000 Informatik, Wissen, Systeme
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SoNAR (IDH)
(2020)
A Contemporary Nolli Map
(2023)
More than 250 years ago, Giovanni Battista Nolli, an Italian architect, engineer and cartographer, was concerned with how and where space is or is not publicly accessible. In his map 'La nuova topografia di Roma Comasco', he mapped publicly accessible interior and exterior spaces of Rome with an impressively high level of detail as a figure-ground map. Since Nolli’s time, both the character and diversity of public spaces as well as cartographic technology have changed. This research project aims to adapt some ideas behind Nolli’s map for today’s circumstances on the basis of open data, and seeks to develop methods for processing volunteered geographical information from OpenStreetMap (OSM) to identify, categorize, and map public spaces based on thematic and geometric information.
Developing the next generation of cartographers is essential to sustaining and expanding the mission of the International Cartographic Association. Students and early-career professionals today learn cartographic design alongside a diverse array of conceptual and technical competencies, such as data science, human-computer interaction, information visualization, and machine learning. Accordingly, the next generation of cartographers often are working at the forefront of the discipline, actively reshaping what cartography is and can be.
Unfolding Edges
(2023)
Existing work on visualizing multivariate graphs is primarily concerned with representing the attributes of nodes. Even though edges are the constitutive elements of networks, there have been only few attempts to visualize attributes of edges. In this work, we focus on the critical importance of edge attributes for interpreting network visualizations and building trust in the underlying data. We propose 'unfolding of edges' as an interactive approach to integrate multivariate edge attributes dynamically into existing node-link diagrams. Unfolding edges is an in-situ approach that gradually transforms basic links into detailed representations of the associated edge attributes. This approach extends focus+context, semantic zoom, and animated transitions for network visualizations to accommodate edge details on-demand without cluttering the overall graph layout. We explore the design space for the unfolding of edges, which covers aspects of making space for the unfolding, of actually representing the edge context, and of navigating between edges. To demonstrate the utility of our approach, we present two case studies in the context of historical network analysis and computational social science. For these, web-based prototypes were implemented based on which we conducted interviews with domain experts. The experts' feedback suggests that the proposed unfolding of edges is a useful tool for exploring rich edge information of multivariate graphs.
Was sehe ich? Visualisierungsstrategien für Datentransparenz in der Historischen Netzwerkanalyse
(2022)
Die Historische Netzwerkanalyse (HNA) hat sich zu einem etablierten Forschungsfeld entwickelt. Zu ihren wichtigsten methodischen Herausforderungen gehört die Suggestionskraft von Visualisierungen. Die Transparenz bezüglich der Datenquellen ist daher für die HNA sowohl bei selbst erhobenen als auch bei sekundär genutzten Daten Voraussetzung, will sie geisteswissenschaftlichen Kriterien der Nachprüfbarkeit und Nachvollziehbarkeit von Interpretationen erfüllen. Dieser Beitrag beschreibt und diskutiert – aufbauend auf einem iterativen und durch Workshops sowie einer Nutzer*innenstudie begleiteten Forschungsprozess – vier Designziele zur Verwirklichung einer solchen Transparenz: 1) Aufnahme und Kommunikation von Datenprovenienzen, 2) Dokumentation vorausgegangener Prozesse, 3) Offenhaltung der Interpretierbarkeit der Daten und 4) Unterstützung von Folgeforschung. Anschließend werden beispielhafte Umsetzungsstrategien in Form von Prototypen präsentiert.
Over the last few years, data visualization, especially the visualization of spatial data, has become of ever-increasing importance in modern online journalism. While there is a broad range of research projects that focus on developing new methods, techniques, and implementations, empirical analysis of the potential implications of this trend is still rare. In this paper, the potential influence of visualizations in online journalism is in the focus: perceived credibility. The need for such empirical research is emphasized by presenting a preliminary quantitative study that assesses the impact of maps and information visualization on the perceived credibility of online news articles.
Die Falte
(2020)
This contribution explores the instructive tensions between art-historical research and semantic data modeling. While the potential of LOD-applications is obvious in terms of standardization and precision some aspects of research may not be formally represented. Therefore we propose to bridge LOD and full text descriptions through information visualization.
To Classify is to Interpret
(2023)
Taxonomy building is a task that requires interpreting and classifying data within a given frame of reference, which comes to play in many areas of application that deal with knowledge and information organization. In this paper, we explore how taxonomy building can be supported with systems that integrate machine learning (ML). However, relying only on black-boxed ML-based systems to automate taxonomy building would sideline the users’ expertise. We propose an approach that allows the user to iteratively take into account multiple model’s outputs as part of their sensemaking process. We implemented our approach in two real-world use cases. The work is positioned in the context of HCI research that investigates the design of ML-based systems with an emphasis on enabling human-AI collaboration.
