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LinkedData

383 bytes added, 13:46, 24 November 2008
Aims and Overview
== Aims and Overview ==
The aim of this tutorial is to provide participants with a detailed conceptual understanding of how to publish Linked Data on the Web, and detailed exposure a gentle introduction to the practical and technical steps that make up the publishing process. In addition to a conceptual introduction to Linked Data, the tutorial will cover best practices in topics such as minting URIs for published data sets, vocabulary selection, choosing what RDF data to expose, and interlinking distributed data sets. Specific patterns will be presented for publishing different forms of data set, such as data from static files, relational databases and existing Web APIs. Participants will also be shown how to debug published data.
The second focus of the tutorial will be applications that consume Linked Data from the Web. We will give an overview about existing Linked Data browsers, Web of Data search engines as well as Linked Data Mashups and cover the existing software frameworks that can be used to build applications on top of the Data Web.  Lastly the tutorial will be to provide a collaborative space to explore putting some of the ideas of linked data into practice. The idea is that people can split off into groups, or work independently on adding linked data support to an existing application, exploring modeling issues of what vocabularies to use for particular data sets, and brain storming about new vocabularies that may be needed in the library world.
The tutorial will combine presentations by the tutors with demonstrations, interactive sessions, and group discussion. Other than a broad technical understanding of the Web development and Web publishing process, and a basic conceptual understanding of the Semantic Web, there are no pre-requisites for participation in the tutorial, which will be of interest to the full spectrum of code4lib2009 attendees, including researchers, developers, data managers/publishers and those seeking to comercially exploit the Semantic Web by publishing Linked Data.

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