NDLI: Learning-based evaluation of visual analytic systems

Please wait, while we are loading the content...

Developing qualitative metrics for visual analytic environments

Many roads lead to Rome: mapping users' problem solving strategies

Exploring information visualization: describing different interaction patterns

Towards information-theoretic visualization evaluation measure: a practical example for Bertin's matrices

Learning-based evaluation of visual analytic systems

A descriptive model of visual scanning

Generating a synthetic video dataset

Is your user hunting or gathering insights?: identifying insight drivers across domains

Comparing benchmark task and insight evaluation methods on timeseries graph visualizations

Do Mechanical Turks dream of square pie charts?

Comparing information graphics: a critical look at eye tracking

Evaluating information visualization in large companies: challenges, experiences and recommendations

Learning-based evaluation of visual analytic systems

Content Provider	ACM Digital Library
Author	Kielman, Joseph Ribarsky, William Pyzh, Roman Chang, Remco Ziemkiewicz, Caroline
Abstract	Evaluation in visualization remains a difficult problem because of the unique constraints and opportunities inherent to visualization use. While many potentially useful methodologies have been proposed, there remain significant gaps in assessing the value of the open-ended exploration and complex task-solving that the visualization community holds up as an ideal. In this paper, we propose a methodology to quantitatively evaluate a visual analytics (VA) system based on measuring what is learned by its users as the users reapply the knowledge to a different problem or domain. The motivation for this methodology is based on the observation that the ultimate goal of a user of a VA system is to gain knowledge of and expertise with the dataset, task, or tool itself. We propose a framework for describing and measuring knowledge gain in the analytical process based on these three types of knowledge and discuss considerations for evaluating each. We propose that through careful design of tests that examine how well participants can reapply knowledge learned from using a VA system, the utility of the visualization can be more directly assessed.
Starting Page	29
Ending Page	34
Page Count	6
File Format	PDF
ISBN	9781450300070
DOI	10.1145/2110192.2110197
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2010-04-10
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Learning Visualization Evaluation methodology
Content Type	Text
Resource Type	Article

Central Library (ISO-9001:2015 Certified)
Indian Institute of Technology Kharagpur
Kharagpur, West Bengal, India | PIN - 721302

See location in the Map
03222 282435
Mail: support@ndl.gov.in

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in