+ └── <...>
+ └── <...>
+```
diff --git a/docs/guides/rdl-metadata.md b/docs/guides/rdl-metadata.md
new file mode 100644
index 00000000..129ba71e
--- /dev/null
+++ b/docs/guides/rdl-metadata.md
@@ -0,0 +1,10 @@
+# RDL metadata
+
+## Adoption of the metadata schema
+
+Metadata enables datasets to be found by human and machine searches, and so users can easily identify the dataset contents. It is strongly encouraged that any risk dataset being uploaded online has metadata prepared and uploaded with it.
+
+The Risk Data Library Standard defines metadata in JSON format, but it can be translated into table (csv/excel). `WIP`
+
+- Option 1. Write directly into JSON file (templates are available at ...)
+- Option 2. Use JSON metadata creation tool. This tool is standalone (not part of DDH) AND UNDER DEVELOPMENT. It uses an xsl file containing metadata in a specified structure, and exports a JSON file to be saved with the dataset.
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diff --git a/docs/img/vln_multi-table.jpg b/docs/img/vln_multi-table.jpg
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diff --git a/docs/implementation/index.md b/docs/implementation/index.md
deleted file mode 100644
index dc2ebcbb..00000000
--- a/docs/implementation/index.md
+++ /dev/null
@@ -1,20 +0,0 @@
-# Implementation
-
-The RDL schema and standard can be adopted to risk project data in different ways:
-
-- [**Structure and naming convention**](local.md) of risk data files and folders
-- [**Catalogue implementation**](jkan.md) based on open-source *JKAN* static content creator for simple file storage and download
-- [**Database implementation**](postgres.md) based on *PostGRESQL* for advanced features
-
-
-
-```{eval-rst}
-.. toctree::
- :maxdepth: 1
- :hidden:
-
- local
- jkan
- postgres
-
-```
diff --git a/docs/implementation/jkan.md b/docs/implementation/jkan.md
deleted file mode 100644
index 196eb151..00000000
--- a/docs/implementation/jkan.md
+++ /dev/null
@@ -1,5 +0,0 @@
-# JKAN catalogue
-
-Live istance of RDL JKAN catalogue available at [jkan.riskdatalibrary.org](https://jkan.riskdatalibrary.org).
-
-
diff --git a/docs/implementation/local.md b/docs/implementation/local.md
deleted file mode 100644
index 6ae2f692..00000000
--- a/docs/implementation/local.md
+++ /dev/null
@@ -1,40 +0,0 @@
-# Local schema implementation
-
-Structuring and naming of risk data files within a project folder represent the simplest and most direct level of implementation of the Risk Data Standard.
-
-## Structure of project folder
-
-
-
-## Naming convention for files
-
-To help univocally identify the content of a dataset file, the filename should summarise all the key information that allow to distinquish it from the others.
-The general format, all in lower caps, uses a tag approach to build the full filename:
-
-```
- [component_code]-{project_name}-[country_iso]-{schema_specifics}-{time}
-```
-
-The name is made of \[required\] and {optional} attributes. Each component uses the most relevant attribute as schema_specifics, for example:
-
-- Hazard:
- `hzd-[country_iso]-{project_name}-{hazard_type}-{process_type}-{hazard_trigger}-{frequency}-{time}`
- Example: pluvial flood hazard scenario with return period 10 years in 2050 for Afghanistan is named:
- **hzd-afg-mhra-fl-fpf-rp10-2050**
-
-- Exposure:
- `exp-[country_iso]-{project_name}-{occupancy}-{exposure_model}-{time}`
- Example: residential exposure in Madagascar from Open Street Map 2015 is named:
- **exp-mdg-swio_rafi-residential-osm-2015**
-
-- Vulnerability:
- `vln-[country_iso]-{project_name}-{hazard_type}-{occupancy}-{vulnerability_model}`
- Example: flood depth-damage function developed for India by JRC over industrial land cover is named:
- **vln-ind-fl-industrial-jrc**
-
-- Loss:
- `lss-[country_iso]-{project_name}-{hazard_type}-{occupancy}-{time}`
- Example: eartquake losses over Madagascar infrastructures over the period 1920-2012 is named:
- **lss-mdg-eq-infrastructrure-1920_2012**
-
-
diff --git a/docs/implementation/postgres.md b/docs/implementation/postgres.md
deleted file mode 100644
index 7fc6c71a..00000000
--- a/docs/implementation/postgres.md
+++ /dev/null
@@ -1,3 +0,0 @@
-# PostGRESQL database
-
-
diff --git a/docs/index.md b/docs/index.md
index 3ff03346..efbdcb4f 100644
--- a/docs/index.md
+++ b/docs/index.md
@@ -2,22 +2,21 @@
# 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 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 RDLS provides a unique way to create, store, exchange and use disaster different risk information together. It is at the core of the Risk Data Library, a suite of open source tools to work with disaster and climate risk 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:
-- [**Core standards**](standards.md): description of existing open data standards used in the RDLS
-- [**Taxonomy**](taxonomies/index.md): details of taxonomies adopted by the RDLS
-- [**Data model**](data_model/index.md): how to organize and link the data using the RDLS schema
-- [**Implementation**](implementation/index.md): how to apply the RDLS in your project
-- [**Tutorials**](tutorials/index.md): how to adopte and use RDLS for different pruposes
-- [**About**](about/index.md): other information on the roadmap, history, governance and license
-
-
+- [Overview](rdl/index.md): The core standards used within the RDLS, use cases and a roadmap
+- [Data model](data_model/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.