Approximately four percent of the world’s population suffers from anxiety disorders. This makes anxiety disorders one of the most common mental illnesses and a significant global health concern. As social media is a primary source of health information and communication, this study aims at investigating how the hashtag #anxiety is used on Twitter and Instagram. The hashtag #anxiety was chosen because it is commonly used by the social media community to post or tweet about anxiety disorders, such as social anxiety, thus providing broad access to the data. We followed a quantitative approach and gathered open data from December 24th, 2019 to January 1st, 2020. Furthermore, we used a qualitative content analysis to detect topics and patterns within the data. Coding focused on identifying goals, motivations, and feelings concerning anxiety (disorders) and information sharing. Findings show that content and appearance of posts are strongly shaped by characteristics of the platforms. Additionally, the results unveil that both platforms serve as mediua for sharing information regarding mental health matters, such as personal experiences, challenges, and coping strategies, thereby cultivating a sense of community and support among users dealing with comparable issues. Twitter predominantly functions for real-time updates, in-situ interactions, and emergency communication, while Instagram's visual nature appears to offer a venue for creative expression through images and captions, illuminating the emotional and personal narratives of mental health journeys.
Im Beitrag werden a) Einblicke in den Prozess gegeben, der 2019 zur Open-Access-Strategie des Landes Brandenburg geführt hat, b) die wesentlichen Aussagen, Leitprinzipien, Ziele und Maßnahmen des Strategiepapiers und das Umsetzungskonzept, speziell zur Vernetzungs- und Kompetenzstelle, vorgestellt, c) Ausblicke auf die konkreten kommenden Unterstützungsstrukturen gegeben, die die Brandenburger Einrichtungen in die Lage versetzen sollen, die Leitprinzipien der Strategie mit Leben zu füllen und ihre Ziele zu erreichen.
This paper presents Emosaic, a tool for visualizing the emotional tone of text documents, considering multiple dimensions of emotion and varying levels of semantic granularity. Emosaic is grounded in psychological research on the relationship between language, affect, and color perception. We capitalize on an established three-dimensional model of human emotion: valence (good, nice vs. bad, awful), arousal (calm, passive vs. exciting, active) and dominance (weak, controlled vs. strong, in control). Previously, multi-dimensional models of emotion have been used rarely in visualizations of textual data, due to the perceptual challenges involved. Furthermore, until recently most text visualizations remained at a high level, precluding closer engagement with the deep semantic content of the text. Informed by empirical studies, we introduce a color mapping that translates any point in three-dimensional affective space into a unique color. Emosaic uses affective dictionaries of words annotated with the three emotional parameters of the valence-arousal-dominance model to extract emotional meanings from texts and then assigns to them corresponding color parameters of the hue-saturation-brightness color space. This approach of mapping emotion to color is aimed at helping readers to more easily grasp the emotional tone of the text. Several features of Emosaic allow readers to interactively explore the affective content of the text in more detail; e.g., in aggregated form as histograms, in sequential form following the order of text, and in detail embedded into the text display itself. Interaction techniques have been included to allow for filtering and navigating of text and visualizations.
KEW@T ist ein anwendungsorientiertes Forschungsprojekt zur Verknüpfung von digitalen Inhalten aus den Bereichen digitales Kulturerbe und Kulturtourismus am Beispiel des Landes Brandenburg. Das Projekt, welches in Kooperation mit der Tourismus Marketing Brandenburg GmbH durchgeführt wurde, wird aus Mitteln des Europäischen Fonds für regionale Entwicklung (EFRE) und des Landes Brandenburg gefördert.
Der Beitrag gibt einen Überblick über die Gründungsmotive aller Angehörigen der Fachhochschule Potsdam. Zudem erfolgt ein Einblick in die Fachkulturen Archiv, Bibliothek, Design, Bau, Kulturarbeit, Architektur, soziale Arbeit und Restaurierung. Der Beitrag beruht auf einer im November 2021 bis Januar 2022 durchgeführten Umfrage zuzüglich Gespräche mit ausgewählten Expert*innen. Insgesamt haben 305 Personen an der Untersuchung teilgenommen (Rücklaufquote ca. 7%). Diese Personen können den fünf Fachbereichen Sozial- und Bildungswissenschaften, Stadt/ Bau/ Kultur, Bauingenieurwesen, Design und Informationswissenschaften zugeordnet werden. Es wurden ausschließlich Personen, die bereits selbstständig sind, sich derzeit in der Planung einer Selbstständigkeit befinden oder aber ernsthaft an einer Selbstständigkeit interessiert sind, gebeten, Aussagen zu Gründungsmotiven zu machen (n=176). Die Ergebnisse zeigen, dass die Gründungsmotive Unabhängigkeit und Streben nach eigenverantwortlicher Tätigkeit ohne Vorgesetzte für beide Geschlechter von großer Bedeutung sind. Etwa jeder Zehnte gab an, dass die Selbstständigkeit ihnen helfen würde, Beruf und Familie zu vereinbaren. Unabhängigkeit und Streben nach eigenverantwortlicher Tätigkeit ohne Chef*in wurde von Studierenden und Absolvent*innen am häufigsten genannt, während für Mitarbeitende ebenso Unabhängig, aber auch ihre Erfahrungen in einer Selbstständigkeit zu nutzen relevanter sind. Bezogen auf die einzelnen Fachbereiche werden Unterschiede in der Gründungsmotivation deutlich, wobei über alle Fachbereiche hinweg erneut das Unabhängigkeitsmotiv und das Streben nach einer eigenverantwortlichen Tätigkeit bedeutsam ist. Für die Entwicklung eines tiefergehenden Verständnisses für die jeweilige Fachkultur wurden Gespräche mit Expert*innen geführt. Es wird aufgezeigt, welche Normen, Werte und Erfolgsmaßstäbe für die Fachkulturen „Archiv“, „Bibliothek“, „Design“, „Bau“, „Kulturarbeit“, „Architektur“, „soziale Arbeit“, „Restaurierung“ charakteristisch sind. Es wird reflektiert, welche Bedeutung „Risikobereitschaft“, „Unabhängigkeit“, „freie Entfaltung“, „selbständiges Arbeiten“, „Kreativität“, „Entscheidungen unter Unsicherheit“, „finanzielle Anreize“ in der jeweiligen Fachkultur hat.
