Introduction to VISUAL 2014-Workshop on visualizations and user interfaces for knowledge engineering and linked data analytics

IVANOVA, Valentina, KAUPPINEN, Tomi, LOHMANN, Steffen, MAZUMDAR, Suvodeep, PESQUITA, Catia and XU, Kai (2014). Introduction to VISUAL 2014-Workshop on visualizations and user interfaces for knowledge engineering and linked data analytics. In: LAMBRIX, Patrick, HYVÖNEN, Eero, BLOMQVIST, Eva, PRESUTTI, Valentina, QI, Guilin, SATTLER, Uli, DING, Ying and GHIDINI, Chiara, (eds.) Knowledge Engineering and Knowledge Management. EKAW 2014, , VISUAL, EKM1, and ARCOE-Logic, Linköping, Sweden, November 24-28, 2014. Revised Selected Papers. Lecture Notes in Computer Science (8982). Cham, Springer, 80-82.

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Official URL: https://link.springer.com/chapter/10.1007/978-3-31...
Link to published version:: https://doi.org/10.1007/978-3-319-17966-7_8

Abstract

VISUAL 2014 addressed the challenges in providing knowledge engineers and data analysts with visualizations and well-designed user interfaces to support the understanding of the concepts, data instances and relationships in different domains. The workshop was organized around two tracks: one focused on visualizations and user interfaces for Knowledge Engineering, and the other on Visual Analytics for dynamic and large-scale data. Six contributions were presented at the workshop, which also included an interactive tool demonstration session.

Item Type: Book Section
Additional Information: Paper originally presented at the International Conference on Knowledge Engineering and Knowledge Management, EKAW 2014, Linköping, Sweden, November 24-28, 2014. Book is also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 8982). Lecture Notes in Computer Science series ISSN: 0302-9743.
Departments - Does NOT include content added after October 2018: Faculty of Science, Technology and Arts > Department of Computing
Identification Number: https://doi.org/10.1007/978-3-319-17966-7_8
Page Range: 80-82
Depositing User: Suvodeep Mazumdar
Date Deposited: 19 Jan 2018 12:01
Last Modified: 18 Mar 2021 16:30
URI: https://shura.shu.ac.uk/id/eprint/16899

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