Data Collaboratives
Examples
The following are the most common form of this type of collaboration:
Research Partnerships
in which corporations share data with academic institutions to advance scientific research.
Data Cooperatives
in which corporations, government and citizens create joint databases with shared contributions.
Conditions for success
The success of a data collaborative is ultimately measured by the positive impact and value it generates for the intended population. Participants and sponsors should define metrics, indicators, or targets to assess the impact of their collective efforts and continuously evaluate and improve their activities to maximize societal benefits.
References
The following references were used as inspiration for this piece:
- https://datacollaboratives.org
- The Value of Data and Data Collaboratives for Good: A Roadmap for Philanthropies to Facilitate Systems Change Through Data. Verhulst, Stefaan.
Data Science for Social Good: Philanthropy and Social Impact in a Complex World - Lapucci, Massimo, Cattuto Ciro
References
TrustRelay is proud to support meaningful data spaces in Switzerland, together with:
Why TrustRelay?
Spaces
Use spaces to invite a group of companies and people that will use shared data for a common purpose.
Organization Accounts
Accounts allow users to login and relate to each other based on their work's email domain.
Real-time SQL Query
Use our distributed query engine to retrieve data from decentralized data sources (no need to centralize all data in a single place).
Data Sharing Agreements
If you're a data provider you can use our templates to create a simple yet effective Data Sharing Agreements.
Electronic Signatures
Most Data Sharing Agreements should be legally-binding, this is why we offer you the possibility to use electronic signatures.
Confidential Computing
Data is a precious asset, we use confidential computing to safeguard it and make sure only the authorized people can access it.