TY - JOUR A1 - Scheck, Ester A1 - Binn, Andrea A1 - Dörk, Marian A1 - Ledermann, Florian T1 - A Contemporary Nolli Map BT - Using OpenStreetMap Data to Represent Urban Public Spaces JF - Abstracts of the ICA N2 - 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. KW - OpenStreetMap KW - Öffentlicher Raum KW - Geoinformationssystem Y1 - 2023 U6 - https://doi.org/10.5194/ica-abs-6-223-2023 SN - 2570-2106 IS - 6 SP - 1 EP - 2 PB - Copernicus Publications CY - Göttingen ER - TY - CHAP A1 - Heisig, Peter ED - Bratianu, Constantin ED - Handzic, Meliha ED - Bolisani, Ettore T1 - Knowledge Management Essentials BT - Reflections on the Core of the Discipline and Future Outlook T2 - The Future of Knowledge Management N2 - 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. KW - Wissensmanagement KW - Künstliche Intelligenz Y1 - 2023 SN - 978-3-031-38696-1 U6 - https://doi.org/10.1007/978-3-031-38696-1_5 SN - 2199-8671 SP - 91 EP - 109 PB - Springer International Publishing CY - Cham ER - TY - JOUR A1 - Meier, Sebastian A1 - Bogucka, Edyta P. A1 - Ledermann, Florian A1 - Roth, Robert E. A1 - Słomska-Przech, Katarzyna A1 - Vörös, Fanni T1 - Opportunities and Challenges for the Next Generation of Cartographers JF - Abstracts of the ICA N2 - 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. KW - Kartograf KW - International Cartographic Association Y1 - 2023 U6 - https://doi.org/10.5194/ica-abs-6-162-2023 SN - 2570-2106 IS - 6 SP - 1 EP - 3 PB - Copernicus Publications CY - Göttingen ER - TY - JOUR A1 - Bludau, Mark-Jan A1 - Dörk, Marian A1 - Tominski, Christian T1 - Unfolding Edges BT - Adding Context to Edges in Multivariate Graph Visualization JF - Computer Graphics Forum N2 - 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. KW - Node-Link Diagram KW - Visualisierung KW - Computational Social Science Y1 - 2023 U6 - https://doi.org/10.1111/cgf.14831 SN - 0167-7055 VL - 42 IS - 3 SP - 297 EP - 309 PB - Wiley-Blackwell CY - Oxford ER - TY - CHAP A1 - Meier, Sebastian A1 - Glinka, Katrin ED - Stolze, Markus ED - Loch, Frieder ED - Baldauf, Matthias ED - Alt, Florian ED - Schneegass, Christina ED - Kosch, Thomas ED - Hirzle, Teresa ED - Sadeghian, Shadan ED - Draxler, Fiona ED - Bektas, Kenan ED - Lohan, Katrin ED - Knierim, Pascal T1 - To Classify is to Interpret BT - Building Taxonomies from Heterogeneous Data through Human-AI Collaboration T2 - Proceedings of Mensch und Computer 2023 N2 - 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. KW - Künstliche Intelligenz KW - Taxonomie KW - Maschinelles Lernen KW - Mensch-Maschine-Schnittstelle Y1 - 2023 SN - 979-8-4007-0771-1 U6 - https://doi.org/10.1145/3603555.3608532 SP - 395 EP - 401 PB - Association for Computing Machinery CY - New York ER - TY - JOUR A1 - Bruhn, Thomas A1 - Meier, Sebastian A1 - Lawrence, Mark G. T1 - Interactive network visualization on the integration of mindsets and sustainability : creating conditions for emergence through a relational narrative JF - Innovation : The European Journal of Social Science Research N2 - 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. KW - Stakeholder KW - Nachhaltigkeit KW - Transdisziplinarität KW - Visualisierung KW - Datenbank Y1 - 2022 U6 - https://doi.org/10.1080/13511610.2022.2101987 SN - 1351-1610 VL - 36 IS - 1 SP - 71 EP - 84 PB - Routledge, Taylor & Francis Group CY - London ER - TY - CHAP A1 - Meier, Sebastian T1 - Semi-automatic spatial classification of heterogeneous spatial open government data : use case of Germany T2 - Abstracts of the International Cartographic Association N2 - 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. KW - Open Government Data KW - Klassifikation KW - Ähnlichkeitssuche KW - Taxonomie KW - Automation Y1 - 2022 U6 - https://doi.org/10.5194/ica-abs-5-59-2022 SN - 2570-2106 PB - Copernicus Publications CY - Göttingen ER - TY - CHAP ED - Heisig, Peter T1 - Proceedings of the 17th International Conference on Knowledge Management BT - “Knowledge, Uncertainty and Risks: From individual to global scale” N2 - 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. KW - Wissensmanagement KW - Big Data KW - Information Engineering Y1 - 2022 UR - https://digital.library.unt.edu/ark:/67531/metadc2026753/ CY - Denton ER - TY - JOUR A1 - Rodighiero, Dario A1 - Derry, Lins A1 - Duhaime, Douglas A1 - Kruguer, Jordan A1 - Mueller, Maximilian C. A1 - Pietsch, Christopher A1 - Schnapp, Jeffrey T. A1 - Steward, Jeff T1 - Surprise machines : revealing Harvard Art Museums’ image collection JF - Information Design Journal N2 - 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. KW - Künstliche Intelligenz KW - Digitales Archiv KW - Museumskunde KW - Netzwerk KW - Visualisierung Y1 - 2022 U6 - https://doi.org/10.1075/idj.22013.rod SN - 1569-979X VL - 27 IS - 1 SP - 21 EP - 34 PB - John Benjamins Publishing Company CY - Amsterdam ER - TY - CHAP A1 - Morat, Paul A1 - Schwerdtfeger, Aaron A1 - Heidmann, Frank T1 - Nachtalb BT - A multisensory Neurofeedback VR-Interface T2 - Proceedings SIGGRAPH 2022 : Immersive Pavilion N2 - 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. KW - brain computer interfaces KW - extended reality KW - virtual reality KW - Gehirn-Computer-Schnittstelle KW - Virtuelle Realität KW - Neurofeedback Y1 - 2022 SN - 978-1-4503-9369-0 U6 - https://doi.org/10.1145/3532834.3536207 SP - 1 EP - 2 PB - Association for Computing Machinery CY - New York ER -