Visual Analytics System for LOD Using Sampling-based Structure Estimation

• Published in: Transactions of the Japanese Society for Artificial Intelligence Vol. 32; no. 1; pp. WII-B_1 - 11
• Main Authors: Yabe, Ayaka, Ishikawa, Hiroshi, Takama, Yasufumi
• Format: Journal Article
• Language: English; Japanese
• Published: Tokyo The Japanese Society for Artificial Intelligence 2017; Japan Science and Technology Agency
• Subjects: Analytics; Linked Data; linked open data; resource description framework; Resource Description Framework-RDF; Sampling; Scientific visualization; Tables; Target recognition; visual analytics; Visualization

This paper proposes information visualization system for exploratory LOD (Linked Open Data) Analysis. The LOD is a framework to make data open to the public. Recently, it has been widely used to publish various kinds of data such as statistical data, geographical data, and academic data. The RDF (Re...