#33 Introducing Open Data Product Specification - purpose and values for the Data Economy
International standards are a vital tool in ensuring products and services are interchangeable and compatible across borders, removing barriers to trade, reducing production and supply chain costs and building confidence in business services and protecting consumers.
The Emerging Data Economy lacks standards. Thus we have launched the development of The Open Data Product Specification. In the "Open Data Product" focus is on the latter words and the prefix 'open' refers to the openness of the standard. Any kind of connotations to open data are not intentional, intended, or desirable.
The Data Product Specification aims for the same impact in the Data Economy as what OpenAPI specification did for the API Economy
Read more below or watch the story as a video
Problems of the data economy
The data products and data as a service solutions are spread around increasing amount of market places, tool stack for the data product design, development and management is a wild west, consumers have a hard time knowing what they are purchasing or how to compare data products to find a best possible fit in their situation.
In short, the data economy lacks a data product standard. By working together and openly, we can increase interoperability, growth, and data reuse with help of shared specifications.
Open Data Product Specification
The Open Data Product Specification is a vendor-neutral, open-source machine-readable data product metadata model. It defines the objects and attributes as well as the structure of digital data products. The work is based on existing standards (schema.org), best practices and emerging concepts like Data Mesh. The reasoning is that we reuse and proudly copy instead of reinventing the wheel.
The Open data Product Specification contains four build-in aspects.
The first is business - the model contains standard objects to define any modern business model for the data product including subscription, dynamic pricing, and pay per use to mention a few. Common product attributes have been included as well. Quality attributes and SLA help you to describe the level of service.
The second is Technical - The standard describes the needed technical aspects of the data product including data pipeline and access to it, data models used and deployment. The standard enables fluent DataOps and pipeline development for the purposes of business.
The third is legal - Data licensing has been standardized and made easy and fast to implement. With predefined options, anyone can easily define terms and conditions for sharing the data.
The fourth and final is Ethical - The model fulfills the current requirement of taking privacy and personal data aspects into account. With clarity in what to include in the license, all parties involved know what they get and what they are allowed to do with the data.
What about the value for the data economy?
The standard has at least 5 benefits for the Data Economy:
Enable interoperability between organizations, data platforms, marketplaces, and tools.
Reduce data product metadata conversions and errors between systems and organizations
Increase the speed of designing, testing, and implementing data products.
Speed up tools development around data product design, development and management.
Enable creation of automated data product deployment with standard methods (DataOps)
Share the link with your staff
The specification is published with an open license which enforces the adoption and future development. Take a look at it and share the link with your data model experts and data product managers.