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Interfacing with power
(2017)
Drawing connections
(2018)
An/Leiten
(2017)
Carrying Computerization
(2018)
Durch und über Computer
(2019)
Einleitung : Interface
(2021)
From shock to shift
(2023)
We present a multi-dimensional, multi-level, and multi-channel approach to data visualization for the purpose of constructive climate journalism. Data visualization has assumed a central role in environmental journalism and is often used in data stories to convey the dramatic consequences of climate change and other ecological crises. However, the emphasis on the catastrophic impacts of climate change tends to induce feelings of fear, anxiety, and apathy in readers. Climate mitigation, adaptation, and protection—all highly urgent in the face of the climate crisis—are at risk of being overlooked. These topics are more difficult to communicate as they are hard to convey on varying levels of locality, involve multiple interconnected sectors, and need to be mediated across various channels from the printed newspaper to social media platforms. So far, there has been little research on data visualization to enhance affective engagement with data about climate protection as part of solution-oriented reporting of climate change. With this research we characterize the unique challenges of constructive climate journalism for data visualization and share findings from a research and design study in collaboration with a national newspaper in Germany. Using the affordances and aesthetics of travel postcards, we present Klimakarten, a data journalism project on the progress of climate protection at multiple spatial scales (from national to local), across five key sectors (agriculture, buildings, energy, mobility, and waste), and for print and online use. The findings from quantitative and qualitative analysis of reader feedback confirm our overall approach and suggest implications for future work.
Tracing and Telling
(2023)
Cultural collections have transcended the boundaries of physical showcases and storage cabinets, evolving into intricate digital webs of interconnected data. The research project Restaging Fashion aimed to expand the possibilities for experiencing the linkages in digitized cultural heritage, focusing on the visualization of collection holdings related to the history of garments. Through graph-based narratives, the project investigated the complex interplay between the linear – and at times tentative – art historical discourses and the non-linear explorations of associated cultural heritage data. The resulting visualizations have been designed with the aim to allow for curated and dynamic exploration of the collection along research essays and their interrelated graphs.
In November 2022, the US company OpenAI launched its chatbot ChatGPT built on top of its large language models (LLMs). “This chatbot has redefined the standards of artificial intelligence, proving that machines can indeed ‘learn’ the complexities of human language and interaction”, urteilte Forbes in May 2023.
As new trends constantly emerge worldwide, such as ChatGPT, it is necessary to approach the promotion of these tools to the broader population in an appropriate manner. New technologies and artificial intelligence tools simultaneously offer enhanced functionality but also the potential for misuse, such as plagiarism. Therefore, in the home countries of the authors, various discussions have been initiated at numerous universities and other organisations over the years regarding the advantages and disadvantages of these tools and how to best utilize them. It will be important for university teachers to actively integrate tools such as ChatGPT into their teaching and to critically reflect on the necessary competences for the use of such a chatbot. To achieve such learning objectives, the first step is to understand how ChatGPT works and how it can be used. In the following, the focus is on one such application, namely how ChatGPT can be used in cultural marketing.
Digital qualifiziertes Personal ist die Grundlage für eine zukunftsfähige Wissenschaftslandschaft. Die Omnipräsenz von digitalen Daten und Informationen, von Tools für Kommunikation und Kollaboration stellt nicht nur Wissenschaft und Forschung vor neue Herausforderungen, sondern die gesamte Gesellschaft. Überall bedarf es digitaler Kompetenzen, um mit den Möglichkeiten der digitalen Transformation bewusst und mündig umgehen zu können. Hier bietet die Informationswissenschaft gemeinsam mit der Informatik als Basiswissenschaft für alle Wissenschaften Ansätze und Lösungen, so zum Beispiel im Bereich Data Science und Data Stewardship. Basierend auf einem Diskussionspapier (Attallah et al., 2020) widmeten sich 19 Expert*innen im Kontext eines Interview-Podcasts der AG 6 „Digital qualifiziertes Personal“ der Allianz der Wissenschaftsorganisationen diesem komplexen Thema. Die 15 durchgeführten (Doppel-) Interviews bildeten die Basis für die Datengrundlage und wurden explorativ und softwaregestützt qualitativ analysiert. Ziel war die ergebnisoffene, aber möglichst umfängliche Abbildung und Analyse der von den Expert*innen angesprochenen Handlungsfelder, um unter anderem folgende Forschungsfragen beantworten zu können: Welche Kompetenzen werden für die digitale Qualifikation in den Wissenschaftsorganisationen benötigt? Welche Möglichkeiten und Verantwortlichkeiten für eine Kompetenzvermittlung gibt es? Welchen Beitrag können die Informationswissenschaften leisten?
