Connecting policy and practice through data standards
The word ‘standard’ means different things to different people. To policy audiences, a standard is often about describing what information should be collected, shared or disclosed. To a technical audience, a standard may be about specifying how data should be structured, represented and exchanged. To expert audiences, a standard might be about definitions and measurement criteria.
With the team @opendataservices I spend a lot of time working on Policy Related Open Data Standards (which for now I’ll call PRODS for want of a better acronym). These are technical specifications with a standard-setting policy agenda.
The success of these standards rests not only on interoperability and error free data exchange, but also on the creation of new collections of data that play an active role in supporting social change, and upon change in organisational practices that have an impact on governance, as well on data availability.
Standards and specifications: policy and interoperability
Effective data standards make policy change measurable, and ensure that transparency initiatives result in information that is usable, useful and in-use.
The diagram below explores the the relationship.
PRODS start from a policy goal, such as increased transparency and participation in public contracting. This sets a high level ‘policy standard’ that implementers should strive to achieve. However, exactly what meeting that standard looks like might not be specified in detail: that’s where the technical standard (and specification) comes in. The specification makes data interoperable, and means we can create replicable validation rules: tests that act as proxy measures of whether or not the policy standard has been met.
Interoperability for all: improving incentives for adoption
Validation of data, as a proxy measure for implementation of a policy standard is just one use-case for interoperable data. If a standard is designed right, there can be many other possible use-cases.
When a standard is designed to meet these use cases too, then:
- There are more champions for adoption of the standard;
- The process of publishing data using the specification can have greater impact;
- Adoption of the standard can better survive changing political contexts;
This is why it is vital to think about both policy and practice uses of data when developing a standard, and to design with the interaction of standard, specification, policy and guidance in mind.
By putting all these pieces together, there is the chance of a virtuous cycle that aligns a range of different communities, creating a greater chance of meaningful social impact.
More on Open Standards for Data
This blog post was drafted as part of the ODI supported Open Standards for Data project. You can read more about Open Data Services Co-operative work supporting standards development on our blog.
