In recent years we have seen an explosion in the use of VIVO outside of the institutional and clinical/translational medicine sphere and in uses that go beyond its original intent for researcher networked profiles. This has occurred in such NSF funded projects as the DataNet Program that includes the Datanet Federation Consortium (http://datafed.org/) and SEAD-Sustainable Environment Actionable Data (http://sead-data.net/) as well as in such other large collaborative multi-disciplinary groups such as the Alfred P. Sloan Foundation Funded Deep Carbon Observatory (https://dco.gl.ciw.edu/). Additionally, we have seen extended interest in networked use-case functionality and Web-based services for clinical and translational medicine from areas of the NIH funded CTSA Program.
This panel will focus on collaborative aspects of VIVO for use with multi-institutional and multi-disciplinary science groups both for building researcher social networks but also in developing VIVO in new ways as a semantic interface layer for science. The panel will offer a gap analysis for additional functionality that should be targeted for the new VIVO application development community from their particular science collaboration perspective. Each speaker in this panel is using VIVO in very different ways from how it was first envisioned. All of which extend VIVO towards uses that are working closer and closer to a true open linked data reality for collaborative team science. The implementation of VIVO as a component of cyberinfrastructure for multi-disciplinary scientific discovery and collaboration will only enable better uses of individual institutional and funding agency based open data.
This panel brings together the perspectives of experts from four projects each of which use VIVO within their own cyberinfrastructure environments for linked and generally open data analytics. Discussion will include extensions to VIVO for data publication, for use with grid- based data environments, for use with collaborative scientific semantic driven systems, and for use with existing clinical and translational medicine collaborative tools.