Analytic provenance for sensemaking: a research agenda
- Submitting institution
-
Middlesex University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 778
- Type
- D - Journal article
- DOI
-
10.1109/MCG.2015.50
- Title of journal
- IEEE Computer Graphics and Applications
- Article number
- -
- First page
- 56
- Volume
- 35
- Issue
- 3
- ISSN
- 0272-1716
- Open access status
- Out of scope for open access requirements
- Month of publication
- May
- Year of publication
- 2015
- URL
-
http://eprints.mdx.ac.uk/15814/
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
5
- Research group(s)
-
-
- Citation count
- 26
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- During complex visual analytic tasks, it is important to maintain a record of analytic provenance.So is important to keep a history of data manipulations and associated reasoning to support reflection, audit and training. This paper is significant because it describes key research challenges involved in capturing, visualising and utilising analytic provenance information. This offers both a ‘call-to-action’ and orientation to communities interested in making scientific progress on these difficult questions. Provenance can be used for exploration guidance, can facilitate collaboration, and help us understand what we can trust from possibly uncertain data, and improve visual analytics.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -