TimeNotes: A Study on Effective Chart Visualization and Interaction Techniques for Time-Series Data
- Submitting institution
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King's College London
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 87320986
- Type
- D - Journal article
- DOI
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10.1109/TVCG.2015.2467751
- Title of journal
- IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS
- Article number
- -
- First page
- 549
- Volume
- 22
- Issue
- 1
- ISSN
- 1077-2626
- Open access status
- Out of scope for open access requirements
- Month of publication
- August
- Year of publication
- 2015
- URL
-
-
- Supplementary information
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-
- 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
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2
- Research group(s)
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-
- Citation count
- 20
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The paper introduces TimeNotes, the first visual analytics tool for multi-dimensional biological time series data. It delves into TimeNotes development, validation and rigorous evaluation against challenges of visualizing multi-dimensional time-varying biological data. The paper was also invited for presentation at IEEE Vis Conference. TimeNotes has been mentioned on Microsoft “Machine Learning Blog” as one of the four most interesting work influencing the use of ML in the area of time-series visualization https://blogs.technet.microsoft.com/machinelearning/2015/11/11/ieee-visualization-conference-2015-increasing-influenceof- machine-learning/. TimeNotes is integrated into Framework4 (http://framework4.co.uk/), platform for smart sensor data analytics used internationally: Institut für Terrestrische und Aquatische Wildtierforschung (Germany), Laboratorio Ecotono (Argentina), ECOCEAN Inc.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -