footprints": [ + { + "id": "0064232_EventSet1_KAZ_20", + "intensity_measure": "fl_wd:m" + } + ] + }, + { + "id": "0064232_EventSet1_KAZ_50", + "calculation_method": "simulated", + "hazard": { + "id": "0064232_EventSet1_KAZ_50", + "type": "flood", + "processes": [ + "fluvial_flood" + ], + "intensity_measure": "fl_wd:m" + }, + "occurrence": { + "probabilistic": { + "return_period": 50 + } + }, + "footprints": [ + { + "id": "0064232_EventSet1_KAZ_50", + "intensity_measure": "fl_wd:m" + } + ] + }, + { + "id": "0064232_EventSet1_KAZ_100", + "calculation_method": "simulated", + "hazard": { + "id": "0064232_EventSet1_KAZ_100", + "type": "flood", + "processes": [ + "fluvial_flood" + ], + "intensity_measure": "fl_wd:m" + }, + "occurrence": { + "probabilistic": { + "return_period": 100 + } + }, + "footprints": [ + { + "id": "0064232_EventSet1_KAZ_100", + "intensity_measure": "fl_wd:m" + } + ] + }, + { + "id": "0064232_EventSet1_KAZ_200", + "calculation_method": "simulated", + "hazard": { + "id": "0064232_EventSet1_KAZ_200", + "type": "flood", + "processes": [ + "fluvial_flood" + ], + "intensity_measure": "fl_wd:m" + }, + "occurrence": { + "probabilistic": { + "return_period": 200 + } + }, + "footprints": [ + { + "id": "0064232_EventSet1_KAZ_200", + "intensity_measure": "fl_wd:m" + } + ] + }, + { + "id": "0064232_EventSet1_KAZ_500", + "calculation_method": "simulated", + "hazard": { + "id": "0064232_EventSet1_KAZ_500", + "type": "flood", + "processes": [ + "fluvial_flood" + ], + "intensity_measure": "fl_wd:m" + }, + "occurrence": { + "probabilistic": { + "return_period": 500 + } + }, + "footprints": [ + { + "id": "0064232_EventSet1_KAZ_500", + "intensity_measure": "fl_wd:m" + } + ] + }, + { + "id": "0064232_EventSet1_KAZ_1000", + "calculation_method": "simulated", + "hazard": { + "id": "0064232_EventSet1_KAZ_1000", + "type": "flood", + "processes": [ + "fluvial_flood" + ], + "intensity_measure": "fl_wd:m" + }, + "occurrence": { + "probabilistic": { + "return_period": 1000 + } + }, + "footprints": [ + { + "id": "0064232_EventSet1_KAZ_1000", + "intensity_measure": "fl_wd:m" + } + ] + }, + { + "id": "0064232_EventSet1_KGZ_5", + "calculation_method": "simulated", + "hazard": { + "id": "0064232_EventSet1_KGZ_5", + "type": "flood", + "processes": [ + "fluvial_flood" + ], + "intensity_measure": "fl_wd:m" + }, + "occurrence": { + "probabilistic": { + "return_period": 5 + } + }, + "footprints": [ + { + "id": "0064232_EventSet1_KGZ_5", + "intensity_measure": "fl_wd:m" + } + ] + }, + { + "id": "0064232_EventSet1_KGZ_10", + "calculation_method": "simulated", + "hazard": { + "id": "0064232_EventSet1_KGZ_10", + "type": "flood", + "processes": [ + "fluvial_flood" + ], + "intensity_measure": "fl_wd:m" + }, + "occurrence": { + "probabilistic": { + "return_period": 10 + } + }, + "footprints": [ + { + "id": "0064232_EventSet1_KGZ_10", + "intensity_measure": "fl_wd:m" + } + ] + }, + { + "id": "0064232_EventSet1_KGZ_20", + "calculation_method": "simulated", + "hazard": { + "id": "0064232_EventSet1_KGZ_20", + "type": "flood", + "processes": [ + "fluvial_flood" + ], + "intensity_measure": "fl_wd:m" + }, + "occurrence": { + "probabilistic": { + "return_period": 20 + } + }, + "footprints": [ + { + "id": "0064232_EventSet1_KGZ_20", + "intensity_measure": "fl_wd:m" + } + ] + }, + { + "id": "0064232_EventSet1_KGZ_50", + "calculation_method": "simulated", + "hazard": { + "id": "0064232_EventSet1_KGZ_50", + "type": "flood", + "processes": [ + "fluvial_flood" + ], + "intensity_measure": "fl_wd:m" + }, + "occurrence": { + "probabilistic": { + "return_period": 50 + } + }, + "footprints": [ + { + "id": "0064232_EventSet1_KGZ_50", + "intensity_measure": "fl_wd:m" + } + ] + }, + { + "id": "0064232_EventSet1_KGZ_100", + "calculation_method": "simulated", + "hazard": { + "id": "0064232_EventSet1_KGZ_100", + "type": "flood", + "processes": [ + "fluvial_flood" + ], + "intensity_measure": "fl_wd:m" + }, + "occurrence": { + "probabilistic": { + "return_period": 100 + } + }, + "footprints": [ + { + "id": "0064232_EventSet1_KGZ_100", + "intensity_measure": "fl_wd:m" + } + ] + }, + { + "id": "0064232_EventSet1_KGZ_200", + "calculation_method": "simulated", + "hazard": { + "id": "0064232_EventSet1_KGZ_200", + "type": "flood", + "processes": [ + "fluvial_flood" + ], + "intensity_measure": "fl_wd:m" + }, + "occurrence": { + "probabilistic": { + "return_period": 200 + } + }, + "footprints": [ + { + "id": "0064232_EventSet1_KGZ_200", + "intensity_measure": "fl_wd:m" + } + ] + }, + { + "id": "0064232_EventSet1_KGZ_500", + "calculation_method": "simulated", + "hazard": { + "id": "0064232_EventSet1_KGZ_500", + "type": "flood", + "processes": [ + "fluvial_flood" + ], + "intensity_measure": "fl_wd:m" + }, + "occurrence": { + "probabilistic": { + "return_period": 500 + } + }, + "footprints": [ + { + "id": "0064232_EventSet1_KGZ_500", + "intensity_measure": "fl_wd:m" + } + ] + }, + { + "id": "0064232_EventSet1_KGZ_1000", + "calculation_method": "simulated", + "hazard": { + "id": "0064232_EventSet1_KGZ_1000", + "type": "flood", + "processes": [ + "fluvial_flood" + ], + "intensity_measure": "fl_wd:m" + }, + "occurrence": { + "probabilistic": { + "return_period": 1000 + } + }, + "footprints": [ + { + "id": "0064232_EventSet1_KGZ_1000", + "intensity_measure": "fl_wd:m" + } + ] + }, + { + "id": "0064232_EventSet1_TJK_5", + "calculation_method": "simulated", + "hazard": { + "id": "0064232_EventSet1_TJK_5", + "type": "flood", + "processes": [ + "fluvial_flood" + ], + "intensity_measure": "fl_wd:m" + }, + "occurrence": { + "probabilistic": { + "return_period": 5 + } + }, + "footprints": [ + { + "id": "0064232_EventSet1_TJK_5", + "intensity_measure": "fl_wd:m" + } + ] + }, + { + "id": "0064232_EventSet1_TJK_10", + "calculation_method": "simulated", + "hazard": { + "id": "0064232_EventSet1_TJK_10", + "type": "flood", + "processes": [ + "fluvial_flood" + ], + "intensity_measure": "fl_wd:m" + }, + "occurrence": { + "probabilistic": { + "return_period": 