The increasing interest in analysing, describing, and improving the research process requires the development of new forms of scholarly data publication and analysis that integrates lessons and approaches from the field of Semantic Technologies, Science of Science, Digital Libraries, and Artificial Intelligence. This editorial summarises the content of the Special Issue on Scholarly Data Analysis (Semantics, Analytics, Visualisation), which aims to showcase some of the most interesting research efforts in the field. This issue includes an extended version of the best papers of the last two editions of the 'Semantics, Analytics, Visualisation: Enhancing Scholarly Dissemination' (SAVE-SD 2017 and 2018) workshop at The Web Conference.
Gonzalez-Beltran, A., Osborne, F., Peroni, S., Vahdati, S. (2019). Editorial: Special Issue on Scholarly Data Analysis (Semantics, Analytics, Visualisation). DATA SCIENCE, 2(1-2), 177-179 [10.3233/DS-190023].
Editorial: Special Issue on Scholarly Data Analysis (Semantics, Analytics, Visualisation)
Osborne, Francesco;
2019
Abstract
The increasing interest in analysing, describing, and improving the research process requires the development of new forms of scholarly data publication and analysis that integrates lessons and approaches from the field of Semantic Technologies, Science of Science, Digital Libraries, and Artificial Intelligence. This editorial summarises the content of the Special Issue on Scholarly Data Analysis (Semantics, Analytics, Visualisation), which aims to showcase some of the most interesting research efforts in the field. This issue includes an extended version of the best papers of the last two editions of the 'Semantics, Analytics, Visualisation: Enhancing Scholarly Dissemination' (SAVE-SD 2017 and 2018) workshop at The Web Conference.
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