[{"data":1,"prerenderedAt":185},["ShallowReactive",2],{"person:\u002Fpersons\u002Farnold-arz":3,"person-projects:arnold-arz":85},{"path":4,"personId":5,"name":6,"category":11,"external":12,"phone":13,"email":14,"room":15,"picture":16,"externalProfiles":17,"website":7,"publications":33,"projects":34,"address":38,"en":42},"\u002Fpersons\u002Farnold-arz","arnold-arz",{"leadingTitle":7,"suffixTitle":8,"first":9,"last":10},"","M.Sc.","Arnold","Arz von Straussenburg","Team member",false,"+49 261 287 - 2505","aarz@uni-koblenz.de","A129","\u002Fmedia\u002Fpeople\u002Farnold-arz\u002Fportrait.jpg",[18,21,24,27,30],{"title":19,"link":20},"Research Gate","https:\u002F\u002Fwww.researchgate.net\u002Fprofile\u002FArnold-Arz-Von-Straussenburg",{"title":22,"link":23},"LinkedIn","https:\u002F\u002Fwww.linkedin.com\u002Fin\u002Farnold-arz\u002F",{"title":25,"link":26},"Xing","https:\u002F\u002Fwww.xing.com\u002Fprofile\u002FArnold_ArzvonStraussenburg\u002Fcv",{"title":28,"link":29},"GitHub","https:\u002F\u002Fgithub.com\u002FArceoavs",{"title":31,"link":32},"Universität Koblenz","https:\u002F\u002Fwww.uni-koblenz.de\u002Fde\u002Finformatik\u002Fiwvi\u002Friehle\u002Fteam\u002Farnold-arz",{"bibtexUrl":7},[35,36,37],"ih-evrski","eg-das","sparci",{"street":39,"postcode":40,"city":41},"Universitätsstraße 1","D-56070","Koblenz",{"role":43,"about":44,"awards":84},"Doctoral Researcher",{"researchFoci":45,"education":51,"positions":63,"appointments":83},[46,47,48,49,50],"Internet-of-Things (IoT)","Generative AI","Design Science Research (DSR)","Information Systems (IS)","Large Language Models (LLMs)",[52,56,60],{"startDate":53,"endDate":54,"description":55},"09\u002F2021","02\u002F2022","Semester Abroad at Tunghai University (東海大學), Taiwan",{"startDate":57,"endDate":58,"description":59},"10\u002F2019","06\u002F2022","Master Studies in Information Systems at the University of Münster",{"startDate":61,"endDate":57,"description":62},"10\u002F2016","Bachelor Studies in Information Systems at the University of Münster",[64,68,72,76,79],{"startDate":65,"endDate":66,"description":67},"07\u002F2021","present","Student Assistant at University of Koblenz-Landau, Chair for Information Systems and Smart Data",{"startDate":69,"endDate":70,"description":71},"12\u002F2019","06\u002F2021","Student Assistant at University of Münster, Chair for Information Systems and Information Management",{"startDate":73,"endDate":74,"description":75},"05\u002F2018","05\u002F2021","Member of the Board, Symposium Oeconomicum Münster e.V.",{"startDate":77,"endDate":57,"description":78},"05\u002F2019","Working Student at finklyn GmbH",{"startDate":80,"endDate":81,"description":82},"10\u002F2018","04\u002F2019","Software Engineering Tutor at University of Münster, Chair for Software Development and Verification",[],[],[86,124,151],{"id":87,"title":88,"body":89,"description":95,"extension":102,"meta":103,"metadata":104,"navigation":117,"path":118,"projectId":36,"projectStatus":119,"seo":120,"stem":121,"url":122,"__hash__":123},"projects\u002Fprojects\u002Feg-das.md","Entwicklung von Geschäftsmodellen für nachhaltige Datentreuhandplattformen mit offenen Architekturen und Schnittstellen, unter Beibehaltung der Datenhoheit für kleine und mittelständische Unternehmen",{"type":90,"value":91,"toc":99},"minimark",[92,96],[93,94,95],"p",{},"EG-DAS is a pioneering initiative aimed at developing sustainable business models for data trusteeship platforms with open architectures and interfaces. The project's core objective is to enable small and medium-sized enterprises (SMEs) to effectively and securely manage their data while maintaining data sovereignty. By incorporating cutting-edge technologies such as cloud infrastructure, IoT, and AI, EG-DAS provides a platform that not only simplifies data management but also fosters innovative business models and collaborations. The project is structured around six key components, including a business model for platform operators, a reference architecture, a detailed roles and rights concept, data governance mechanisms, a best-practice guide for trust management, and a catalog of best practices for process integration.",[93,97,98],{},"The initiative is particularly focused on ensuring that SMEs can navigate the challenges of a data-driven world. EG-DAS emphasizes the importance of data sovereignty, ensuring that data owners retain control over their data. This approach is crucial in today’s digital landscape, where data security and privacy are of paramount importance. Through EG-DAS, SMEs are equipped with the tools and knowledge required for efficient, secure, and sovereign data management, thereby enhancing their competitiveness in a rapidly evolving digital economy.",{"title":7,"searchDepth":100,"depth":100,"links":101},2,[],"md",{},[105,108,111,114],{"name":106,"value":107},"Project Time","01.10.2023 - 01.03.2026",{"name":109,"value":110},"Funding Source","Federal Ministry of Research, Technology and Space of Germany",{"name":112,"value":113},"Project Number","16DTM218",{"name":115,"value":116},"Keywords","IoT, data trusteeship",true,"\u002Fprojects\u002Feg-das","definitely finished",{"title":88,"description":95},"projects\u002Feg-das",null,"3pZxsyVLF58sCPoDoGwgLyt81t_AoHewjz48Mgf1KXQ",{"id":125,"title":126,"body":127,"description":131,"extension":102,"meta":140,"metadata":141,"navigation":117,"path":147,"projectId":35,"projectStatus":119,"seo":148,"stem":149,"url":122,"__hash__":150},"projects\u002Fprojects\u002Fih-evrski.md","Interdisziplinärer