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2014 | OriginalPaper | Chapter

Visualization of Semantic Data Based on Selected Predicates

Authors : Gábor Rácz, Gergő Gombos, Attila Kiss

Published in: Transactions on Computational Collective Intelligence XIV

Publisher: Springer Berlin Heidelberg

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Abstract

Due to the spreading of semantic technologies, the volume of the datasets that are described in the Resource Description Framework (RDF) is dynamically growing. The RDF framework is suitable for integrating data from heterogeneous sources; however, the resulted datasets can be larger and extremely complex than before, new tools are needed to analyze them. In this paper, we present a method which aims to help to understand the structure of semantic datasets. It can reduce the size and the complexity of a dataset while preserves the selected parts of it. The method consists of a filtering and a compaction phases that are implemented according to the MapReduce distributed programing model to be able to handle large volume of data. The result of the method can be visualized as a labeled directed graph that is suitable to give an overview of the structure of the dataset. It may reveal hidden connections or different kinds of problems related to the completeness and correctness of the data.

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Title: Visualization of Semantic Data Based on Selected Predicates
Authors: Gábor Rácz
Gergő Gombos
Attila Kiss
Publisher: Springer Berlin Heidelberg
Book: Transactions on Computational Collective Intelligence XIV
Print ISBN: 978-3-662-44508-2

Electronic ISBN: 978-3-662-44509-9

Copyright Year: 2014
DOI: https://doi.org/10.1007/978-3-662-44509-9_9

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