P337 - INFORMATIK 2023 - Designing Futures: Zukünfte gestalten
Auflistung P337 - INFORMATIK 2023 - Designing Futures: Zukünfte gestalten nach Erscheinungsdatum
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- KonferenzbeitragExtraction of Information from Invoices – Challenges in the Extraction Pipeline(INFORMATIK 2023 - Designing Futures: Zukünfte gestalten, 2023) Thiée, Lukas-Walter; Krieger, Felix; Funk, BurkhardtData from invoices are key information for business processes. In order to use the data and create business value, the information must be captured in a digital and structured form. Leveraging digital tools and AI/ML is state-of-the-art in the extraction of information from invoices. However, the existing approaches are trained on specific languages and layouts, and while focusing on the performance of individual metrics, they neglect the demonstration of the pipeline from raw data to processable information. In this paper, we investigate the types of information on invoices and address the challenges in the extraction pipeline. We contribute by providing a morphological framework for the problematization and design of a pipeline as part of a design science study.
- KonferenzbeitragPost Pandemic Follow-Up(INFORMATIK 2023 - Designing Futures: Zukünfte gestalten, 2023) Selzer, Annika; Timm, Ingo J.Now that we (hopefully) enter the post-pandemic era, we urgently need to cope with the lessons learned during the COVID-19-pandemic, e.g., that we are not ready to ensure a privacy- friendly sharing of data which could help to reduce the spread of contagious diseases in the future. This paper reflects on this challenge and proposes a way for the privacy-friendly sharing of data.
- KonferenzbeitragPerspektiven computergestützter harmonischer Analyse: Beethovens op. 14 Nr. 1 als Gegenstand gattungsübergreifender Korpusanalyse(INFORMATIK 2023 - Designing Futures: Zukünfte gestalten, 2023) Klauk, Stephanie; Kleinertz, Rainer; Schmolenzky, Pascal; Weiß, Christof; Müller, MeinardMit der zunehmenden Digitalisierung von Notentexten und Einspielungen vermehren sich die Möglichkeiten computergestützter Darstellungen und Analysen. Derartige harmonische Analyseverfahren sollen im Beitrag einem Fassungsvergleich des Kopfsatzes von Beethovens op. 14/1 zugrunde gelegt und mit traditionellen musikwissenschaftlichen Methoden abgeglichen werden. Die daraus abgeleiteten Hypothesen erweitern einerseits den Blick auf Beethovens Bearbeitungspraxis und lassen sich andererseits vom konkreten Fallbeispiel ‒ Klaviersonate versus Streichquartettfassung ‒ auf die entsprechenden Gattungen im Sinne von Korpusanalysen übertragen.
- KonferenzbeitragControlled Run-Time Adaptivity in Industrial Agent Systems - Challenges and Research Prospects(INFORMATIK 2023 - Designing Futures: Zukünfte gestalten, 2023) Sudeikat, Jan; Köhler-Bußmeier, MichaelDeveloping Cyber-physical Systems (CPS) inherently requires enabling run-time adaptivity. These systems integrate physical components, which operate in changeable contexts. In addition, objectives may change, due to socio-technical aspects. Industrial agents have been proposed for enhancing future industrial automation and control systems and integrating agents in industrial systems is an active field of research. Besides enabling technical compatibility of agent concepts and frameworks, the design and orchestration of agent activities have to be fine-tuned and a goal-directed adaption@run.time requires that the system can analyze its own structure at run-time; therefore, the system’s structure has to be reflected inside the system. Here, we outline current work and research challenges on how explicit organizational modeling can facilitate developing industrial agent systems. We discuss architectural aspects and outline how adaptations of organizations can be enabled, modeled and automated following the MAPE-K approach.
- KonferenzbeitragSIENA: Sprachmodellbasierte Identifikation und Extraktion von Nutzeranforderungen(INFORMATIK 2023 - Designing Futures: Zukünfte gestalten, 2023) Zwanzig, Dorian; Kahl, Anja; Dietrich, UteIn diesem Artikel wird eine innovative Methode zur Identifikation und Extraktion von Nutzeranforderungen aus natürlichsprachlichen Quellen präsentiert. Als Ausgangsbasis dient uns eine Fallstudie zur Entwicklung einer Fachanwendung für Physiotherapeuten. Die Methode nutzt OpenAI's Generative Pretrained Transformer (GPT) Modelle und deren Fähigkeit zur Verarbeitung natürlicher Sprache. Eine quantitative Analyse wurde durchgeführt, um die Wirksamkeit dieser Sprachmodelle bei der Anforderungsanalyse zu bewerten. Die Ergebnisse zeigen deutlich, dass die verwendeten GPT-Modelle eine effektive und kostengünstige Unterstützung bei der Anforderungsanalyse sein können.
