VISUALIZING RDF AND KNOWLEDGE GRAPHS INTERACTIVE FRAMEWORK TO SUPPORT ANALYSIS DECISION

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Published: 2020-02-10

Page: 43-46


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.

*Author to whom correspondence should be addressed.


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.

Keywords: Analytics, big data, interaction, RDF, visualization.


How to Cite

AHMED SOLIMAN, H. A. S., & TABAK, A. (2020). VISUALIZING RDF AND KNOWLEDGE GRAPHS INTERACTIVE FRAMEWORK TO SUPPORT ANALYSIS DECISION. Journal of Global Economics, Management and Business Research, 12(1), 43–46. Retrieved from https://ikprress.org/index.php/JGEMBR/article/view/4920

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