Current systems for exploring scholarly data exhibit a number of shortcomings in their ability to facilitate the identification of research trends and identify 'interesting' connections between researchers. To address these issues we have developed Rexplore, a novel system which combines statistics, human-computer interaction, and semantic technologies, to support knowledge-based exploration and visualization of scholarly data. In this paper we focus on the functionalities provided by Rexplore for visualizing research trends and we use as an example research in "Social Networks", which has experienced dramatic growth in the years 2000-2010.

Osborne, F., Motta, E. (2013). Exploring research trends with Rexplore. D-LIB MAGAZINE, 19(9-10) [10.1045/september2013-osborne].

Exploring research trends with Rexplore

Osborne F
;
2013

Abstract

Current systems for exploring scholarly data exhibit a number of shortcomings in their ability to facilitate the identification of research trends and identify 'interesting' connections between researchers. To address these issues we have developed Rexplore, a novel system which combines statistics, human-computer interaction, and semantic technologies, to support knowledge-based exploration and visualization of scholarly data. In this paper we focus on the functionalities provided by Rexplore for visualizing research trends and we use as an example research in "Social Networks", which has experienced dramatic growth in the years 2000-2010.
Articolo in rivista - Articolo scientifico
Scientifica
Algorithms; Bibliographic data; Data exploration; Data visualization; Design; Experimentation; Human factors; Performance; Scholarly data; Semantic technologies; Visual analytics;
English
Osborne, F., Motta, E. (2013). Exploring research trends with Rexplore. D-LIB MAGAZINE, 19(9-10) [10.1045/september2013-osborne].
Osborne, F; Motta, E
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/10281/381200
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