Title
An Affordance-Based Framework for Human Computation and Human-Computer Collaboration
Abstract
Visual Analytics is “the science of analytical reasoning facilitated by visual interactive interfaces” [70]. The goal of this field is to develop tools and methodologies for approaching problems whose size and complexity render them intractable without the close coupling of both human and machine analysis. Researchers have explored this coupling in many venues: VAST, Vis, InfoVis, CHI, KDD, IUI, and more. While there have been myriad promising examples of human-computer collaboration, there exists no common language for comparing systems or describing the benefits afforded by designing for such collaboration. We argue that this area would benefit significantly from consensus about the design attributes that define and distinguish existing techniques. In this work, we have reviewed 1,271 papers from many of the top-ranking conferences in visual analytics, human-computer interaction, and visualization. From these, we have identified 49 papers that are representative of the study of human-computer collaborative problem-solving, and provide a thorough overview of the current state-of-the-art. Our analysis has uncovered key patterns of design hinging on humanand machine-intelligence affordances, and also indicates unexplored avenues in the study of this area. The results of this analysis provide a common framework for understanding these seemingly disparate branches of inquiry, which we hope will motivate future work in the field.
Year
DOI
Venue
2012
10.1109/TVCG.2012.195
IEEE Trans. Vis. Comput. Graph.
Keywords
Field
DocType
data visualisation,groupware,human computer interaction,affordance-based framework,analytical reasoning,human computation,human-computer collaboration,visual analytics,visual interactive interface,Human computation,framework,human complexity,theory
Computer vision,Data visualization,Collaborative software,Computer science,Visualization,Visual analytics,Analytic reasoning,Human–computer interaction,Artificial intelligence,Affordance,Computer graphics,Theory of computation
Journal
Volume
Issue
ISSN
18
12
1077-2626
Citations 
PageRank 
References 
7
0.45
25
Authors
2
Name
Order
Citations
PageRank
R. Jordan Crouser118915.89
Remco Chang298364.96