For full interoperability, different datasets need to share the same values for the same things (e.g. the code for a prefecture of Guinea, or for a humanitarian cluster). This page lists some sources for taxonomies, code lists, and special formats useful for humanitarian data, but there are, obviously, many more.
- ISO 3166-1 Country codes (
- This standard includes three types of code for each country, a three-letter alphabetic code (e.g.
SYRfor Syria), a two-letter alphabetic code (e.g.
SY), and a numeric code (e.g.
760). Humanitarian data uses mainly the three-letter versions, while the two-letter versions are familiar from Internet top-level domains (except that “GB” for Great Britain changes to “UK” for the Internet domains).
- United Nations p-codes (
- The UN Secretariat’s Humanitarian Office maintains lists of subnational codes for countries that have international humanitarian responses. These codes are much-more granular than the ISO 3166-2 codes, and the majority of humanitarian datasets use them. The code list is not (yet) available in a single place, but is embedded in various geographical datasets.
- IASC international clusters (
- IASC clusters are both thematic identifiers and organisational structures for coordinating a humanitarian response. Many humanitarian organisations work within the cluster system, and it is common to classify humanitarian needs and responses by cluster.
- OECD DAC sector classifications (
- A multi-level taxonomy of purpose codes by sector and subsector(s), maintained by the OECD’s Development Assistance Committee (DAC), e.g. “
110” for Education (in general), “
112” for Education/Basic Education, and “
11240” for Education/Basic Education/Early childhood education.
- IASC indicators registry (
- 426 humanitarian indicators defined by the Inter-Agency Standing Committee for each IASC Cluster (e.g. “AAP-3” for “Number of persons consulted (disaggregated by sex/age) before designing a program/project [alternatively: while implementing the program/project]”). Many of the indicators have PDF documentation with detailed guidance.
- Proposed SDG indicators (
- Non-final list of indicators and codes for the inter-governmental Sustainable Development Goals, e.g. “
1.5.2” for the Proportion of health and educational facilities affected by hazardous events.
- GLIDEnumber (
- A unique number assigned to a humanitarian crisis, e.g. “
OT-2011-000025-SYR” for the complex crisis in Syria. Originally, GLIDE focussed mainly on non-conflict crises such as natural disasters or epidemics, but members have increasingly been creating GLIDE numbers for conflict situations as well. GLIDE numbers are widely used in the humanitarian community.
- OCHA FTS organisation codes (
- An XML-format file listing codes for over 7,000 aid-related organisations, e.g. “
14406” for the Dura Islamic Society for the Orphans.
- OECD DAC Donor and agency codes (
- Identifiers for national donors and major aid agencies, from the OECD’s Development Assistance Committee (DAC), e.g. “
966” for the World Food Programme
- Global Database of Humanitarian Organisations (
- A database of organisations that have responded to at least one humanitarian emergency, downloadable in Excel format. The GDHO has unique integer identifiers for each organisation.
- IASC Humanitarian Profile (
- A classification system for casualties and displaced populations, from the Inter-Agency Standing Committee. Also known as the Humanitarian Caseload. The classification words provide a good basis for HXL attribute names, e.g.
Project and activity codes
- IATI activity status (
- A series of numeric codes for the lifecycle of a project or activity: 1 for Pipeline/identification, 2 for Implementation, 3 for Completion, etc.
- IATI aid types
- A classification system for how an organisation is spending a quantity of aid money, e.g. B03 for Contributions to specific-purpose programmes and funds managed by international organisations (multilateral, INGO).
- ISO 8601 Representation of dates and times (
- There is a huge risk of confusion over dates in humanitarian datasets: for example, does “
1/9/15” represent 1 September 2015 or 9 January 2015? The only safe and reliable method for encoding dates is the ISO 8601 standard, and specifically, the W3 subset of ISO 8601. Examples: “
2015” (the year 2015), “
2015-09” (September 2015), “
2015-09-01” (1 September 2015). There are also advanced encodings for weeks (e.g. “
2015-W03” for the third week of 2015), durations (e.g. “
P1Y3M” represents a 1 year, 3 month duration), etc. To avoid confusion, please always use ISO 8601 dates in humanitarian data sets.