Is hosted by the Chair of Business Information Systems. As well as the Institute for Applied Informatics. Development of methods, tools and applications for adaptive Knowledge Engineering in the context of the Semantic Web. AKSW is committed to the free software.

DCMI Global Meetings and Conferences. DCMI Global Meetings and Conferences. International Conference on Dublin Core and Metadata Applications. The annual Dublin Core conferences bring together leading metadata researchers and professionals from around the world. Proceedings of the International Conference on Dublin Core and Metadata Applications. Cover a full range of topics related to standards and technologies for metadata.

The Linking Open Data cloud diagram. This web page is the home of the. This image shows datasets that have been published in Linked Data. Format, by contributors to the Linking Open Data. Community project and other individuals and organisations. It is based on metadata collected and curated by contributors to the Data Hub. Clicking the image will take you to an interactive SVG version, where each dataset is a hyperlink to its entry in Datahub. The diagram is maintained by Andrejs Abele.

Mathias dot niepert at neclab dot eu. MSc, PhD in Computer Science, Indiana University. I am a senior researcher at NEC Labs in Heidelberg. From 2012-2015 I was a research associate at the University of Washington in Seattle. I was also a member of the Data and Web Science Research Group. At the University of Mannheim. I am also co-founder of several open-source digital humanities projects such as the Indiana Philosophy Ontology Project. And the Linked Humanities Project.

Silk is an open source framework for integrating heterogeneous data sources. Generating links between related data items within different Linked Data sources. Linked Data publishers can use Silk to set RDF links from their data sources to other data sources on the Web. Applying data transformations to structured data sources. And the Linked Data book. Silk - Link Specification Language. The linking process is based on the.

Extracting Structured Data from the Common Crawl. The Web Data Commons project extracts structured data from the Common Crawl. The largest web corpus available to the public, and provides the extracted data for public download in order to support researchers and companies in exploiting the wealth of information that is available on the Web. Data sets extracted from the December 2014 Common Crawl corpus available for download.

To get EDIT-rights for the wiki, please create an account. Welcome the PlanetData Project Wiki. Please visit the official project website. For the professional web presence. Name, affilliation, contact details. Name, country, city. Description, associated WPs, leader. Overview and links to designated WP pages.