Knowledge-Assisted Visual Analytics (KnoVA)
Data analysis is a knowledge-oriented process, to which knowledge constitutes both an input and an output: while prior knowledge is required for interpreting the data as well as for formulating and testing hypotheses. This process generally yields a number of insights, which can be condensed into new knowledge. Nevertheless, prior knowledge is generally tacit: it is used throughout the process, but seldom formalized or made explicit.
Visual Analytics (VA), “the science of analytical reasoning facilitated by interactive visual interfaces”, is a multidisciplinary approach to make sense of data, combining the enormous processing power of computers with the outstanding perceptual and cognitive capabilities of humans. Users of VA systems need to rely on prior knowledge to gain insights from data, formulate and test hypotheses, interpret results, and discover new knowledge. Users’ tacit knowledge is taken into account for designing visualization methods, but the systematic utilization of explicit knowledge is largely unexplored.
An approach towards gathering knowledge from users is knowledge-assisted Visual Analytics (KnoVA), which aims for externalizing users’ tacit knowledge, modeling it as explicit knowledge, and easing the VA process.
You should provide a systematic overview of existing approaches in scientific literature that follow the concepts of knowledge-assisted Visual Analytics (KnoVA). In particular, you should explore, how to ease the VA process by incorporating prior knowledge (explicit/implicit, operational/domain knowledge).
Starting point(s) for research:
Paolo Federico, Markus Wagner, Alexander Rind, Albert Amor-Amorós, Silvia Miksch, Wolfgang Aigner, "The Role of Explicit Knowledge: A Conceptual Model of Knowledge-Assisted Visual Analytics", Proceedings of the IEEE Conference on Visual Analytics Science and Technology (IEEE VAST 2017), 2017.
Paolo Federico, Jürgen Unger, Albert Amor-Amorós, Lucia Sacchi, Denis Klimov, Silvia Miksch, "Gnaeus: Utilizing Clinical Guidelines for a Knowledge-Assisted Visualisation of EHR Cohorts", Proceedings of the EuroVis Workshop on Visual Analytics (EuroVA), pp. 79-83, 2015.
Markus Wagner, Alexander Rind, Niklas Thür,Wolfgang Aigner. "A Knowledge-Assisted Visual Malware Analysis System: Design, Validation, and Reflection of KAMAS", Computers & Security, 67:1–15, 2017.
Markus Wagner, Djordje Slijepcevic, Brian Horsak, Alexander Rind,Matthias Zeppelzauer, and Wolfgang Aigner
"KAVAGait: Knowledge-Assisted Visual Analytics for Clinical Gait Analysis", IEEE Transactions on Visualization and Computer Graphics (TVCG) 25(3): 1528–1542 (2018).