People Who Stare at Screens
(2023)
Video Conferencing
(2023)
The COVID-19 pandemic has reorganized existing methods of exchange, turning comparatively marginal technologies into the new normal. Multipoint videoconferencing in particular has become a favored means for web-based forms of remote communication and collaboration without physical copresence. Taking the recent mainstreaming of videoconferencing as its point of departure, this anthology examines the complex mediality of this new form of social interaction. Connecting theoretical reflection with material case studies, the contributors question practices, politics and aesthetics of videoconferencing and the specific meanings it acquires in different historical, cultural and social contexts.
Reflecting on the history and development of the knowledge management discipline from an academic and applied research perspective, this chapter will outline the KM essentials as core of the discipline and open questions to be addressed in the future. Secondly, the author will discuss in particular the role of KM within organizational practice in regard to the overall societal challenges all organizations are facing today globally. Thirdly, the chapter will provide an outlook of the discipline in the light of future developments and suggests some research topics to be addressed by interdisciplinary KM research in the future. Beside on drawing on more than 35 years of experience in the KM field, this contribution will profit from previous research undertaken on the future of KM (2002 and 2012), contributions to guidelines and standards for KM (e.g., CEN, DIN, ISO), as well as from working with European Fortune 500 companies over the past 25 years.
Narrelations
(2019)
We present findings from interdisciplinary research at the intersection between literary studies, information visualization, and interface design. Despite a growing interest in text visualization among literary scholars, so far, narrative visualizations are not designed to support the particular tasks involved in narratological analysis and often fail to reveal nuanced narratological features. One major outcome of our iterative research and design process is Narrelations, a novel visualization technique specifically suited for analyzing and interpreting narrative levels of a story and temporal aspects of its narrative representation. The visualization provides an overview of the nesting and distribution of narrative levels, integrates the representation of temporal phenomena, and facilitates the examination of correlations between these aspects. With this research we explore how collaboratively designed visual encodings and interaction techniques may allow for an insightful analysis at a high level coupled with a close inspection of text passages. We discuss prior work relevant to our research objectives and explain the specific characteristics of narrative levels and temporal aspects of narrative representation. After describing the research process and design principles, we apply the visualization on a test corpus of eight annotated German short stories and demonstrate its heuristic value for literary analyses and interpretations. In particular, we explore the intricate connections between the literary content of the novellas and their narrative form.
The Fold
(2020)
We propose the philosophical notion of the fold as an evocative vocabulary for the design and critique of interactive data visualizations. An expanding range of application areas, such as digital art history and literary studies, illustrates the potential of data visualization for research and education in the humanities. Coinciding with the increasing currency of data as evidence in the humanities, this research addresses a growing interest in data visualization for visual analysis and argumentation. For example, cultural collection visualizations promise a range of possibilities for visual and interactive representations of digital cultural heritage, used both for free exploration and focused research. Based on the concept of the fold, prominently advanced by Gilles Deleuze, this paper outlines a critical framework that draws attention towards the complexity of the underlying data. The fold offers a way to analyze and conceptualize visualizations through the lens of three integrated operations: explication, implication, and complication. It is an opportunity to think of interactive visualizations as portals into coherent, elastic, and ultimately infinite information spaces. Accordingly, it rejects the separation between interactivity and visual encoding and draws attention to the transitions between multiple states of a visualization. We identify design patterns of the fold in data visualizations, devise a framework for the critical interpretation of interactivity in data visualization, and demonstrate the implications for the digital humanities.
