Transforming Literature-intensive Research Processes Through Text Analytics - Design, implementation and Lessons Learned

Abstract

The continuing growth of scientific publications raises the question how research processes can be digitalized and thus realized more productively. Especially in information technology fields, research practice is characterized by a rapidly growing volume of publications. For the search process various information systems exist. However, the analysis of the published content is still a highly manual task. Therefore, we propose a text analytics system that allows a fully digitalized analysis of literature sources. We have realized a prototype by using EBSCO Discovery Service in combination with IBM Watson Explorer and demonstrated the results in real-life research projects. Potential addressees are research institutions, consulting firms, and decision-makers in politics and business practice.


Editor: H. Kemal İlter, Ankara Yıldırım Beyazıt University, Turkey

Received: August 19, 2018, Accepted: October 18, 2018, Published: November 10, 2018
Copyright: © 2018 IMISC Bensberg et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.