Defragmenting Research Areas with Knowledge Visualization and Visual Text Analytics
VisUSAL Research Group, Universidad de Salamanca, 37008 Salamanca, Spain
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Appl. Sci. 2020, 10(20), 7248; https://doi.org/10.3390/app10207248
Received: 27 September 2020
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Revised: 14 October 2020
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Accepted: 14 October 2020
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Published: 16 October 2020
(This article belongs to the Special Issue Applications of Cognitive Infocommunications (CogInfoCom))
The increasing specialization of science is motivating the fragmentation of traditional and well-established research areas into interdisciplinary communities of practice that focus on cooperation between experts to solve problems in a wide range of domains. This is the case of problem-driven visualization research (PDVR), in which groups of scholars use visualization techniques in different application domains such as the digital humanities, bioinformatics, sports science, or computer security. In this paper, we employ the findings obtained during the development of a novel visual text analytics tool we built in previous studies, GlassViz, to automatically detect interesting knowledge associations and groups of common interests between these communities of practice. Our proposed method relies on the statistical modeling of author-assigned keywords to make its findings, which are demonstrated in two use cases. The results show that it is possible to propose interactive, semisupervised visual approaches that aim at defragmenting a body of research using text-based, automatic literature analysis methods.
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Keywords:
visual text analytics; problem-driven visualization research; methodology transfer; author-assigned keywords; distributional similarity; knowledge visualization
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MDPI and ACS Style
Benito-Santos, A.; Therón Sánchez, R. Defragmenting Research Areas with Knowledge Visualization and Visual Text Analytics. Appl. Sci. 2020, 10, 7248. https://doi.org/10.3390/app10207248
AMA Style
Benito-Santos A, Therón Sánchez R. Defragmenting Research Areas with Knowledge Visualization and Visual Text Analytics. Applied Sciences. 2020; 10(20):7248. https://doi.org/10.3390/app10207248
Chicago/Turabian StyleBenito-Santos, Alejandro, and Roberto Therón Sánchez. 2020. "Defragmenting Research Areas with Knowledge Visualization and Visual Text Analytics" Applied Sciences 10, no. 20: 7248. https://doi.org/10.3390/app10207248
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