@@ -26,13 +25,10 @@ The RDL is a collaborative project managed by the [Global Facility for Disaster
:maxdepth: 1
:hidden:
- keyconcepts
- standards
- taxonomies/index
- usecases
+ rdl/index
data_model/index
- implementation/index
- tutorials/index
+ taxonomies/index
+ guides/index
+ glossary
about/index
-
```
diff --git a/docs/rdl/core-standards.md b/docs/rdl/core-standards.md
new file mode 100644
index 00000000..56116870
--- /dev/null
+++ b/docs/rdl/core-standards.md
@@ -0,0 +1,36 @@
+# 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/index.md b/docs/rdl/index.md
new file mode 100644
index 00000000..93ac9a32
--- /dev/null
+++ b/docs/rdl/index.md
@@ -0,0 +1,12 @@
+# Overview
+
+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.
+
+```{eval-rst}
+.. toctree::
+ :maxdepth: 1
+
+ core-standards
+ use-cases
+ roadmap
+```
diff --git a/docs/rdl/roadmap.md b/docs/rdl/roadmap.md
new file mode 100644
index 00000000..2e60dae8
--- /dev/null
+++ b/docs/rdl/roadmap.md
@@ -0,0 +1,40 @@
+# History and roadmap
+
+## History (2016-2021)
+
+The Risk Data Library project is led by the Global Facility for Disaster Reduction and Recovery ([GFDRR](https://www.gfdrr.org/en)), under its [Digital Earth](https://www.gfdrr.org/en/digitalearthpartnership) Thematic Area.
+GFDRR is a global partnership that helps developing countries better understand and reduce their vulnerability to natural hazards and climate change.
+
+The RDL project originated under the GFDRR Innovation Labs uses cutting-edge science and technology to make high-quality risk information available faster and at lower costs, and develop new tools that allow decision-makers and communities to collect, share, and understand risk information. We tailor our approach to support the full range of disaster risk management interventions — from preparedness to risk reduction to consideration of financial solutions.
+
+The Risk Data Library concept emerged from in-depth research into the risk information needs and priorities of the DRM sector. In 2014, GFDRR and the UK Government Department for International Development (DfID) launched an 18-month consultation with donors, data producers and users from over a hundred organisations across the DRM community. Several priority needs were identified and seed funding made available to projects that would start to address them. The Risk Data Library began as one of these projects and addresses four of the eight priorities identified in the research:
+
+- Plausible hazard scenarios for developing countries
+- Open and freely available vulnerability functions
+- Exposure datasets suitable for detailed risk assessment
+- An established standard for model interoperability
+
+The [Solving the Puzzle report](https://www.gfdrr.org/en/solving-puzzle-innovating-reduce-risk) documents the findings and recommendations of the consultation. This report provides a community perspective on priorities for future collaboration and investment in the development and use of disaster risk information for developing countries. The focus is on high-impact activities that will promote the creation and use of risk-related data, catastrophe risk models, and platforms, and that will improve and facilitate the understanding and communication of risk assessment results.
+
+On the recommendations of 'Solving the Puzzle', GFDRR commissioned the development of risk data schema, comprising connected components:
+
+- An open exposure data schema. The Global Earthquake Model Foundation (GEM) led the development of the exposure component (GED4ALL) of the RDL schema. GEM has continued to contribute to the project by developing the modeled loss component and creating the unified schema and database.
+- University College London (UCL) EPICentre developed the vulnerability component (MOVER) and has continued to refine this in collaboration with GEM.
+- The British Geological Survey (BGS) led the development of the hazard data component of the RDL schema.
