The project Linked Data for Professional Education (LD4PE), funded between 2014 and 2017 by the Institute of Museum and Library Studies (IMLS) and lead by the University of Washington Information School, developed a web-based exploratorium to support structured discovery of online learning resources about Linked Data. The project produced this website, which has been converted into a static site for preservation, and a Linked Data Competency Index. DCMI will keep this site online on a "best effort" basis as long as resources permit. The Internet Archive's Wayback Machine should be regarded as the source of archival copies for the long term.

Querying Heterogeneous Datasets on the Linked Data Web: Challenges, Approaches, and Trends

The growing number of datasets published on the Web as Linked Data brings both opportunities for high data availability and challenges inherent to querying data in a semantically heterogeneous and distributed environment. Approaches used for querying siloed databases fail at Web-scale because users don't have prior understanding of all the available datasets. This article investigates the main challenges in constructing a query and search solution for Linked Data and analyzes existing approaches and trends.

URL: http://dx.doi.org/10.1109/MIC.2011.141
Keywords: Query, Semantic Web, Natural language, RDF, Semantic search
Author: O’Riain, Sean
Publisher: IEEE
Date created: 2012-01-09 05:00:00.000
Language: http://id.loc.gov/vocabulary/iso639-2/eng
Time required: P20M
Educational use: professionalDevelopment
Educational audience: student
Interactivity type: expositive

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Querying Heterogeneous Datasets on the Linked Data Web: Challenges, Approaches, and Trends