From 221aff12b7d41a4307bbf87fb3dc80665c9b4ef4 Mon Sep 17 00:00:00 2001 From: Duncan Dewhurst Date: Mon, 7 Aug 2023 10:31:42 +1200 Subject: [PATCH 1/7] docs: Restructure and update landing page content --- docs/about/index.md | 4 +- docs/{rdl => about}/roadmap.md | 0 docs/glossary.md | 2 +- docs/guides/{ => datasets}/formats.md | 6 +- docs/guides/datasets/index.md | 12 + .../{preparation.md => datasets/packaging.md} | 10 +- docs/guides/index.md | 15 +- docs/guides/{rdl-metadata.md => metadata.md} | 2 +- docs/index.md | 38 +- docs/rdl/core-standards.md | 36 - docs/rdl/how.md | 1 + docs/rdl/index.md | 12 +- .../index.md => rdl/other-standards.md} | 49 +- docs/rdl/what.md | 11 + docs/rdl/{use-cases.md => why.md} | 2 +- docs/reference/codelists.md | 2 +- docs/reference/index.md | 8 +- docs/reference/schema.md | 4 +- docs/taxonomies/ged4all.md | 769 ------------------ 19 files changed, 103 insertions(+), 880 deletions(-) rename docs/{rdl => about}/roadmap.md (100%) rename docs/guides/{ => datasets}/formats.md (98%) create mode 100644 docs/guides/datasets/index.md rename docs/guides/{preparation.md => datasets/packaging.md} (98%) rename docs/guides/{rdl-metadata.md => metadata.md} (95%) delete mode 100644 docs/rdl/core-standards.md create mode 100644 docs/rdl/how.md rename docs/{taxonomies/index.md => rdl/other-standards.md} (61%) create mode 100644 docs/rdl/what.md rename docs/rdl/{use-cases.md => why.md} (99%) delete mode 100644 docs/taxonomies/ged4all.md diff --git a/docs/about/index.md b/docs/about/index.md index a862c531..d7479a34 100644 --- a/docs/about/index.md +++ b/docs/about/index.md @@ -1,15 +1,15 @@ # About -This user guide is written to support use of the Risk Data Library Standard. +This section provides background information on the Risk Data Library Standard (RDLS), including how it is governed, its history and roadmap, and who to contact for more information. ```{eval-rst} .. toctree:: :maxdepth: 1 - :hidden: contacts changelog governance license + roadmap ``` diff --git a/docs/rdl/roadmap.md b/docs/about/roadmap.md similarity index 100% rename from docs/rdl/roadmap.md rename to docs/about/roadmap.md diff --git a/docs/glossary.md b/docs/glossary.md index 75716596..094f7e8b 100644 --- a/docs/glossary.md +++ b/docs/glossary.md @@ -1,6 +1,6 @@ -# Glossary of terms +# Glossary In this section, you will find definition of key concepts behind the RDLS including what is a disaster, how to reduce disaster risk through disaster disaster risk management and disaster risk assessment and what are the different types of risk data needed. diff --git a/docs/guides/formats.md b/docs/guides/datasets/formats.md similarity index 98% rename from docs/guides/formats.md rename to docs/guides/datasets/formats.md index 3918e173..e049ed56 100644 --- a/docs/guides/formats.md +++ b/docs/guides/datasets/formats.md @@ -1,4 +1,4 @@ -# Data formats +# How to format risk datasets Risk data can be made of spatial or non-spatial data. @@ -16,7 +16,7 @@ Below is a list of recommended and common geodata formats used for risk data. ```{note} Always prefer WIDE geodatabase table formatting instead of LONG format when working in GIS environment; by duplicating vector rows, the geospatial information is also duplicated, which cause the size of the data to increase exponentially, and slows down the spatial processing. -![Screenshot](../img/tab_format.png) +![Screenshot](../../img/tab_format.png) ``` ### Raster data: GeoTIFF / COG (`.tif`) @@ -51,7 +51,7 @@ Conversion from `.shp` to `.gpkg` is lossless and usually size-efficient. Where ```{note} Wide table formatting is preferred instead of long format. -![Screenshot](../img/tab_format.png) +![Screenshot](../../img/tab_format.png) ``` ### Documents diff --git a/docs/guides/datasets/index.md b/docs/guides/datasets/index.md new file mode 100644 index 00000000..95c8fca0 --- /dev/null +++ b/docs/guides/datasets/index.md @@ -0,0 +1,12 @@ +# How to publish risk datasets + +This section provides guidance on how to publish risk datasets. For guidance on how to publish RDLS metadata, see [how to publish RDLS metadata](../metadata.md). + +```{eval-rst} +.. toctree:: + :maxdepth: 1 + + formats + packaging + +``` diff --git a/docs/guides/preparation.md b/docs/guides/datasets/packaging.md similarity index 98% rename from docs/guides/preparation.md rename to docs/guides/datasets/packaging.md index a098a662..2c151609 100644 --- a/docs/guides/preparation.md +++ b/docs/guides/datasets/packaging.md @@ -1,4 +1,4 @@ -# Data packaging +# How to package risk datasets This section describes common data formats and file types developed during a risk assessment. For each of the hazard, exposure, vulnerability and loss components, it describes possible grouping of multiple files into minimal resources associated with a dataset, which can make it easier to find and download resources of the same type. @@ -18,7 +18,7 @@ We also need to consider: ```{caution} In general, splitting raster datasets into smaller parts is not advised, according to self-dependency and completeness criteria. For data efficiency, always consider a larger extent than needed as to avoid cross-border artefacts. Instead of splitting rasters, consider storing the raster in an alternative format that maybe more size-efficient (see Formats sections). -![Screenshot](../img/raster_clip.jpg) +![Screenshot](../../img/raster_clip.jpg) ``` Structuring risk data well when it is generated and before it is delivered to a client is important to ensure data folder are intuitive to search, and make dataset upload more efficient (and it is easier to do first time than changing the structure later). Decisions on how to structure risk data should be taken on a project-by-project basis, because there is a wide variety of how data are structured depending on the components of a project. For a country-scale analysis, we advise to follow the following structure of folders when preparing data for delivery / upload to a risk data catalog: @@ -57,7 +57,7 @@ Hazard data typically include hazard maps representing one or more historical ev Generally, hazard data (footprints) takes the form of raster (geospatial grid) data (`GeoTIFF / COG`), less often as vector data (`gpkg`, `shp`). Supporting data (hazard curves, historical catalogue) could come as tables (`csv`, `xlsx`) or vector data (`gpkg`, `shp`). -```{figure} ../img/hzd_tc.jpg +```{figure} ../../img/hzd_tc.jpg --- align: left width: 98% @@ -115,7 +115,7 @@ Exposure data typically describe the location, characteristics and value of indi Exposure geospatial data can take the form of vector (`gpkg`, `shp`), or raster (`GeoTIFF / COG`). In some cases, exposure comes as table (`csv`, `xls`). -```{figure} ../img/exp_formats.jpg +```{figure} ../../img/exp_formats.jpg --- align: left width: 98% @@ -207,7 +207,7 @@ We recommend to group exposure data using the following hierarchy: This hierarchy can be maintained also when packing all the data in one file (e.g. multiple csvs into one excel file), which is advised _unless specifically demanded by the data use_ (e.g. data are formatted for usage into a specific model). ``` -```{figure} ../img/vln_multi-table.jpg +```{figure} ../../img/vln_multi-table.jpg --- align: left width: 98% diff --git a/docs/guides/index.md b/docs/guides/index.md index 1a20d1f2..e7e23197 100644 --- a/docs/guides/index.md +++ b/docs/guides/index.md @@ -1,17 +1,12 @@ -# Guides +# Guidance -Below is the guidance on best practices for dataset creation, packaging, metadata creation according to the RDL schema and distribution. - -- [Data preparation and packaging](preparation.md) of risk data files and folders -- [Data formats](formats.md) recommended and supported formats to store and share data +This section provides guidance on how to publish RDLS metadata and how to publish risk datasets. ```{eval-rst} .. toctree:: - :maxdepth: 1 - :hidden: + :maxdepth: 2 - preparation - formats - rdl-metadata + metadata + datasets/index ``` diff --git a/docs/guides/rdl-metadata.md b/docs/guides/metadata.md similarity index 95% rename from docs/guides/rdl-metadata.md rename to docs/guides/metadata.md index 129ba71e..c7f0a753 100644 --- a/docs/guides/rdl-metadata.md +++ b/docs/guides/metadata.md @@ -1,4 +1,4 @@ -# RDL metadata +# How to publish RDLS metadata ## Adoption of the metadata schema diff --git a/docs/index.md b/docs/index.md index 383a65ca..4f3abb51 100644 --- a/docs/index.md +++ b/docs/index.md @@ -1,24 +1,21 @@ - - # Risk Data Library Standard - -The **Risk Data Library Standard (RDLS)** is an open data standard to make it easier to work with disaster and climate risk data. It provides a common description of the data used and produced in risk assessments, including **hazard**, **exposure**, **vulnerability**, and **modelled loss or impact**, data. - -The Risk Data Library (RDL) project grew out of in-depth community consultation on improving access to **risk information** and is a result of the collective effort and ongoing support of internationally-recognised research institutions and established global partnerships with combined expertise across multiple hazards and all aspects of risk assessment. Its overarching purpose is to support disaster resilience work by making risk data better and easier to work with. - -The RDLS gives risk experts a single language to describe hazard, exposure, vulnerability and modelled loss datasets. It gives datasets an underlying consistency that makes them highly interoperable and easily read by both people and machines. The schema contains labels for key metadata fields, making it easier to identify datasets hosted in different online catalogs without relying on external files or descriptions. - -The RDLS has been developed by World Bank GFDRR for disaster and climate risk assessments but is intended to be used by anyone involved in generating or using disaster risk information. - -This documentation provides a technical overview of the RDLS and its different elements: - -- [Overview](rdl/index.md): The