VISUALIZING RDF AND KNOWLEDGE GRAPHS INTERACTIVE FRAMEWORK TO SUPPORT ANALYSIS DECISION
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.