Visual analytics

R. A. Leite, “Events analysis in visual analytics”, TU Wien, Vienna, 2021.
Author
Advisor
Co-Advisor
Abstract

With the increase of remote work due to COVID-19 and the overall movement towards open source projects, distributed version control system, like Git gained popularity overthe last years. The publicly available data on platforms (e.g., GitHub) therefore becomes richer and attracts sociologists and software analysts for further analysis.This master thesis aims to visualize GitHub trends using Visual Analytics. The data used originates from the GitHub API as well as GitHub Archive, is multivariate and contains different types of information containing repositories, users and events. This data will be extended by the temporal dimension to identify potential trends. For the problem definition and further methodology, the design triangle as described by Mikschet. al is being used.The outcome of the thesis is a prototype, that not only enables domain experts to fulfill common tasks related to identifying GitHub anomalies and trends but also allows foruser interaction to focus on more granular analysis. While many trends can potentially be visualized, this thesis will focus on a small subset of trends to introduce a generic approach and evaluate it on given scenarios and tasks. The general group of potential user groups is broad, but there is a strong emphasis on analysts in technology industries.The prototype was evaluated with domain experts in different fields of expertise that were asked to perform given tasks that can be fulfilled using the developed prototype. The results of the evaluation showed, that there is a strong interest in the analysis of GitHub data and that the right encodings and visualization methods can help find patterns and trends significantly.

Year of Publication
2021
Secondary Title
Institute of Visual Computing and Human-Centered Technology
Paper
Number of Pages
68
reposiTUm Handle
20.500.12708/18896
Publisher
TU Wien
Place Published
Vienna
DOI
10.34726/hss.2021.93182
T. Anderl, “Identifying GitHub trends using temporal analysis”, Institute of Visual Computing and Human-Centered Technology. TU Wien, Vienna, p. 68, 2021.
Master Thesis
AC16386639
Author
Advisor
Co-Advisor
Abstract

The global expansion of wind energy requires robust and meaningful geographic information about its locations. Studies have shown how enriched global data on wind infrastructure can be generated using OpenStreetMap but have neglected to represent and make it analyzable using visual tools. For an accurate visual investigation, knowing which parameters can be used to characterize wind farms and which visual encodings are suitable for global and local analysis are essential. With this aim in mind, we conducted a design study that produced a dataset called the Enriched Data of Wind Farms (EDWin) and a prototype for its interactive visualization. Through a user study, we evaluated the tool's appropriateness for exploring unproven claims about wind farms from the literature and identifying specific wind farms characteristics through simplified visual encoding. The prototype enabled users to complete the tasks, but many needed help from the interviewer due to the need for an improved dynamic grouping functionality. Furthermore, interviews with wind energy experts revealed which features are relevant for the community to describe wind farms. They can be divided into technical, temporal, terrain, and weather characteristics. From those we have covered, several insights were generated, including that the worldwide predominant land cover for the installation of wind infrastructure is agricultural land and that the predominant landform is flat terrain.

Year of Publication
2023
Paper
Number of Pages
95
reposiTUm Handle
20.500.12708/177274
Publisher
TU Wien
Place Published
Vienna
DOI
10.34726/hss.2023.102920
M. Haller, “What do wind farms look like? Visualizing global wind farms”. TU Wien, Vienna, p. 95, 2023.
Master Thesis
AC16856157
Author
Advisor
Co-Advisor
Abstract