core standards used within the RDLS, use cases and a roadmap -- [Reference](reference/index.md): how to organize and link the data using the RDLS schema -- [Taxonomy](taxonomies/index.md): details of taxonomies adopted by the RDLS -- [Guides](guides/index.md): how to implement the RDLS in your project -- [About](about/index.md): other information on the roadmap, history, governance and license - -The RDL is a collaborative project managed by the [Global Facility for Disaster Reduction and Recovery (GFDRR)](https://www.gfdrr.org/) of the World Bank Group. +The Risk Data Library Standard (RDLS) is an **open metadata standard** for describing risk datasets used in climate and disaster risk assessments. + +The purpose of the RDLS is to enable risk reduction and resilience building by making it easier for risk data publishers to describe their datasets and for risk data users to identify datasets to use in their work. Many different organisations produce or use risk datasets, including humanitarian organisations, insurance companies, academic institutions and multi-lateral development banks. + +The key feature of the RDLS is the metadata standard for describing **hazard**, **exposure**, **vulnerability**, and **loss** datasets. In addition to the metadata standard, the RDLS provides guidance on packaging and formatting for risk datasets, although it does not seek to standardise risk datasets themselves. + +The RDLS is curated by the [Global Facility for Disaster Reduction and Recovery](https://www.gfdrr.org) and is intended for use by anyone involved in publishing or using disaster risk data. It is an open standard and community contributions are welcome. + +The standard originated from in-depth consultations with the disaster and climate risk modeling community on improving access to risk datasets. It is the result of the collective effort and ongoing support of internationally-recognised research institutions and established global partnerships, bring together expertise in multiple hazards and all aspects of risk assessment. + +To help you use RDLS effectively, the documentation includes the following sections: + +* An [introduction](rdl/index.md) to the RDLS +* [Reference](reference/index.md) documentation for the metadata standard +* [Guidance](guides/index.md) on how to publish metadata in RDLS format and how to package and format risk datasets +* A [glossary](glossary.md) of risk terminology +* Background information [about](about/index.md) the RDLS, including how it is governed, its history and roadmap, and who to contact for more information ```{eval-rst} .. toctree:: @@ -27,7 +24,6 @@ The RDL is a collaborative project managed by the [Global Facility for Disaster rdl/index reference/index - taxonomies/index guides/index glossary about/index diff --git a/docs/rdl/core-standards.md b/docs/rdl/core-standards.md deleted file mode 100644 index 56116870..00000000 --- a/docs/rdl/core-standards.md +++ /dev/null @@ -1,36 +0,0 @@ -# Core standards - -RDLS has been built based on existing open data standards. - -In this section you will find a short summary of the core standards upon which the RDL data model has been built. - -## General standards - -RDLS is built using [JSON](https://www.json.org/json-en.html) (JavaScript Object Notation). JSON is a lightweight data-interchange format which is easy for humans to read and write and easy for machines to parse and generate. - -## Exposure standards - -**GED4ALL**: -In 2018 an international consortium led by the Global Earthquake Model Foundation (GEM) developed an open, multi-scale exposure data schema for multi-hazard analysis (GED4ALL) in response to recommendations from community consultation. GED4ALL simplified certain detailed engineering aspects of the original global exposure model focussed on earthquake hazards ([GED4GEM](https://journals.sagepub.com/doi/10.1177/8755293020919429)), while also expanding the exposure parameters included, so the impacts of other hazards could be related to exposure data using the standard. In this standard, GED4ALL is used as a reference in the exposure, vulnerability and loss components, to describe the exposure type to which losses relate, and to facilitate matching of appropriate vulnerability functions to exposure data, for example. -Details about the development of GED4ALL are reported [here](https://riskdatalibrary.org/resources). - -## Hazard data standards - -In 2018 an international consortium led by the British Geological Survey developed a first-of-its-kind standard for hazard information. -In this standard, we developed a list of hazard type codes and process type codes which are used as a reference in the hazard, vulnerability and loss components of the standard, and facilitate matching of appropriate vulnerability functions to hazard data, for example. -Details about the development are reported [here](https://riskdatalibrary.org/resources). - -**GLIDE disaster event identifier**: -Since the beginning of 2004, GLobal IDEntifier numbers (GLIDE) are produced at (GLIDEnumber.net) for all new disaster events reported by partner institutions and those discovered by ADRC. -A GLIDE number comprises two letters to identify the disaster type (e.g. EQ - earthquake); the year of the disaster; a six-digit, sequential disaster number; and the three-letter ISO code for country of occurrence. E.g., the GLIDE number for West-India Earthquake in India is: EQ-2001-000033-IND. This number is posted by the above organizations and in many other websites, on their documents relating to that particular disaster and gradually other partners will include it in whatever information they generate. As information suppliers join in this initiative, documents and data pertaining to specific events may be easily retrieved from various sources, or linked together using the unique GLIDE numbers. List of services using GLIDE: https://glidenumber.net/glide/public/links.jsp -The RDL Standard uses a GLIDE number in the `hazard.event` object, to denote the historical event to which hazard event data relates, e.g., the simulated hazard intensity footprint of that event. - -## Vulnerability data standards - -In 2018 an international consortium led by the UCL EPICentre developed a first-of-its-kind standard for vulnerability information, called MOVER. -Details about the development are reported [here](https://riskdatalibrary.org/resources). - -## Loss data standards - -In 2019 GEM and UCL EPICentre developed a first-of-its-kind standard for loss information. -Details about the development are reported [here](https://riskdatalibrary.org/resources). diff --git a/docs/rdl/how.md b/docs/rdl/how.md new file mode 100644 index 00000000..3e89373e --- /dev/null +++ b/docs/rdl/how.md @@ -0,0 +1 @@ +# How do I implement the RDLS? diff --git a/docs/rdl/index.md b/docs/rdl/index.md index 93ac9a32..2a39c068 100644 --- a/docs/rdl/index.md +++ b/docs/rdl/index.md @@ -1,12 +1,14 @@ -# Overview +# Introduction -This section provides more detail on the core standards that are used within the Risk Data Library Standard, use cases for documenting risk data with the RDLS, and a roadmap for development. +This section provides an introduction to the Risk Data Library Standard (RDLS). ```{eval-rst} .. toctree:: :maxdepth: 1 - core-standards - use-cases - roadmap + what + why + how + other-standards + ``` diff --git a/docs/taxonomies/index.md b/docs/rdl/other-standards.md similarity index 61% rename from docs/taxonomies/index.md rename to docs/rdl/other-standards.md index 1581548c..cac37705 100644 --- a/docs/taxonomies/index.md +++ b/docs/rdl/other-standards.md @@ -1,10 +1,25 @@ - +# How does RDLS relate to other standards? -# Taxonomies +RDLS has been built based on existing open data standards. -The Risk Data Library Standard defines taxonomies for describing risk data. In this section you will find a short summary of the taxonomies that can be used with the RDLS, as well as the other main taxonomies for disaster risk assessments. +In this section you will find a short summary of the core standards upon which the RDL data model has been built. -## Hazard taxonomies +## General standards + +RDLS is built using [JSON](https://www.json.org/json-en.html) (JavaScript Object Notation). JSON is a lightweight data-interchange format which is easy for humans to read and write and easy for machines to parse and generate. + +## Hazard data standards + +In 2018 an international consortium led by the British Geological Survey developed a first-of-its-kind standard for hazard information. +In this standard, we developed a list of hazard type codes and process type codes which are used as a reference in the hazard, vulnerability and loss components of the standard, and facilitate matching of appropriate vulnerability functions to hazard data, for example. +Details about the development are reported [here](https://riskdatalibrary.org/resources). + +**GLIDE disaster event identifier**: +Since the beginning of 2004, GLobal IDEntifier numbers (GLIDE) are produced at (GLIDEnumber.net) for all new disaster events reported by partner institutions and those discovered by ADRC. +A GLIDE number comprises two letters to identify the disaster type (e.g. EQ - earthquake); the year of the disaster; a six-digit, sequential disaster number; and the three-letter ISO code for country of occurrence. E.g., the GLIDE number for West-India Earthquake in India is: EQ-2001-000033-IND. This number is posted by the above organizations and in many other websites, on their documents relating to that particular disaster and gradually other partners will include it in whatever information they generate. As information suppliers join in this initiative, documents and data pertaining to specific events may be easily retrieved from various sources, or linked together using the unique GLIDE numbers. List of services using GLIDE: https://glidenumber.net/glide/public/links.jsp +The RDL Standard uses a GLIDE number in the `hazard.event` object, to denote the