Political and legal aspects
As noted above, political will is important to implementation, and any initiative should seek to have a mandate, which could be political or legal, formal or informal. Examples of open data policies can be accessed via the OGP or the World Bank’s toolkit.
The mandate should enable the team overseeing the initiative to motivate and support other parts of the entity to publish the relevant data or share it for publication. Attard et al. (2015) found that entities can be discouraged from joining an open government data initiative by a lack of awareness, motivation, capacity, budget provision or technical support.
The broader policy context can hinder a mandate’s implementation. Areas that may need examining include potentially conflicting regulations, such as on privacy and data protection, existing copyright and licensing frameworks, liability of data providers and – in some cases – regulation around competition (Attard et al., 2015).
It is important to attach an open licence to published data. This signals to the user that they have permission to download and use it. This is particularly relevant where the user wishes to analyse or process the data for something that is public facing, or on which they wish to build a business (see Open Data Institute guidance).
Finally, the overall budget required for an initiative is difficult to assess and varies greatly. The Open Data Institute has developed a guide to planning and costing an open data initiative.
Technical aspects
Initiatives will usually have a portal – an online repository into which either a central team or individual data owners upload data. This is not strictly necessary, however, and as long as data is discoverable it can be uploaded via existing services, such as a publisher’s main website.
Data should be published to existing standards, as set out in principle 4 of the Open Data Charter, for example. Standards are agreed ways of structuring data that enable users to combine and compare data from different sources.
Guidelines are available to help with prioritising datasets, such as the ODI’s How to prioritise open data to drive global development. However, choosing the data that should be made open is best done by engaging users and allowing them to request datasets they think they can use. Many portals accept requests, or provide ways to give feedback on existing data. For example, the Colombian government’s open data portal allows users to give datasets ‘thumbs up’ or ‘down’.
When it comes to the publication of data, anonymisation is crucial. The UK Anonymisation Network provides many resources to assist in this. See also the Guide to Data Protection by the UK Information Commissioner’s Office.
Attard et al. (2015) summarise the literature on criteria for calculating data quality as:
- usability – includes aspects like interoperability and discoverability
- accuracy – the extent to which metadata correctly describes the respective information
- completeness – the number of completed fields in a data/metadata record
- consistency – whether field records follow a consistent syntactical format, for example of dates
- timeliness – the extent to which the data or metadata is kept up to date
- accessibility – how easy it is to discover and understand published information
- openness – such as via Tim Berners-Lee’s Five Star Scheme for Linked Open Data
For more details, see the W3C eGov Interest Group steps for publishing open government data.
Assessing readiness and progress
A number of tools exist for assessing open data readiness and implementation:
- Open Data Certificate – an online tool for checking datasets meet criteria for open data
- Open Data Readiness Assessment – a detailed study developed by the World Bank that is delivered in country
- Open Data Barometer and Open Data Census, which provide comparable rankings
- The Open Data Institute’s Pathway tool, which allows institutions to self-assess their progress towards implementation
- Attard, J., Orlandi, F., Scerri, S., & Auer, S. (2015). A systematic review of open government data initiatives. Government Information Quarterly, 32(4), 399-418.
