Paper Info
Title
The Role of Explicit Knowledge: A Conceptual Model of Knowledge-Assisted Visual Analytics
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.
Year
DOI
Venue
2017
10.1109/VAST.2017.8585498
2017 IEEE Conference on Visual Analytics Science and Technology (VAST)
Keywords
Field
DocType
Automated analysis,tacit knowledge,explicit knowledge,visual analytics,information visualization,theory and model
Data science,Data modeling,Data mining,Data visualization,Conceptual model,Computer science,Explicit knowledge,Knowledge economy,Visual analytics,Knowledge-based systems,Tacit knowledge
Conference
ISSN
ISBN
Citations 
2325-9442
978-1-5386-3164-5
3
PageRank 
References 
Authors
0.39
59
6
Name
Order
Citations
PageRank
Paolo Federico1525.20
Markus Wagner235843.21
Alexander Rind318714.75
Albert Amor-Amoros4122.58
Silvia Miksch52212174.85
wolfgang aigner684251.72