Exploration and Visualization in the Web of Big Linked Data: A Survey of the State of the Art

January 29, 2016 ยท The Cartographer ยท ๐Ÿ› EDBT/ICDT Workshops

๐Ÿ“š THE CARTOGRAPHER: The Cartographer
Survey/review paper โ€” maps the landscape rather than implementing a method.

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"Title-pattern auto-detect: Exploration and Visualization in the Web of Big Linked Data: A Survey of the State of the Art"

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Authors Nikos Bikakis, Timos Sellis arXiv ID 1601.08059 Category cs.HC: Human-Computer Interaction Cross-listed cs.DB Citations 112 Venue EDBT/ICDT Workshops Last Checked 8 days ago
Abstract
Data exploration and visualization systems are of great importance in the Big Data era. Exploring and visualizing very large datasets has become a major research challenge, of which scalability is a vital requirement. In this survey, we describe the major prerequisites and challenges that should be addressed by the modern exploration and visualization systems. Considering these challenges, we present how state-of-the-art approaches from the Database and Information Visualization communities attempt to handle them. Finally, we survey the systems developed by Semantic Web community in the context of the Web of Linked Data, and discuss to which extent these satisfy the contemporary requirements.
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