As digital technology continues to reshape communication and content consumption, collaboration and collective ideation have become fundamental to modern web technologies. Interactive articles aim to encourage active information exploration to foster knowledge creation. However, the integration of collaboration and tools like the infinite canvas remains unexplored in this context. This thesis investigates the opportunities and limitations of this area. It presents an exploration of the infinite canvas and examines its strengths and challenges for collaborative interactive articles. Through the design and implementation of an application built for Miro, a web-based platform utilizing the infinite canvas for creative collaboration, it investigates the design process for the infinite canvas. In a thinking-aloud user study, this thesis evaluates this application and its integration in this environment. This revealed that the infinite canvas offers an immersive virtual space, though collaborative artifact design introduces unique challenges. The distinction between shared and individual artifacts underscores the importance of considering the collaborative artifact space. Providing a clear user experience proved to be crucial, especially for inexperienced users. Tasks and input methods for end-users need to be kept simple. This thesis identifies two distinct user roles for the design of collaborative interactive articles: facilitators who guide group activities and participants who seek insights. It adopts the idea of Gamestorming as a framework for goal-driven collaboration to facilitate group work and provide engaging activities. Combined with semantic information present on an infinite canvas, this opens up further use cases. Moreover, information visualization techniques highlight possibilities to create engaging and interactive artifacts on the infinite canvas. In the context of visual analytics, the infinite canvas acts as a dynamic visual database, enabling direct interaction with data entities and relationships. Consequently, information visualizations can provide an overview of the infinite canvas and enhance the exploration of content. In the end, this thesis contributes to the collaborative and interactive potential of the infinite canvas, offering insights for the design of interactive articles and explorable visualizations.

Year of Publication
2023
Paper
Number of Pages
123
reposiTUm Handle
20.500.12708/188311
Publisher
TU Wien
Place Published
Vienna
DOI
10.34726/hss.2023.102921
P. Klein, “Reimagining design: Exploring the potential of the infinite canvas for collaborative interactive articles”. TU Wien, Vienna, p. 123, 2023.
Master Thesis
AC16945461
Author
Advisor
Co-Advisor
Abstract

In art historical research, the study of social networks can provide insights into complex interactions between artists. However, despite the successful use of network visualizations in the field of art history, there are still many open questions as well as challenges that need to be solved in order to support art historians in the best possible way for their research. For example, existing approaches offer only limited possibilities to visually explore art historical networks with regard to their geographical context as well as their temporal development. Furthermore, so-called node-link diagrams are usually used for the visual representation of networks, which in the past revealed weaknesses in comparison with other representations in various studies. Finally, it is difficult to evaluate applications with respect to their suitability in the art history domain, since established evaluation approaches are often not conducted with domain experts. We present Exhibitions Explorer, a solution which enables the interactive, visual exploration of art historical networks. The solution integrates different visualization approaches from research into a new visualization concept that focuses on the requirements of the domain. Using an insight-based evaluation approach, we also demonstrate that, provided a suitable visualization concept, network visualizations can lead to a high quantity and quality of domain-relevant insights.

Year of Publication
2023
Secondary Title
Institute of Visual Computing and Human-Centered Technology
Paper
Number of Pages
123
reposiTUm Handle
20.500.12708/139675
Publisher
TU Wien
Place Published
Vienna
DOI
10.34726/hss.2023.99642
A. Nedas, “Utilizing visual analytics for network exploration in the domain of art history research”, Institute of Visual Computing and Human-Centered Technology. TU Wien, Vienna, p. 123, 2023.
Master Thesis
AC16736591
V. Filipov, “"Networks in Time and Space, Visual Analytics of Dynamic Network Representations"”, TU Wien, Vienna, 2024.
V. Filipov, “Dynamic Perspectives: Visualizing Time and Networks for Analytical Insights”, Shonan Meeting 189: Advancing Visual Computing in Materials Science. Shonan, 2024.
V. Filipov, “Visual Analytics”, Wintergraph 2024. Kaprun, 2024.
F. Sperrle, El-Assady, M., Arleo, A., and Ceneda, D., “A Wizard of Oz Study of Guidance Strategies and Dynamics”, IEEE Transactions on Visualization and Computer Graphics, 2024.
M. Tuscher, Filipov, V., Kamencek, T., Rosenberg, R., and Miksch, S., “Mapping the Avantgarde: Visualizing Modern Artists' Exhibition Activity”, in EuroVis 2024 - Short Papers, 2024.