CanLink Thesis Finder Canada: Making a standalone linked data project operational

CanLink Thesis Finder Canada: Making a standalone linked data project operational, Sharon Farnel and Danoosh Davoodi

The underlying data model enhances entities such as authors, supervisors and subjects with URIs (e.g. VIAF, LCSH, FAST) in order to satisfy the “linking out” principle of linked data.

The data is mostly harvested from institutions' OAI/PMH end points and was processed using Python and pushed to a local triplestore. The front end application is developed using React accessing data from the triplestore and SolR (for search).

In this session, we will provide an overview of the CanLink project, focusing on data (sources, harvesting, modeling), development of the user interface, and steps taken to make the project sustainable and scalable over time. We hope to engage attendees in discussions on how to move linked data in libraries from standalone projects to operationalized initiatives.