Graph Technologies for the Analysis of Historical Social Networks Using Heterogeneous Data Sources
(2020)
Over the last decades, cultural heritage institutions have provided extensive machine-readable data, such as bibliographic and archival metadata, full-text collections, and authority records containing multitudes of implicit and explicit statements about the social relations between various types of entities. In this paper, we discuss how approaches to the creation and operation of advanced research infrastructure for historical network analysis (HNA) based on heterogeneous data sources from cultural heritage institutions can be examined and evaluated. Based on our interdisciplinary research, we describe challenges and strategies with a special focus on the issue of data processing, sketch out the advantages of human-centered project design in the form of a preliminary co-design workshop, and present an iterative approach to data visualization.
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.
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.
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.
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.
This article investigates data journalism epistemology through Michel Foucault’s definition of power. The growing demand for data-savvy reporters with computational skills has been proven to shift the newsrooms’ culture in media companies across the globe. Previous research has documented journalists’ shift towards a data-centred epistemology and the increasingly important role of computation and data-driven practices in newsrooms. By focusing on inexperienced journalists as they mobilise data journalism for the first time, this research openly discusses its epistemology as a form of Foucauldian power: which epistemological tensions – individual or structural – emerge among newcomers when reporting extensively with data? The article presents the case of a newly formed data journalism team at taz, a German cooperative media company. It is based on qualitative data collected through action research, namely six in-depth interviews, auto-ethnographic notes and self-reflective inquiries. Data are framed through Foucault’s concepts of power and will to truth. Results show the discord between data journalism epistemology and its practical implementation. Despite prioritising democratic access to data, technologies and non-hierarchical forms of cooperation, data journalism remains largely dependent on traditional methods and culture.
Transdisciplinary research processes often involve the integration of knowledge and stakeholders from various backgrounds. Here, we introduce the story of the research project AMA (A Mindset for the Anthropocene) on the role of mindsets in the context of sustainability and present an interactive visualization tool that we developed for stakeholder mapping and research communication. Through this platform, we provide access and navigation to everyone interested in this field of research and we have simultaneously created a channel for all stakeholders to co-create content. Here, we describe the design and functionalities of the platform and the participatory way it was developed as part of our stakeholder engagement. We discuss upon how such a design allows for reflection of potential biases in transdisciplinary research processes and simultaneously catalyzing self-organization in stakeholder networks.
As part of the research project Open Data Cloud Services (ODCS), we have been trying to overcome some of the limitations introduced through the heterogeneity of spatial open government data (sOGD). In this paper we describe some of the challenges of sODG and one of the tools we built to spatially organize heterogenous sOGD, to make it easier for users to find data and automatically integrate it into existing data structures and in the future allow for cross-dataset spatial analysis.
The 17th International Conference on Knowledge Management was held in the historic city of Potsdam, Germany. The conference was among the first post-pandemic face to face conferences, and the overall theme of the 17th edition of the ICKM conference rightly focused on “Knowledge, Uncertainty and Risks: From individual to global scale” at different levels of analysis and agency.
Der Einfluss digitaler Technologien auf organisatorische Abläufe und die Interaktion zwischen Beteiligten nehmen in der Gesellschaft ständig zu. An der Schnittstelle von Mensch und Technik beschreibt dieses Buch im Rahmen eines interdisziplinären Ansatzes unterschiedliche Menschenbilder und -modelle. Es ermöglicht somit einen spannenden Perspektivwechsel auf die Entwicklung und den Einsatz digitaler Technologien. Erkennbar werden dabei zahlreiche Gemeinsamkeiten, aber auch gegenläufige Positionen aus technischer, ethischer, pädagogischer oder rechtlicher Sicht.
Nachtalb
(2022)
Nachtalb is an immersive interface that enables brain-to-brain interaction using multisensory feedback. With the help of the g.tec Unicorn Hybrid Black brain-computer-interface (BCI), brain-activity-data is measured and translated visually with the Oculus Quest 2, tactilely with the bHaptics TactSuit and auditorily with 3D Sound. This intends to create a feedback loop that turns brain activity from data-input into sensory output which directly influences the brain activity data-input again.
In Case You Don’t Know What To Play is a framework for designing a Virtual Reality application that uses spatial distortion to influence the user’s visual perception and ultimately shall manipulate their sense of time. Spatial orientation allows us to judge distances regarding their temporal component. In particular, in self-motion we can estimate the duration it takes to cover a given distance, since time and spatial perception are connected. This connection can be broken with the help of Virtual Reality technology and a perceptual conflict can be created.
Surprise Machines is a project of experimental museology that sets out to visualize the entire image collection of the Harvard Art Museums, with a view to opening up unexpected vistas on more than 200,000 objects usually inaccessible to visitors. The project is part of the exhibition organized by metaLAB (at) Harvard entitled Curatorial A(i)gents and explores the limits of artificial intelligence to display a large set of images and create surprise among visitors. To achieve this feeling of surprise, a choreographic interface was designed to connect the audience’s movement with several unique views of the collection.
Aktuelle Geschehnisse wie das Inkrafttreten des Kodex „Leitlinien zur Sicherung guter wissenschaftlicher Praxis" der Deutschen Forschungsgemeinschaft (DFG) oder der Aufbau der Nationalen Forschungsdateninfrastruktur (NFDI) und der European Open Science Cloud (EOSC) stellen Anbietende, Produzierende und Nutzende von Forschungsdaten vor fachwissenschaftliche, technische, rechtliche und organisatorische Herausforderungen. Das Praxishandbuch Forschungsdatenmanagement behandelt umfassend alle relevanten Aspekte des Forschungsdatenmanagements und der derzeitigen Rahmenbedingungen im Datenökosystem.
Insbesondere die praktischen Implikationen der Datenpolitik und des -rechts, des jeweiligen Datenmarkts, der Datenkultur, der persönlichen Qualifizierung, des Datenmanagements sowie des „FAIR"en Datentransfers und der Datennachnutzung werden untersucht. Das Praxishandbuch gibt überdies einen Überblick über Projekte, Entwicklungen und Herausforderungen beim Forschungsdatenmanagement.
Am 16. Juni 2021 fand ein Interview mit dem Herausgeber und den Herausgeberrinnen statt, das Ihnen Einblicke in die Intentionen, inhaltlichen Einflüsse sowie ihre Gedanken für die Zukunft des Forschungsdatenmanagements gibt. Hier finden Sie das Webinar auf Youtube : https://www.youtube.com/watch?v=H-v1KPTWsac
Der NFDI e.V. wird einen bedeutsamen Beitrag für einen besseren Umgang mit Forschungsdaten leisten, doch der Erfolg der nationalen Forschungsdateninfrastruktur ist letztlich von einer Einbindung der gesamten Wissenschaftsgemeinschaft und -infrastruktur abhängig. Die vielfältigen Forschungseinrichtungen einzubinden, erfordert Koordination auf vielen Ebenen. Speziell Hochschulen haben eine tragende Rolle für sowohl disziplinäre und interdisziplinäre Forschung als auch wissenschaftliche Ausbildung in Deutschland und sind damit zentrale Akteure für die fachübergreifende Forschungsdateninfrastruktur. Durch die Förderung von Kooperationen und Koordination auf Ebene von Ländern oder Länderverbünden lässt sich die Entwicklung der nationalen Forschungsdateninfrastruktur unterstützen. Landesinitiativen für Forschungsdatenmanagement (FDM) oder ähnliche koordinierende Einrichtungen können die digitale Transformation in der Forschung durch Information, den Aufbau von Kooperationen und die Qualifikation von Personal unterstützen. Ihre Einrichtung, dauerhafte Etablierung und Einbeziehung in die Arbeit des NFDI e.V. ist ein wichtiger Beitrag zur Schaffung einer nationalen Forschungsdateninfrastruktur.
