Project Summary

Many VIVO implementers find collecting, mapping, and loading data into VIVO to be quite difficult. For example, data on publications, grants, and datasets produced by an institution’s faculty can be difficult to find and disambiguate. Understanding the ontologies used to describe data in VIVO and mapping faculty data to those ontologies involves a steep learning curve. Also, transforming the data to a linked data format, such as VIVO RDF, has proven difficult for most implementers due to gaps in skills and knowledge. These barriers have prevented organizations from joining the VIVO community and adopting the technology that enables access, discovery, and analysis of scholarship data.

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