[{"language":[{"iso":"eng"}],"keyword":["static analysis","data collection","data protection","privacy-aware reporting"],"user_id":"88024","department":[{"_id":"76"}],"_id":"64823","external_id":{"arxiv":["2601.20459"]},"status":"public","abstract":[{"text":"Current legal frameworks enforce that Android developers accurately report the data their apps collect. However, large codebases can make this reporting challenging. This paper employs an empirical approach to understand developers' experience with Google Play Store's Data Safety Section (DSS) form.\r\n\r\nWe first survey 41 Android developers to understand how they categorize privacy-related data into DSS categories and how confident they feel when completing the DSS form. To gain a broader and more detailed view of the challenges developers encounter during the process, we complement the survey with an analysis of 172 online developer discussions, capturing the perspectives of 642 additional developers. Together, these two data sources represent insights from 683 developers.\r\n\r\nOur findings reveal that developers often manually classify the privacy-related data their apps collect into the data categories defined by Google-or, in some cases, omit classification entirely-and rely heavily on existing online resources when completing the form. Moreover, developers are generally confident in recognizing the data their apps collect, yet they lack confidence in translating this knowledge into DSS-compliant disclosures. Key challenges include issues in identifying privacy-relevant data to complete the form, limited understanding of the form, and concerns about app rejection due to discrepancies with Google's privacy requirements.\r\nThese results underscore the need for clearer guidance and more accessible tooling to support developers in meeting privacy-aware reporting obligations. ","lang":"eng"}],"type":"conference","publication":"Proceedings of the IEEE/ACM 13th International Conference on Mobile Software Engineering and Systems (MOBILESoft '26). Association for Computing Machinery, New York, NY, USA, 65–68.","conference":{"start_date":"2026-04-12","name":"13th International Conference on Mobile Software Engineering and Systems 2024","location":"Rio de Janeiro, Brazil","end_date":"2026-04-18"},"title":"Challenges in Android Data Disclosure: An Empirical Study.","author":[{"first_name":"Mugdha","last_name":"Khedkar","id":"88024","full_name":"Khedkar, Mugdha"},{"id":"32312","full_name":"Schlichtig, Michael","orcid":"0000-0001-6600-6171","last_name":"Schlichtig","first_name":"Michael"},{"full_name":"Soliman, Mohamed Aboubakr Mohamed","id":"102489","last_name":"Soliman","first_name":"Mohamed Aboubakr Mohamed"},{"first_name":"Eric","orcid":"0000-0003-3470-3647","last_name":"Bodden","id":"59256","full_name":"Bodden, Eric"}],"date_created":"2026-03-04T08:10:43Z","date_updated":"2026-03-13T12:10:10Z","citation":{"ama":"Khedkar M, Schlichtig M, Soliman MAM, Bodden E. Challenges in Android Data Disclosure: An Empirical Study. In: <i>Proceedings of the IEEE/ACM 13th International Conference on Mobile Software Engineering and Systems (MOBILESoft ’26). Association for Computing Machinery, New York, NY, USA, 65–68.</i> ; 2026.","ieee":"M. Khedkar, M. Schlichtig, M. A. M. Soliman, and E. Bodden, “Challenges in Android Data Disclosure: An Empirical Study.,” presented at the 13th International Conference on Mobile Software Engineering and Systems 2024, Rio de Janeiro, Brazil, 2026.","chicago":"Khedkar, Mugdha, Michael Schlichtig, Mohamed Aboubakr Mohamed Soliman, and Eric Bodden. “Challenges in Android Data Disclosure: An Empirical Study.” In <i>Proceedings of the IEEE/ACM 13th International Conference on Mobile Software Engineering and Systems (MOBILESoft ’26). Association for Computing Machinery, New York, NY, USA, 65–68.