Combining Systems with Linked Open Data

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has title::The Implications of Different Storage Models when Linking Heterogeneous User Information
status: ongoing
Master: project within::Knowledge Technology and Intelligent Internet Applications
Student name: student name::Karl Lundfall
Start start date:=2015/02/16
End end date:=2015/07/07
Supervisor: Victor de Boer
Second supervisor: Stefan Schlobach
Company: has company::
Thesis: has thesis::Media:Thesis.pdf
Poster: has poster::Media:Posternaam.pdf

Signature supervisor



When facing challenges like integrating datasets, ameliorating reusability and answering complex questions about implications in the data, semantic techniques like RDF (Resource Description Framework) can be of great value. These technologies promote an open web of information, making sharing and taking part of information much easier, but can also raise problems like dubious data reliability and/or privacy issues.

TTC (Text-to-change) is a company for equipping people and organizations in developing countries with high-quality information and important knowledge which could otherwise be hard to acquire for them. The company is currently posed with the issue of maintaining multiple projects within different systems, covering different and/or overlapping problems. In the near future, they want to organize their data to be able to merge different systems with one another and to get a better overview of the information. They are also planning to implement visualization tools for different representations the data. Furthermore, the shift from traditional phones (also known as feature phones) towards smart phones is soon expected to happen among the target users, which opens up for opportunities of implementing more intricate services.

We want to investigate the possibilities of using semantic technology on these datasets and examine the extended possibilities of this method as opposed to the existing traditional data structures. We will see how RDF would benefit the objectives of the company as well as looking for additional information that could be inferred from the data. As subquestions, we will also investigate privacy concerns that could be raised as well as exploring which external datasets could be integrated with the data.