10 + } + }, + "footprints": [ + { + "id": "0064232_EventSet1_TJK_10", + "intensity_measure": "fl_wd:m" + } + ] + }, + { + "id": "0064232_EventSet1_TJK_20", + "calculation_method": "simulated", + "hazard": { + "id": "0064232_EventSet1_TJK_20", + "type": "flood", + "processes": [ + "fluvial_flood" + ], + "intensity_measure": "fl_wd:m" + }, + "occurrence": { + "probabilistic": { + "return_period": 20 + } + }, + "footprints": [ + { + "id": "0064232_EventSet1_TJK_20", + "intensity_measure": "fl_wd:m" + } + ] + }, + { + "id": "0064232_EventSet1_TJK_50", + "calculation_method": "simulated", + "hazard": { + "id": "0064232_EventSet1_TJK_50", + "type": "flood", + "processes": [ + "fluvial_flood" + ], + "intensity_measure": "fl_wd:m" + }, + "occurrence": { + "probabilistic": { + "return_period": 50 + } + }, + "footprints": [ + { + "id": "0064232_EventSet1_TJK_50", + "intensity_measure": "fl_wd:m" + } + ] + }, + { + "id": "0064232_EventSet1_TJK_100", + "calculation_method": "simulated", + "hazard": { + "id": "0064232_EventSet1_TJK_100", + "type": "flood", + "processes": [ + "fluvial_flood" + ], + "intensity_measure": "fl_wd:m" + }, + "occurrence": { + "probabilistic": { + "return_period": 100 + } + }, + "footprints": [ + { + "id": "0064232_EventSet1_TJK_100", + "intensity_measure": "fl_wd:m" + } + ] + }, + { + "id": "0064232_EventSet1_TJK_200", + "calculation_method": "simulated", + "hazard": { + "id": "0064232_EventSet1_TJK_200", + "type": "flood", + "processes": [ + "fluvial_flood" + ], + "intensity_measure": "fl_wd:m" + }, + "occurrence": { + "probabilistic": { + "return_period": 200 + } + }, + "footprints": [ + { + "id": "0064232_EventSet1_TJK_200", + "intensity_measure": "fl_wd:m" + } + ] + }, + { + "id": "0064232_EventSet1_TJK_500", + "calculation_method": "simulated", + "hazard": { + "id": "0064232_EventSet1_TJK_500", + "type": "flood", + "processes": [ + "fluvial_flood" + ], + "intensity_measure": "fl_wd:m" + }, + "occurrence": { + "probabilistic": { + "return_period": 500 + } + }, + "footprints": [ + { + "id": "0064232_EventSet1_TJK_500", + "intensity_measure": "fl_wd:m" + } + ] + }, + { + "id": "0064232_EventSet1_TJK_1000", + "calculation_method": "simulated", + "hazard": { + "id": "0064232_EventSet1_TJK_1000", + "type": "flood", + "processes": [ + "fluvial_flood" + ], + "intensity_measure": "fl_wd:m" + }, + "occurrence": { + "probabilistic": { + "return_period": 1000 + } + }, + "footprints": [ + { + "id": "0064232_EventSet1_TJK_1000", + "intensity_measure": "fl_wd:m" + } + ] + }, + { + "id": "0064232_EventSet1_TKM_5", + "calculation_method": "simulated", + "hazard": { + "id": "0064232_EventSet1_TKM_5", + "type": "flood", + "processes": [ + "fluvial_flood" + ], + "intensity_measure": "fl_wd:m" + }, + "occurrence": { + "probabilistic": { + "return_period": 5 + } + }, + "footprints": [ + { + "id": "0064232_EventSet1_TKM_5", + "intensity_measure": "fl_wd:m" + } + ] + }, + { + "id": "0064232_EventSet1_TKM_10", + "calculation_method": "simulated", + "hazard": { + "id": "0064232_EventSet1_TKM_10", + "type": "flood", + "processes": [ + "fluvial_flood" + ], + "intensity_measure": "fl_wd:m" + }, + "occurrence": { + "probabilistic": { + "return_period": 10 + } + }, + "footprints": [ + { + "id": "0064232_EventSet1_TKM_10", + "intensity_measure": "fl_wd:m" + } + ] + }, + { + "id": "0064232_EventSet1_TKM_20", + "calculation_method": "simulated", + "hazard": { + "id": "0064232_EventSet1_TKM_20", + "type": "flood", + "processes": [ + "fluvial_flood" + ], + "intensity_measure": "fl_wd:m" + }, + "occurrence": { + "probabilistic": { + "return_period": 20 + } + }, + "footprints": [ + { + "id": "0064232_EventSet1_TKM_20", + "intensity_measure": "fl_wd:m" + } + ] + }, + { + "id": "0064232_EventSet1_TKM_50", + "calculation_method": "simulated", + "hazard": { + "id": "0064232_EventSet1_TKM_50", + "type": "flood", + "processes": [ + "fluvial_flood" + ], + "intensity_measure": "fl_wd:m" + }, + "occurrence": { + "probabilistic": { + "return_period": 50 + } + }, + "footprints": [ + { + "id": "0064232_EventSet1_TKM_50", + "intensity_measure": "fl_wd:m" + } + ] + }, + { + "id": "0064232_EventSet1_TKM_100", + "calculation_method": "simulated", + "hazard": { + "id": "0064232_EventSet1_TKM_100", + "type": "flood", + "processes": [ + "fluvial_flood" + ], + "intensity_measure": "fl_wd:m" + }, + "occurrence": { + "probabilistic": { + "return_period": 100 + } + }, + "footprints": [ + { + "id": "0064232_EventSet1_TKM_100", + "intensity_measure": "fl_wd:m" + } + ] + }, + { + "id": "0064232_EventSet1_TKM_200", + "calculation_method": "simulated", + "hazard": { + "id": "0064232_EventSet1_TKM_200", + "type": "flood", + "processes": [ + "fluvial_flood" + ], + "intensity_measure": "fl_wd:m" + }, + "occurrence": { + "probabilistic": { + "return_period": 200 + } + }, + "footprints": [ + { + "id": "0064232_EventSet1_TKM_200", + "intensity_measure": "fl_wd:m" + } + ] + }, + { + "id": "0064232_EventSet1_TKM_500", + "calculation_method": "simulated", + "hazard": { + "id": "0064232_EventSet1_TKM_500", + "type": "flood", + "processes": [ + "fluvial_flood" + ], + "intensity_measure": "fl_wd:m" + }, + "occurrence": { + "probabilistic": { + "return_period": 500 + } + }, + "footprints": [ + { + "id": "0064232_EventSet1_TKM_500", + "intensity_measure": "fl_wd:m" + } + ] + }, + { + "id": "0064232_EventSet1_TKM_1000", + "calculation_method": "simulated", + "hazard": { + "id": "0064232_EventSet1_TKM_1000", + "type": "flood", + "processes": [ + "fluvial_flood" + ], + "intensity_measure": "fl_wd:m" + }, + "occurrence": { + "probabilistic": { + "return_period": 1000 + } + }, + "footprints": [ + { + "id": "0064232_EventSet1_TKM_1000", + "intensity_measure": "fl_wd:m" + } + ] + }, + { + "id": "0064232_EventSet1_UZB_5", + "calculation_method": "simulated", + "hazard": { + "id": "0064232_EventSet1_UZB_5", + "type": "flood", + "processes": [ + "fluvial_flood" + ], + "intensity_measure": "fl_wd:m" + }, + "occurrence": { + "probabilistic": { + "return_period": 5 + } + }, + "footprints": [ + { + "id": "0064232_EventSet1_UZB_5", + "intensity_measure": "fl_wd:m" + } + ] + }, + { + "id": "0064232_EventSet1_UZB_10", + "calculation_method": "simulated", + "hazard": { + "id": "0064232_EventSet1_UZB_10", + "type": "flood", + "processes": [ + "fluvial_flood" + ], + "intensity_measure": "fl_wd:m" + }, + "occurrence": { + "probabilistic": { + "return_period": 10 + } + }, + "footprints": [ + { + "id": "0064232_EventSet1_UZB_10", + "intensity_measure": "fl_wd:m" + } + ] + }, + { + "id": "0064232_EventSet1_UZB_20", + "calculation_method": "simulated", + "hazard": { + "id": "0064232_EventSet1_UZB_20", + "type": "flood", + "processes": [ + "fluvial_flood" + ], + "intensity_measure": "fl_wd:m" + }, + "occurrence": { + "probabilistic": { + "return_period": 20 + } + }, + "footprints": [ + { + "id": "0064232_EventSet1_UZB_20", + "intensity_measure": "fl_wd:m" + } + ] + }, + { + "id": "0064232_EventSet1_UZB_50", + "calculation_method": "simulated", + "hazard": { + "id": "0064232_EventSet1_UZB_50", + "type": "flood", + "processes": [ + "fluvial_flood" + ], + "intensity_measure": "fl_wd:m" + }, + "occurrence": { + "probabilistic": { + "return_period": 50 + } + }, + "footprints": [ + { + "id": "0064232_EventSet1_UZB_50", + "intensity_measure": "fl_wd:m" + } + ] + }, + { + "id": "0064232_EventSet1_UZB_100", + "calculation_method": "simulated", + "hazard": { + "id": "0064232_EventSet1_UZB_100", + "type": "flood", + "processes": [ + "fluvial_flood" + ], + "intensity_measure": "fl_wd:m" + }, + "occurrence": { + "probabilistic": { + "return_period": 100 + } + }, + "footprints": [ + { + "id": "0064232_EventSet1_UZB_100", + "intensity_measure": "fl_wd:m" + } + ] + }, + { + "id": "0064232_EventSet1_UZB_200", + "calculation_method": "simulated", + "hazard": { + "id": "0064232_EventSet1_UZB_200", + "type": "flood", + "processes": [ + "fluvial_flood" + ], + "intensity_measure": "fl_wd:m" + }, + "occurrence": { + "probabilistic": { + "return_period": 200 + } + }, + "footprints": [ + { + "id": "0064232_EventSet1_UZB_200", + "intensity_measure": "fl_wd:m" + } + ] + }, + { + "id": "0064232_EventSet1_UZB_500", + "calculation_method": "simulated", + "hazard": { + "id": "0064232_EventSet1_UZB_500", + "type": "flood", + "processes": [ + "fluvial_flood" + ], + "intensity_measure": "fl_wd:m" + }, + "occurrence": { + "probabilistic": { + "return_period": 500 + } + }, + "footprints": [ + { + "id": "0064232_EventSet1_UZB_500", + "intensity_measure": "fl_wd:m" + } + ] + }, + { + "id": "0064232_EventSet1_UZB_1000", + "calculation_method": "simulated", + "hazard": { + "id": "0064232_EventSet1_UZB_1000", + "type": "flood", + "processes": [ + "fluvial_flood" + ], + "intensity_measure": "fl_wd:m" + }, + "occurrence": { + "probabilistic": { + "return_period": 1000 + } + }, + "footprints": [ + { + "id": "0064232_EventSet1_UZB_1000", + "intensity_measure": "fl_wd:m" + } + ] + } + ] + } + ] + }, + "links": [ + { + "href": "https://raw.githubusercontent.com/GFDRR/rdl-standard/0__2__0/schema/rdls_schema.json", + "rel": "describedby" + } + ] + } + ] +} diff --git a/examples/hazard/aqueduct/Hazard metadata_Event sets.csv b/examples/hazard/aqueduct/Hazard metadata_Event sets.csv new file mode 100644 index 00000000..d4f65773 --- /dev/null +++ b/examples/hazard/aqueduct/Hazard metadata_Event sets.csv @@ -0,0 +1,8 @@ +Dataset identifier,https://www.wri.org/data/aqueduct-floods-hazard-maps +Event set identifier,1 +Analysis type,probabilistic +Calculation Method,simulated +Event count,10 +Occurrence range,1/2 to 1/1000 years +"Spatial coverage: +Spatial scale",global diff --git a/examples/hazard/aqueduct/Hazard metadata_Event sets_Hazards.csv b/examples/hazard/aqueduct/Hazard metadata_Event sets_Hazards.csv new file mode 100644 index 00000000..f0bf1995 --- /dev/null +++ b/examples/hazard/aqueduct/Hazard metadata_Event sets_Hazards.csv @@ -0,0 +1,6 @@ +Dataset identifier,https://www.wri.org/data/aqueduct-floods-hazard-maps,https://www.wri.org/data/aqueduct-floods-hazard-maps +Event set identifier,1,1 +Hazard identifier,1,2 +Hazard type,flood,flood +Hazard processes,fluvial_flood,coastal_flood +Intensity measure,fl_wd:m,fl_wd:m diff --git a/examples/hazard/aqueduct/Links.csv b/examples/hazard/aqueduct/Links.csv new file mode 100644 index 00000000..5310cc7e --- /dev/null +++ b/examples/hazard/aqueduct/Links.csv @@ -0,0 +1,3 @@ +Dataset identifier,https://www.wri.org/data/aqueduct-floods-hazard-maps +Link target,https://raw.githubusercontent.com/GFDRR/rdl-standard/0__2__0/schema/rdls_schema.json +Link relation type,describedby diff --git a/examples/hazard/aqueduct/Resources.csv b/examples/hazard/aqueduct/Resources.csv new file mode 100644 index 00000000..efa0df74 --- /dev/null +++ b/examples/hazard/aqueduct/Resources.csv @@ -0,0 +1,8 @@ +Dataset identifier,https://www.wri.org/data/aqueduct-floods-hazard-maps +Resource identifier,1 +Resource title,Flood hazard maps +Resource description,Collection of fluvial and pluvial hazard maps; baseline and climate scenarios +Format,geotiff +Spatial resolution,1000 +Coordinate reference system,EPSG:4326 +resources/0/url,http://wri-projects.s3.amazonaws.com/AqueductFloodTool/download/v2/index.html diff --git a/examples/hazard/aqueduct/datasets.csv b/examples/hazard/aqueduct/datasets.csv new file mode 100644 index 00000000..b483bdef --- /dev/null +++ b/examples/hazard/aqueduct/datasets.csv @@ -0,0 +1,20 @@ +Dataset identifier,https://www.wri.org/data/aqueduct-floods-hazard-maps +Title,Aqueduct Floods Hazard Maps +Description,"Aqueduct Floods is an online platform that measures riverine and coastal flood risks under both current baseline conditions and future projections in 2030, 2050, an 2080. In addition to providing hazard maps and assessing risks, Aqueduct Floods enables its users to conduct comprehensive cost-benefit analysis to evaluate the value of dike flood protection strategies." +Risk data type,hazard +"Publisher: +Name",Water Resource Institute +"Publisher: +URL",https://www.wri.org +Dataset version,2020 +Project title,Aqueduct +Additional details,"The Aqueduct flood-hazard model is a global gridded dataset of flood hazard produced at the global scale. It provides flood water extent and depth for a range of pluvial and fluvial hazard scenarios, expressed as “return period”, which indicates the probability of occurrence (i.e. once in 2, 5, 10, 20, 50, 100, 250, 500 and 1000 years). The Data are at 1 km resolution and have a global coverage." +"Spatial coverage: +Spatial scale",global +"Contact point: +Name",Mattia Amadio +"Contact point: +Email address",mamadio@worldbank.org +"Creator: +Name",Water Resource Institute +License,CC-BY-4.0 diff --git a/examples/hazard/aqueduct/example.json b/examples/hazard/aqueduct/example.json new file mode 100644 index 00000000..30467081 --- /dev/null +++ b/examples/hazard/aqueduct/example.json @@ -0,0 +1,79 @@ +{ + "datasets": [ + { + "id": "https://www.wri.org/data/aqueduct-floods-hazard-maps", + "title": "Aqueduct Floods Hazard Maps", + "description": "Aqueduct Floods is an online platform that measures riverine and coastal flood risks under both current baseline conditions and future projections in 2030, 2050, an 2080. In addition to providing hazard maps and assessing risks, Aqueduct Floods enables its users to conduct comprehensive cost-benefit analysis to evaluate the value of dike flood protection strategies.", + "risk_data_type": [ + "hazard" + ], + "publisher": { + "name": "Water Resource Institute", + "url": "https://www.wri.org" + }, + "version": "2020", + "project": "Aqueduct", + "details": "The Aqueduct flood-hazard model is a global gridded dataset of flood hazard produced at the global scale. It provides flood water extent and depth for a range of pluvial and fluvial hazard scenarios, expressed as “return period”, which indicates the probability of occurrence (i.e. once in 2, 5, 10, 20, 50, 100, 250, 500 and 1000 years). The Data are at 1 km resolution and have a global coverage.", + "spatial": { + "scale": "global" + }, + "contact_point": { + "name": "Mattia Amadio", + "email": "mamadio@worldbank.org" + }, + "creator": { + "name": "Water Resource Institute" + }, + "license": "CC-BY-4.0", + "resources": [ + { + "id": "1", + "title": "Flood hazard maps ", + "description": "Collection of fluvial and pluvial hazard maps; baseline and climate scenarios", + "format": "geotiff", + "spatial_resolution": 1000, + "coordinate_system": "EPSG:4326", + "access_url": "http://wri-projects.s3.amazonaws.com/AqueductFloodTool/download/v2/index.html" + } + ], + "hazard": { + "event_sets": [ + { + "id": "1", + "analysis_type": "probabilistic", + "calculation_method": "simulated", + "event_count": 10, + "occurrence_range": "1/2 to 1/1000 years", + "spatial": { + "scale": "global" + }, + "hazards": [ + { + "id": "1", + "type": "flood", + "processes": [ + "fluvial_flood" + ], + "intensity_measure": "fl_wd:m" + }, + { + "id": "2", + "type": "flood", + "processes": [ + "coastal_flood" + ], + "intensity_measure": "fl_wd:m" + } + ] + } + ] + }, + "links": [ + { + "href": "https://raw.githubusercontent.com/GFDRR/rdl-standard/0__2__0/schema/rdls_schema.json", + "rel": "describedby" + } + ] + } + ] +} diff --git a/examples/hazard/aqueduct/figure.png b/examples/hazard/aqueduct/figure.png new file mode 100644 index 00000000..b02715fe Binary files /dev/null and b/examples/hazard/aqueduct/figure.png differ diff --git a/examples/hazard/fathom/Hazard metadata_Event sets.csv b/examples/hazard/fathom/Hazard metadata_Event sets.csv new file mode 100644 index 00000000..b885f4e0 --- /dev/null +++ b/examples/hazard/fathom/Hazard metadata_Event sets.csv @@ -0,0 +1,8 @@ +Dataset identifier,FTH_example +Event set identifier,1 +Analysis type,probabilistic +Calculation Method,simulated +Event count,10 +Occurrence range,1/10 to 1/1000 years +"Spatial coverage: +Spatial scale",global diff --git a/examples/hazard/fathom/Hazard metadata_Event sets_Hazards.csv b/examples/hazard/fathom/Hazard metadata_Event sets_Hazards.csv new file mode 100644 index 00000000..1869b6c2 --- /dev/null +++ b/examples/hazard/fathom/Hazard metadata_Event sets_Hazards.csv @@ -0,0 +1,6 @@ +Dataset identifier,FTH_example,FTH_example +Event set identifier,1,1 +Hazard identifier,1,2 +Hazard type,flood,flood +Hazard processes,fluvial_flood,pluvial_flood +Intensity measure,fl_wd:m,fl_wd:m diff --git a/examples/hazard/fathom/Links.csv b/examples/hazard/fathom/Links.csv new file mode 100644 index 00000000..fcfe7cef --- /dev/null +++ b/examples/hazard/fathom/Links.csv @@ -0,0 +1,3 @@ +Dataset identifier,FTH_example +Link target,https://raw.githubusercontent.com/GFDRR/rdl-standard/0__2__0/schema/rdls_schema.json +Link relation type,describedby diff --git a/examples/hazard/fathom/Resources.csv b/examples/hazard/fathom/Resources.csv new file mode 100644 index 00000000..f09d1298 --- /dev/null +++ b/examples/hazard/fathom/Resources.csv @@ -0,0 +1,8 @@ +Dataset identifier,FTH_example,FTH_example,FTH_example +Resource identifier,1,2,3 +Resource title,Fluvial hazard - Undefended,Fluvial hazard - Defended,Pluvial hazard - Undefended +Resource description,"Fluvial flood hazard maps (10), not accounting any flood defence","Fluvial flood hazard maps (10), accounting for flood defence (estimate)","Pluvial flood hazard maps (10), not accounting any flood defence" +Format,geotiff,geotiff,geotiff +Spatial resolution,90,90,90 +Coordinate reference system,EPSG:4326,EPSG:4326,EPSG:4326 +resources/0/url,http://example.com/FTH-THA-fluvial-undefended,http://example.com/FTH-THA-fluvial-defended,http://example.com/FTH-THA-pluvial-undefended diff --git a/examples/hazard/fathom/datasets.csv b/examples/hazard/fathom/datasets.csv new file mode 100644 index 00000000..d518544c --- /dev/null +++ b/examples/hazard/fathom/datasets.csv @@ -0,0 +1,24 @@ +Dataset identifier,FTH_example +Title,FATHOM flood hazard maps +Description,Probabilistic modelling of fluvial and pluvial flood hazard +Risk data type,hazard +"Publisher: +Name",Fathom +"Publisher: +URL",https://www.fathom.global/ +Dataset version,2 +Additional details,"The FATHOM flood-hazard model (previously known as SSBN), is a global gridded dataset of flood hazard produced at the global scale. It provides flood water extent and depth for a range of pluvial and fluvial hazard scenarios, expressed as “return period”, which indicates the probability of occurrence (i.e. once in 5, 10, 20, 50, 75, 100, 200, 250, 500, 750 and 1000 years). The Data are at 3 arc second (approximately 90m) resolution and have a global coverage between 56°S and 60°N. Each country set includes three subsets: +- Fluvial Undefended (FU): no flood defence accounted +- Fluvial Defended (FD): flood defence estimated by protection standards proxied by GDP (FloProS) +- Pluvial Undefended (PU): pluvial cumulation hazard maps, no flood defence accounted" +"Spatial coverage: +Spatial scale",national +License,commercial +"Contact point: +Name",Mattia Amadio +"Contact point: +Email address",mamadio@worldbank.org +"Creator: +Name",Mattia Amadio +"Creator: +Email address",mamadio@worldbank.org diff --git a/examples/hazard/fathom/example.json b/examples/hazard/fathom/example.json new file mode 100644 index 00000000..150650fe --- /dev/null +++ b/examples/hazard/fathom/example.json @@ -0,0 +1,97 @@ +{ + "datasets": [ + { + "id": "FTH_example", + "title": "FATHOM flood hazard maps", + "description": "Probabilistic modelling of fluvial and pluvial flood hazard", + "risk_data_type": [ + "hazard" + ], + "publisher": { + "name": "Fathom", + "url": "https://www.fathom.global/" + }, + "version": "2", + "details": "The FATHOM flood-hazard model (previously known as SSBN), is a global gridded dataset of flood hazard produced at the global scale. It provides flood water extent and depth for a range of pluvial and fluvial hazard scenarios, expressed as “return period”, which indicates the probability of occurrence (i.e. once in 5, 10, 20, 50, 75, 100, 200, 250, 500, 750 and 1000 years). The Data are at 3 arc second (approximately 90m) resolution and have a global coverage between 56°S and 60°N. Each country set includes three subsets:\n- Fluvial Undefended (FU): no flood defence accounted\n- Fluvial Defended (FD): flood defence estimated by protection standards proxied by GDP (FloProS)\n- Pluvial Undefended (PU): pluvial cumulation hazard maps, no flood defence accounted", + "spatial": { + "scale": "national" + }, + "license": "commercial", + "contact_point": { + "name": "Mattia Amadio", + "email": "mamadio@worldbank.org" + }, + "creator": { + "name": "Mattia Amadio", + "email": "mamadio@worldbank.org" + }, + "resources": [ + { + "id": "1", + "title": "Fluvial hazard - Undefended", + "description": "Fluvial flood hazard maps (10), not accounting any flood defence", + "format": "geotiff", + "spatial_resolution": 90, + "coordinate_system": "EPSG:4326", + "download_url": "http://example.com/FTH-THA-fluvial-undefended" + }, + { + "id": "2", + "title": "Fluvial hazard - Defended", + "description": "Fluvial flood hazard maps (10), accounting for flood defence (estimate)", + "format": "geotiff", + "spatial_resolution": 90, + "coordinate_system": "EPSG:4326", + "download_url": "http://example.com/FTH-THA-fluvial-defended" + }, + { + "id": "3", + "title": "Pluvial hazard - Undefended", + "description": "Pluvial flood hazard maps (10), not accounting any flood defence", + "format": "geotiff", + "spatial_resolution": 90, + "coordinate_system": "EPSG:4326", + "download_url": "http://example.com/FTH-THA-pluvial-undefended" + } + ], + "hazard": { + "event_sets": [ + { + "id": "1", + "analysis_type": "probabilistic", + "calculation_method": "simulated", + "event_count": 10, + "occurrence_range": "1/10 to 1/1000 years", + "spatial": { + "scale": "global" + }, + "hazards": [ + { + "id": "1", + "type": "flood", + "processes": [ + "fluvial_flood" + ], + "intensity_measure": "fl_wd:m" + }, + { + "id": "2", + "type": "flood", + "processes": [ + "pluvial_flood" + ], + "intensity_measure": "fl_wd:m" + } + ] + } + ] + }, + "links": [ + { + "href": "https://raw.githubusercontent.com/GFDRR/rdl-standard/0__2__0/schema/rdls_schema.json", + "rel": "describedby" + } + ] + } + ] +} diff --git a/examples/hazard/fathom/figure.png b/examples/hazard/fathom/figure.png new file mode 100644 index 00000000..b7ad990e Binary files /dev/null and b/examples/hazard/fathom/figure.png differ diff --git a/examples/vulnerability/flood_jrc/Attributions.csv b/examples/vulnerability/flood_jrc/Attributions.csv new file mode 100644 index 00000000..40f415ae --- /dev/null +++ b/examples/vulnerability/flood_jrc/Attributions.csv @@ -0,0 +1,7 @@ +Dataset identifier,https://publications.jrc.ec.europa.eu/repository/handle/JRC105688,https://publications.jrc.ec.europa.eu/repository/handle/JRC105688 +Attribution identifier,1,2 +"Entity: +Name",JRC,Jan Huizinga +"Entity: +URL",https://publications.jrc.ec.europa.eu/repository/handle/JRC105688, +Role,distributor,author diff --git a/examples/vulnerability/flood_jrc/Links.csv b/examples/vulnerability/flood_jrc/Links.csv new file mode 100644 index 00000000..bcb44a2c --- /dev/null +++ b/examples/vulnerability/flood_jrc/Links.csv @@ -0,0 +1,3 @@ +Dataset identifier,https://publications.jrc.ec.europa.eu/repository/handle/JRC105688 +Link target,https://raw.githubusercontent.com/GFDRR/rdl-standard/0__2__0/schema/rdls_schema.json +Link relation type,describedby diff --git a/examples/vulnerability/flood_jrc/Referenced by.csv b/examples/vulnerability/flood_jrc/Referenced by.csv new file mode 100644 index 00000000..5717c537 --- /dev/null +++ b/examples/vulnerability/flood_jrc/Referenced by.csv @@ -0,0 +1,7 @@ +Dataset identifier,https://publications.jrc.ec.europa.eu/repository/handle/JRC105688 +Related resource identifier,1 +Name,JRC Technical report - Global flood depth-damage functions +Author names,Jan Huizinga;Hans de Moel;Wojciech Szewczyk +Publication date,2017-04-12 +URL,https://publications.jrc.ec.europa.eu/repository/bitstream/JRC105688/global_flood_depth-damage_functions__10042017.pdf +Digital object identifier,10.2760/16510 diff --git a/examples/vulnerability/flood_jrc/Resources.csv b/examples/vulnerability/flood_jrc/Resources.csv new file mode 100644 index 00000000..18e5b21a --- /dev/null +++ b/examples/vulnerability/flood_jrc/Resources.csv @@ -0,0 +1,6 @@ +Dataset identifier,https://publications.jrc.ec.europa.eu/repository/handle/JRC105688 +Resource identifier,1 +Resource title,Global flood depth-damage functions database +Resource description,"This spreadsheet contains two components required for flood damage assessment: fractional depth-damage functions and maximum damage values. The damage functions provide the share of asset that is damaged at a given flood depth, while the maximum damage values provide the associated maximum damage value for the given asset and, when combined together, they yield the monetary value of the damage." +Format,xlsx +resources/0/url,https://publications.jrc.ec.europa.eu/repository/bitstream/JRC105688/copy_of_global_flood_depth-damage_functions__30102017.xlsx diff --git a/examples/vulnerability/flood_jrc/Vulnerability metadata_Asset cost.csv b/examples/vulnerability/flood_jrc/Vulnerability metadata_Asset cost.csv new file mode 100644 index 00000000..964443e1 --- /dev/null +++ b/examples/vulnerability/flood_jrc/Vulnerability metadata_Asset cost.csv @@ -0,0 +1,4 @@ +Dataset identifier,https://publications.jrc.ec.europa.eu/repository/handle/JRC105688,https://publications.jrc.ec.europa.eu/repository/handle/JRC105688 +Cost identifier,1,2 +vulnerability/cost/0/type,structure,content +Cost unit,EUR,EUR diff --git a/examples/vulnerability/flood_jrc/datasets.csv b/examples/vulnerability/flood_jrc/datasets.csv new file mode 100644 index 00000000..e64df8a5 --- /dev/null +++ b/examples/vulnerability/flood_jrc/datasets.csv @@ -0,0 +1,47 @@ +Dataset identifier,https://publications.jrc.ec.europa.eu/repository/handle/JRC105688 +Title,Global flood depth-damage functions +Description,This dataset contains damage curves depicting fractional damage function of water depth as well as maximum damage values for a variety of assets and land use classes. +Risk data type,vulnerability +"Publisher: +Name",EU Joint Research Center (JRC) +"Publisher: +URL",https://publications.jrc.ec.europa.eu/repository/handle/JRC105688 +Dataset version,2017 +Dataset purpose,"Assessing potential damage of flood events is an important component in flood risk management. Determining direct flood damage is commonly done using depth-damage curves, which denote the flood damage that would occur at specific water depths per asset or per land-use class. Many countries have developed flood damage models using depth-damage curves based on analysis of past flood events and on expert judgement. However, the fact that such damage curves are not available for all regions hampers damage assessments in some areas. Moreover, due to different methodologies employed for various damage models in different countries, damage assessments cannot be directly compared with each other, obstructing also supra-national flood damage assessments." +Additional details,"Based on an extensive literature survey concave damage curves have been developed for each continent, while differentiation in flood damage between countries is established by determining maximum damage values at the country scale. These maximum damage values are based on construction cost surveys from multinational construction companies, which provide a coherent set of detailed building cost data across dozens of countries. A consistent set of maximum flood damage values for all countries was computed using statistical regressions with socio-economic World Development Indicators. Further, based on insights from the literature survey, guidance is also given on how the damage curves and maximum damage values can be adjusted for specific local circumstances, such as urban vs. rural locations or use of specific building material. This dataset can be used for consistent supra-national scale flood damage assessments, and guide assessment in countries where no damage model is currently available." +"Spatial coverage: +Spatial scale",global +License,CC-BY-4.0 +"Contact point: +Name",Mattia Amadio +"Contact point: +Email address",mamadio@worldbank.org +"Creator: +Name",EU Joint Research Center (JRC) +"Vulnerability metadata: +Primary hazard type",flood +"Vulnerability metadata: +Hazard intensity measurement",fl_wd:m +"Vulnerability metadata: +Exposure category",buildings +"Vulnerability metadata: +Exposure taxonomy scheme",internal +"Vulnerability metadata: +Vulnerability impact: +Impact type",direct +"Vulnerability metadata: +Vulnerability impact: +Impact metric",damage_ratio +"Vulnerability metadata: +Vulnerability impact: +Impact unit",percentage +"Vulnerability metadata: +Vulnerability impact: +Impact base data type",inferred +"Vulnerability metadata: +Spatial coverage: +Spatial scale",global +"Vulnerability metadata: +Impact functions: +Fragility function: +Fragility function approach",hybrid diff --git a/examples/vulnerability/flood_jrc/example.json b/examples/vulnerability/flood_jrc/example.json new file mode 100644 index 00000000..048f4f0b --- /dev/null +++ b/examples/vulnerability/flood_jrc/example.json @@ -0,0 +1,108 @@ +{ + "datasets": [ + { + "id": "https://publications.jrc.ec.europa.eu/repository/handle/JRC105688", + "title": "Global flood depth-damage functions", + "description": "This dataset contains damage curves depicting fractional damage function of water depth as well as maximum damage values for a variety of assets and land use classes.", + "risk_data_type": [ + "vulnerability" + ], + "publisher": { + "name": "EU Joint Research Center (JRC)", + "url": "https://publications.jrc.ec.europa.eu/repository/handle/JRC105688" + }, + "version": "2017", + "purpose": "Assessing potential damage of flood events is an important component in flood risk management. Determining direct flood damage is commonly done using depth-damage curves, which denote the flood damage that would occur at specific water depths per asset or per land-use class. Many countries have developed flood damage models using depth-damage curves based on analysis of past flood events and on expert judgement. However, the fact that such damage curves are not available for all regions hampers damage assessments in some areas. Moreover, due to different methodologies employed for various damage models in different countries, damage assessments cannot be directly compared with each other, obstructing also supra-national flood damage assessments.", + "details": "Based on an extensive literature survey concave damage curves have been developed for each continent, while differentiation in flood damage between countries is established by determining maximum damage values at the country scale. These maximum damage values are based on construction cost surveys from multinational construction companies, which provide a coherent set of detailed building cost data across dozens of countries. A consistent set of maximum flood damage values for all countries was computed using statistical regressions with socio-economic World Development Indicators. Further, based on insights from the literature survey, guidance is also given on how the damage curves and maximum damage values can be adjusted for specific local circumstances, such as urban vs. rural locations or use of specific building material. This dataset can be used for consistent supra-national scale flood damage assessments, and guide assessment in countries where no damage model is currently available.", + "spatial": { + "scale": "global" + }, + "license": "CC-BY-4.0", + "contact_point": { + "name": "Mattia Amadio", + "email": "mamadio@worldbank.org" + }, + "creator": { + "name": "EU Joint Research Center (JRC)" + }, + "vulnerability": { + "hazard_primary": "flood", + "intensity": "fl_wd:m", + "category": "buildings", + "taxonomy": "internal", + "impact": { + "type": "direct", + "metric": "damage_ratio", + "unit": "percentage", + "base_data_type": "inferred" + }, + "spatial": { + "scale": "global" + }, + "functions": { + "fragility": { + "approach": "hybrid" + } + }, + "cost": [ + { + "id": "1", + "dimension": "structure", + "unit": "EUR" + }, + { + "id": "2", + "dimension": "content", + "unit": "EUR" + } + ] + }, + "attributions": [ + { + "id": "1", + "entity": { + "name": "JRC", + "url": "https://publications.jrc.ec.europa.eu/repository/handle/JRC105688" + }, + "role": "distributor" + }, + { + "id": "2", + "entity": { + "name": "Jan Huizinga" + }, + "role": "author" + } + ], + "referenced_by": [ + { + "id": "1", + "name": "JRC Technical report - Global flood depth-damage functions", + "authorNames": [ + "Jan Huizinga", + "Hans de Moel", + "Wojciech Szewczyk" + ], + "datePublished": "2017-04-12", + "url": "https://publications.jrc.ec.europa.eu/repository/bitstream/JRC105688/global_flood_depth-damage_functions__10042017.pdf", + "doi": "10.2760/16510" + } + ], + "resources": [ + { + "id": "1", + "title": "Global flood depth-damage functions database", + "description": "This spreadsheet contains two components required for flood damage assessment: fractional depth-damage functions and maximum damage values. The damage functions provide the share of asset that is damaged at a given flood depth, while the maximum damage values provide the associated maximum damage value for the given asset and, when combined together, they yield the monetary value of the damage.", + "format": "xlsx", + "download_url": "https://publications.jrc.ec.europa.eu/repository/bitstream/JRC105688/copy_of_global_flood_depth-damage_functions__30102017.xlsx" + } + ], + "links": [ + { + "href": "https://raw.githubusercontent.com/GFDRR/rdl-standard/0__2__0/schema/rdls_schema.json", + "rel": "describedby" + } + ] + } + ] +} diff --git a/examples/vulnerability/flood_jrc/figure.png b/examples/vulnerability/flood_jrc/figure.png new file mode 100644 index 00000000..1a3b1a8b Binary files /dev/null and b/examples/vulnerability/flood_jrc/figure.png differ diff --git a/flatten-tool b/flatten-tool new file mode 160000 index 00000000..6a8e94d9 --- /dev/null +++ b/flatten-tool @@ -0,0 +1 @@ +Subproject commit 6a8e94d955fcab5c2ef818ac2b034503c2807579 diff --git a/manage.py b/manage.py index 7e88b230..93dbcd1d 100755 --- a/manage.py +++ b/manage.py @@ -18,6 +18,7 @@ referencedir = basedir / 'docs' / 'reference' schemadir = basedir / 'schema' codelistdir = schemadir / 'codelists' +exampledir = basedir / 'examples' def read_lines(filename): @@ -379,12 +380,40 @@ def cli(): @cli.command() def pre_commit(): - """Update reference documentation and format Markdown files + """Update example CSV files, update reference documentation and format Markdown files. """ # Load schema schema = json_load('rdls_schema.json') + # Remove example CSV files + for path in glob.glob(f"{exampledir}/*/*/*.csv"): + os.remove(path) + + # Generate example CSV files + for example_path in glob.glob(f"{exampledir}/*/*/example.json"): + + command = f"flatten-tool flatten -s schema/rdls_schema.json -f csv --root-list-path datasets -m datasets -o {'/'.join(example_path.split('/')[:-1])} --truncation-length 50 --use-titles --remove-empty-schema-columns --line-terminator LF {example_path}" + + subprocess.run(command.split(" ")) + + for path in glob.glob(f"{exampledir}/*/*/*.csv"): + with open(path, 'r') as f: + # Transpose example CSV files for column-wise presentation + rows = zip(*csv.reader(f)) + + with open(path, 'w') as f: + writer = csv.writer(f, lineterminator="\n") + + # Omit titles of parent objects + parent_titles = path.split("/")[-1].split(".csv")[0].split("_") + for row in rows: + row_title = row[0] + for i in range(0, len(parent_titles)): + row_title = row_title.replace(f"{':'.join(parent_titles[0:len(parent_titles)-i])}:", "") + + writer.writerow([row_title.replace(":", ":\n")] + list(row[1:])) + # Update schema.md update_schema_docs(schema) diff --git a/requirements.txt b/requirements.txt index 65cc158c..4b8481a6 100644 --- a/requirements.txt +++ b/requirements.txt @@ -2,7 +2,7 @@ # This file is autogenerated by pip-compile with Python 3.11 # by the following command: # -# pip-compile +# pip-compile requirements.in # alabaster==0.7.12 # via sphinx diff --git a/schema/rdls_schema.json b/schema/rdls_schema.json index 06394e3a..b5ede119 100644 --- a/schema/rdls_schema.json +++ b/schema/rdls_schema.json @@ -17,7 +17,7 @@ ], "properties": { "id": { - "title": "Identifier", + "title": "Dataset identifier", "type": "string", "description": "A unique identifier for the dataset. Use of an HTTP URI is recommended.", "minLength": 1 @@ -153,7 +153,7 @@ "uniqueItems": true }, "hazard": { - "title": "Hazard dataset metadata", + "title": "Hazard metadata", "type": "object", "description": "Metadata that is specific to datasets that describe processes or phenomena that may cause loss of life, injury or other health impacts, property damage, social and economic disruption or environmental degradation.", "required": [ @@ -174,7 +174,7 @@ "minProperties": 1 }, "exposure": { - "title": "Exposure dataset metadata", + "title": "Exposure metadata", "type": "object", "description": "Metadata that is specific to datasets that describe the situation of people, infrastructure, housing, production capacities and other tangible human assets located in hazard-prone areas.", "required": [ @@ -216,7 +216,7 @@ "minProperties": 1 }, "vulnerability": { - "title": "Vulnerability dataset metadata", + "title": "Vulnerability metadata", "type": "object", "description": "Metadata that is specific to datasets that describe the physical fragility and vulnerability relationships in relation to specific hazards or combinations of individual hazards.", "required": [ @@ -620,7 +620,7 @@ "minProperties": 1 }, "loss": { - "title": "Loss dataset metadata", + "title": "Loss metadata", "type": "object", "description": "Metadata that is specific to datasets that describe the losses associated with people, infrastructure, housing, production capacities and other tangible human assets due to the occurrence of one or more hazards.", "required": [ @@ -937,7 +937,7 @@ ], "properties": { "id": { - "title": "Identifier", + "title": "Attribution identifier", "type": "string", "description": "A locally unique identifier for the attribution.", "minLength": 1 @@ -967,7 +967,7 @@ ], "properties": { "id": { - "title": "Identifier", + "title": "Related resource identifier", "type": "string", "description": "A locally unique identifier for the related resource.", "minLength": 1 @@ -1019,7 +1019,7 @@ ], "properties": { "id": { - "title": "Identifier", + "title": "Source identifier", "type": "string", "description": "A locally unique identifier for the source.", "minLength": 1 @@ -1439,7 +1439,7 @@ ], "properties": { "id": { - "title": "Identifier", + "title": "Gazetteer entry identifier", "type": "string", "description": "An identifier drawn from the gazetteer identified in `.scheme`.", "minLength": 1 @@ -1531,7 +1531,7 @@ ], "properties": { "id": { - "title": "Identifier", + "title": "Hazard identifier", "description": "A local identifier for this hazard.", "type": "string", "minLength": 1 @@ -1997,7 +1997,7 @@ ], "properties": { "id": { - "title": "Identifier", + "title": "Cost identifier", "type": "string", "description": "A locally unique identifier for this cost.", "minLength": 1 @@ -2436,7 +2436,7 @@ "minLength": 1 }, "id": { - "title": "ID", + "title": "Classification identifier", "description": "The classification code taken from the scheme.", "type": "string", "minLength": 1 diff --git a/tests/test_csv.py b/tests/test_csv.py index 4090d285..ecb26590 100644 --- a/tests/test_csv.py +++ b/tests/test_csv.py @@ -29,7 +29,7 @@ def test_valid(): """ errors = 0 - for path, name, text, fieldnames, rows in walk_csv_data(): + for path, name, text, fieldnames, rows in walk_csv_data(excluded=('.git', '.ve', '_static', 'build', 'fixtures', 'flatten-tool', 'docson', 'examples')): codelist = is_codelist(fieldnames) width = len(fieldnames) columns = [] diff --git a/tests/test_json.py b/tests/test_json.py index 91776eea..1a191381 100644 --- a/tests/test_json.py +++ b/tests/test_json.py @@ -11,7 +11,7 @@ def test_empty(): """Tests that files (JSON and other files) are not empty.""" - empty_files_paths = [path for path in get_empty_files() if "src/" not in path[0]] + empty_files_paths = [path for path in get_empty_files(excluded=('.git', '.ve', '_static', 'build', 'fixtures', 'flatten-tool', 'docson')) if "src/" not in path[0]] warn_and_assert(empty_files_paths, "{0} is empty, run: rm {0}", "Files are empty. See warnings below.") @@ -20,7 +20,7 @@ def test_indent(): Test that JSON files are indented properly. Note this test can often fail on problems that are not to do with indents. """ - misindented_files_paths = [path for path in get_misindented_files() if "src/" not in path[0]] + misindented_files_paths = [path for path in get_misindented_files(excluded=('.git', '.ve', '_static', 'build', 'fixtures', 'flatten-tool', 'docson')) if "src/" not in path[0]] warn_and_assert( misindented_files_paths, "{0} is not indented as expected", @@ -31,5 +31,5 @@ def test_indent(): def test_invalid_json(): """Test whether all JSON files can be parsed.""" warn_and_assert( - get_invalid_json_files(excluded=('.git', '.ve', '_static', 'build', 'fixtures', "_build")), "{0} is not valid JSON: {1}", "JSON files are invalid. See warnings below." + get_invalid_json_files(excluded=('.git', '.ve', '_static', 'build', 'fixtures', 'flatten-tool', 'docson')), "{0} is not valid JSON: {1}", "JSON files are invalid. See warnings below." )