</i>, 2026.","apa":"Khedkar, M., Schlichtig, M., Soliman, M. A. M., &#38; Bodden, E. (2026). Challenges in Android Data Disclosure: An Empirical Study. <i>Proceedings of the IEEE/ACM 13th International Conference on Mobile Software Engineering and Systems (MOBILESoft ’26). Association for Computing Machinery, New York, NY, USA, 65–68.</i> 13th International Conference on Mobile Software Engineering and Systems 2024, Rio de Janeiro, Brazil.","short":"M. Khedkar, M. Schlichtig, M.A.M. Soliman, E. Bodden, in: Proceedings of the IEEE/ACM 13th International Conference on Mobile Software Engineering and Systems (MOBILESoft ’26). Association for Computing Machinery, New York, NY, USA, 65–68., 2026.","bibtex":"@inproceedings{Khedkar_Schlichtig_Soliman_Bodden_2026, title={Challenges in Android Data Disclosure: An Empirical Study.}, booktitle={Proceedings of the IEEE/ACM 13th International Conference on Mobile Software Engineering and Systems (MOBILESoft ’26). Association for Computing Machinery, New York, NY, USA, 65–68.}, author={Khedkar, Mugdha and Schlichtig, Michael and Soliman, Mohamed Aboubakr Mohamed and Bodden, Eric}, year={2026} }","mla":"Khedkar, Mugdha, et al. “Challenges in Android Data Disclosure: An Empirical Study.” <i>Proceedings of the IEEE/ACM 13th International Conference on Mobile Software Engineering and Systems (MOBILESoft ’26). Association for Computing Machinery, New York, NY, USA, 65–68.</i>, 2026."},"year":"2026"},{"language":[{"iso":"eng"}],"keyword":["Industry 4.0","Taxonomy","Data spaces","Characterization"],"publication":"Lecture Notes in Business Information Processing","abstract":[{"lang":"eng","text":"Data spaces are receiving an emerging interest in Information Systems Research and industry practice. They are central to many European research initiatives and shape the data economy in Industry 4.0. Generally, they aim to create secure environments for cross-organizational data management and sharing. Currently, there is considerable interest in developing new data spaces in Industry 4.0, also accelerated through regulatory changes. However, key questions about what precisely characterizes a data space in Industry 4.0 remain unresolved. Against this backdrop, we build a taxonomy of data spaces in the Industry 4.0 context. We identified nine distinctive dimensions and 40 corresponding characteristics among the 19 data spaces analyzed. The taxonomy enables clearer classification and nomenclature of data spaces in this context. This short paper will ignite planned further research on data spaces in Industry 4.0 and contribute to a conceptualization of a taxonomic theory for interested researchers."}],"date_created":"2026-01-27T11:56:10Z","publisher":"Springer Nature Switzerland","title":"What Characterizes Data Spaces in Industry 4.0? Towards a Better Understanding","quality_controlled":"1","year":"2026","department":[{"_id":"563"}],"user_id":"51711","_id":"63754","type":"conference","status":"public","author":[{"first_name":"Oliver","last_name":"Werth","full_name":"Werth, Oliver"},{"last_name":"Koldewey","orcid":"https://orcid.org/0000-0001-7992-6399","id":"43136","full_name":"Koldewey, Christian","first_name":"Christian"},{"first_name":"Mathias","full_name":"Uslar, Mathias","last_name":"Uslar"},{"first_name":"Julian","full_name":"Zerbin, Julian","id":"51711","last_name":"Zerbin"}],"date_updated":"2026-03-18T07:12:49Z","doi":"10.1007/978-3-032-14518-5_3","conference":{"location":"Stuttgart, Germany","end_date":"2025-11-26","start_date":"2025-11-24","name":"16th