Newswise — MILWAUKEE _ Professor Richard Smiraglia of the University of Wisconsin-Milwaukee’s School of Information Studies has been awarded a $175,000 grant from the Institute of Museum and Library Services. Smiraglia will lead a collaborative project, Digging into the Knowledge Graph, with international partners Andrea Scharnhorst (Data Archiving and Networked Services at the Royal Netherlands Academy of Arts and Sciences) and Rick Szostak (University of Alberta, Canada).

The grant is one of 14 awarded through the prestigious Trans-Atlantic Platform for the Social Sciences and Humanities (T-AP) Digging into Data Challenge

The primary goal of Digging into the Knowledge Graph is to address the challenge of using the Linked Open Data (LOD) Cloud and Semantic Web technologies properly.

The Semantic Web is a term for the structuring of information in a way that facilitates linkages among computers, people and data on the World Wide Web.

Linked Open Data is a technique for making data available online that enables broad reuse by supporting connections between disparate datasets.

The team will enhance findability and storage for humanities and social science datasets that use Linked Open Data.  The project will enhance researchers’ ability to search the Semantic Web and contribute to it. It will also provide trusted digital repositories the ability to archive Linked Data.

The team will pilot the work with focused studies in musicology and economics, and enable wider knowledge creation by making the metadata for these Linked Open Data datasets available for data mining.

"Digging into the Knowledge Graph offers us an unprecedented opportunity to discover navigable pathways in conceptual space — not just metaphorically but as the realization of the power of structured knowledge to resolve very real human dilemmas,” Smiraglia said. “We are very excited by the prospect of learning to navigate the LOD cloud."

Smiraglia and his international team of researchers are among 14 winning teams working collaboratively to demonstrate how cutting-edge big data techniques can be used to investigate a wide range of research questions across the humanities and social sciences.