Mit dem BMBF geförderten Verbundprojekt EcoDM (Förderkennzeichen 16DWWQP) wurde erforscht, welche Herausforderungen, Chancen und Hindernisse sich im Bereich des rasanten digitalen Datenwachstums ergeben und wie Rahmenbedingungen aussehen könnten, Daten systematisch und FAIR (Findable, Accessible, Interoperable, Reusable) nutzen und teilen zu können. Einen zentralen Teil der Untersuchung bildeten neben Landscape- und Gap-Analysen Leitfaden-gestützte Interviews mit Expert:innen aus den Bereichen Wissenschaft, Wirtschaft, Public Sector und Qualifikation. Basierend auf den Projektergebnissen wurden 31 bereichsübergreifende Empfehlungen zur Förderung des Teilens und Nachnutzens von Daten entwickelt, die in dieser Broschüre mit einem Begleitwort veröffentlicht werden.
Datenmanagementpläne bilden die Grundlage für einen verantwortungsvollen Umgang mit Forschungsdaten. Gerade (Fach)Hochschulen der Angewandten Wissenschaften stellt dies jedoch vor große Herausforderungen, da sie bislang auf wenig etablierte Strukturen, Standards und Best Practices aus den für sie charakteristischen praxisrelevanten Disziplinen und Kooperationen zurückgreifen können. Das Projekt SAN-DMP will genau in diesem Spannungsfeld ansetzen um die Bedarfe unterschiedlicher Stakeholdergruppen in Bezug auf Datenmanagementpläne (DMP) zu untersuchen. Durch qualitative Methoden sollen evidenzbasierte Umsetzungsszenarien und Handlungsempfehlungen für das Forschungsdatenmanagement entstehen, die auf die substanziellen Bedürfnisse dieses Hochschultyps zugeschnitten sind. Die Expert:innen der verschiedenen Hochschulen und die Forschungscommunity werden schon im Forschungsprozess miteingebunden und die Ergebnisse werden offen publiziert, um die Diskussion und den Wissensaustausch (oder -transfer) anzuregen. Der vorliegende Artikel beschreibt Ausgangslage und methodisches Vorgehen des Projekts.
Overview of the CLEF-2022 CheckThat! Lab on Fighting the COVID-19 Infodemic and Fake News Detection
(2022)
We describe the fifth edition of the CheckThat! lab, part of the 2022 Conference and Labs of the Evaluation Forum (CLEF). The lab evaluates technology supporting tasks related to factuality in multiple languages: Arabic, Bulgarian, Dutch, English, German, Spanish, and Turkish. Task 1 asks to identify relevant claims in tweets in terms of check-worthiness, verifiability, harmfullness, and attention-worthiness. Task 2 asks to detect previously fact-checked claims that could be relevant to fact-check a new claim. It targets both tweets and political debates/speeches. Task 3 asks to predict the veracity of the main claim in a news article. CheckThat! was the most popular lab at CLEF-2022 in terms of team registrations: 137 teams. More than one-third (37%) of them actually participated: 18, 7, and 26 teams submitted 210, 37, and 126 official runs for tasks 1, 2, and 3, respectively.
The fifth edition of the CheckThat! Lab is held as part of the 2022 Conference and Labs of the Evaluation Forum (CLEF). The lab evaluates technology supporting various factuality tasks in seven languages: Arabic, Bulgarian, Dutch, English, German, Spanish, and Turkish. Task 1 focuses on disinformation related to the ongoing COVID-19 infodemic and politics, and asks to predict whether a tweet is worth fact-checking, contains a verifiable factual claim, is harmful to the society, or is of interest to policy makers and why. Task 2 asks to retrieve claims that have been previously fact-checked and that could be useful to verify the claim in a tweet. Task 3 is to predict the veracity of a news article. Tasks 1 and 3 are classification problems, while Task 2 is a ranking one.
Citizen Social Science
(2019)