International Conference on Software Business (ICSOB 2025)"},"publication_identifier":{"isbn":["9783032145178","9783032145185"],"issn":["1865-1348","1865-1356"]},"publication_status":"published","citation":{"apa":"Werth, O., Koldewey, C., Uslar, M., &#38; Zerbin, J. (2026). What Characterizes Data Spaces in Industry 4.0? Towards a Better Understanding. <i>Lecture Notes in Business Information Processing</i>. 16th International Conference on Software Business (ICSOB 2025), Stuttgart, Germany. <a href=\"https://doi.org/10.1007/978-3-032-14518-5_3\">https://doi.org/10.1007/978-3-032-14518-5_3</a>","bibtex":"@inproceedings{Werth_Koldewey_Uslar_Zerbin_2026, place={Cham}, title={What Characterizes Data Spaces in Industry 4.0? Towards a Better Understanding}, DOI={<a href=\"https://doi.org/10.1007/978-3-032-14518-5_3\">10.1007/978-3-032-14518-5_3</a>}, booktitle={Lecture Notes in Business Information Processing}, publisher={Springer Nature Switzerland}, author={Werth, Oliver and Koldewey, Christian and Uslar, Mathias and Zerbin, Julian}, year={2026} }","mla":"Werth, Oliver, et al. “What Characterizes Data Spaces in Industry 4.0? Towards a Better Understanding.” <i>Lecture Notes in Business Information Processing</i>, Springer Nature Switzerland, 2026, doi:<a href=\"https://doi.org/10.1007/978-3-032-14518-5_3\">10.1007/978-3-032-14518-5_3</a>.","short":"O. Werth, C. Koldewey, M. Uslar, J. Zerbin, in: Lecture Notes in Business Information Processing, Springer Nature Switzerland, Cham, 2026.","ama":"Werth O, Koldewey C, Uslar M, Zerbin J. What Characterizes Data Spaces in Industry 4.0? Towards a Better Understanding. In: <i>Lecture Notes in Business Information Processing</i>. Springer Nature Switzerland; 2026. doi:<a href=\"https://doi.org/10.1007/978-3-032-14518-5_3\">10.1007/978-3-032-14518-5_3</a>","chicago":"Werth, Oliver, Christian Koldewey, Mathias Uslar, and Julian Zerbin. “What Characterizes Data Spaces in Industry 4.0? Towards a Better Understanding.” In <i>Lecture Notes in Business Information Processing</i>. Cham: Springer Nature Switzerland, 2026. <a href=\"https://doi.org/10.1007/978-3-032-14518-5_3\">https://doi.org/10.1007/978-3-032-14518-5_3</a>.","ieee":"O. Werth, C. Koldewey, M. Uslar, and J. Zerbin, “What Characterizes Data Spaces in Industry 4.0? Towards a Better Understanding,” presented at the 16th International Conference on Software Business (ICSOB 2025), Stuttgart, Germany, 2026, doi: <a href=\"https://doi.org/10.1007/978-3-032-14518-5_3\">10.1007/978-3-032-14518-5_3</a>."},"place":"Cham"},{"abstract":[{"text":"This study proposes a fault diagnostics methodology that addresses the challenges posed by highly imbalanced datasets typical of railway applications, where faulty conditions constitute the minority class. Fault diagnostics is performed from the component level upward, considering each sensor’s proximity to its respective critical component. Advanced signal analysis, feature engineering, and automated data-driven model generation techniques were explored to achieve comprehensive diagnostics, such that the model development process accounts for variations in the operating conditions and differing levels of information availability. The proposed methodology is evaluated on datasets