Linked Open Data Creating Knowledge Out Of Interlinked Data

Linked Open Data -- Creating Knowledge Out of Interlinked Data

Linked Open Data (LOD) is a pragmatic approach for realizing the Semantic Web vision of making the Web a global, distributed, semantics-based information system. This book presents an overview on the results of the research project “LOD2 -- Creating Knowledge out of Interlinked Data”. LOD2 is a large-scale integrating project co-funded by the European Commission within the FP7 Information and Communication Technologies Work Program. Commencing in September 2010, this 4-year project comprised leading Linked Open Data research groups, companies, and service providers from across 11 European countries and South Korea. The aim of this project was to advance the state-of-the-art in research and development in four key areas relevant for Linked Data, namely 1. RDF data management; 2. the extraction, creation, and enrichment of structured RDF data; 3. the interlinking and fusion of Linked Data from different sources and 4. the authoring, exploration and visualization of Linked Data.

Knowledge-Driven Harmonization of Sensor Observations: Exploiting Linked Open Data for IoT Data Streams

The rise of the Internet of Things leads to an unprecedented number of continuous sensor observations that are available as IoT data streams. Harmonization of such observations is a labor-intensive task due to heterogeneity in format, syntax, and semantics. We aim to reduce the effort for such harmonization tasks by employing a knowledge-driven approach. To this end, we pursue the idea of exploiting the large body of formalized public knowledge represented as statements in Linked Open Data.

Linked Open Data -- Creating Knowledge Out of Interlinked Data