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It’s About Time: User-centered Evaluation of Visual Representations for Temporal Data
Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, Faculty of Science & Engineering.
2021 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The primary goal for collecting and analyzing temporal data differs between individuals and their domain of expertise e.g., forecasting might be the goal in meteorology, anomaly detection might be the goal in finance. While the goal differs, one common denominator is the need for exploratory analysis of the temporal data, as this can aid the search for useful information. However, as temporal data can be challenging to understand and visualize, selecting appropriate visual representations for the domain and data at hand becomes a challenge. Moreover, many visual representations can show a single variable that changes over time, displaying multiple variables in a clear and easily accessible way is much harder, and inference-making and pattern recognition often require visualization of multiple variables. Additionally, as visualization aims to gain insight, it becomes crucial to investigate whether the representations used help users gain this insight. Furthermore, to create effective and efficient visual analysis tools, it is vital to understand the structure of the data, how this data can be represented, and have a clear understanding of the user needs. Developing useful visual representations can be challenging, but through close collaboration and involvement of end-users in the entire process, useful results can be accomplished. 

This thesis aims to investigate the usability of different visual representations for different types of multivariate temporal data, users, and tasks. Five user studies have been conducted to investigate different representation spaces, layouts, and interaction methods for investigating representations’ ability to facilitate users when analyzing and exploring such temporal datasets. The first study investigated and evaluated the experience of different radial design ideas for finding and comparison tasks when presenting hourly data based on an analog clock metaphor. The second study investigated 2D and 3D parallel coordinates for pattern finding. In the third study, the usability of three linear visual representations for presenting indoor climate data was investigated with domain experts. The fourth study continued on the third study and developed and evaluated a visual analytics tool with different visual representations and interaction techniques with domain experts. Finally, in the fifth study, another visual analytics tool presenting visual representations of temporal data was developed and evaluated with domain experts working and conducting experiments in Antarctica. 

The research conducted within the scope of this thesis concludes that it is vital to understand the characteristics of the temporal data and user needs for selecting the optimal representations. Without this knowledge, it becomes much harder to choose visual representations to help users gain insight from the data. It is also crucial to evaluate the perception and usability of the chosen visual representations. 

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2021. , p. 53
Series
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 2120
National Category
Human Computer Interaction
Identifiers
URN: urn:nbn:se:liu:diva-173609DOI: 10.3384/diss.diva-173609ISBN: 9789179297107 (print)OAI: oai:DiVA.org:liu-173609DiVA, id: diva2:1531414
Public defence
2021-03-26, Online via Zoom: https://liu-se.zoom.us/j/66155056377, ID: 661 5505 6377, 09:30 (English)
Opponent
Supervisors
Available from: 2021-02-26 Created: 2021-02-26 Last updated: 2022-02-09Bibliographically approved
List of papers
1. A Study on 2D and 3D Parallel Coordinates for Pattern Identification in Temporal Multivariate Data
Open this publication in new window or tab >>A Study on 2D and 3D Parallel Coordinates for Pattern Identification in Temporal Multivariate Data
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2019 (English)Conference paper, Published paper (Refereed)
Abstract [en]

Parallel coordinates are commonly used for non-temporal multivariate data, but there is little support for their usability for displaying temporal multivariate data. In this paper, we introduce a study evaluating the usability of 2D and 3D parallel coordinates for pattern identification in temporal multivariate data. The results indicate that 3D parallel coordinates have higher usability, as measured with higher accuracy and faster response time as well as subjective ratings, compared to 2D.

