Special issue on “advances in visual analytics and mining visual data”

Victor Chang, Shadi A. Aljawarneh, Chung‐Sheng Li

Research output: Contribution to journalEditorialpeer-review

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Visual and multimedia analytics provides an emerging field of research combining strengths from information analytics, geospatial analytics, scientific analytics, statistical analytics, knowledge discovery, data management and knowledge representation, presentation, production and dissemination, cognition, perception, and interaction (Chen, Chiang and Storey, 2012). The aim is to gain insight into homogeneous, contradictory, and incomplete data through the combination of automatic analysis methods with human background knowledge and intuition.

While the scope of visual analytics is broad, one principle that has emerged over the years is the need for visual analytics systems to leverage
computational methods in data mining, knowledge discovery, and machine learning for large-scale data analysis. In these systems, the human
operator works alongside the computational processes in an integrated fashion. Therefore, computing systems or services can sift through large
amounts of data and identify the relevant information, while the human interactively explores the reduced data space to discover trends and patterns and make informed decisions. These two components operate in coordination, allowing for a continuous and cooperative analytical loop
(Cybulski et al., 2015; Valdez et al., 2016). Top papers from Data 2018, Madrid, Spain and the best paper from FEMIB 2019 in Crete, Greece, have
been invited. Through a robust and competitive review process, six papers have been selected.
Original languageEnglish
JournalExpert Systems
Publication statusPublished - 29 Jun 2020


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