Hub zur Vermittlung von Kompetenzen in Entwicklung, Umgang und Anwendung von erklärbaren, vertrauenswürdigen, resilienten und sicheren KI-Verfahren (IH-evrsKI)",{"type":90,"value":128,"toc":138},[129,132,135],[93,130,131],{},"Artificial Intelligence (AI) is becoming increasingly prevalent in all areas of life. In the near future, AI will play a significant role in many industries. With an understanding of AI, individuals are in a position to understand and critically evaluate how AI will impact their private and professional lives in the future.",[93,133,134],{},"The project \"Interdisziplinärer Hub zur Vermittlung von Kompetenzen in Entwicklung, Umgang und Anwendung von erklärbaren, vertrauenswürdigen, resilienten und sicheren KI-Verfahren (IH-evrsKI)\" is an interdisciplinary research project funded by the Federal Ministry of Education and Research (BMBF). The project aims at teaching aspects of explainable, trustworthy, resilient, and secure Artificial Intelligence (AI) in a sustainable way to students of different disciplines.",[93,136,137],{},"With an interdisciplinary research group, which includes researchers from all departments of the University of Koblenz, teaching and learning concepts are developed, which enable students to approach AI from different perspectives. In addition to regarding AI as a measure for solving complex data-related problems, vulnerabilities and security issues of AI are discussed to address the explainability and trustworthiness of these methods. Additionally, social and psychological issues along with legal aspects must be considered. As such, the project aims to provide students with a broad range of competencies that are essential for understanding, critically discussing, and developing AI technologies.",{"title":7,"searchDepth":100,"depth":100,"links":139},[],{},[142,144,145],{"name":106,"value":143},"01.12.2021 - 30.11.2025",{"name":109,"value":110},{"name":112,"value":146},"16DHBKI039","\u002Fprojects\u002Fih-evrski",{"title":126,"description":131},"projects\u002Fih-evrski","hwY6vvuadeosph0nhCQXBUX_ym0_k6pl2cs9PTkGyFU",{"id":152,"title":153,"body":154,"description":158,"extension":102,"meta":170,"metadata":171,"navigation":117,"path":181,"projectId":37,"projectStatus":119,"seo":182,"stem":183,"url":176,"__hash__":184},"projects\u002Fprojects\u002Fsparci.md","Socio-Physical Advanced Research Cloud Infrastructure\" (SPARCI)",{"type":90,"value":155,"toc":168},[156,159,162,165],[93,157,158],{},"The \"Socio-Physical Advanced Research Cloud Infrastructure\" (SPARCI) is a DFG-co-funded large-scale equipment (DFG: Großgerät) that provides a powerful computer cluster with a connected long-range wide-area network infrastructure (LoRaWAN infrastructure) for researchers and lecturers. The high-performance infrastructure is the basis for extensive research projects involving the mining, storage, analysis, and use of large amounts of data (Big Data) in sociotechnical (human-machine) and cyber-physical (mechanical and electronic things) systems. Data sources and data recipients are derived from research on information systems in enterprises, public administration, and the public World Wide Web. The project pushes into new areas of intelligent linking of real and physical objects with their virtual environment and their use in the aforementioned domains.",[93,160,161],{},"The envisioned research has very high computational power and storage capacity requirements for exploring growing datasets and executing artificial intelligence and machine learning methods. In particular, the development of deep learning algorithms and neural networks are leading to a new need for GPU-based computing power that can reduce the computation time required to process existing and growing datasets to a usable level and which is provided by the equipment.",[93,163,164],{},"To collect sensor data, the large-scale device includes a LoRaWAN infrastructure that will be both stationary on the university campus and usable in off-campus research projects. This infrastructure enables wireless, energy-efficient, bidirectional transmission of, for example, sensor data over distances of several kilometers and also allows geolocation of transmitters using multilateration and time-difference-of-arrival methods via the arrival times of data packets at multiple receiving devices.",[93,166,167],{},"The research groups involved have extensive prior experience in machine learning, innovative approaches to Web Science, collaboration systems, Internet of Things and IT concepts in public administration. The specific combination of specialisations of the involved research groups enables the necessary interdisciplinary, holistic approach. To maintain compliance aspects, the project will develop a concept for storing large amounts of heterogeneous sensor data, taking into account aspects related to data protection, data security, and privacy of individuals.",{"title":7,"searchDepth":100,"depth":100,"links":169},[],{},[172,174,177,179],{"name":106,"value":173},"28.10.2019- 31.07.2025",{"name":175,"value":176,"url":176},"Website","https:\u002F\u002Fwww.uni-koblenz-landau.de\u002Fen\u002Fcampus-koblenz\u002Ffb4\u002Fiwvi\u002Fsparci",{"name":112,"value":178},"01FS14030",{"name":109,"value":180},"DFG and University of Koblenz-Landau","\u002Fprojects\u002Fsparci",{"title":153,"description":158},"projects\u002Fsparci","GciQEQ0PxDGBREDfQLCEYAdsbtiaEIZovyAjpT304iw",1782386010515]