from the MONOCAB, for scenarios with limited faulty instances and on the Beijing 2024 IEEE PHM Conference data challenge, which focused on fault diagnostics of railway systems under various fault modes and operating conditions.","lang":"eng"}],"status":"public","type":"conference","publication":"PHM Society Asia-Pacific Conference","article_number":"1","keyword":["MONOCAB","Beijing Data Challenge","Diagnostics of railway systems"],"language":[{"iso":"eng"}],"project":[{"_id":"1355","name":"enableATO – Automatisierter Bahnverkehr als Backbone für eine nachhaltige, vernetzte Mobilität im ländlichen Raum"}],"_id":"64787","user_id":"9557","department":[{"_id":"151"}],"year":"2025","citation":{"ieee":"O. K. Aimiyekagbon, A. Löwen, R. Hanselle, T. Rief, M. Beck, and W. Sextro, “Multilevel fault diagnostics for railway applications using limited historical data,” in <i>PHM Society Asia-Pacific Conference</i>, 2025, vol. 5, doi: <a href=\"https://doi.org/10.36001/phmap.2025.v5i1.4449\">10.36001/phmap.2025.v5i1.4449</a>.","chicago":"Aimiyekagbon, Osarenren Kennedy, Alexander Löwen, Raphael Hanselle, Thomas Rief, Maximilian Beck, and Walter Sextro. “Multilevel Fault Diagnostics for Railway Applications Using Limited Historical Data.” In <i>PHM Society Asia-Pacific Conference</i>, Vol. 5, 2025. <a href=\"https://doi.org/10.36001/phmap.2025.v5i1.4449\">https://doi.org/10.36001/phmap.2025.v5i1.4449</a>.","bibtex":"@inproceedings{Aimiyekagbon_Löwen_Hanselle_Rief_Beck_Sextro_2025, title={Multilevel fault diagnostics for railway applications using limited historical data}, volume={5}, DOI={<a href=\"https://doi.org/10.36001/phmap.2025.v5i1.4449\">10.36001/phmap.2025.v5i1.4449</a>}, number={1}, booktitle={PHM Society Asia-Pacific Conference}, author={Aimiyekagbon, Osarenren Kennedy and Löwen, Alexander and Hanselle, Raphael and Rief, Thomas and Beck, Maximilian and Sextro, Walter}, year={2025} }","short":"O.K. Aimiyekagbon, A. Löwen, R. Hanselle, T. Rief, M. Beck, W. Sextro, in: PHM Society Asia-Pacific Conference, 2025.","mla":"Aimiyekagbon, Osarenren Kennedy, et al. “Multilevel Fault Diagnostics for Railway Applications Using Limited Historical Data.” <i>PHM Society Asia-Pacific Conference</i>, vol. 5, 1, 2025, doi:<a href=\"https://doi.org/10.36001/phmap.2025.v5i1.4449\">10.36001/phmap.2025.v5i1.4449</a>.","apa":"Aimiyekagbon, O. K., Löwen, A., Hanselle, R., Rief, T., Beck, M., &#38; Sextro, W. (2025). Multilevel fault diagnostics for railway applications using limited historical data. <i>PHM Society Asia-Pacific Conference</i>, <i>5</i>, Article 1. <a href=\"https://doi.org/10.36001/phmap.2025.v5i1.4449\">https://doi.org/10.36001/phmap.2025.v5i1.4449</a>","ama":"Aimiyekagbon OK, Löwen A, Hanselle R, Rief T, Beck M, Sextro W. Multilevel fault diagnostics for railway applications using limited historical data. In: <i>PHM Society Asia-Pacific Conference</i>. Vol 5. ; 2025. doi:<a href=\"https://doi.org/10.36001/phmap.2025.v5i1.4449\">10.36001/phmap.2025.v5i1.4449</a>"},"intvolume":"         5","publication_status":"published","quality_controlled":"1","title":"Multilevel fault diagnostics for railway applications using limited historical data","doi":"10.36001/phmap.2025.v5i1.4449","date_updated":"2026-02-27T20:46:44Z","author":[{"last_name":"Aimiyekagbon","full_name":"Aimiyekagbon, Osarenren Kennedy","id":"9557","first_name":"Osarenren Kennedy"},{"last_name":"Löwen","full_name":"Löwen, Alexander","id":"47233","first_name":"Alexander"},{"full_name":"Hanselle, Raphael","last_name":"Hanselle","first_name":"Raphael"},{"first_name":"Thomas","full_name":"Rief, Thomas","last_name":"Rief"},{"full_name":"Beck, Maximilian","last_name":"Beck","first_name":"Maximilian"},{"id":"21220","full_name":"Sextro, Walter","last_name":"Sextro","first_name":"Walter"}],"date_created":"2026-02-27T20:41:54Z","volume":5},{"doi":"10.30844/i4sd.25.1.18","main_file_link":[{"open_access":"1"}],"date_updated":"2025-02-15T09:40:52Z","oa":"1","volume":2025,"author":[{"first_name":"Iris","last_name":"Gräßler","orcid":"0000-0001-5765-971X","id":"47565","full_name":"Gräßler, Iris"},{"first_name":"Jens","orcid":"http://orcid.org/0000-0001-8778-2989","last_name":"Pottebaum","full_name":"Pottebaum, Jens","id":"405"},{"first_name":"Peter","full_name":"Nyhuis, Peter","last_name":"Nyhuis"},{"last_name":"Stark","full_name":"Stark, Rainer","first_name":"Rainer"},{"first_name":"Klaus-Dieter","full_name":"Thoben, Klaus-Dieter","last_name":"Thoben"},{"first_name":"Petra","last_name":"Wiederkehr","full_name":"Wiederkehr, Petra"}],"intvolume":"      2025","citation":{"mla":"Gräßler, Iris, et al. “Hybrid Decision Support in Product Creation - Improving Performance with Data Science and Artificial Intelligence.” <i>Industry 4.0 Science</i>, vol. 2025, no. 1, GITO mbH Verlag, 2025, doi:<a href=\"https://doi.org/10.30844/i4sd.25.1.18\">10.30844/i4sd.25.1.18</a>.","short":"I. Gräßler, J. Pottebaum, P. Nyhuis, R. Stark, K.-D. Thoben, P. Wiederkehr, Industry 4.0 Science 2025 (2025).","bibtex":"@article{Gräßler_Pottebaum_Nyhuis_Stark_Thoben_Wiederkehr_2025, title={Hybrid Decision Support in Product Creation - Improving performance with data science and artificial intelligence}, volume={2025}, DOI={<a href=\"https://doi.org/10.30844/i4sd.25.1.18\">10.30844/i4sd.25.1.18</a>}, number={1}, journal={Industry 4.0 Science}, publisher={GITO mbH Verlag}, author={Gräßler, Iris and Pottebaum, Jens and Nyhuis, Peter and Stark, Rainer and Thoben, Klaus-Dieter and Wiederkehr, Petra}, year={2025} }","apa":"Gräßler, I., Pottebaum, J., Nyhuis, P., Stark, R., Thoben, K.-D., &#38; Wiederkehr, P. (2025). Hybrid Decision Support in Product Creation - Improving performance with data science and artificial intelligence. <i>Industry 4.0 Science</i>, <i>2025</i>(1). <a href=\"https://doi.org/10.30844/i4sd.25.1.18\">https://doi.org/10.30844/i4sd.25.1.18</a>","chicago":"Gräßler, Iris, Jens Pottebaum, Peter Nyhuis, Rainer Stark, Klaus-Dieter Thoben, and Petra Wiederkehr. “Hybrid Decision Support in Product Creation - Improving Performance with Data Science and Artificial Intelligence.” <i>Industry 4.0 Science</i> 2025, no. 1 (2025). <a href=\"https://doi.org/10.30844/i4sd.25.1.18\">https://doi.org/10.30844/i4sd.25.1.18</a>.","ieee":"I. Gräßler, J. Pottebaum, P. Nyhuis, R. Stark, K.-D. Thoben, and P. Wiederkehr, “Hybrid Decision Support in Product Creation - Improving performance with data science and artificial intelligence,” <i>Industry 4.0 Science</i>, vol. 2025, no. 1, 2025, doi: <a href=\"https://doi.org/10.30844/i4sd.25.1.18\">10.30844/i4sd.25.1.18</a>.","ama":"Gräßler I, Pottebaum J, Nyhuis P, Stark R, Thoben K-D, Wiederkehr P. Hybrid Decision Support in Product Creation - Improving performance with data science and artificial intelligence. <i>Industry 40 Science</i>. 