Place, publisher, year, edition, pages
IV 2019: IEEE conference proceedings, 2019
Series
IEEE International Conference on Information Visualisation, ISSN 2375-0138
Keywords
Temporal Data, User Evaluation, 2D Parallel Coordinates, 3D Parallel Coordinates
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:liu:diva-159079 (URN)10.1109/IV.2019.00033 (DOI)000507461900024 ()978-1-7281-2838-2 (ISBN)
Conference
2019 23rd International Conference Information Visualization (IV)
Available from: 2019-07-22 Created: 2019-07-22 Last updated: 2021-11-14
2. A Study on Visual Representations for Active Plant Wall Data Analysis
Open this publication in new window or tab >>A Study on Visual Representations for Active Plant Wall Data Analysis
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2019 (English)In: DATA, E-ISSN 2306-5729, Vol. 4, no 2, article id 74Article in journal (Refereed) Published
Abstract [en]

The indoor climate is closely related to human health, well-being, and comfort. Thus, an understanding of the indoor climate is vital. One way to improve the indoor climates is to place an aesthetically pleasing active plant wall in the environment. By collecting data using sensors placed in and around the plant wall both the indoor climate and the status of the plant wall can be monitored and analyzed. This manuscript presents a user study with domain experts in this field with a focus on the representation of such data. The experts explored this data with a Line graph, a Horizon graph, and a Stacked area graph to better understand the status of the active plant wall and the indoor climate. Qualitative measures were collected with Think-aloud protocol and semi-structured interviews. The study resulted in four categories of analysis tasks: Overview, Detail, Perception, and Complexity. The Line graph was found to be preferred for use in providing an overview, and the Horizon graph for detailed analysis, revealing patterns and showing discernible trends, while the Stacked area graph was generally not preferred. Based on these findings, directions for future research are discussed and formulated. The results and future directions of this research can facilitate the analysis of multivariate temporal data, both for domain users and visualization researchers.

Place, publisher, year, edition, pages
MDPI, 2019
Keywords
visualization; qualitative evaluation; temporal multivariate data; active plant walls, Visualisering; kvalitativ utvärdering; tidsvarierande multivariate data; active plant walls
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:liu:diva-157027 (URN)10.3390/data4020074 (DOI)000475303500028 ()
Available from: 2019-05-23 Created: 2019-05-23 Last updated: 2021-02-26Bibliographically approved
3. PINGU Principles of Interactive Navigation for Geospatial Understanding
Open this publication in new window or tab >>PINGU Principles of Interactive Navigation for Geospatial Understanding
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2020 (English)In: 2020 IEEE PACIFIC VISUALIZATION SYMPOSIUM (PACIFICVIS), IEEE , 2020, p. 216-225Conference paper, Published paper (Refereed)
Abstract [en]

Monitoring conditions in the periglacial areas of Antarctica helps geographers and geologists to understand physical processes associated with mesoscale land systems. Analyzing these unique temporal datasets poses a significant challenge for domain experts, due to the complex and often incomplete data, for which corresponding exploratory tools are not available. In this paper, we present a novel visual analysis tool for extraction and interactive exploration of temporal measurements captured at the polar station at the James Ross Island in Antarctica. The tool allows domain experts to quickly extract information about the snow level, originating from a series of photos acquired by trail cameras. Using linked views, the domain experts can interactively explore and combine this information with other spatial and non-spatial measures, such as temperature or wind speed, to reveal the interplay of periglacial and aeolian processes. An abstracted interactive map of the area indicates the position of measurement spots to facilitate navigation. The design of the tool was made in tight collaboration with geographers, which resulted in an early prototype, tested in the pilot study. The following version of the tool and its usability has been evaluated in the user study with five domain experts and their feedback was incorporated into the final version, presented in this paper. This version was again discussed with two experts in an informal interview. Within these evaluations, they confirmed the significant benefit of the tool for their research tasks.

Place, publisher, year, edition, pages
IEEE, 2020
Series
IEEE Pacific Visualization Symposium, ISSN 2165-8765
Keywords
Human-centered computing; Visualization; Visualization techniques; Treemaps; Human-centered computing; Visualization; Visualization design and evaluation methods
National Category
Human Computer Interaction
Identifiers
urn:nbn:se:liu:diva-170939 (URN)10.1109/PacificVis48177.2020.7567 (DOI)000578516400027 ()978-1-7281-5697-2 (ISBN)
Conference
IEEE Pacific Visualization Symposium (PacificVis), Tianjin, PEOPLES R CHINA, apr 14-17, 2020
Available from: 2020-11-01 Created: 2020-11-01 Last updated: 2021-02-26

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Akram Hassan, Kahin

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