+- Collaborating partners in the first phase of schema development also included HOTOSM, ImageCat, Norwegian Geotechnical Institute, NERC National Oceanographic Centre, CIMA Foundation, Earth Observatory Singapore, Global Volcano Model, and the Global Flood Partnership.
+- GeoSolutions developed an open pilot risk visualization dashboard (HEV-E), intended to visualize the contents of the hazard, exposure and vulnerability schema.
+
+In 2019, the existing schema was updated by GEM and UCL EPICentre and they developed a modeled loss schema.
+
+In 2020 the existing schema, still focussed on a database format for storing data, was updated to enable closer integration of the four components by creating a unified database and common tables linking all schema.
+
+Through 2021, GFDRR worked with open data standards specialists to explore modifying the database schema into an open standard. At the same time, a new lightweight data catalog, using the JKAN standard, was developed as a pilot for an open data catalog.
+
+## Roadmap (2022 onwards)
+
+In 2022, GFDRR obtained grant funding from the [Swiss Re Foundation](https://www.swissrefoundation.org/) to further develop the Risk Data Library Standard, as an open standard.
+
+- GFDRR worked with the World Bank Development Data Hub (Data Catalog) team to establish the [Risk data Library Collection](https://datacatalog.worldbank.org/search/collections/rdl).
+- GFDRR established the Disaster and Climate Risk Fellowship program, in which The Digital Earth team at GFDRR is recruiting fellows from vulnerable countries to support World Bank disaster and climate risk data projects and contribute to the adoption of the new Risk Data Library Standard. The fellowship program offers a 6-month placement for climate and disaster risk professionals from selected climate-vulnerable countries to work with the Risk Data Library Standard to access, create and communicate climate risk knowledge with their communities. The selected countries are: Bangladesh, Democratic Republic of the Congo, India, Indonesia, Philippines, and South Africa.
+- GFDRR collaborated with the [Open Data Services Co-operative](https://opendataservices.coop/) to establish the JSON standard and improve documentation and sustainability of RDLS using open standards best practice.
+- GFDRR and Swiss Re Foundation established a new steering committee for the period of the grant funding, to oversee development of the standard and outcomes of the fellowship program. The steering committee comprises members of the original development teams, and data users from the insurance industry and curators of other open data standards.
diff --git a/docs/rdl/use-cases.md b/docs/rdl/use-cases.md
new file mode 100644
index 00000000..20b228e2
--- /dev/null
+++ b/docs/rdl/use-cases.md
@@ -0,0 +1,29 @@
+# Use cases
+
+A **risk analyst** is scoping available risk data for a **disaster risk reduction project**. Searching the **RDL catalog** they can review the available data for the location of interest. They can then interrogate the data easily given the detailed and consistent **metadata** available, to make a decision on whether to directly use it in their analysis or invest in improving it.
+
+***Value***: Reduced time to find and understand existing data.
+
+______________________________________________________________________
+
+A **development bank** produces public good dashboards to deliver **risk insights** to client governments. The dashboard uses risk data from multiple projects to estimate the **number of assets or population** exposed to risk to assist in prioritising investments. Pulling data via the **RDL API**, many different datasets can be ingested and applied through a single workflow.
+
+***Value***: Efficient data pipelines to ingest multiple datasets with confidence in the consistency of data structure and metadata.
+
+______________________________________________________________________
+
+An **academic research team** needs to demonstrate the impact of a **risk analytics and urban planning project**, by making the data available for others to use. Their dataset are formatted according to the **RDL standards** and published in a data catalogue set up for the project, using the **template implementation** available through the RDL project.
+
+***Value***: The pre-designed open-source deployable solutions can assist a research group achieve impact efficiently.
+
+______________________________________________________________________
+
+An **insurance industry analyst or model developer** needs to **build a new catastrophe model** or **analyse a new portfolio** to insure in an emerging market, where the company has limited experience and data. They are searching for existing data to support their analysis and find some existing data created by consultants in the development sector, shared via the Risk Data Library Collection of the World Bank Data Catalog, formatted according to the **RDL standards** and available to download and use.
+
+***Value***: The data can be used directly or improved to assess the risk to the new portfolio, and could expedite the placement of insurance cover for vulnerable communities.
+
+______________________________________________________________________
+
+A **humanitarian organisation** are creating a **disaster risk financing** program to fund, ex-ante, disaster response and recovery and an **anticipatory action** program. They are relying on historical observations to assess the risk to define a suitable risk layered approach and select the correct DRF solutions, and want to improve this method by including probabilistic analysis. Using RDL tools they are able to find datasets and the results of previous risk analysis. Because the datasets are formatted according to the **RDL standards** they are able to quickly understand the contents of the data and whether it is suitable for their use.
