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Best Practice: Open Data Business Models & Value Disciplines

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This is one of a set of Best Practices for implementing the (Revised) PSI Directive developed by the .

Creative Commons Licence Share-PSI Best Practice: Develop Open Data Business Model by Share-PSI 2.0 is licensed under a Creative Commons Attribution 4.0 International License.


Open data holds considerable economic and social value beyond the walls of the governments and institutions that share their data. In response to the economic opportunities presented by the increasing availability of open data, a business model needs to be developed by any open data-driven organisation (at all levels). This will describe how value is created and captured through the decisions made and the resulting consequences.


There are still many open data-driven organisations, especially at midstream and downstream levels, that are struggling to comprehend how to generate revenue and survive by adapting to the changes brought on by the ubiquitous growth of open data and 'Big Data.' In addition, open data-driven organisations have difficulty distinguishing different business models and understanding which one suits their organisational goal.


To exploit the value of open data, to maximise the benefits, and to enable the creation of innovative products and services, data-driven organisations should develop and implement a business model before starting their business. This is required to ensure that the products and services generate necessary value proposition and meet the needs of the customers/users and eventually generate substantial revenue. The 6-Values Open Data Business Model Framework ensures that managers are taking into an account all aspects of an effective and efficient business model and understand the effect of the different aspects on each other.

Why is this a Best Practice?

On the one hand, many open data-driven organisations, specifically at upstream level, have successfully designed, developed and implemented their business model but they need to understand the demand side (from mid and downstream organisations) in order to serve them better. On the other hand, midstream and downstream organisations are facing difficulties in developing a business model that allows them to better understand that demand. This best practice helps all types of organisations to overcome the challenges of developing a business model that is effective in identifying what is going on in the open data industry and what more needs to be done to support and feed both demand and supply side. Moreover, developing and implementing an effective and efficient business model can lead to customers/users' satisfaction, emerging innovative products and services, revenue generation and survivability of the organisation and eventually can lead to maximising the economic value of open data.

How do I implement this Best Practice?

In order to be able to start designing and developing this best practice, an organisation needs the following:

  • Team up and have required expertise (preferably people with both open data and business development knowledge).
  • Patience and courage in searching and sensing the market, existing open data products and services, potential collaborators, and existing competitors.
  • Define market niche.
  • Open data value discipline/s must be identified before developing the business model.

Open data value disciplines help organisations to focus on delivering superior customer value. Products or services must meet one or multiple value disciplines. There are four Open Data Value Disciplines:

  1. Usefulness - tailors value proposition to directly support the needs of consumers in one way or another.
  2. Process Improvement - tailors value proposition to match to the needs of the customer specifically for improving processes.
  3. Performance - tailors value proposition for a better performance.
  4. Customer Loyalty - tailors value proposition to target customer loyalty.

Further reading

Emerging Business Models for the Open Data Industry: Characterization and Analysis (PDF); Fatemeh Ahmadi Zeleti, Adegboyega Ojo, Edward Curry; 2014, INSIGHT Centre for Data Analytics

Where has this best practice been implemented?

Country Implementation Contact Point
Ireland The Marine Institute
USA Open Data Impact Map


Local Guidance

This Best Practice is cited by, or is consistent with, the advice given within the following guides:

Contact Info

Fatemeh Ahmadi-Zeleti, Insight Centre for Data Analytics, NUI Galway, Ireland

Issue Tracker

Any matters arising from this BP, including implementation experience, lessons learnt, places where it has been implemented or guides that cite this BP can be recorded and discussed on the project's GitHub repository

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