2025;2025(1). doi:<a href=\"https://doi.org/10.30844/i4sd.25.1.18\">10.30844/i4sd.25.1.18</a>"},"publication_identifier":{"issn":["2942-6170"]},"publication_status":"published","article_type":"original","alternative_title":["Hybride Entscheidungsunterstützung in der Produktentstehung - Mit Data Science und Künstlicher Intelligenz die Leistungsfähigkeit erhöhen"],"_id":"58650","department":[{"_id":"152"}],"user_id":"405","status":"public","type":"journal_article","title":"Hybrid Decision Support in Product Creation - Improving performance with data science and artificial intelligence","publisher":"GITO mbH Verlag","date_created":"2025-02-15T09:31:30Z","year":"2025","quality_controlled":"1","issue":"1","keyword":["AI","artificial intelligence","Data Science","decision support","extreme data","Künstliche Intelligenz","product creation","product development"],"language":[{"iso":"eng"}],"abstract":[{"text":"Technical systems are characterized by increasing interdisciplinarity, complexity and networking. A product and its corresponding production systems require interdisciplinary multi-objective optimization. Sustainability and recyclability demands increase said complexity. The efficiency of previously established engineering methods is reaching its limits, which can only be overcome by systematic integration of extreme data. The aim of \"hybrid decision support\" is as follows: Data science and artificial intelligence should be used to supplement human capabilities in conjunction with existing heuristics, methods, modeling and simulation to increase the efficiency of product creation.","lang":"eng"}],"publication":"Industry 4.0 Science"},{"year":"2025","quality_controlled":"1","title":"Towards Practicable Algorithms for Rewriting Graph Queries Beyond DL-Lite","publisher":"Springer Nature Switzerland","date_created":"2025-07-02T11:46:06Z","abstract":[{"text":"Despite the advantages that the virtual knowledge graph paradigm has brought to many application domains, state-of-the-art systems still do not support popular graph database management systems like Neo4j. Their query rewriting algorithms focus on languages like conjunctive queries and their unions, which were developed for relational data and are poorly suited for graph data. Moreover, they also limit the expressiveness of the ontology languages that admit rewritings, restricting them to those that enjoy the so-called FO-rewritability property. Rewritings have thus focused on the DL-Lite family of Description Logics. In this paper, we propose a technique for rewriting a family of navigational queries for a suitably tailored fragment of ELHI. Leveraging navigational features in the target query language, we can include some widely-used axiom shapes not supported by DL-Lite. We implemented a proof-of-concept prototype that rewrites into Cypher queries, and tested it on a real-world cognitive neuroscience use case with promising results.","lang":"eng"}],"publication":"The Semantic Web - 22nd European Semantic Web Conference, {ESWC} 2025, Portoroz, Slovenia, June 1-5, 2025, Proceedings, Part {I}","keyword":["Ontology-based Data Access","Property Graphs","Navigational Queries"],"language":[{"iso":"eng"}],"citation":{"short":"B. Löhnert, N. Augsten, C. Okulmus, M. Ortiz, in: The Semantic Web - 22nd European Semantic Web Conference, {ESWC} 2025, Portoroz, Slovenia, June 1-5, 2025, Proceedings, Part {I}, Springer Nature Switzerland, 2025, pp. 342--361.","mla":"Löhnert, Bianca, et al. “Towards Practicable Algorithms for Rewriting Graph Queries Beyond DL-Lite.” <i>The Semantic Web - 22nd European Semantic Web Conference, {ESWC} 2025, Portoroz, Slovenia, June 1-5, 2025, Proceedings, Part {I}</i>, vol. 15718, Springer Nature Switzerland, 2025, pp. 342--361, doi:<a