+
+***Value***: The data can be improve existing methods in risk financing to make DRF solution more efficient and sustainable.
diff --git a/docs/standards.md b/docs/standards.md
deleted file mode 100644
index be0ca8fe..00000000
--- a/docs/standards.md
+++ /dev/null
@@ -1,7 +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.
diff --git a/docs/taxonomies/ged4all.md b/docs/taxonomies/ged4all.md
index 41e85a38..2d800687 100644
--- a/docs/taxonomies/ged4all.md
+++ b/docs/taxonomies/ged4all.md
@@ -12,7 +12,7 @@ The taxonomy covers four main categories:
## Buildings
-The buildings taxonomy is based on GEM openquake taxonomy, with some semplifications. The taxonomy string is built as sequence of attributes separeted by slash:
+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/…`
@@ -22,115 +22,116 @@ Missing attributes can be skipped from the string, e.g.
-| 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 nd 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 |
+| 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
@@ -153,26 +154,25 @@ 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. |
+| 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
@@ -183,164 +183,161 @@ 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 |
+| 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 ditribution line through pylones: `PWG/SSM/ANC`
+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 |
+| 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 wasterwater treatment plants, lifting stations and
+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 wasterwater
+`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 |
+| 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 dissimination of information (e.g. telephones offices, call centers, TV stations, radio station, telecomunication 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.
+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 |
-
-
+| 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
@@ -350,131 +347,130 @@ The taxonomy for crops, livestock and forestry was defined based on existing cla
-| 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 | |
+| 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 | | |
+| 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 rees 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) |
+| 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
@@ -493,292 +489,287 @@ Natural hazards are a complex phenomenon featuring large number of interactions
-| 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) |
+| 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) |
+| 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 enrollment ratio, tertiary |
-| | EDUEACSTG | Gross enrollment ratio, secondary |
-| | EDUEACBGP | Ratio of girls to boys in primary and secondary education |
-| | EDUEACEPG | Gross enrollment ratio, primary |
-| | EDUEACCPT | Children out of school, primary |
+| 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 |
+| 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 |
+<<<<<<< HEAD
### Governance
+=======
+>>>>>>> dev
-| 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 |
+### 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 |
+| 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 |
+| 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 |
+| 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 |
-
-
diff --git a/docs/taxonomies/index.md b/docs/taxonomies/index.md
index 00b7ea11..aa34880e 100644
--- a/docs/taxonomies/index.md
+++ b/docs/taxonomies/index.md
@@ -2,126 +2,29 @@
# Taxonomies
-The RDLS defines taxonomies for describing risk data. In this section you will find a short summary of the taxonomies recommended for the RDLS, as well as the other main taxonomies for disaster risk assessments.
+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.
## Hazard taxonomies
-There are several existing taxonomies that could have been adopted to describe hazard data. The RDL project performed a review of most of them.
-
-This resulted in an new taxonomy to unify the existing taxonomies for the purpose of risk data 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.
-
-### RDLS Hazard Taxonomy (recommended)
-
-The **RDLS Hazard Taxonomy** classifies hazard phenomena as main hazard (8 categories) and hazard process (27 categories):
-
-
-
-| **Hazard type** | **Process type** |
-|---|---|
-| Coastal Flood | Coastal Flood |
-| Coastal Flood | Storm Surge |
-| Convective Storm | Tornado |
-| Drought | Agricultural Drought |
