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#1 Data Economy standard

Open Data Product Specification

Technical specification of a machine-readable data product metadata model. It defines the objects and attributes as well as the structure of digital data products.

Build-in aspects:

  • Technical (infrastructure & access)

  • Business (pricing & plans)

  • Legal (licensing & IPR)

  • Ethical (privacy & mydata)

The Open Data Product Specification aims for the same impact in the Data Economy as what OpenAPI specification did for the API 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 specification.

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.


Critical part of the
value chain


The specification enables frictionless value chain development operations between data product design tools, data marketplaces, data platforms, and data pipelines.


The standard enables multichannel multi headed hydra solution output.


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)

What data management professionals say

New York Office

Jouni Miikki,
Principal Software Engineer

Great way to keep everything together and inform about the data product and licensing model involved with it.


Antti Loukiala,
Technical Lead Data Platforms

Standardization of commonly needed parts. There is a clear need for this kind of standardization.


Piyush Palka,
Chief Data Officer

This is fantastic!  A lot of organizations can have clarity on how data should be monetized and if they want to what could be the design specification and pricing models.


4 Build-in aspects


The model contains standard objects to define any modern business model for the data product including subscription, dynamic pricing, and pay per use.


Common product attributes have been included as well. Quality attributes and SLA help you to describe level of service.


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.


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 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.

Shared Desk

Use, contribute and enjoy!

Take the standard into use, spread the word, build tools around it, contribute, tweet about it - become part of the community!


9 Design principles

Make it hard to misuse

Must be Practical

Make it long-lasting

If practice deviates from the spec, change the spec

Do the hard work to make it simple

Consistent in content and style

Developer experience is the key

Reuse existing solutions

MAke, learn, validate, iterate


How it all got started?

Jarkko Moilanen was invited to join the ranks of data platform development company in Dec 2018. In May 2019 Jarkko had worked with multiple data operating companies and discovered the need to build new tools - business tools for data owners. This resulted in the creation of Data Product Toolkit.

The toolkit however was somewhat crippled without underlying machine-readable data product standard; something that binds together business, technology, legal and ethical aspects of the data product. The idea of Open Data Product Specification was born around Sept 2019. However, the idea was buried under other development tasks and the dream almost died.

Sept 2021 Jarkko resurrected the standardization idea and quickly drafted the first version of the specification in cooperation with Jussi Niilahti.


The Open Data Prioduct Specification version 1.0 was published in 5th Feb 2022.

What happens next is up to you!

Build tools, Design Data Products, monetize data, automate data product pipelines.

It all starts from getting familiar with the data product Specification

Open Data Product Initiative

Open Data Product Initiative (“ODPI”) provides an open source community, within which industry participants may easily contribute to building vendor-neutral, portable and open specifications for providing technical metadata for Data Products and Services – such as the “Open Data Product Specification” – and supporting tooling for validating the integrity of the specifications or instantiations of it. 

The ODPI is as such not intended to be a destination for community/consumer-focused tooling outside of the specification itself.

At the moment development and maintenance will be  managed in an open source, Technical Steering Committee (“TSC”), open to any participant. In addition companies can purchase membership which gives them a seat at the Strategy Group.

Read more about groups and governance

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17th International Conference on Design Science Research in Information Systems and Technology

June 1-3 June 2022 St. Petersburg, FL, USA

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