VISUALIZING RDF AND KNOWLEDGE GRAPHS INTERACTIVE FRAMEWORK TO SUPPORT ANALYSIS DECISION

Hatem Ahmed Sayed Ahmed Soliman and Ahmad Tabak
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Hatem Ahmed Sayed Ahmed Soliman: College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, 211106, China.
Ahmad Tabak: Department of Control and Automation Engineering, University of Aleppo, Aleppo, Syria.

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Abstract: Knowledge graphs are progressively important source of data and context information in many fields especially in Data Science; there is no doubt that the first step in data analysis is data exploration in which visualization plays an important role; Data visualization has become significant research challenge involving several issues related to storing, querying, indexing, visual presentation, interaction data [1]. The Semantic Web Resource Description Framework (RDF) describes metadata that aims to make the Web content not only machine-readable but also machine-understandable; this paper outline of Graph-based Visualization Systems overview and proposes Visualizing interactive RDF and knowledge Graphs Framework to support analysis decision.

Date: 2020-02-10
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Published in Journal of Global Economics, Management and Business Research, 2020, 12 (1), pp.43-46

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-05263328

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