The Role of Explicit Knowledge: A Conceptual Model of Knowledge-Assisted Visual Analytics

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Abstract

Visual Analytics (VA) aims to combine the strengths of humans and

computers for effective data analysis. In this endeavor, humans’

tacit knowledge from prior experience is an important asset that can

be leveraged by both human and computer to improve the analytic

process. While VA environments are starting to include features to

formalize, store, and utilize such knowledge, the mechanisms and

degree in which these environments integrate explicit knowledge

varies widely. Additionally, this important class of VA environments

has never been elaborated on by existing work on VA theory. This

paper proposes a conceptual model of Knowledge-assisted VA conceptually

grounded on the visualization model by van Wijk. We

apply the model to describe various examples of knowledge-assisted

VA from the literature and elaborate on three of them in finer detail.

Moreover, we illustrate the utilization of the model to compare different

design alternatives and to evaluate existing approaches with

respect to their use of knowledge. Finally, the model can inspire designers

to generate novel VA environments using explicit knowledge

effectively.
Conference Name
Proceedings of the IEEE Conference on Visual Analytics Science and Technology (IEEE VAST 2017)
Publisher
IEEE
Conference Location
Phoenix, AZ, US
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http://www.cvast.tuwien.ac.at/sites/default/files/federico-2017-vast.pdf
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