Theoretical and Empirical Modeling of Identity and Sentiments in Collaborative Groups (THEMIS.COG) was an interdisciplinary research collaboration of computer scientists and social scientists from the University of Waterloo (Canada), Potsdam University of Applied Sciences (Germany), and Dartmouth College (USA). This white paper summarizes the results of our research at the end of the grant term. Funded by the Trans-Atlantic Platform’s Digging Into Data initiative, the project aimed at theoretical and empirical modeling of identity and sentiments in collaborative groups. Understanding the social forces behind self-organized collaboration is important because technological and social innovations are increasingly generated through informal, distributed processes of collaboration, rather than in formal organizational hierarchies or through market forces. Our work used a data-driven approach to explore the social psychological mechanisms that motivate such collaborations and determine their success or failure. We focused on the example of GitHub, the world’s current largest digital platform for open, collaborative software development. In contrast to most, purely inductive contemporary approaches leveraging computational techniques for social science, THEMIS.COG followed a deductive, theory-driven approach. We capitalized on affect control theory, a mathematically formalized theory of symbolic interaction originated by sociologist David R. Heise and further advanced in previous work by some of the THEMIS.COG collaborators, among others. Affect control theory states that people control their social behaviours by intuitively attempting to verify culturally shared feelings about identities, social roles, and behaviour settings. From this principle, implemented in computational simulation models, precise predictions about group dynamics can be derived. It was the goal of THEMIS.COG to adapt and apply this approach to study the GitHub collaboration ecosystem through a symbolic interactionist lens. The project contributed substantially to the novel endeavor of theory development in social science based on large amounts of naturally occurring digital data.
Social anxiety disorder (SAD) is one of the most commonly diagnosed anxiety disorders and a health concern that has a significant impact on the affected individuals’ quality of life. Although there is a need to develop methods and tools to support those affected by SAD, it is especially challenging to conduct participatory design with this psychologically vulnerable group of people. This paper presents the design, implementation and evaluation of a participatory format built on a toolkit, a cultural probe and an online prototyping workshop to gain insights into the challenges and needs experienced in the everyday lives of those affected by severe social anxiety. We provide the theoretical framework for designing a participatory format for this vulnerable group, introduce and discuss our methodological approach, and present the lessons learned from implementing and evaluating the format in two workshop sessions with a total of 15 participants.
The five editions of the CheckThat! lab so far have focused on the main tasks of the information verification pipeline: check-worthiness, evidence retrieval and pairing, and verification. The 2023 edition of the lab zooms into some of the problems and - for the first time - it offers five tasks in seven languages (Arabic, Dutch, English, German, Italian, Spanish, and Turkish): Task 1 asks to determine whether an item, text or a text plus an image, is check-worthy; Task 2 requires to assess whether a text snippet is subjective or not; Task 3 looks for estimating the political bias of a document or a news outlet; Task 4 requires to determine the level of factuality of a document or a news outlet; and Task 5 is about identifying authorities that should be trusted to verify a contended claim.
Journalism has become more data-driven and inherently visual in recent years. Photographs, illustrations, infographics, data visualizations, and general images help convey complex topics to a wide audience. The way that visual artifacts influence how readers form an opinion beyond the text is an important issue to research, but there are few works about this topic. In this context, we research the persuasive, emotional and memorable dimensions of data visualizations and illustrations in journalistic storytelling for long-form articles. We conducted a user study and compared the effects which data visualizations and illustrations have on changing attitude towards a presented topic. While visual representations are usually studied along one dimension, in this experimental study, we explore the effects on readers' attitudes along three: persuasion, emotion, and information retention. By comparing different versions of the same article, we observe how attitudes differ based on the visual stimuli present, and how they are perceived when combined. Results indicate that the narrative using only data visualization elicits a stronger emotional impact than illustration-only visual support, as well as a significant change in the initial attitude about the topic. Our findings contribute to a growing body of literature on how visual artifacts may be used to inform and influence public opinion and debate. We present ideas for future work to generalize the results beyond the domain studied, the water crisis.