historical event to which hazard event data relates, e.g., the simulated hazard intensity footprint of that event. + +### Hazard taxonomies The RDL project performed a review of the most relevant hazard taxonomies and derived a classification focusing on those hazards and processes that are more often required in disaster risk assessments, while mapping and matching alternative definitions into one consistent framework. There are several existing taxonomies that could have been adopted to describe hazard data: @@ -18,22 +33,14 @@ The RDL project performed a review of the most relevant hazard taxonomies and de - [Munich-RE](https://www.cred.be/downloadFile.php?file=sites/default/files/DisCatClass_264.pdf) covers 27 natural hazards 13 main categories (Geophysical, Meteorological, Hydrological, Climatological, Biological, Extraterrestrial). -## Exposure taxonomies +## Exposure standards The exposure schema can accommodate different descriptions of assets using a taxonomy which describes their characteristics (e.g. building occupancy, construction, age, height, etc. or road surface type). -### GED4all (recommended) - -[GED4all](ged4all.md) has been developed by GFDRR under the UK-DFID Challenge Fund, this open exposure database schema is meant for multi-hazard risk analysis. GED4ALL can be populated with building-level data from OpenStreetMap (OSM) following the [guidance](https://wiki.openstreetmap.org/wiki/GED4ALL) from the Humanitarian OSM Team, which collects contributions from the community on how OSM tags can be best aligned with the GED4ALL taxonomy. This is the suggested option for classification of exposure data in the RDL. - -```{eval-rst} -.. toctree:: - :maxdepth: 1 - :hidden: - - ged4all +### GED4ALL +In 2018 an international consortium led by the Global Earthquake Model Foundation (GEM) developed an open, multi-scale exposure data schema for multi-hazard analysis ([GED4ALL](https://wiki.openstreetmap.org/wiki/GED4ALL)) in response to recommendations from community consultation. GED4ALL simplified certain detailed engineering aspects of the original global exposure model focussed on earthquake hazards ([GED4GEM](https://journals.sagepub.com/doi/10.1177/8755293020919429)), while also expanding the exposure parameters included, so the impacts of other hazards could be related to exposure data using the standard. In this standard, GED4ALL is used as a reference in the exposure, vulnerability and loss components, to describe the exposure type to which losses relate, and to facilitate matching of appropriate vulnerability functions to exposure data, for example. Details about the development of GED4ALL are reported [here](https://riskdatalibrary.org/resources). -``` +GED4ALL can be populated with building-level data from OpenStreetMap (OSM) following the [guidance](https://wiki.openstreetmap.org/wiki/GED4ALL) from the Humanitarian OSM Team, which collects contributions from the community on how OSM tags can be best aligned with the GED4ALL taxonomy. This is the suggested option for classification of exposure data in the RDL. ### GEM Building Taxonomy @@ -67,10 +74,12 @@ Example: In CEDE data asset characteristics are separated into individual column | ------------- | ---------------- | --------------- | --------- | | 301 | 112 | 1 | 0 | -## Vulnerability taxonomies +## Vulnerability data standards -Content under development. +In 2018 an international consortium led by the UCL EPICentre developed a first-of-its-kind standard for vulnerability information, called MOVER. +Details about the development are reported [here](https://riskdatalibrary.org/resources). -## Loss taxonomies +## Loss data standards -Content under development. +In 2019 GEM and UCL EPICentre developed a first-of-its-kind standard for loss information. +Details about the development are reported [here](https://riskdatalibrary.org/resources). diff --git a/docs/rdl/what.md b/docs/rdl/what.md new file mode 100644 index 00000000..8dfc3732 --- /dev/null +++ b/docs/rdl/what.md @@ -0,0 +1,11 @@ +# What is the RDLS + +Scope + +Metadata and data + +Content + +Structure + +Schema and codelists diff --git a/docs/rdl/use-cases.md b/docs/rdl/why.md similarity index 99% rename from docs/rdl/use-cases.md rename to docs/rdl/why.md index 5fc915a8..54be3902 100644 --- a/docs/rdl/use-cases.md +++ b/docs/rdl/why.md @@ -1,4 +1,4 @@ -# Use cases +# Why use the RDLS? This page provides some use cases for the Risk Data Library Standard (RDLS), to give examples of its value to different organisations and roles connected with publishing and using risk data. diff --git a/docs/reference/codelists.md b/docs/reference/codelists.md index 1b33262c..ac476d97 100644 --- a/docs/reference/codelists.md +++ b/docs/reference/codelists.md @@ -316,7 +316,7 @@ file: ../../codelists/closed/geometry_type.csv ### hazard_type -The RDLS offers a classification of hazards that are more often required in disaster risk assessments, based on the review and mapping of existing alternative definitions into one consistent framework. +The RDLS offers a classification of hazards that are more often required in disaster risk assessments, based on the review and mapping of existing alternative definitions into one consistent framework. For more information, see [hazard taxonomies](../rdl/other-standards.md#hazard-taxonomies). The hazard_type codelist classifies hazard phenomena by the main hazard to which they relate. Hazard phenomena can also be classified by the hazard process to which they relate. For more information, see the [process_type codelist](#process_type). diff --git a/docs/reference/index.md b/docs/reference/index.md index 0bcd0415..7243261a 100644 --- a/docs/reference/index.md +++ b/docs/reference/index.md @@ -1,12 +1,14 @@ -# Reference +# Metadata reference ```{note} Throughout the reference documentation, the key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT", "SHOULD", "SHOULD NOT", "RECOMMENDED", "NOT RECOMMENDED", "MAY", and "OPTIONAL" are to be interpreted as described in [RFC2119](https://datatracker.ietf.org/doc/html/rfc2119). ``` -The [schema reference](schema.md) is the canonical reference for the structure of the Risk Data Library Standard (RDLS) data model, the meaning of each field, and the rules that must be followed to publish RDLS data. You can also [view the schema in an interactive browser](browser.md). +This section specifies the structure and format of Risk Data Library Standard (RDLS) metadata. -The [codelist reference](codelists.md) is the canonical reference for the meaning of the codes used to limit and standardise the possible values of fields in RDLS data. +The [schema reference](schema.md) is the canonical reference for the structure of RDLS metadata, the meaning of each field, and the rules that must be followed to publish RDLS metadata. You can also [view the schema in an interactive browser](browser.md). + +The [codelist reference](codelists.md) is the canonical reference for the meaning of the codes used to limit and standardise the possible values of fields in RDLS metadata. ______________________________________________________________________ diff --git a/docs/reference/schema.md b/docs/reference/schema.md index dd7e2167..1b4eddef 100644 --- a/docs/reference/schema.md +++ b/docs/reference/schema.md @@ -197,14 +197,14 @@ Schema attributes for an earthquake hazard map related to an occurrence probabil ## Exposure -The exposure component describes metadata for datasets containing information on the distribution and characteristics of built environment assets (buildings and infrastructure) and natural assets and population, that are used in risk assessment. The exposure component provides codelists to describe the type of assets and costs, and the taxonomy scheme that is used to describe construction and demographic information contained in the dataset. +The exposure component describes metadata for datasets containing information on the distribution and characteristics of built environment assets (buildings and infrastructure) and natural assets and population, that are used in risk assessment. The exposure component provides codelists to describe the type of assets and costs, and the taxonomy scheme that is used to describe construction and demographic information contained in the dataset. For more information, see [exposure standards](../rdl/other-standards.md#exposure-standards). The exposure component uses exposure categories consistent with the vulnerability and loss components of this standard. Spatial reference and location information are described using existing external standards. Temporal information can include date and duration of events or year of scenario, and is defined using the Dublin Core standards. ```{eval-rst} .. mermaid:: - classDiagram + classDiagramtaxonomies Model -- Asset1 Model -- Asset2 Model: Category diff --git a/docs/taxonomies/ged4all.md b/docs/taxonomies/ged4all.md deleted file mode 100644 index 4f58f2b6..00000000 --- a/docs/taxonomies/ged4all.md +++ /dev/null @@ -1,769 +0,0 @@ -# GED4all exposure taxonomy - -We encourage the use of GED4all taxonomy, described in full [here](https://wiki.openstreetmap.org/wiki/GED4ALL).
-In order to summarise all the asset information into a single alphanumeric string, a tool will be provided, similar to the ['taxtweb'](https://platform.openquake.org/taxtweb/) tool available from GEM dedicated to _buildings_ taxonomy. - -The taxonomy covers four main categories: - -- [Buildings](#buildings) -- [Lifelines](#lifelines) -- [Crops, Livestock and Forestry](#crops-livestock-and-forestry) -- [Socio-Economic indicators](#socio-economic-indicators) - -## Buildings - -The buildings taxonomy is based on GEM OpenQuake taxonomy, with some simplifications. The taxonomy string is built as sequence of attributes separated by slash: - -`MATERIAL/HEIGHT/DATE/OCCUPANCY/SHAPE/…` - -Missing attributes can be skipped from the string, e.g. - -2-floors detached residential dwelling, reinforced concrete structure: `CR/H:2/RES1` - -
- -| Attribute | Code | Description | -| ---------------------------------------------------- | :------: | ----------------------------------------------------------------------------------------------------------------------------- | -| Material of the Lateral Load-Resisting System (LLRS) | -- | Unknown material | -| | C | Concrete, unknown reinforcement | -| | CU | Concrete, unreinforced \* | -| | CR | Concrete, reinforced | -| | SRC | Concrete, composite with steel section | -| | S | Steel | -| | ME | Metal (except steel) | -| | M | Masonry, unknown reinforcement | -| | MUR | Masonry, unreinforced | -| | MCF | Masonry, confined | -| | MR | Masonry, reinforced | -| | E | Earth, unknown reinforcement | -| | EU | Earth, unreinforced | -| | ER | Earth, reinforced | -| | W | Wood | -| | MIX | Mixed materials (hybrid or composite) | -| | INF | Informal materials | -| | MATO | Other material | -| Height | -- | Number of storeys unknown | -| | H:n | n is the exact number of storeys above ground | -| | HBET:a-b | a-b is the range of number of storeys above ground (a=upper bound, and b= lower bound). a-b, range of number of storeys above | -| | HAPP:n | HAPP:n, approximate number of storeys above ground. | -| Date of Construction or Retrofit | -- | Year unknown | -| | Y :n | n is the exact date of construction or retrofit | -| | YBET:a-b | a and b are the upper and lower bound for the date of construction or retrofit | -| | YPRE:n | n is the latest possible date of construction or retrofit | -| | YAPP:n | n is the approximate date of construction or retrofit | -| Occupancy | -- | Unknown occupancy type | -| | RES | Residential, unknown type | -| | RES1 | Residential, Single dwelling | -| | RES2 | Residential, Multi-unit | -| | RES2A | Residential, 2 Units (duplex) | -| | RES2B | Residential, 3-4 Units | -| | RES2C | Residential, 5-9 Units | -| | RES2D | Residential, 10-19 Units | -| | RES2E | Residential, 20-49 Units | -| | RES2F | Residential, 50+ Units | -| | RES3 | Residential, Temporary lodging | -| | RES4 | Residential, Institutional housing | -| | RES5 | Residential, Mobile home | -| | COM | Commercial and public, Unknown type | -| | COM1 | Commercial and public, Retail trade | -| | COM2 | Commercial and public, Wholesale trade and storage (warehouse) | -| | COM3 | Commercial and public, Offices, professional/technical services | -| | COM4 | Commercial and public, Hospital/medical clinic | -| | COM5 | Commercial and public, Entertainment | -| | COM6 | Commercial and public, Public building | -| | COM7 | Commercial and public, Covered parking garage | -| | COM8 | Commercial and public, Bus station | -| | COM9 | Commercial and public, Railway station | -| | COM10 | Commercial and public, Airport | -| | COM11 | Commercial and public, Recreation and leisure | -| | MIX | Mixed, unknown type | -| | MIX1 | Mixed use, Mostly residential and commercial | -| | MIX2 | Mixed use, Mostly commercial and residential | -| | MIX3 | Mixed use, Mostly commercial and industrial | -| | MIX4 | Mixed use, Mostly residential and industrial | -| | MIX5 | Mixed use, Mostly industrial and commercial | -| | MIX6 | Mixed use, Mostly industrial and residential | -| | IND | Industrial, unknown type | -| | IND1 | Industrial, Heavy industrial | -| | IND2 | Industrial, Light industrial | -| | AGR | Agriculture, unknown type | -| | AGR1 | Agriculture, Produce storage | -| | AGR2 | Agriculture, Animal shelter | -| | AGR3 | Agriculture, Agricultural processing | -| | ASS | Assembly, unknown type | -| | ASS1 | Assembly, Religious gathering | -| | ASS2 | Assembly, Arena | -| | ASS3 | Assembly, Cinema or concert hall | -| | ASS4 | Assembly, Other gatherings | -| | GOV | Government, unknown type | -| | GOV1 | Government, general services | -| | GOV2 | Government, emergency response | -| | EDU | Education, unknown type | -| | EDU1 | Education, Pre-school facility | -| | EDU2 | Education, School | -| | EDU3 | Education, College/university, offices and/or classrooms | -| | EDU4 | Education, College/university, research facilities and/or labs | -| | OCO | Other occupancy type | -| Ground floor hydrodynamics | -- | Ground floor hydrodynamics unknown | -| | GFO | Ground floor plan fully open (no walls) | -| | GFH | Ground floor plan partially open (i.e. with at least 50% of walls). | -| | GFM | Not open, many doors and/or windows (i.e. more than 20% of wall surface area). | -| | GFN | Not open, few doors and/or windows (i.e. less than 20% of wall surface area) | -| Roof Shape | -- | Unknown roof shape | -| | RSH1 | Flat | -| | RSH2 | Pitched with gable ends | -| | RSH3 | Pitched and hipped | -| | RSH4 | Pitched with dormers | -| | RSH5 | Monopitch | -| | RSH6 | Sawtooth | -| | RSH7 | Curved | -| | RSH8 | Complex regular | -| | RSH9 | Complex irregular | -| | RSHO | Roof shape, other | -| Floor | -- | Floor material, unknown | -| | FN | No elevated or suspended floor material (single-storey building) | -| | FM | Masonry | -| | FE | Earthen | -| | FC | Concrete | -| | FME | Metal | -| | FW | Wood | -| | FO | Floor material, other | - -
- -______________________________________________________________________ - -## Lifelines - -The **lifelines** taxonomy includes all infrastructures commonly found in populated areas, such as: - -- [Roads and railways](#roads-and-railways) -- [Pipelines](#pipelines) -- [Energy generation and power grid](#energy-generation-and-power-grid) -- [Potable water and wastewater system](#potable-water-and-wastewater-systems) -- [Communication systems](#communication-systems) - -Three main sources of information have been used for the definition of this taxonomy: FP7 EU Project [Syner-G](http://www.vce.at/SYNER-G), HAZUS11 recommendations, and the OpenStreetMap (OSM) classification system. - -### Roads and railways - -This taxonomy is strongly based on the classification system adopted by OpenStreetMap, since OSM is undoubtedly the largest and most complete source of open information concerning the location of roads and railways. -The taxonomy string is simply `TYPE+CATEGORY`, e.g. - -Secondary road: `RDN+SE` - -
- -| Attribute | Code | Description | -| --------------- | :----: | -------------------------------------------------------------------------------------------------------------------------------------- | -| Road network | RDN+MO | Motorway: restricted access major divided highway (i.e. freeway), normally with 2 or more running lanes plus emergency hard shoulder | -| | RDN+TR | Trunk: the most important roads in a country's system that aren't motorways (not necessarily be a divided highway) | -| | RDN+PR | Primary: the next most important roads in a country's system (often link larger towns) | -| | RDN+SE | Secondary: the next most important roads in a country's system (often link towns) | -| | RDN+TE | Tertiary: the next most important roads in a country's system (often link smaller towns and villages) | -| | RDN+UN | Unclassified: the least important through roads in a country's system (often link villages and hamlets) | -| | RDN+RE | Residential: roads which serve as an access to housing, without function of connecting settlements. Often lined with housing. | -| | RDN+SR | Service: access roads to, or within an industrial estate, camp site, business park, car park etc. | -| | RDN | Unknown: no information concerning road typology | -| Railway network | RLW+LR | Light rail: a higher-standard tram system, normally in its own right-of-way. Often reaches a considerable length (tens of kilometer) | -| | RLW+MR | Monorail: a single-rail railway | -| | RLW+RL | Rail: full sized passenger or freight trains in the standard gauge for the country or state | -| | RLW+SW | Subway: a city passenger underground rail service running mostly grade separated | -| | RLW+TR | Tram: one or two carriage rail vehicles, usually sharing motor road. | -| | RLW | Unknown: no additional information concerning rail typology. | - -
- -### Pipelines - -The taxonomy presented herein has been developed using the classification experience developed in Syner-G and STREST (Crowley et al., 2016). -The taxonomy string is simply `PPL/CONTENT/POSITION/MATERIAL/JOINT_TYPE/SOIL_TYPE/DIAMETER`, e.g. - -Large elevated pipe for potable water: `CPW/PEL/DLG` - -
- -| Attribute | Code | Description | -| ---------- | :--: | --------------------------- | -| Content | CGS | Gas | -| | COL | Oil | -| | CPW | Potable water | -| | CWW | Wastewater | -| | COT | Other content | -| | -- | Unknown | -| Position | PBU | Buried | -| | PEL | Elevated | -| Material | MPC | Polyvinyl chloride | -| | MPE | Polyethylene | -| | MCI | Cast iron | -| | MDI | Ductile iron | -| | MWS | Welded steel | -| | MRM | Reinforced plastic mortar | -| | MRM | Resin transfer moulding | -| | MAC | Asbestos-cement | -| | MC | Concrete | -| | MCL | Clay | -| | MO | Other material | -| | MUB | Unknown, brittle | -| | MUD | Unknown, ductile | -| | -- | Unknown material | -| Joint type | JAW | Arc welded | -| | JGW | Gas welded | -| | JCE | Cemented | -| | JFW | Fillet weld | -| | JBS | Bell and spigot (caulked) | -| | JRI | Riveted | -| | JMR | Mechanical restrained | -| | JSC | Screwed | -| | JRU | Rubber gasket | -| | JSG | Unknown, segmented | -| | JCO | Unknown, continuous | -| | JO | Other joint | -| | -- | Unknown joint | -| Soil type | SCO | Corrosive | -| | SNC | Non corrosive | -| | -- | Unknown soil type | -| Diameter | DSM | Small (\< 40 cm) | -| | DLG | Large (≥ 40 cm) | -| | -- | Unknown diameter | - -
- -### Energy generation and power grid - -We follow the taxonomy adopted by HAZUS, which allows capturing the capacity (e.g. voltage) of the elements. For the purposes of assessing damage due to natural disasters, it is also relevant to identify the presence of anchorage and whether the elements have been designed according to a particular code. The taxonomy for component of the power grid can thus be presented in the following manner: `PWG/ENERGYSOURCE/COMPONENT/ANCHORAGE/CODE PROVISIONS`, e.g. - -Electric distribution line through pylons: `PWG/SSM/ANC` - -
- -| Attribute | Code | Description | -| ----------------- | :--: | ---------------------------------------- | -| Energy Source | OIL | Oil | -| | GEO | Geothermal | -| | NUC | Nuclear | -| | HYD | Hydroelectric | -| | WND | Wind | -| | SOL | Solar | -| | TDL | Tidal wave | -| | GAS | Gas | -| | BIO | Biomass | -| | O | Other | -| | -- | Unknown | -| Power Capacity | PC: | Value (integer) | -| | -- | Unknown power capacity | -| Power grid | SSL | Low Voltage (\<115 KV) Substation | -| | SSM | Medium Voltage (115-500 KV) Substation | -| | SSH | High Voltage (>500 KV) Substation | -| | DTC | Distribution circuit | -| | TMT | Transmission tower | -| Grid anchorage | ANC | Anchored | -| | AUN | Unanchored | -| | -- | Unknown anchorage | -| Code provisions | CDN | No code (non-engineered) | -| | CDL | Low code | -| | CDM | Moderate code | -| | CDH | High code | -| | C99 | Code provisions unknown | - -
- -### Potable water and wastewater systems - -Potable water systems are comprised by water treatment plants, storage tanks, pipelines and pumping stations, while wastewater systems are composed by wastewater treatment plants, lifting stations and -pipelines. Our classification is based on the HAZUS guidelines. - -The alphanumeric taxonomy strings are:
-`PWR/COMPONENT/ANCHORAGE/CODE PROVISIONS` for potable water
-`WWR/COMPONENT/ANCHORAGE/CODE PROVISIONS` for wastewater - -
- -| Attribute | Code | Description | -| ----------------- | :--: | ------------------------------------------------- | -| **Potable water** | PWR | | -| Component | PWS | Small potable water treatment plant (\<50 MGD) | -| | PWM | Medium potable water treatment plant (50-200 MGD) | -| | PWL | Large potable water treatment plant (>200 MGD) | -| | PPS | Small pumping plant (\<10 MGD) | -| | PPM | Medium pumping plant (10-50 MGD) | -| | PPL | Large pumping plant (>50 MGD) | -| Anchorage | ANC | Anchored | -| | AUN | Unanchored | -| | -- | Unknown anchorage | -| Code provisions | CDN | No code (non-engineered) | -| | CDL | Low code | -| | CDM | Moderate code | -| | CDH | High code | -| | -- | Code provisions unknown | -| **Wastewater** | WWR | | -| Component | WWS | Small wastewater treatment plant (\<50 MGD) | -| | WWM | Medium wastewater treatment plant (50-200 MGD) | -| | WWL | Large wastewater treatment plant (>200 MGD) | -| | LSS | Small lift station (\<10 MGD) | -| | LSM | Medium lift station (10-50 MGD) | -| | LSL | Large lift station (>50 MGD) | -| Anchorage | ANC | Anchored | -| | AUN | Unanchored | -| | -- | Unknown anchorage | -| Code provisions | CDN | No code (non-engineered) | -| | CDL | Low code | -| | CDM | Moderate code | -| | CDH | High code | -| | -- | Code provisions unknown | - -
- -### Communication systems - -A communication system is comprised by offices dedicated to the reception and dissemination of information (e.g. telephones offices, call centers, TV stations, radio station, telecommunication stations), supporting transmitter towers and distribution circuits. The components have been classified based on the classification system proposed by HAZUS. For the purposes of assessing damage due to natural disasters, it is also relevant to identify the presence of anchorage and whether the elements have been designed according to a particular code. -
The taxonomy string for the components of a communication system is: -
`COM/COMPONENT/ANCHORAGE/CODE`
- -| Attribute | Code | Description | -| --------------- | :--: | -------------------------------- | -| Component | TRD | AM or FM radio transmitters | -| | TTV | TV stations or transmitters | -| | TWE | Weather stations or transmitters | -| | TTT | Telecommunication transmitters | -| | TOT | Other stations or transmitters | -| | DTC | Distribution circuit | -| Anchorage | ANC | Anchored | -| | AUN | Unanchored | -| | -- | Unknown anchorage | -| Code provisions | CDN | No code (non-engineered) | -| | CDL | Low code | -| | CDM | Moderate code | -| | CDH | High code | -| | -- | Code provisions unknown | - -______________________________________________________________________ - -## Crops, Livestock and Forestry - -The taxonomy for crops, livestock and forestry was defined based on existing classification systems supported by the Food and Agriculture Organization (FAO). For crops, the classification system in the 2000 agricultural census programme was adopted. This system comprises a wide range of attributes such as growing cycle (temporary/permanent), crop species, crop variety, season, land type, amongst others. The taxonomy proposed herein uses the first and second categorization levels proposed by FAO, as well as the growing cycle (e.g. permanent or temporary). A simple alphanumeric code is attributed to each class of crop. - -### Crops - -
- -| Attribute | Code | Description | -| ----------------------------------------------------- | :-----: | ------------------------------------------------- | -| Cereals | CRP1+1 | Wheat | -| | CRP1+2 | Maize | -| | CRP1+3 | Rice | -| | CRP1+4 | Sorghum | -| | CRP1+5 | Barley | -| | CRP1+6 | Rye | -| | CRP1+7 | Oats | -| | CRP1+8 | Millets | -| | CRP1+9 | Other | -| Vegetables and melons | CRP2+1 | Leafy or stem vegetables | -| | CRP2+2 | Fruit-bearing vegetables | -| | CRP2+3 | Root, bulb, or tuberous vegetables | -| | CRP2+4 | Mushrooms and truffles | -| | CRP2+5 | Other | -| Fruits and nuts | CRP3+1 | Tropical and subtropical fruits | -| | CRP3+2 | Citrus fruits | -| | CRP3+3 | Grapes | -| | CRP3+5 | Berries | -| | CRP3+6 | Pome fruits and stone fruits | -| | CRP3+7 | Nuts | -| | CRP3+8 | Other | -| Oilseed crops | CRP4+1 | Soya beans | -| | CRP4+2 | Groundnuts | -| | CRP4+3 | Other | -| Root/tuber crops with high starch or inulin content | CRP5+1 | Potatoes | -| | CRP5+2 | Sweet potatoes | -| | CRP5+3 | Cassava Yams | -| | CRP5+4 | Other | -| Beverage and spice crops | CRP6+1 | Beverage crops | -| | CRP6+2 | Spice crops | -| | CRP6+3 | Other | -| Leguminous crops | CRP7+1 | Beans | -| | CRP7+2 | Broad beans | -| | CRP7+3 | Chick peas | -| | CRP7+4 | Cow peas | -| | CRP7+5 | Lentils | -| | CRP7+6 | Lupins | -| | CRP7+7 | Peas | -| | CRP7+8 | Pigeon peas | -| | CRP7+9 | Leguminous crops | -| | CRP7+10 | Other | -| Sugar crops | CRP8+1 | Sugar beet | -| | CRP8+2 | Sugar cane | -| | CRP8+3 | Sweet sorghum | -| | CRP8+4 | Other | -| Other crops | CRP9+1 | Grasses and other fodder crops | -| | CRP9+2 | Fibre crops | -| | CRP9+3 | Medicinal, aromatic, pesticidal, or similar crops | -| | CRP9+4 | Rubber | -| | CRP9+5 | Flower crops | -| | CRP9+6 | Tobacco | -| | CRP9+7 | Other | -| Unknown crop | CRP | | - -
- -### Livestock - -
- -| Attribute | Code | Description | -| ------------------- | :----: | ------------------------------------------- | -| Large ruminants | LVS1+1 | Cattle | -| | LVS1+2 | Buffaloes | -| | LVS1+3 | Yaks | -| Small ruminants | LVS2+1 | Sheep | -| | LVS2+2 | Goats | -| Pigs or swines | LVS3 | | -| Equines | LVS4+1 | Horses | -| | LVS4+2 | Mules and hinnies | -| | LVS4+3 | Asses | -| | LVS4+4 | Other (e.g. zebras) | -| Camels and camelids | LVS5+1 | Camels | -| | LVS5+2 | Llamas and alpacas | -| Poultry | LVS6+1 | Chickens | -| | LVS6+2 | Ducks | -| | LVS6+3 | Geese | -| | LVS6+4 | Turkeys | -| | LVS6+5 | Guinea fowls | -| | LVS6+6 | Pigeons | -| | LVS6+7 | Other | -| Other animals | LVS7+1 | Deer, elk, reindeer | -| | LVS7+2 | Fur-bearing animals such as foxes and minks | -| | LVS7+3 | Dogs and cats | -| | LVS7+4 | Rabbits and hares | -| | LVS7+5 | Other (e.g. emus, ostriches, elephants) | -| Insects | LVS8+1 | Bees | -| | LVS8+2 | Silkworms | -| | LVS8+3 | Other worms or insects | -| Unknown livestock | | | - -
- -### Forestry - -
- -| Attribute | Code | Description | -| ----------------------------------- | :----: | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -| Closed forest | FRT1+1 | Mainly evergreen forest - the canopy is never without green foliage, but individual trees may shed their leaves (e.g. Sumatra, Atrato Valley (Colombia), Atlantic slopes of Costa Rica, Amazon Basin). | -| | FRT1+2 | Mainly deciduous forest - majority of trees shed their foliage simultaneously in connection to unfavourable season (e.g. North and South America, Southern slopes of the Himalayas and Europe) | -| | FRT1+3 | Extremely xeromorphic forest - dense stands of trees, composed by species such as bottle or tuft rees with succulent leaves (e.g. thorn forest in Southwestern North America and Southwestern Africa) | -| Woodland | FRT2+1 | Mainly evergreen woodland - the canopy is never without green foliage, but individual trees may shed their leaves (e.g. Mediterranean Basin). | -| | FRT2+2 | Mainly deciduous woodland - majority of trees shed their foliage simultaneously in connection to unfavourable season (e.g. Southern California and American Southeast, Mediterranean Basin) | -| | FRT2+3 | Extremely xeromorphic woodland - dense stands of trees, composed by species such as bottle or tuft trees with succulent leaves (e.g. Southwestern North America and Southwestern Africa) | -| Scrub | FRT3+1 | Mainly evergreen scrub - the canopy is never without green foliage, but individual species may shed their leaves (e.g. Mediterranean dwarf palm shrubland, Chaparral shrubland in California or Hawaiian tree fern thicket). | -| | FRT3+2 | Mainly deciduous scrub - majority of scrub shed their foliage simultaneously in connection to unfavourable season (e.g. peat mosses in Scotland) | -| | FRT3+3 | Extremely xeromorphic (subdesert) shrubland - very open stands of shrubs, often composed by vegetation with green branches without leaves, some of them with thorns (e.g. mulga scrub in Australia). | -| Dwarf-scrub and related communities | FRT4+1 | Mainly evergreen dwarf-scrub - mostly dense dwarf scrub evergreen dominating the landscape (e.g. East Mediterranean mountains). | -| | FRT4+2 | Mainly deciduous scrub - majority of vegetation shed their foliage simultaneously in connection to unfavourable season (e.g. Sierra Nevada in California ) | -| | FRT4+3 | Extremely xeromorphic dwarf-shrubland - more or less open formations consisting of dwarf-shrubs or succulent species (e.g. Australia). | -| | FRT4+4 | Tundra - slowly growing, low formations, consisting mainly of dwarf-shrubs beyond the subpolar tree line (e.g. Alaska, Northern Canada, Greenland, Norway, Finland and Siberia). | -| | FRT4+5 | Mossy bog formations with dwarf-shrub - peat accumulations formed mainly by mosses which generally cover the surface as well (e.g. Western Siberian Lowlands in Russia). | -| Herbaceous vegetation | FRT5+1 | Tall graminoid vegetation - Mostly composed by tall grasslands with heights of over 2 m. Forbs can be presented but their coverage is less than 50% (e.g. Northeast Bolivia, African savannah and upper Nile Valley). | -| | FRT5+2 | Medium tall grassland - Mostly composed by grasslands with heights between 0.5 and 2 m. Forbs can be presented but their coverage is less than 50% (e.g. Sahel region in Africa, Eastern Kansas, glasslands in New Zealand) | -| | FRT5+3 | Short grassland - Mostly composed by grasslands with heights below 0.5 m. Forbs can be presented but their coverage is less than 50% (e.g. alpine regions of Kenya, Colombia and Venezuela). | -| | FRT5+4 | Forb vegetation - the plant community if mostly composed by forbs (more than 50%). (e.g. Sonoran Desert) | -| | FRT5+5 | Hydromorphic fresh-water vegetation - mostly composed by aquatic plants that are structurally supported by water, in wet or flooded regions most of the year (e.g. Amazon Basin) | - -
- -______________________________________________________________________ - -## Socio-Economic indicators - -Natural hazards are a complex phenomenon featuring large number of interactions that result into loss of lives, livelihoods and interruption of systems. The socio-economic indicators are related to the capacity of populations to prepare, respond and recover from potential damage. For example, education theme is related to awareness, which is essential for a population to avoid and cope with a disaster. The Socio-economic Indicators taxonomy aims at identifying and describing a set of variables which provide a basis for understanding and measuring resilience, social vulnerability and economic vulnerability. The taxonomy system is divided into eight main themes (economy, education, environment, government and institutional capacity, index, health, infrastructure and population), each theme is later subdivided to different levels of detail. The eight main themes in the Socio-economic Indicator Taxonomy are the following: - -- [Population](#population): defines community demographics: structure, distribution and size. -- [Economy](#economy): measures the welfare and social security levels of communities -- [Education](#education): provides information about invested resources and expected outcome of education, access and participation to education -- [Environment](#environment): defines the underlying conditions that make an environment susceptible to damage, disaster experience and prevalence -- [Governance and institutional capacity](#governance): institutional performance and regulatory efficiency, corruption control and stability of political system -- [Health](#health): population health conditions and health sector capabilities -- [Index](#index): range of indexes that cover different sectors, for example, the Disaster Risk Index used by the United Nation Development programme to monitor the global evolution of risk. -- [Infrastructure](#infrastructure): Transportation and communication infrastructure, status and access to utility lifelines - -### Population - -
- -| Attribute | Code | Description | -| --------------------- | :-------: | ------------------------------------------------------ | -| Population Structure | POPPPSPOP | Population | -| | POPPPSRPP | Rural population | -| | POPPPSRUB | Urbanization Rate | -| | POPPPSSRI | Sex ratio | -| | POPPPSUPR | Urban population | -| | POPPPSADP | Age dependency ratio | -| | POPPPSAPD | Average Population Density (areas over 400 ppl/km2) | -| | POPPPSCAO | Percentage of land area with over 400 people per km2 | -| | POPPPSIMP | Foreign Born Migrants | -| | POPPPSLPF | Labour force participation rate - Female | -| | POPPPSNMR | Net migration rate | -| | POPPPSPGR | Population growth rate | -| Vulnerable Population | POPVNPSLP | Slum population in urban areas | -| | POPVNPPUF | Population under 5 | -| | POPVNPPIP | Percentage of the population below income poverty line | -| | POPVNPITA | International tourism arrivals | -| | POPVNPFPP | Female Population | -| | POPVNPASE | Population over 65 | -| | POPVNPTPP | Refugees (country of origin) | - -
- -### Economy - -
- -| Attribute | Code | Description | -| ------------------------------- | :-------: | ------------------------------------------------------------------------ | -| Economic Activity | ECOEACVLE | Value lost due to electrical outages | -| | ECOEACBEX | Budget expenditures | -| | ECOEACCDC | Carbon Dioxide Emissions | -| | ECOEACCPI | Consumer price index | -| | ECOEACEXS | Exports | -| | ECOEACFCE | Final consumption expenditure | -| | ECOEACFDP | Foreign direct investment, net inflows | -| | ECOEACGCE | General government final consumption expenditure | -| | ECOEACGFC | Gross fixed capital formation | -| | ECOEACGGE | Greenhouse gas emissions | -| | ECOEACGNC | GDP Nominal per population | -| | ECOEACGRB | General government revenue | -| | ECOEACGRN | GDP Nominal | -| | ECOEACGS1 | Gross savings | -| | ECOEACGUS | GNI per capita | -| | ECOEACHEE | Net Household final consumption expenditure | -| | ECOEACICR | Implied PPP conversion rate | -| | ECOEACIDA | Inflation, GDP deflator | -| | ECOEACIMP | Imports | -| | ECOEACIPD | Income payments (BoP) | -| | ECOEACMEP | Military expenditures | -| | ECOEAC039 | Adjusted savings: consumption of fixed capital | -| | ECOEACPCM | PPP conversion factor (GDP) to market exchange rate ratio | -| | ECOEACPEE | Remittance Inflows | -| | ECOEACPEP | Public expenditure on education | -| | ECOEACTIN | Total investment | -| | ECOEACTR1 | International tourism receipts as a percent of total exports | -| | ECOEACTRA | Trade | -| | ECOEACTRE | International tourism receipts as a percent of GDP | -| Economic Resources | ECOERETRG | Total reserves (includes gold) | -| | ECOERE040 | Adjusted savings: mineral depletion | -| | ECOERE042 | Adjusted savings: energy depletion | -| | ECOERE226 | Net ODA received per capita | -| | ECOEREBRE | Budget revenues | -| | ECOERECNT | Net taxes on products | -| | ECOEREDEX | Debt - external | -| | ECOEREGGD | General government gross debt | -| | ECOEREGNS | Gross national savings | -| | ECOEREGPC | GDP at purchasing power parity per capita | -| | ECOEREIRP | Inflation rate (consumer prices) | -| | ECOERELAP | Land use - arable land | -| | ECOERELCP | Land use - permanent crops | -| | ECOEREMQP | Money and quasi money (M2) | -| | ECOERENLB | General government net lending/borrowing | -| | ECOEREPDP | Public debt | -| | ECOERERDE | Research and development expenditure | -| | ECOERETRV | Tax revenue | -| | ECOERETTR | Total tax rate | -| Economic Composition | ECOECPAGR | GDP composition by sector - agriculture | -| | ECOECPWRT | Wholesale, retail trade, restaurants and hotels (ISIC G-H) | -| | ECOECPTSC | Transport, storage and communication (ISIC I) | -| | ECOECPSER | GDP - composition by sector - services | -| | ECOECPOTA | Other Activities (ISIC J-P) | -| | ECOECPMMU | Mining, Manufacturing, Utilities (ISIC C-E) | -| | ECOECPIND | GDP composition by sector - industry | -| | ECOECPCON | Construction (ISIC F) | -| | ECOECPAHF | Agriculture, hunting, forestry, fishing (ISIC A-B) | -| Income Distribution and Poverty | ECOIDPLIS | Income share held by lowest 20% | -| | ECOIDPPPL | Population below national poverty line | -| | ECOIDPPOG | Poverty gap at \$2 a day (PPP) | -| | ECOIDPGIN | GINI index | -| | ECOIDPISF | Income share held by fourth 20 % | -| | ECOIDPISH | Income share held by highest 20% | -| | ECOIDPISS | Income share held by second 20 % | -| | ECOIDPIST | Income share held by third 20 % | -| | ECOIDPPGP | Poverty gap at \$1.25 a day (PPP) | -| Labour Market | ECOLAMLPT | Labor force participation rate | -| | ECOLAMRRD | Researchers in R&D | -| | ECOLAMTEC | Technicians in R&D | -| | ECOLAMUEP | Unemployment Rate | -| | ECOLAMEAT | Employment in agriculture | -| | ECOLAMEIT | Employment in industry | -| | ECOLAMEPT | Ratio of youth employment to population ages 15-24 | -| | ECOLAMEST | Employment in services | -| | ECOLAMFLM | Female legislators, senior officials and managers | -| | ECOLAMLAF | Labor force | -| | ECOLAMLP1 | Female labor participation rate | -| | ECOLAMPET | Employment to population ratio ages 15+ | -| Trade Economics | ECOTRECID | Cost to import | -| | ECOTREMIC | Merchandise imports CIF | -| | ECOTREISS | Imports of goods and services | -| | ECOTRECED | Cost to export | -| | ECOTRE072 | Tariff rate, most favored nation, weighted mean, all products percentage | -| | ECOTREMTR | Merchandise trade | -| | ECOTREIGD | Imports of goods and services (BoP) | -| | ECOTREMEX | Merchandise exports to developing economies within region | -| | ECOTREEVI | Export volume index | -| | ECOTREEVE | Export value index | -| | ECOTREEEE | Merchandise exports FOB | -| | ECOTRECPT | Container port traffic (TEU: 20 foot equivalent units) | - -
- -### Education - -
- -| Attribute | Code | Description | -| ----------------- | :-------: | --------------------------------------------------------- | -| Education Outcome | EDUEOCSAF | Female population without secondary education or higher | -| | EDUEEOCCT | Primary School Completion Rate | -| | EDUEOCEYS | Expected Years of Schooling | -| | EDUEOCLFM | Ratio of young literate males to females ages 15-24 | -| | EDUEOCLFP | Illiteracy - female | -| | EDUEOCLMP | Illiteracy - male | -| | EDUEOCLTP | Illiteracy | -| | EDUEOCMYS | Mean Years of Schooling | -| | EDUEOCSAM | Male population without secondary education or higher | -| | EDUEOCSTJ | Scientific and technical journal articles | -| Education Access | EDUEACEEG | Education expenditures | -| | EDUEACPTS | Pupil-teacher ratio, secondary | -| | EDUEACPTP | Pupil-teacher ratio, primary | -| | EDUEACETG | Gross enrolment ratio, tertiary | -| | EDUEACSTG | Gross enrolment ratio, secondary | -| | EDUEACBGP | Ratio of girls to boys in primary and secondary education | -| | EDUEACEPG | Gross enrolment ratio, primary | -| | EDUEACCPT | Children out of school, primary | - -
