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 ๐ EDBT/ICDT Workshops
"No code URL or promise found in abstract"
"Title-pattern auto-detect: Exploration and Visualization in the Web of Big Linked Data: A Survey of the State of the Art"
Evidence collected by the PWNC Scanner
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.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
๐ Similar Papers
In the same crypt โ Human-Computer Interaction
R.I.P.
๐ป
Ghosted
R.I.P.
๐ป
Ghosted
Improving fairness in machine learning systems: What do industry practitioners need?
R.I.P.
๐ป
Ghosted
Identifying Stable Patterns over Time for Emotion Recognition from EEG
R.I.P.
๐ป
Ghosted
Questioning the AI: Informing Design Practices for Explainable AI User Experiences
R.I.P.
๐ป
Ghosted
Deep Learning for Sensor-based Human Activity Recognition: Overview, Challenges and Opportunities
R.I.P.
๐ป
Ghosted