A Systematic Mapping on the use of Visual Data Mining to Support the Conduct of Systematic Literature Reviews
Katia R. Felizardo, Stephen G. MacDonell, Em\'ilia Mendes, Jos\'e, Carlos Maldonado

TL;DR
This paper systematically maps the use of visual data mining techniques to support systematic literature reviews, revealing limited research in software engineering but more activity in medicine, especially during data extraction and synthesis.
Contribution
It provides a comprehensive overview of existing research on VDM in SLRs and highlights gaps in its application across different review phases.
Findings
Most studies are in medicine, not software engineering.
VDM is mainly used during data extraction and synthesis.
Limited research on VDM support in planning and reporting phases.
Abstract
A systematic literature review (SLR) is a methodology used to find and aggregate all relevant existing evidence about a specific research question of interest. Important decisions need to be made at several points in the review process, relating to search of the literature, selection of relevant primary studies and use of methods of synthesis. Visualization can support tasks that involve large collections of data, such as the studies collected, evaluated and summarized in an SLR. The objective of this paper is to present the results of a systematic mapping study (SM) conducted to collect and evaluate evidence on the use of a specific visualization technique, visual data mining (VDM), to support the SLR process. We reviewed 20 papers and our results indicate a scarcity of research on the use of VDM to help with conducting SLRs in the software engineering domain. However, most of the…
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