This paper was written by Tim Davies of Open Data Services Co-operative with financial support from the Joined-up Data Standards (JUDS) project. JUDS is a joint effort of Development Initiatives (DI) and Publish What You Fund, with funding support from Omidyar Network. The JUDS team is grateful to Tim Davies for his work on this paper.READ ONLINE DOWNLOAD
Many of the datasets and standards created to further transparency created over recent years include information about transactions involving government entities. Persistent, non-overlapping and widely used identifiers are important to enable machines to combine data from multiple sources, and then to answer questions such as the following.
- How much money has been spent by the UK Department for Health with small or medium enterprises?
- How much money has the official Ugandan education system received from government donors in the last five years?
In these cases, the use of an identifier would allow human or machine data users to clearly identify: (a) the companies or charities in receipt of money; and (b) the government entities providing and receiving money. It is increasingly straightforward (though not entirely without challenge) to identify commercial organisations or charities unambiguously through the use of official identification and registration numbers. However, government entities often lack such stable public identifiers. As a result, there can be many missed connections in current datasets.
Previous efforts to identify a ‘Government Entity Identifier’ (GEI) for use in the International Aid Transparency Initiative (IATI) were not able to suggest a clear approach. This paper revisits the problem. Following a detailed exploration of the different requirements that any solution must address, we provide an updated assessment of potential methods to be adopted to better join up data about government agencies.
This paper explores options for a universal method of identifying government entities in datasets describing transactions from or to government agencies. It was developed based on dialogue with the org-id.guide partners and the IATI community between September 2016 and June 2017.