-| Drought | Hydrological Drought |
-| Drought | Meteorological Drought |
-| Drought | Socio-economic Drought |
-| Earthquake | Primary Rupture |
-| Earthquake | Secondary Rupture |
-| Earthquake | Ground Motion |
-| Earthquake | Liquefaction |
-| Extreme Temperature | Extreme cold |
-| Extreme Temperature | Extreme heat |
-| Flood | Fluvial Flood |
-| Flood | Pluvial Flood |
-| Landslide | Landslide |
-| Landslide | Snow Avalanche |
-| Tsunami | Tsunami |
-| Volcanic | Ashfall |
-| Volcanic | Ballistics |
-| Volcanic | Proximal hazards |
-| Volcanic | Lahar |
-| Volcanic | Lava |
-| Volcanic | Pyroclastic Flow |
-| Wildfire | Wildfire |
-| Strong Wind | Extratropical cyclone |
-| Strong Wind | Tropical cyclone |
-
-
-
-
-Each hazard type and associated processes can have one or more type of measure metrics, which include the unit of measure:
-
-
-
-**Hazard type** | **Metric:Unit** | **Description**
----|---|---
-EQ | PGA:g | Peak ground acceleration in g
-EQ | PGA:m/s2 | Peak ground acceleration in m/s2 (meters per second squared)
-EQ | PGV:m/s | Peak ground velocity in m/s
-EQ | AvgSa:m/s2 | Average spectral acceleration
-EQ | Sd(T1):m | Spectral displacement
-EQ | Sv(T1):m/s | Spectral velocity
-EQ | PGDf:m | Permanent ground deformation
-EQ | D:s | Significant duration
-EQ | IA:m/s | Arias intensity (Iα) or (IA) or (Ia)
-EQ | Neq:- | Effective number of cycles
-EQ | EMS:- | European macroseismic scale
-EQ | MMI:- | Modified Mercalli Intensity
-EQ | CAV:m/s | Cumulative absolute velocity
-EQ | D_B:s | Bracketed duration
-FL, CF | fl_wd:m | Flood water depth
-FL, CF | fl_wv:m/s | Flood flow velocity
-WI | v_ect(3s):km/h | 3-sec at 10m sustained wind speed (kph)
-WI | v_ect(1m):km/h | 1-min at 10m sustained wind speed (kph)
-WI | v_etc(10m):km/h | 10-min sustained wind speed (kph)
-WI | PGWS_tcy:km/h | Peak gust wind speed
-LS | ls_fd:m | Landslide flow depth
-LS | I_DF:m3/s2 | Debris-flow intensity index
-LS | v_lsl:m/s2 | Landslide flow velocity
-LS | ls_mfd:m | Maximum foundation displacement
-LS | SD_lsl:m | Landslide displacement
-TS | Rh_tsi:m | Tsunami wave runup height
-TS | d_tsi:m | Tsunami inundation depth
-TS | MMF:m4/s2 | Modified momentum flux
-TS | F_drag:kN | Drag force
-TS | Fr:- | Froude number
-TS | v_tsi:m/s | Tsunami velocity
-TS | F_QS:kN | Quasi-steady force
-TS | MF:m3/s2 | Momentum flux
-TS | h_tsi:m | Tsunami wave height
-TS | Fh_tsi:m | Tsunami Horizontal Force
-VO | h_vaf:m | Ash fall thickness
-VO | L_vaf:kg/m2 | Ash loading
-DR | CMI:- | Crop Moisture Index
-DR | PDSI:- | Palmer Drought Severity Index
-DR | SPI:- | Standard Precipitation Index
-
-
-
-
-### Other hazard taxonomies
-
-For a mapping between RDLS Hazard Taxonomy and other existing hazard taxonomies, please see this here.
-
-List of other hazard taxonomies below:
-
-- [**UNDRR**](https://www.undrr.org/publication/hazard-definition-and-classification-review) (formerly UNISDR) recently proposed an extended taxonomy that covers 300 natural and anthropogenic hazards in 8 categories (Meteo-Hydrological, Geohazard, Environmental, Extraterrestrial, Chemical, Biological, Technological, Societal).
-
-- [**Disaster Risk Management Knowledge Centre**](https://drmkc.jrc.ec.europa.eu/risk-data-hub) covers 32 natural and anthropogenic hazards in 8 categories (Geophysical, Hydrological, Meteorological, Climatological, Biological, Technological, Transportation, Malicious).
-
-- [**Inspire**](https://inspire.ec.europa.eu/codelist/NaturalHazardCategoryValue) covers 25 natural hazards in 6 categories (Geological/hydrological, Meteorological/climatological, Fires, Biological, Cosmic, Other).
-
-- [**EM-DAT**](https://www.emdat.be/classification) covers 34 natural and technological hazards in 9 categories (Geophysical, Meteorological, Hydrological, Climatological, Biological, Extraterrestrial, Industrial accident, Transport accident, Miscelleanous accident).
-
-- [**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 taxonomy
-
-The exposure schema can accomodate different descriptions of assets using a taxonomy which describes their characteristics (e.g. building occupancy, construction, age, height, etc. or road surface type).
+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:
+
+- [UNDRR](https://www.undrr.org/publication/hazard-definition-and-classification-review) (formerly UNISDR) recently proposed an extended taxonomy that covers 300 natural and anthropogenic hazards in 8 categories (Meteo-Hydrological, Geohazard, Environmental, Extraterrestrial, Chemical, Biological, Technological, Societal).
