“A Licensing Model and Ecosystem for Data Sharing” is a spokes project led by researchers at Massachusetts Institute of Technology (MIT), Brown University, and Drexel University, as part of the Northeast Big Data Innovation Hub.
We are addressing data sharing challenges that are too frequently held up due legal matters, policies, privacy concerns, and other challenges that interfere with finalizing an agreement.
Sharing of data sets can provide tremendous mutual benefits for industry, researchers, and nonprofit organizations. A major obstacle is that data often comes with prohibitive restrictions on how it can be used. Beyond open data protocols, many attempts to share relevant data sets between different stakeholders in industry and academia fail or require a large investment to make data sharing possible.
We are addressing these challenges by: 1) Creating a licensing model for data that facilitates sharing data that is not necessarily open or free between different organizations, 2) Developing a prototype data sharing software platform, ShareDB that will enforce agreement terms and restrictions for the licenses developed, and (3) Developing and integrating relevant metadata that will accompany the datasets shared under the different licenses, making them easily searchable and interpretable.
“A Licensing Model and Ecosystem for Data Sharing” is also linked with the Northeast Data Sharing Group, comprising of many different stakeholders to make the licensing model widely accepted and usable in many application domains (e.g., health and finance).
Research supported by National Science Foundation/IIS/BD Spokes/Award #1636788
Data Sharing Agreements
We are collecting examples of data sharing agreements, licenses, partnerships, and contracts as part of this effort. Please send examples to Metadata Research Center Research Assistant, Sam Grabus. All identifying information will remain confidential.
Publications and activities
- Grabus, S., Greenberg, J. (2017, in press). Toward a metadata framework for sharing sensitive and closed data: An analysis of data sharing agreement attributes. In MTSR-2017: Proceedings of the 11th Metadata and Semantics Research Conference. Tallinn, Estonia, November 28-December 1st, 2017. [Paper]
- Greenberg, J. (2017). BIG DATA: Balancing Impacts, Investments and Education 2017 ESS/SAES/ARD Fall Meeting: A Question of Balance Workshop, Philadelphia, PA, September 26, 2017 [SLIDES]
- “Enabling Seamless Data Sharing in Industry and Academia” workshop, Drexel University, Sept. 29-30, 2017 (Workshop Report)
- Binnig, C. Data sharing project. 2017 Annual Workshop of the Northeast Big Data Innovation Hub, February, 24, 2017 (Powerpoint Slides)
- Grabus, S. (2017, March 15-17). ShareDB: A Licensing Model and Ecosystem for Data Sharing. Poster presented at the 2017 Joint PI Meeting of NSF BIGDATA and NSF Big Data Hubs & Spokes, Washington, D.C. (Poster)
- Sam Madden, Lead PI, Massachusetts Institute of Technology
- Carsten Binnig, PI, Brown University
- Sam Grabus, Doctoral student, Graduate Research Assistant, Drexel University
- Jane Greenberg, PI, Drexel University
- Famien Koko, Graduate Student, MIT
- Hongwei Liu, Post-Graduate Researcher, Drexel University
- Tim Kraska, PI, Brown University
- Danny Weitzner, PI, MIT