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Master Thesis von Branislav Vidojevic

Last modified Jun 14, 2019

Analysis and design of a semantic modeling language to describe public data sources

Ever since Tim Berners-Lee introduced the Semantic Web term, the research community, and afterward also the companies, have changed the way how they perceive data on the Internet. As the Internet expands rapidly, a need arose to organize and interconnect existing data with the new data that is coming into the Internet. SemanticWeb has a significant influence in this area as it comes in the form of an add-on onto the World Wide Web and provides a set of standards and protocols for data sharing and reusing across the Internet. Since utilizing the benefits of Semantic Web could not be as fast as harvesting the benefits of data sharing, data integration, and remote data access, solutions that use the power of the Semantic Web are not as widely in use as other solutions. What will be given in this Master Thesis is an overview of state-of-the-art solutions in the area of data integration with the emphasis on the handling of semantic metadata. Based on that analysis, we give a recommendation on how to semantically annotate data that resides in multiple disparate open data sources. Afterward, we describe the process of implementation of a library, which can help in solving problems as such. In the end, we utilize the developed solution in the existing platform for data integration where we describe benefits and downfalls of solutions that use the Semantic Web.

 

Keywords:

Semantic Web, Data Integration, Data Engineering, Linked Data, Open Data, Web of Data, JSON, JSON-LD, REST, MIDAS

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