Welcome to Cyber-ShARE
Created in 2007, the Cyber-ShARE Center of Excellence brings together experts in computer science, computational mathematics, education, earth science, and environmental science. The team addresses the challenge of providing information to scientists and other users of cyberinfrastructure (CI)* that allows them to make informed decisions about the resources that they retrieve and to have confidence in using results from CI-based applications. The Cyber-ShARE team conducts innovative research to facilitate the development of CI-based applications and increase their use by scientists by enhancing CI results with provenance information, trust recommendations, and uncertainty levels (areas that are recognized as essential for the success of CI); by creating scientist-centered tools and artifacts; and by contributing CI resources to appropriate CI portals.
*Cyberinfrastructure (CI) is the technical infrastructure, organizational practices, and social norms required to collectively provide for the smooth operation of work in which interactions may be distributed across time and geographic location. (Edwards et al., Cyberinfrastructure Vision for 21st Century Discovery, March 2007).
Research
Cyber-ShARE focuses on the following projects, each with significant contributions to the educational components:
- Computer Science - Believing and Accepting Cyber-Results: focuses on promoting the scientist’s use of CI by including trust and uncertainty management in support of workflow results.
- Geoscience - Integrated Analysis for Development of 3-D Models of Earth Structure: addresses the problem of obtaining different results from the analysis of geophysical studies of the Earth’s structure, mainly due to mischaracterization of measurement uncertainty, by applying results from optimization and trust models research (e.g., data assimilation and inversion methods using sensor information) to geophysics.
- Environmental Science - Advancing the Utility of Cyberinfrastructure in Environmental Science: addresses the challenge of optimizing data streams and sensor arrays in ecological and environmental networks through use-case studies to improve characterization of various environmental phenomena and processes.