href=\"https://doi.org/10.1007/978-3-031-94575-5_19\">10.1007/978-3-031-94575-5_19</a>.","bibtex":"@inproceedings{Löhnert_Augsten_Okulmus_Ortiz_2025, series={Lecture Notes in Computer Science}, title={Towards Practicable Algorithms for Rewriting Graph Queries Beyond DL-Lite}, volume={15718}, DOI={<a href=\"https://doi.org/10.1007/978-3-031-94575-5_19\">10.1007/978-3-031-94575-5_19</a>}, booktitle={The Semantic Web - 22nd European Semantic Web Conference, {ESWC} 2025, Portoroz, Slovenia, June 1-5, 2025, Proceedings, Part {I}}, publisher={Springer Nature Switzerland}, author={Löhnert, Bianca and Augsten, Nikolaus and Okulmus, Cem and Ortiz, Magdalena}, year={2025}, pages={342--361}, collection={Lecture Notes in Computer Science} }","apa":"Löhnert, B., Augsten, N., Okulmus, C., &#38; Ortiz, M. (2025). Towards Practicable Algorithms for Rewriting Graph Queries Beyond DL-Lite. <i>The Semantic Web - 22nd European Semantic Web Conference, {ESWC} 2025, Portoroz, Slovenia, June 1-5, 2025, Proceedings, Part {I}</i>, <i>15718</i>, 342--361. <a href=\"https://doi.org/10.1007/978-3-031-94575-5_19\">https://doi.org/10.1007/978-3-031-94575-5_19</a>","ama":"Löhnert B, Augsten N, Okulmus C, Ortiz M. Towards Practicable Algorithms for Rewriting Graph Queries Beyond DL-Lite. In: <i>The Semantic Web - 22nd European Semantic Web Conference, {ESWC} 2025, Portoroz, Slovenia, June 1-5, 2025, Proceedings, Part {I}</i>. Vol 15718. Lecture Notes in Computer Science. Springer Nature Switzerland; 2025:342--361. doi:<a href=\"https://doi.org/10.1007/978-3-031-94575-5_19\">10.1007/978-3-031-94575-5_19</a>","ieee":"B. Löhnert, N. Augsten, C. Okulmus, and M. Ortiz, “Towards Practicable Algorithms for Rewriting Graph Queries Beyond DL-Lite,” in <i>The Semantic Web - 22nd European Semantic Web Conference, {ESWC} 2025, Portoroz, Slovenia, June 1-5, 2025, Proceedings, Part {I}</i>, Portorož, Slovenia, 2025, vol. 15718, pp. 342--361, doi: <a href=\"https://doi.org/10.1007/978-3-031-94575-5_19\">10.1007/978-3-031-94575-5_19</a>.","chicago":"Löhnert, Bianca, Nikolaus Augsten, Cem Okulmus, and Magdalena Ortiz. “Towards Practicable Algorithms for Rewriting Graph Queries Beyond DL-Lite.” In <i>The Semantic Web - 22nd European Semantic Web Conference, {ESWC} 2025, Portoroz, Slovenia, June 1-5, 2025, Proceedings, Part {I}</i>, 15718:342--361. Lecture Notes in Computer Science. Springer Nature Switzerland, 2025. <a href=\"https://doi.org/10.1007/978-3-031-94575-5_19\">https://doi.org/10.1007/978-3-031-94575-5_19</a>."},"intvolume":"     15718","page":"342--361","publication_status":"published","publication_identifier":{"isbn":["9783031945748","9783031945755"],"issn":["0302-9743","1611-3349"]},"main_file_link":[{"url":"https://arxiv.org/abs/2405.18181","open_access":"1"}],"conference":{"start_date":"2025-06-01","name":"22th European Semantic Web Conference (ESWC 2025)","location":"Portorož, Slovenia","end_date":"2025-06-05"},"doi":"10.1007/978-3-031-94575-5_19","date_updated":"2025-07-02T11:55:19Z","oa":"1","author":[{"first_name":"Bianca","last_name":"Löhnert","full_name":"Löhnert, Bianca"},{"last_name":"Augsten","full_name":"Augsten, Nikolaus","first_name":"Nikolaus"},{"full_name":"Okulmus, Cem","id":"114410","orcid":"0000-0002-7742-0439","last_name":"Okulmus","first_name":"Cem"},{"first_name":"Magdalena","full_name":"Ortiz, Magdalena","last_name":"Ortiz"}],"volume":15718,"status":"public","type":"conference","_id":"60497","user_id":"114410","series_title":"Lecture Notes in Computer Science","department":[{"_id":"888"}]},{"publication":"Journal of Aerosol Science","keyword":["POCS","Projection onto