Date of Award

8-9-2014

Document Type

Open Access Thesis

Department

Computer Science and Engineering

First Advisor

Manton M. Matthews

Abstract

The web before linked data was a database of html documents. These documents were meant for human consumption and it was hard for machines to make sense of data in html documents. The linked data was introduced with the aim of making the web a global database of data that is machine processable. Linked Data describes a method of publishing structured data so that it can be interlinked and become more useful. Realizing the promise of linked data a lot of people started publishing linked data. But the process of publishing the huge amount of existing data is cumbersome and usually takes someone very knowledgeable to do it. Publishing linked data on the web requires finding appropriate vocabularies that describe the semantics of the data. Finding such vocabularies is difficult to a new user. The proposed system will suggest vocabularies to use when somebody is trying to publish linked data. The system does so by using string similarity metrics to match entity and property names in our dataset to Class and Property names in existing RDF vocabularies.

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