Special Issue "CDEC: Cross-disciplinary Data Exchange and Collaboration"
Deadline for manuscript submissions: closed (30 April 2020).
Interests: market of data; design of data; creativity; information retrieval; knowledge structuring
Due to recent social movement of big data and artificial intelligence, the importance of data and data mining has been increasing. In the background of these expectations, there are externalizations of interdisciplinary issues. Many papers about data mining have been published, and the processes of analyzing data have been shared widely. However, there are not many studies targeting the process of Cross-disciplinary Data Exchange and Collaboration (CDEC) using knowledge acquired through data mining. Because CDEC includes various activities of different stakeholders, it is difficult to evaluate the patterns or the processes quantitatively. CDEC includes the practical fields which analytically performs the topics using data, the challenging solutions against social issues, and cross-disciplinary data collaboration and its processes. CDEC targets, not only cleanly formatted single data, but also heterogeneous data that affect human behaviors, thoughts, and intentions in different domains. We also focus on the discussion to obtain tacit knowledge of data mining through analysis and synthesis. In addition to these research fields, the cognitive approach for observing the processes of knowledge discovery and data exchange is also included in our focus.
The 1st International Workshop on CDEC will be held in Singapore on 17 November 2018, in conjunction with IEEE-ICDM 2018. We believe that this Special Issue provides a chance of reaching even broader audiences to the authors of CDEC 2018, who are therefore invited to submit extended versions of their papers to the Special Issue "Cross-disciplinary Data Exchange and Collaboration" of the journal Information by MDPI. However, authors interested in extending their workshop papers must be aware that the final submitted manuscript must provide a minimum of 50% new content and not exceed 30% copy/paste from the proceedings paper. Each manuscript will be blind reviewed by MDPI academic editors.
Dr. Teruaki Hayashi
Prof. Yukio Ohsawa
Manuscript Submission Information
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