In-Use – Paper 382

Lessons Learned in Building Linked Data for the American Art Collaborative

Craig Knoblock, Pedro Szekely, Eleanor Fink, Duane Degler, David Newbury, Robert Sanderson, Kate Blanch, Sara Snyder, Nilay Chheda, Nimesh Jain, Ravi Raju Krishna, Nikhila Begur Sreekanth and Yixiang Yao

In-Use

clock_eventOctober 19, 2017, 11:20.
house Lehár 1-3
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Abstract

Linked Data has emerged as the preferred method for publishing and sharing cultural heritage data. One of the main challenges for museums is that the defacto standard ontology (CIDOC CRM) is complex and museums lack expertise in semantic web technologies. In this paper we describe the methodology and tools we used to create 5-star Linked Data for 14 American art museums with a team of 12 computer science students and 30 representatives from the museums who mostly lacked expertise in Semantic Web technologies. The project was completed over a period of 18 months and generated 99 mapping files and 9,357 artist links, producing a total of 2,714 R2RML rules and 9.7M triples. More importantly, the project produced a number of open source tools for generating high-quality linked data and resulted in a set of lessons learned that can be applied in future projects. %In this paper, we describe the lessons learned in creating the linked data for these 14 museums, including mapping their data to a shared ontology (CIDOC-CRM), creating the tools and linking the artists in their collections to common repository (The Getty's Union List of Artist Names), and creating an application to explore the data. %This paper describes the lessons learned in addressing this challenge, which includes mapping the data to the complicated CIDOC-CRM domain ontology, dealing with sources with different formats and schemas, and identifying links for large amounts of data with very high accuracy.