+
+- [Disaster Risk Management Knowledge Centre](https://drmkc.jrc.ec.europa.eu/risk-data-hub) covers 32 natural and anthropogenic hazards in 8 categories (Geophysical, Hydrological, Meteorological, Climatological, Biological, Technological, Transportation, Malicious).
+
+- [Inspire](https://inspire.ec.europa.eu/codelist/NaturalHazardCategoryValue) covers 25 natural hazards in 6 categories (Geological/hydrological, Meteorological/climatological, Fires, Biological, Cosmic, Other).
+
+- [EM-DAT](https://www.emdat.be/classification) covers 34 natural and technological hazards in 9 categories (Geophysical, Meteorological, Hydrological, Climatological, Biological, Extraterrestrial, Industrial accident, Transport accident, Miscellaneous accident).
+
+- [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
+
+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.
+[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::
@@ -132,6 +35,36 @@ The exposure schema can accomodate different descriptions of assets using a taxo
```
-### Other exposure taxonomies
+### GEM Building Taxonomy
+
+The [GEM Building Taxonomy](https://www.globalquakemodel.org/gempublications/GEM-building-taxonomy-version-2.0) is dedicated to building characteristics relevant to assessing vulnerability to seismic events. It describes characteristics such as an asset's height, number of storeys, age, occupancy, material, type of roof, floor, foundations and structural system. [TaxtWEB](https://platform.openquake.org/taxtweb) is a tool developed by GEM to assist with the generation of the taxonomy string which is used to describe these attributes.
+
+Example: The string `CR/HEX:1/YEX:1981/RES+RES1` describes a residential single family building, of reinforced concrete construction, built in 1981. This is the short version of the taxonomy, the long version explicitly includes all of the unknown fields too.
+
+### Open Exposure Data (OED)
+
+[OED](https://github.com/OasisLMF/ODS_OpenExposureData) is a standard curated by the Oasis community for the insurance industry. The aim of OED is to provide the industry with a robust, open, and transparent data format. The detailed descriptions of the OED taxonomy to describe an asset (structure, infrastructure, or human) are covered in ['Open Exposure Data Spec.xlsx' with reference and background information](https://github.com/OasisLMF/ODS_OpenExposureData/tree/develop/OpenExposureData/Docs), or \[online\]https://oasislmf.github.io/OpenDataStandards/index.html.
+
+Example: In the Open Exposure Data (OED) Standard and other insurance industry models, asset characteristics are separated into individual columns. This record describes a building classified as general residential, single storey, constructed from adobe masonry, with an unknown year of construction:
+
+| OccupancyCode | ConstructionCode | NumberOfStoreys | YearBuilt |
+| ------------- | ---------------- | --------------- | --------- |
+| 1050 | 5101 | 1 | 0 |
+
+### CEDE
+
+[CEDE (Catastrophe Exposure Data Exchange)](https://docs.air-worldwide.com/Database/CEDE/10.0/webframe.html#topic1.html), is the exposure database format used by Touchstone®, AIR's comprehensive risk management platform that was first released in early 2013. It is publicly available and used widely in the insurance industry to describe asset characteristics and values for catastrophe modelling. CEDE uses a database format and allows users to apply different occupancy and construction schemes and codesets to their data, and add additional fields describing year of construction, number of storeys, etc. The most common taxonomy used in CEDE is [AIRConstruction](https://docs.air-worldwide.com/Database/CEDE/10.0/webframe.html#topic32.html) and [AIROccupancy](https://docs.air-worldwide.com/Database/CEDE/10.0/webframe.html#topic33.html). These codes are also available in the [OED Open Exposure Data Spec](https://github.com/OasisLMF/ODS_OpenExposureData/tree/develop/OpenExposureData/Docs) as OED was based on and builds on CEDE.
+
+Example: In CEDE data asset characteristics are separated into individual columns. This record describes a building classified as general residential, single storey, constructed from adobe masonry, with an unknown year of construction:
+
+| OccupancyCode | ConstructionCode | NumberOfStoreys | YearBuilt |
+| ------------- | ---------------- | --------------- | --------- |
+| 301 | 112 | 1 | 0 |
+
+## Vulnerability taxonomies
+
+Content under development.
+
+## Loss taxonomies
-[**GEM-OpenQuake**](https://platform.openquake.org/taxtweb): developed specifically for the Global Earthquake Model (GEM), this taxonomy is dedicated to buildings for which it describe the size and properties (height, number of storeys, age, occupancy, material, type of roof, floor and foundations).
