What makes an open standard successful?
Our research on user experiences of open standards for data found that a successful open standard:
focuses on solving a specific problem or meeting a clear need
works well with other standards
is clear on how decisions have been made and why
has been implemented and tested
is robust but not verbose
is developed using an open, adaptable process
is delivered early
has included people with a variety of skills and backgrounds
Creating a new open standard can be time consuming and resource intensive, so it is important to take a considered approach.
This may mean using or extending an existing open standard rather than developing a new one.
If developing an open standard is the best approach, consider adopting the Open Stand principles for developing in the open, transparently and cooperatively.
You can also make open standards development more open and inclusive by following inclusive design principles. This may help to make your standard and its benefits more apparent, and the value it creates more observable and measurable.
A successful open standard for data builds the ecosystem around the standard. A variety of people and organisations will adopt, use or be impacted by the standard itself as well as any data sets, products and services developed around it.
Stakeholders can include:
data publishers who produce and share data based on standards for data exchange – for example, the International Federation of Red Cross and Red Crescent Societies (IFRC) is using the Humanitarian Exchange Language (HXL) to increase access to safe water and sanitation to 30 million people by 2025
data modellers who model environments and systems to understand information flows using standards for guidance – for example, the research body, Cooperative Research Centre for Low Carbon Living (CRCLCL) recently developed the Precinct Information Model (PIM) to support 3D modelling and data sharing for urban development
data users who agree on meaning and share information consistently using standards to share vocabulary – for example, the Office of National Statistics’ ethnicity classifications are widely used for capturing, reusing and comparing information about ethnicity
developers who produce tools that support data publishers, from data validation to gap analysis, and from data conversion between formats to platforms for data and model publication – for example, the Humanitarian Data Exchange (HDX) is a platform for finding, sharing, and using humanitarian data
developers who produce tools that support the use of data or models produced using the standard, from apps to research, and from visualisations to physical and digital products – for example, OpenCorporates makes it easy to find information on companies in jurisdictions around the world
policy groups who develop and implement policy that is affected by or supported by open standards for data, including businesses, non-profit organisations and public bodies
How are open standards developed?
Open standards are developed by a variety of organisations, from nationally or internationally recognised formal standards bodies to commercial market leaders, governments, trade associations and other community bodies.
When you develop an open standard, the processes can vary depending on the sector, the aims of the standard, and the needs of the people and organisations involved.
Highly regulated sectors like healthcare or telecoms tend to follow formal processes. They create mandatory standards backed by policy, legislation or influential industry bodies and market leaders.
Formal processes typically feature:
detailed process documents
formal governance practices
one or more working groups
more use of formal language
preference for tried and tested technology
more milestones where committee approval is needed
At the other end of the spectrum, open standards development by other organisations tends to follow fewer formal processes and focus on being responsive to commercial or community needs.
These standards can become de facto due to the standard owner’s influence, engagement with government and industry bodies, or robust adoption by the industry or sector.
Less formal processes typically feature:
a preference for cutting-edge technology that favours the digitally literate
visible engagement with the community
fewer process documents
lightweight governance practices
more use of language that favours the digitally literate
fewer milestones where committee approval is needed
open online change management using repositories like Github
Most open standards development processes fall somewhere between highly formal and informal.
Despite differences in formality, all standards processes follow similar stages. Most standards development processes involve a trigger to scope and start the standards development, then a development stage followed by a launch and adoption.
While this seems linear, there may be cycles of activity with stages repeated or being worked on at the same time – for example, ongoing development and launch or repeated reviews.
Open standards for data development may follow different paths, but with the same goal: to produce a robust, successful and reusable shared agreement that helps to produce better quality data.
Source: The Open Data Institute