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.

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Uses available resources for named entity recognition, extraction, and reconciliation.

AGDISTIS – Graph-Based Disambiguation of Named Entities using Linked Data

The ongoing transition from the current Web of unstructured data to the Web of Data yet requires scalable and accurate approaches for the extraction of [...]

By |January 16th, 2016|Comments Off on AGDISTIS – Graph-Based Disambiguation of Named Entities using Linked Data

Methodological Guidelines for Publishing Government Linked Data

Publishing Linked Data is a process that involves many steps, design decisions and technologies. Some initial guidelines have been provided by Linked Data publishers, but [...]

By |October 21st, 2015|Comments Off on Methodological Guidelines for Publishing Government Linked Data

Knowledge Graph Identification

Large-scale information processing systems are able to extract massive collections of interrelated facts, but unfortunately transforming these candidate facts into useful knowledge is a formidable [...]

By |September 15th, 2015|Comments Off on Knowledge Graph Identification

Real-time RDF Extraction from Unstructured Data Streams

Most of the Web of Data is limited to a large compendium of encyclopedic knowledge describing entities. The timely and massive extraction of RDF facts [...]

By |September 15th, 2015|Comments Off on Real-time RDF Extraction from Unstructured Data Streams

Discovering Missing Semantic Relations Between Entities in Wikipedia

Wikipedia’s infoboxes contain rich structured information of various entities, which have been exploited by the DBpedia project to generate large-scale Linked Data datasets. Among all [...]

By |September 15th, 2015|Comments Off on Discovering Missing Semantic Relations Between Entities in Wikipedia

Providing Linked Data

This video presentation covers the whole spectrum of Linked Data production and exposure. It begins with a grounding in Linked Data principles and best practices, [...]

By |September 15th, 2015|Comments Off on Providing Linked Data

Preserving Linked Data: Challenges and Opportunities

In this video, the speaker begins by discussing the Web of Data and Linked Data Principles, then switches focus to the challenges of publishing and [...]

By |September 15th, 2015|Comments Off on Preserving Linked Data: Challenges and Opportunities

Linked Data at The New York Times: The First 161 Years

The New York Times' commitment to Linked Data began over 160 years ago. Starting in 1851, The New York Times has cataloged its archival articles [...]

By |August 13th, 2015|0 Comments

Using oXygen to Enrich (X)HTML or ePub via Linked Data Sources

This video describes use of the oXygen XML editor to enrich (X)HTML or ePub via Linked Data sources. The result is the generation IST 2.0 [...]

By |August 13th, 2015|0 Comments

From Excel File to RDF with Links to DBpedia and Europeana

This screencast is a step-by-step walk-through showing how to transform Excel tables to RDF data and then link that RDF data to external data sources. [...]

By |August 13th, 2015|0 Comments