+Content under development.
diff --git a/docs/tutorials/data-import.md b/docs/tutorials/data-import.md
deleted file mode 100644
index cc8fea4d..00000000
--- a/docs/tutorials/data-import.md
+++ /dev/null
@@ -1,7 +0,0 @@
-# Import data in the schema DB
-
-## JKAN
-
-## PostGRESQL
-
-
diff --git a/docs/tutorials/data-preparation.md b/docs/tutorials/data-preparation.md
deleted file mode 100644
index 871843c3..00000000
--- a/docs/tutorials/data-preparation.md
+++ /dev/null
@@ -1,3 +0,0 @@
-# Data prepration
-
-
diff --git a/docs/tutorials/deploy.md b/docs/tutorials/deploy.md
deleted file mode 100644
index 8f9cf4b5..00000000
--- a/docs/tutorials/deploy.md
+++ /dev/null
@@ -1,3 +0,0 @@
-# Deploy
-
-
diff --git a/docs/tutorials/index.md b/docs/tutorials/index.md
deleted file mode 100644
index 24e8cfd1..00000000
--- a/docs/tutorials/index.md
+++ /dev/null
@@ -1,11 +0,0 @@
-# Tutorials
-
-```{eval-rst}
-.. toctree::
- :maxdepth: 1
-
- deploy
- data-preparation
- data-import
-
-```
diff --git a/docs/usecases.md b/docs/usecases.md
deleted file mode 100644
index f28569d2..00000000
--- a/docs/usecases.md
+++ /dev/null
@@ -1,19 +0,0 @@
-# Use cases
-
-A **risk analyst** is scoping available risk data for a **disaster risk reduction project**. Searching the **RDL catalog** they can review the available data for the location of interest. They can then interrogate the data easily given the detailed and consistent **metadata** available, to make a decision on whether to directly use it in their analysis or invest in improving it.
-
-***Value***: Reduced time to find and understand existing data.
-
-
-
-A **development bank** produces public good dashboards to deliver **risk insights** to client governments. The dashboard uses risk data from multiple projects to estimate the **number of assets or population** exposed to risk to assist in prioritising investments. Pulling data via the **RDL API**, many different datasets can be ingested and applied through a single workflow.
-
-***Value***: Efficient data pipelines to ingest multiple datasets with confidence in the consistency of data structure and metadata.
-
-
-
-An **academic research team** needs to demonstrate the impact of a **risk analytics and urban planning project**, by making the data available for others to use. Their dataset are formatted according to the **RDL standards** and published in a data catalogue set up for the project, using the **template implementation** available through the RDL project.
-
-***Value***: The pre-designed open-source deployable solutions can assist a research group achieve impact efficiently.
-
-
diff --git a/internal_guide_rdl_on_WBdataCatalog.md b/internal_guide_rdl_on_WBdataCatalog.md
new file mode 100644
index 00000000..eee2030e
--- /dev/null
+++ b/internal_guide_rdl_on_WBdataCatalog.md
@@ -0,0 +1,90 @@
+# RDL collection
+
+The [Risk Data Library Collection](https://datacatalog.worldbank.org/search/collections/rdl) sits within the [World Bank Data Catalog](https://datacatalog.worldbank.org) and is meant to store standard risk data.
+The collection can be accessed from the [collections page](https://datacatalog.worldbank.org/search/collections/) or used as a filter on the left bar to search for data within the collection.
+
+
+
+## Add datasets
+
+Datasets can be submitted for review and publication on the Data Catalog by any World Bank Staff, ETC or STC. These people have the role of `Data depositor`.
+
+
+Datasets needs to be packaged according to the [data preparation guidelines](preparation).
+
+
+
+Two options to upload data:
+
+- **Individually**: using the upload wizard
+- **Bulk**: for large number of datasets, requires support by the [DDH team](../about/contacts.md#ddh-team)
+
+In both cases, datasets can be added to the [RDL Collection](https://datacatalog.worldbank.org/search/collections/rdl) only by the [RDL team](../about/contacts.md#rdl-team), after approval.
+
+### Individual datasets
+
+- Log in to the [Data Catalog](https://datacatalog.worldbank.org/int/home) (top right bar)
+
+- View [My datasets](https://datacatalog.worldbank.org/int/data/mydata) (top right bar)
+ 
+ The page shows dataset number, name, modified date, status (Published, Draft, Under review, Publishing in progress) for datasets you have uploaded or for which you are listed as a contributor
+
+ - Under `Action` you can `edit` or `submit for review` to the [DDH team](../about/contacts.md#ddh-team).
+ - When status is `Published`, the dataset will be visible on the World Bank Data Catalog.
+
+- Click [Add data](https://datacatalog.worldbank.org/int/data/add) (top right bar)
+ Select the option on the right: _`continue`_.
+ 
+
+ 1. **Essential Information**
+ 
+
+
+ 1. **Uploading data**
+
+ - Upload dataset from your local storage
+ - Add a resource title and description
+ - When one resource has been submitted, another one can be added
+ 
+
+
+ 1. **Additional information**
+ 
+
+ - **Tags**: These are important for being able to search the data in the catalog. Suggestions for RDLS data:
+ - Climate Risk or Disaster Risk
+ - Hazard, Exposure, Vulnerability, Loss (depending on the component type)
+ - Flood, Earthquake, Landslide, Tsunami (hazard type)
+ - **Topics**: There is currently no topic for risk analytics or climate and disaster risk - leave blank
+ - **Collection**: this can only be entered by staff with those rights. Provide a list of dataset ID to [Kamwoo Lee](../about/contacts.md#ddh-team) with request to assign data to RDL Collection.
+ 
+
+Once done, click on `Save as draft`. The dataset will appear under `My datasets` list.
+
+### Bulk upload
+
+In cases where large volumes of project data need to be uploaded, DDH team can assist with bulk upload.
+The workflow steps are:
+
+1. Login with WB credentials and store project data on the [DataCatalog Sharepoint](https://worldbankgroup.sharepoint.com.mcas.ms/sites/ddh2/Shared%20Documents/Forms/AllItems.aspx?csf=1&web=1&e=pmjIeC&CT=1683747817820&OR=OWA%2DNT&CID=1c049bb0%2Db912%2D850b%2D383e%2D4dcda23ac626&RootFolder=%2Fsites%2Fddh2%2FShared%20Documents%2FRisk%20Data%20Library&FolderCTID=0x012000374C108104547647A016D80E1BFD3084) - using appropriate folders structuring (Project/Component/...)
+1. Create an excel spreadsheet describing the datatype with each dataset name, URL to data and URL to prepared JSON metadata.
+1. Describe the data structure to be achieved on DDH.
+1. DDH team will copy the data and metadata to DDH Sharepoint.
+1. DDH team will use scripts to upload datasets; these will appear in your `My Datasets` for review and any further editing.
+
+### Add RDL custom metadata
+
+- Create metadata following to Risk Data Library schema in JSON format, including the description and name of resources under that dataset. Either:
+ 1. Write directly into JSON file
+ 1. Use JSON metadata creation tool. This tool is standalone (not part of DDH). It exports a JSON file to be saved with the dataset.
+- Upload metadata with the dataset. Once the import process is concluded, metadata will become available to download from the dataset page and as part of custom metadata shown.
+
+```{figure} https://user-images.githubusercontent.com/44863827/237736456-7d6cafe9-d83c-483e-b03b-02c69d89c705.png
+---
+align: center
+width: 98%
+---
+Example (work in progress) of the RDL metadata visualization within the World Bank Data Catalog (RDL collection).
+```
+
+
diff --git a/requirements.in b/requirements.in
index 49f94699..4ecd45d4 100644
--- a/requirements.in
+++ b/requirements.in
@@ -9,4 +9,4 @@ sphinx-intl
#transifex-client
sphinx_rtd_theme
myst-parser
-mdformat
+mdformat-myst
diff --git a/requirements.txt b/requirements.txt
index 85cecbc5..8cbc8e8d 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -50,9 +50,21 @@ markdown-it-py==2.1.0
markupsafe==2.1.1
# via jinja2
mdformat==0.7.16
+ # via
+ # mdformat-frontmatter
+ # mdformat-myst
+ # mdformat-tables
+mdformat-frontmatter==2.0.1
+ # via mdformat-myst
+mdformat-myst==0.1.5
# via -r requirements.in
+mdformat-tables==0.4.1
+ # via mdformat-myst
mdit-py-plugins==0.3.3
- # via myst-parser
+ # via
+ # mdformat-frontmatter
+ # mdformat-myst
+ # myst-parser
mdurl==0.1.2
# via markdown-it-py
myst-parser==0.18.1
@@ -70,6 +82,12 @@ pyyaml==6.0
# via myst-parser
requests==2.28.1
# via sphinx
+ruamel-yaml==0.17.32
+ # via
+ # mdformat-frontmatter
+ # mdformat-myst
+ruamel-yaml-clib==0.2.7
+ # via ruamel-yaml
six==1.16.0
# via livereload
snowballstemmer==2.2.0