The Role of Explicit Knowledge: A Conceptual Model of Knowledge-Assisted Visual Analytics
| Conference Paper | |
| Teaser Image | |
| Author | |
| Editor | |
| 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 of Publication | 2017 | 
| Conference Name | Proceedings of the IEEE Conference on Visual Analytics Science and Technology (IEEE VAST 2017) | 
| Publisher | IEEE | 
| Conference Location | Phoenix, AZ, US | 
| DOI | |
| reposiTUm Handle | |
| Refereed Designation | https://doi.org/10.1109/vast.2017.8585498 | 
| Funding projects | |
| Video Link | |
| Paper | |
| Attachments | |
| Download citation | 
 
    