A Licensing Model and Ecosystem for Data Sharing

Research Assistant Sam Grabus and visiting scholar Tony Hernández, discussing the data sharing workflow.
Research Assistant Sam Grabus and visiting scholar Tony Hernández, discussing the data sharing workflow.

Project Summary

“A Licensing Model and Ecosystem for Data Sharing” is an NSF Spoke project, led researchers at Massachusetts Institute of Technology (MIT), Drexel University’s Metadata Research Center, and Brown University.

Significant progress has been made with ‘data sharing’ in the open data and open science communities; although sharing ‘sensitive data’ has not progressed at the same speed. Major obstacles include legal and organizational policies, privacy concerns, infrastructure limitations, and prohibitive restrictions on how sensitive data be used and reused.  These obstacles limit society from the full benefits that data sharing can commend.

We are addressing these data sharing challenges through “A Licensing Model and Ecosystem for Data Sharing.” Project goals include: 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, to 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.


Research supported by National Science Foundation/IIS/BD Spokes/Award #1636788 (NSF 2016 award for Big Data Spokes)

Data Sharing Agreements

We are collecting examples of data sharing agreements, licenses, partnerships, and contracts for our initiative. Please reach out to Metadata Research Center Director, Jane Greenberg, if you have any inquiries or examples to share (jg3243 @ drexel dot edu).

Publications and activities

Madden, S. (2017). Towards a Licensing Model and Ecosystem for Data Sharing. Privacy Tools for Data Sharing: Lessons Learned and Directions Forward. Harvard University, December 11, 2017. Abstract and Bio-note (Slides).

Grabus, S., & Greenberg, J. (2017). Toward a Metadata Framework for Sharing Sensitive and Closed Data: An Analysis of Data Sharing Agreement Attributes. In E. Garoufallou, S. Virkus, R. Siatri, & D. Koutsomiha (Eds.), Metadata and Semantic Research: 11th International Conference, MTSR 2017, Tallinn, Estonia, November 28 — December 1, 2017, Proceedings (pp. 300–311). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-319-70863-8_29 [Paper]

Greenberg, J. (2017). Keynote – Sharing Restricted Data: Challenges, Protocols and Implications for Digital Libraries. Joint 8th A-LIEP Conference/19th ICADL Conference, November 14th, Chulalongkorn University, Bangkok, Thailand.

Greenberg, J. (2017). A Licensing Model and Ecosystem for Data Sharing Board on Research Data and Information/US CODATA International Coordination for Science Data Infrastructure. National Academies, Washington, D.C., November 1, 2017. (Slides)

Greenberg, J., et al, (2017). Metadata Solutions for Sharing Restricted Data. BIG DATA: Balancing Impacts, Investments and Education 2017 ESS/SAES/ARD Fall Meeting: A Question of Balance Workshop, Philadelphia, PA, September 26, 2017 (Slides)

Greenberg, J., Grabus, S., Hudson, F., Kraska, T., Madden, S., Bastón, R., and Naum, K. (2017).  “Enabling Seamless Data Sharing in Industry and Academia” Workshop, Drexel University, September, 29-30, 2017: Workshop Report; DOI: https://doi.org/10.17918/D8159V.

Workshop: Enabling Seamless Data Sharing in Industry and Academia Workshop and agenda.

Binnig, C. Data sharing project. 2017 Annual Workshop of the Northeast Big Data Innovation Hub, February, 24, 2017 (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)

Research Team

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