- KonferenzbeitragData Spaces as Enablers for Sustainability(INFORMATIK 2023 - Designing Futures: Zukünfte gestalten, 2023) Hoppe, Christoph; Schmelzer, Robert; Möller, Frederik; Schoormann, ThorstenOne of our society's most fundamental challenges is promoting sustainable development. Data sharing across organizations is one way to spur innovation and address the Sustainable Development Goals (SDGs) through optimizing resource utilization, fostering circular supply chains, and producing accurate information about CO2 emissions. However, organizations often hesitate to share data given a range of concerns, including the fear of data misappropriation or the lack of control over what others do with their data. Data spaces as a novel artifact seek to tackle these issues by providing an integrated data management approach upholding data sovereignty. These spaces can boost sustainable development by being a secure and trusted digital infrastructure for organizations to share data for sustainable purposes. To disclose how this digital solution fosters sustainability, we present a set of 65 potentials of data spaces along with the dimensions of ecological, economic, and social sustainability.
- KonferenzbeitragSustainability in Artificial Intelligence - Towards a Green AI Reference Model(INFORMATIK 2023 - Designing Futures: Zukünfte gestalten, 2023) Weber, Sebastian; Guldner, Achim; Begic Fazlic, Lejla; Dartmann, Guido; Naumann, StefanThe interest in Green Artificial Intelligence (AI) is growing as AI research is increasingly focusing on and taking into account environmental sustainability. This paper aims to clarify and emphasize the distinction between terms like sustainable AI, Green AI, Green by AI, and Green in AI, highlighting their importance in the context of environmentally responsible AI practices. We find that existing Green Software reference models are insufficient for meeting the unique requirements of Green AI. Thus, we argue that a tailored Green AI reference model is needed to guide and promote environmentally responsible practices in the field of AI, addressing the special considerations associated with Green AI.
- KonferenzbeitragDeep Learning Datasets Challenges For Semantic Segmentation - A Survey(INFORMATIK 2023 - Designing Futures: Zukünfte gestalten, 2023) Ponciano, Claire; Schaffert, Markus; Ponciano, Jean-JacquesThis survey offers a comprehensive analysis of challenges encountered when employing large-scale datasets for deep learning-based semantic segmentation, an area with significant implica- tions for industries such as autonomous driving, precision agriculture, and medical imaging. Through a systematic review of 94 papers from Papers with Code, we identified 32 substantial challenges, which we categorized into six key areas: Data Quality and Quantity, Data Preprocessing, Resource Constraints, Data Management and Privacy, Generalization, and Data Compatibility. By identifying and explicating these challenges, our research provides a crucial reference point for future studies aiming to address these issues and enhance the performance of deep learning models for semantic segmentation. Future work will focus on leveraging AI and semantic technologies to provide solutions to these challenges.
- KonferenzbeitragDas Netz hat Geschichte(INFORMATIK 2023 - Designing Futures: Zukünfte gestalten, 2023) Franken, Jonas; Zivkovic, Marco; Thiessen, Nadja; Engels, Jens I.; Reuter, ChristianKritische Infrastrukturen sind häufig über Jahrzehnte gewachsene, komplexe Netze. Den- noch fehlt derzeit die historische Perspektive auf die Aufschichtungstendenzen von Technologien in den Sektoren, die für die Gesellschaft essenzielle Dienste bereitstellen. Ein besseres Verständnis von Ausbreitungs-, Ausbau-, Ersatz- und Ausmusterungsprozessen kann Entscheidungshilfe und Orientierung für resilientere Versorgungsnetzarchitekturen in der Zukunft geben. Kompatibilitäts- probleme mit Legacy-Soft- und Hardware sind bekannte Phänomene in vielen KRITIS-Einrichtun- gen. Entsprechend gewinnen Wissens- und Erfahrungstransfers bei zunehmend komplexen, dennoch über Jahrzehnte verwendete Technologien in landwirtschaftlichen Betrieben enorm an Bedeutung. Der Beitrag vollzieht die Konzeption und Fragestellungen eines interdisziplinären Forschungspro- jekts nach, in welchem die Verwundbarkeit der kritischen Infrastruktursektoren Verkehr und Kom- munikation im Rhein-Main-Gebiet analysiert wird. Von den Leistungen beider Sektoren hängt die digitale Landwirtschaft stark ab. Insbesondere rurale, beim digitalen und Schienennetzausbau häufig vernachlässigte Gebiete werden dabei mittels explorativer Interviewstudie und anschließender ar- chivbasierter, quantitativer Überprüfung der zuvor generierten Hypothesen aus einer raum-zeitli- chen und technischen Perspektive untersucht.
- KonferenzbeitragDesigning alternative future home stories(INFORMATIK 2023 - Designing Futures: Zukünfte gestalten, 2023) Haupt, Benedikt; Pentzold, Christian; Becker, Alexa; Berger, ArneUsually the smart home imaginaries portray nuclear families living in detached houses with a focus on efficiency and energy. In this workshop, we follow the co-design approach to imagine alternative future homes beyond this stereotype. First, we brainstorm the concept of home addressing idiosyncratic needs and expectations. Second, we try three co-design tool adaptations in small groups which allow us to collaboratively imagine speculative futures. LittleBoxes is a cultural probe variation with which participants can configure a speculative future by using inspirational and technological materials. The Tiles IoT Inventor Toolkit adaptation helps to tell detailed stories of how to possibly live with technology in the future. With the IoT Service Kit adaption participants are able to build speculative home scenarios and playfully explore imaginary future technologies within them. There will be two rounds of co-designing, so every participant will explore two of the toolkits. In the last part, we reflect on the experiences as well as discuss if and how participants could imagine adapting the introduced tools beyond the workshop.