- -### Environment - -
- -| Attribute | Code | Description | -| ------------------------ | :-------: | ------------------------------------------------------------ | -| Disaster Prevalence | ENVDIPDFT | Droughts, floods, extreme temperatures | -| | ENVDIPPLM | Population living in areas where elevation is below 5 meters | -| | ENVDIPINP | Natural disasters - Population affected | -| | ENVDIPIND | Natural disasters - Number of deaths | -| | ENVDIPDRR | Disaster risk reduction progress score | -| Basic Geography | ENVGEOLAK | Land Area | -| | ENVGEOCLK | Geographic Classification | -| | ENVGEOFAP | Forest area | -| | ENVGEOWAK | Water Area | -| Landuse/Landcover | ENVLULALP | Arable land | -| | ENVLULFEC | Fertilizer consumption | -| | ENVLULURP | Urban pollution | -| | ENVLULPCP | Permanent cropland | -| | ENVLULALA | Agricultural land | -| Control of Corruption | GICPSCCOC | Control of Corruption | -| | GICPSCCRI | Corruption Index | -| Voice and Accountability | GICLRVSWP | Percentage of seats held by women in national parliaments | -| | GICLRVVOA | Voice and Accountability | -| | GICLRVVTE | Voter Turnout at last parliamentary Election | -| | GICLRVOIR | Official information is available on request | -| Rule of Law | GICLRVETD | Equal treatment and absence of discrimination | -| | GICLRVSLR | Strength of legal rights index | -| | GICPSCROL | Rule of Law | - -
- -### Governance - -| Attribute | Code | Description | -| ------------------------ | :-------: | --------------------------------------------------------------- | -| Political Stability | GICAVTCCL | Civil conflict is effectively limited | -| | GICPSCPSA | Political Stability and Absence of Violence | -| | GICAVTVRG | People do not resort to violence to redress personal grievances | -| | GICAVTLCP | Losses due to theft, robbery, vandalism, and arson | -| | GICAVTIHO | Intentional homicides | -| Government Effectiveness | GICGEFGEF | Government Effectiveness | -| Regulatory Quality | GICGEFREQ | Regulatory Quality | - -### Health - -
- -| Attribute | Code | Description | -| -------------------- | :-------: | ------------------------------------------------------------- | -| Health Status | HEAHSTFRT | Total fertility rate | -| | HEAHSTLRM | Lifetime risk of maternal death | -| | HEAHSTMAL | Infectious and parasitic diseases: Malaria (DALYs) | -| | HEAHSTMEI | One-year-olds lacking immunization against - Measles | -| | HEAHSTTUC | Infectious and parasitic diseases: Tuberculosis (DALYs) | -| | HEAHSTMRI | Infant mortality rate | -| | HEAHSTMUF | Under 5 years mortality rate | -| | HEAHSTPUP | Prevalence of undernourishment | -| | HEAHSTUNC | Unmet need for contraception | -| | HEAHSTAAP | HIV/AIDS - adult prevalence rate | -| | HEAHSTBAS | Births attended by skilled health staff | -| | HEAHSTBRC | Crude birth rate | -| | HEAHSTDII | Infectious and parasitic diseases: Diarrheal diseases (DALYs) | -| | HEAHSTDPC | Dietary Protein Consumption | -| | HEAHSTDRC | Crude death rate | -| | HEAHSTLEX | Life expectancy at birth | -| Healthcare Resources | HEAHCRHBE | Hospital beds | -| | HEAHCREHP | Health expenditure, private | -| | HEAHCREPP | Health expenditure, public | -| | HEAHCRERH | External resources for health | -| | HEAHCRHAT | Health expenditure, total | -| | HEAHCRHEC | Health expenditure per capita | -| | HEAHCRNMW | Nurses and midwives | -| | HEAHCRPHY | Physicians | - -
- -### Index - -
- -| Code | Description | -| :-------: | ------------------------------------------------------------------------- | -| INXHDIGIV | Inequality adjusted Human Development Index (Gender Inequality Index) | -| INXHDI012 | Human Development Index - 2012 | -| INXXXXSFI | State Fragility Index | -| INXXXXPOL | Polity Index IV | -| INXXXXLSC | Liner shipping connectivity index | -| INXXXXGEI | Gender Equity Index | -| INXXXXGBB | GEF benefits index for biodiversity | -| INXXXXEVI | Environmental Vulnerability Index | -| INXXXXESI | Environmental Sustainability Index | -| INXXXXDRI | Disaster Risk Index | -| INXLPICQL | Logistics performance index: Competence and quality of logistics services | - -
- -### Infrastructure - -
- -| Attribute | Code | Description | -| ---------------------------- | :-------: | --------------------------------------------------------- | -| Energy, Water and Sanitation | INFEWSNGC | Natural gas - consumption | -| | INFEWSOCB | Oil - consumption | -| | INFEWSOPB | Oil - production | -| | INFEWSRFC | Renewable internal freshwater resources per capita | -| | INFEWSIWR | Rural population access to improved water source | -| | INFEWSACE | Population with access to electricity | -| | INFEWSECO | Electricity - consumption | -| | INFEWSEIP | Net energy imports | -| | INFEWSEPR | Electricity - production | -| | INFEWSEUP | Energy use (kg of oil equivalent) | -| | INFEWSISP | Population access to improved sanitation facilities | -| | INFEWSISR | Rural population access to improved sanitation facilities | -| | INFEWSISU | Urban population access to improved sanitation facilities | -| | INFEWSIWP | Population access to improved water source | -| | INFEWSIWU | Urban population access to improved water source | -| Transport and Communication | INFTCOBRC | Fixed broadband Internet subscribers | -| | INFTCOATF | Air transport, freight | -| | INFTCOTLC | Telephone lines | -| | INFTCORDE | Road density | -| | INFTCOQPI | Quality of port infrastructure, WEF | -| | INFTCOMVC | Motor vehicles | -| | INFTCOMCC | Mobile cellular subscriptions | -| | INFTCORWG | Railways, goods transported | - -
From a87503000a0b55ee94c8ba21c89fa07ff597ca7f Mon Sep 17 00:00:00 2001 From: Duncan Dewhurst Date: Mon, 7 Aug 2023 10:36:42 +1200 Subject: [PATCH 2/7] docs: Format markdown files --- docs/index.md | 27 ++++++++++++++------------- docs/rdl/other-standards.md | 1 + 2 files changed, 15 insertions(+), 13 deletions(-) diff --git a/docs/index.md b/docs/index.md index 4f3abb51..2431800e 100644 --- a/docs/index.md +++ b/docs/index.md @@ -1,21 +1,22 @@ # Risk Data Library Standard -The Risk Data Library Standard (RDLS) is an **open metadata standard** for describing risk datasets used in climate and disaster risk assessments. - + +The Risk Data Library Standard (RDLS) is an **open metadata standard** for describing risk datasets used in climate and disaster risk assessments. + The purpose of the RDLS is to enable risk reduction and resilience building by making it easier for risk data publishers to describe their datasets and for risk data users to identify datasets to use in their work. Many different organisations produce or use risk datasets, including humanitarian organisations, insurance companies, academic institutions and multi-lateral development banks. - + The key feature of the RDLS is the metadata standard for describing **hazard**, **exposure**, **vulnerability**, and **loss** datasets. In addition to the metadata standard, the RDLS provides guidance on packaging and formatting for risk datasets, although it does not seek to standardise risk datasets themselves. - + The RDLS is curated by the [Global Facility for Disaster Reduction and Recovery](https://www.gfdrr.org) and is intended for use by anyone involved in publishing or using disaster risk data. It is an open standard and community contributions are welcome. - -The standard originated from in-depth consultations with the disaster and climate risk modeling community on improving access to risk datasets. It is the result of the collective effort and ongoing support of internationally-recognised research institutions and established global partnerships, bring together expertise in multiple hazards and all aspects of risk assessment. - + +The standard originated from in-depth consultations with the disaster and climate risk modeling community on improving access to risk datasets. It is the result of the collective effort and ongoing support of internationally-recognised research institutions and established global partnerships, bring together expertise in multiple hazards and all aspects of risk assessment. + To help you use RDLS effectively, the documentation includes the following sections: - -* An [introduction](rdl/index.md) to the RDLS -* [Reference](reference/index.md) documentation for the metadata standard -* [Guidance](guides/index.md) on how to publish metadata in RDLS format and how to package and format risk datasets -* A [glossary](glossary.md) of risk terminology -* Background information [about](about/index.md) the RDLS, including how it is governed, its history and roadmap, and who to contact for more information + +- An [introduction](rdl/index.md) to the RDLS +- [Reference](reference/index.md) documentation for the metadata standard +- [Guidance](guides/index.md) on how to publish metadata in RDLS format and how to package and format risk datasets +- A [glossary](glossary.md) of risk terminology +- Background information [about](about/index.md) the RDLS, including how it is governed, its history and roadmap, and who to contact for more information ```{eval-rst} .. toctree:: diff --git a/docs/rdl/other-standards.md b/docs/rdl/other-standards.md index cac37705..517bfadf 100644 --- a/docs/rdl/other-standards.md +++ b/docs/rdl/other-standards.md @@ -38,6 +38,7 @@ The RDL project performed a review of the most relevant hazard taxonomies and de The exposure schema can accommodate different descriptions of assets using a taxonomy which describes their characteristics (e.g. building occupancy, construction, age, height, etc. or road