Lessons Learned in Building Linked Data for the American Art Collaborative
published: Nov. 28, 2017, recorded: October 2017, views: 13
Report a problem or upload filesIf you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
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.
Link this pageWould you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !