MetaShare is a knowledge-based system that supports the creation of data management plans and provides the functionality to support researchers as they implement those plans. MetaShare is a community-based, user-driven system that is designed around the parallels of the scientific data life cycle and the development cycle of knowledge-based systems.

The purpose is to are provided recommendations and guidance to researchers based on the practices and decisions of similar projects. Using formal knowledge representation in the form of ontologies and rules, the system can generate data collection, dissemination, and management tools to facilitate tasks with respect to using and sharing scientific data.


Scientific data management activities are automated.

Data stewardship requirements, such as dissemination, archiving, and definition of security policies are automated through rule-based systems. Such rules are generated from decisions made by researchers during data management planning and implementation of data stewardship requirements in designated storage facilities.



Scientific data are discoverable and sharable.

Based on decisions made by researchers during data management planning, tools are generated to facilitate data collection and ingestion into knowledge-based systems to support querying and inferencing services.


Data management recommendations are provided.

By continuously collecting decision information about data management planning from the scientific community, the dynamic knowledge-based system can provide recom- mendations based on the decisions that colleagues with similar needs have made on past projects.

Meet the Team


Dr. Ann Q. Gates


Professor & Chair of Computer Science

Associate Vice President of Research

Cyber-ShARE Center Director


Dr. Deana Pennington


Assistant Center Director

Research Assistant Professor


Dr. Monika Akbar


Research Assistant Professor


Frank Osuna


Research Specialist