surface type). ### GED4ALL + In 2018 an international consortium led by the Global Earthquake Model Foundation (GEM) developed an open, multi-scale exposure data schema for multi-hazard analysis ([GED4ALL](https://wiki.openstreetmap.org/wiki/GED4ALL)) in response to recommendations from community consultation. GED4ALL simplified certain detailed engineering aspects of the original global exposure model focussed on earthquake hazards ([GED4GEM](https://journals.sagepub.com/doi/10.1177/8755293020919429)), while also expanding the exposure parameters included, so the impacts of other hazards could be related to exposure data using the standard. In this standard, GED4ALL is used as a reference in the exposure, vulnerability and loss components, to describe the exposure type to which losses relate, and to facilitate matching of appropriate vulnerability functions to exposure data, for example. Details about the development of GED4ALL are reported [here](https://riskdatalibrary.org/resources). GED4ALL can be populated with building-level data from OpenStreetMap (OSM) following the [guidance](https://wiki.openstreetmap.org/wiki/GED4ALL) from the Humanitarian OSM Team, which collects contributions from the community on how OSM tags can be best aligned with the GED4ALL taxonomy. This is the suggested option for classification of exposure data in the RDL. From 0b9654160158557d3a67626997e2220484769e15 Mon Sep 17 00:00:00 2001 From: Duncan Dewhurst Date: Mon, 7 Aug 2023 13:30:16 +1200 Subject: [PATCH 3/7] docs/rdl: Author content for what.md --- docs/img/structure.svg | 1 + docs/rdl/what.md | 36 ++++++++++++++++++++++++++++++------ 2 files changed, 31 insertions(+), 6 deletions(-) create mode 100644 docs/img/structure.svg diff --git a/docs/img/structure.svg b/docs/img/structure.svg new file mode 100644 index 00000000..5fd2913b --- /dev/null +++ b/docs/img/structure.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/docs/rdl/what.md b/docs/rdl/what.md index 8dfc3732..29e179b4 100644 --- a/docs/rdl/what.md +++ b/docs/rdl/what.md @@ -1,11 +1,35 @@ -# What is the RDLS +# What is the RDLS? -Scope +The Risk Data Library Standard (RDLS) is an open metadata standard for describing risk datasets used in climate and disaster risk assessments. -Metadata and data +Metadata is data that provides information about a dataset. The RDLS covers metadata that can apply to any dataset, such as a dataset's title and author, and metadata that is specific to risk datasets, such as the type of hazard a dataset relates to. -Content +RDLS defines risk-specific metadata for describing four types of dataset: -Structure +- **Hazard** datasets concern the processes or phenomena that may result in impacts such as loss of life, property damage and social and economic disruption. For example, the frequency and magnitude of earthquakes. -Schema and codelists +- **Exposure** datasets concern the situation of people, infrastructure and other tangible assets in hazard prone area. For example, the number of people living in an earthquake-affected area. + +- **Vulnerability** datasets concern the susceptibility of exposed people and assets to the impacts of hazards. For example, the likelihood of buildings collapsing in the event of an earthquake. + +- **Loss** datasets concern the damage caused when a hazard occurs. For example, the cost of repairing buildings damaged in an earthquake. + +For more detailed definitions of these terms, refer to the [glossary](../glossary.md). + +The [RDLS schema](../reference/schema.md) defines the meaning, structure and format of RDLS metadata. It defines the list of fields that can be used to describe risk datasets. RDLS metadata is structured as follows: + +![RDLS structure](../img/structure.svg) + +Metadata fields that are common to all resources are specified at the dataset level, whilst metadata fields that can vary by resource are specified at the resource level. Metadata fields that are specific to a particular type of risk data are specified at the dataset level and grouped under the relevant object: Hazard, Exposure, Vulnerability or Loss. + +The schema specifies a title, description and data type for each field. The schema also specifies other rules to which RDLS metadata needs to conform, such as which fields are required (mandatory) and whether fields need to conform to a particular format or range of values. Some fields refer to [codelists](../reference/codelists.md) to limit and standardise their values. + +For example, the `risk_data_type` field is defined as follows: + +```{jsonschema} ../../docs/_readthedocs/html/rdl_schema_0.1.json +--- +include: risk_data_type +--- +``` + +For more information on the fields, structure and format of RDLS metadata, refer to the [metadata reference](../reference/index.md). From a1f48fe7746c0b3f13525308e31c663697c4f7e4 Mon Sep 17 00:00:00 2001 From: Duncan Dewhurst Date: Mon, 7 Aug 2023 13:39:59 +1200 Subject: [PATCH 4/7] docs/rdl: Author content for how.md --- docs/index.md | 2 +- docs/rdl/how.md | 13 +++++++++++++ 2 files changed, 14 insertions(+), 1 deletion(-) diff --git a/docs/index.md b/docs/index.md index 2431800e..4fc938fb 100644 --- a/docs/index.md +++ b/docs/index.md @@ -4,7 +4,7 @@ The Risk Data Library Standard (RDLS) is an **open metadata standard** for descr The purpose of the RDLS is to enable risk reduction and resilience building by making it easier for risk data publishers to describe their datasets and for risk data users to identify datasets to use in their work. Many different organisations produce or use risk datasets, including humanitarian organisations, insurance companies, academic institutions and multi-lateral development banks. -The key feature of the RDLS is the metadata standard for describing **hazard**, **exposure**, **vulnerability**, and **loss** datasets. In addition to the metadata standard, the RDLS provides guidance on packaging and formatting for risk datasets, although it does not seek to standardise risk datasets themselves. +The key feature of the RDLS is the metadata standard for describing **hazard**, **exposure**, **vulnerability**, and **loss** datasets. In addition to the metadata standard, the RDLS provides guidance on packaging and formatting for risk datasets, although it does not seek to standardise the contents of risk datasets. The RDLS is curated by the [Global Facility for Disaster Reduction and Recovery](https://www.gfdrr.org) and is intended for use by anyone involved in publishing or using disaster risk data. It is an open standard and community contributions are welcome. diff --git a/docs/rdl/how.md b/docs/rdl/how.md index 3e89373e..f536ffee 100644 --- a/docs/rdl/how.md +++ b/docs/rdl/how.md @@ -1 +1,14 @@ # How do I implement the RDLS? + +To implement the Risk Data Library Standard (RDLS), you need to author RDLS metadata to describe your risk datasets and publish it alongside your datasets. You can either author RDLS metadata from scratch, or convert existing metadata to RDLS format. + +You can use the following resources and tools to implement RDLS: + +- The RDLS spreadsheet template can be used to author RDLS metadata in spreadsheet format. +- The RDLS metadata toolkit can be used to convert RDLS metadata from spreadsheet format to JSON format and to validate it against the RDLS schema. + +For step-by-step instructions on how to publish RDLS metadata, see the guidance on [how to publish RDLS metadata](../guides/metadata.md). + +In addition to the metadata standard, the RDLS provides [guidance on packaging and formatting risk datasets](../guides/datasets/index.md), although it does not seek to standardise the contents of risk datasets. + +If you have questions about the RDLS or need help implementing it, you can contact a member of the [Risk Data Library team](../about/contacts.md#risk-data-library-team). From 88ba7ce3bbaaa82ad7181e0f144e6324dcbb9396 Mon Sep 17 00:00:00 2001 From: Duncan Dewhurst Date: Mon, 7 Aug 2023 13:43:26 +1200 Subject: [PATCH 5/7] Update changelog --- docs/about/changelog.md | 1 + 1 file changed, 1 insertion(+) diff --git a/docs/about/changelog.md b/docs/about/changelog.md index b14db621..d402620c 100644 --- a/docs/about/changelog.md +++ b/docs/about/changelog.md @@ -80,5 +80,6 @@ This page lists changes to the Risk Data Library Standard. - [#111](https://github.com/GFDRR/rdl-standard/pull/111) - Add Global Library for Schools Infrastructure (GLOSI) to taxonomies. - [#172](https://github.com/GFDRR/rdl-standard/pull/172) - Re-write use cases as user stories, for data publisher and data user roles. +- [#175](https://github.com/GFDRR/rdl-standard/pull/175) - Restructure documentation, rewrite landing page, add new introductory content. ### Other From 40fff029dbe7a1851b9202357e6e2f2efaf10d26 Mon Sep 17 00:00:00 2001 From: odscjen Date: Mon, 7 Aug 2023 10:04:51 +0100 Subject: [PATCH 6/7] schema.md: fix typo in Exposure --- docs/reference/schema.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/reference/schema.md b/docs/reference/schema.md index 0d7aafbf..2b640a9e 100644 --- a/docs/reference/schema.md +++ b/docs/reference/schema.md @@ -204,7 +204,7 @@ The exposure component uses exposure categories consistent with the vulnerabilit ```{eval-rst} .. mermaid:: - classDiagramtaxonomies + classDiagram Model -- Asset1 Model -- Asset2 Model: Category From 1aece4b9772ab76dba360a97f7e7b8700c2f146c Mon Sep 17 00:00:00 2001 From: Duncan Dewhurst Date: Tue, 8 Aug 2023 08:51:30 +1200 Subject: [PATCH 7/7] docs/rdl/what.md: Fix schema link --- docs/rdl/what.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/rdl/what.md b/docs/rdl/what.md index 29e179b4..48423cd0 100644 --- a/docs/rdl/what.md +++ b/docs/rdl/what.md @@ -26,7 +26,7 @@ The schema specifies a title, description and data type for each field. The sche For example, the `risk_data_type` field is defined as follows: -```{jsonschema} ../../docs/_readthedocs/html/rdl_schema_0.1.json +```{jsonschema} ../../docs/_readthedocs/html/rdls_schema.json --- include: risk_data_type ---