convex sets","Data inversion","2D distribution","CDMA","Centrifugal Differential Mobility Analyzer"],"language":[{"iso":"eng"}],"year":"2025","quality_controlled":"1","title":"The POCS-Algorithm—An effective tool for calculating 2D particle property distributions via data inversion of exemplary CDMA measurement data","publisher":"Elsevier BV","date_created":"2025-08-25T16:10:18Z","status":"public","type":"journal_article","article_type":"original","article_number":"106606","funded_apc":"1","_id":"61013","user_id":"464","citation":{"ieee":"T. N. Rüther, D. B. Rasche, and H.-J. Schmid, “The POCS-Algorithm—An effective tool for calculating 2D particle property distributions via data inversion of exemplary CDMA measurement data,” <i>Journal of Aerosol Science</i>, vol. 188, Art. no. 106606, 2025, doi: <a href=\"https://doi.org/10.1016/j.jaerosci.2025.106606\">10.1016/j.jaerosci.2025.106606</a>.","chicago":"Rüther, Torben N., David B. Rasche, and Hans-Joachim Schmid. “The POCS-Algorithm—An Effective Tool for Calculating 2D Particle Property Distributions via Data Inversion of Exemplary CDMA Measurement Data.” <i>Journal of Aerosol Science</i> 188 (2025). <a href=\"https://doi.org/10.1016/j.jaerosci.2025.106606\">https://doi.org/10.1016/j.jaerosci.2025.106606</a>.","ama":"Rüther TN, Rasche DB, Schmid H-J. 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ZEW Discussion Paper No. 25-60, 2025."},"year":"2025","date_created":"2025-11-28T12:07:25Z","author":[{"last_name":"Tinnefeld","full_name":"Tinnefeld, Vicky","first_name":"Vicky"},{"first_name":"Martin","full_name":"Kesternich, Martin","id":"98922","orcid":"0000-0002-0653-7680","last_name":"Kesternich"},{"full_name":"Werthschulte, Madeline","last_name":"Werthschulte","first_name":"Madeline"}],"publisher":"ZEW Discussion Paper No. 25-60","date_updated":"2025-12-01T10:21:20Z","title":"Do Energy-Saving Nudges Deliver During High-Price Periods? 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Our findings show limited effectiveness of the behav-\r\nioral instruments during the high-price period. The feedback risks a “boomerang\r\neffect” among households with above-average initial savings, who reduce their\r\nconservation efforts in response. The reminder does not significantly enhance sav-\r\nings in our main specifications, yet, realizes 1 percentage point savings in alternate\r\nmodels refining for outliers. Potential mechanisms include a significant intention-\r\naction gap and misperceived effectiveness of energy-saving actions, which are not\r\nalleviated by the reminder.","lang":"eng"}],"user_id":"98922","_id":"62697","language":[{"iso":"eng"}],"file_date_updated":"2025-11-28T12:04:11Z","keyword":["Residential energy savings","energy crisis","behavioral interventions","survey data","field experiment"],"ddc":["330"]},{"publication_status":"published","has_accepted_license":"1","publication_identifier":{"isbn":["9783748943334"]},"place":"Baden-Baden","citation":{"chicago":"Steinhardt, Isabel, and Ronny Röwert. “Open Science.” In <i>Hochschulforschung</i>, edited by Peer Pasternack, Gabi Reinmann, and Christian  Schneijderberg, 487–96. Baden-Baden: Nomos, 2025. <a href=\"https://doi.org/10.5771/9783748943334-487\">https://doi.org/10.5771/9783748943334-487</a>.","ieee":"I. Steinhardt and R. Röwert, “Open Science,” in <i>Hochschulforschung</i>, P. Pasternack, G. Reinmann, and C. 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Nomos. <a href=\"https://doi.org/10.5771/9783748943334-487\">https://doi.org/10.5771/9783748943334-487</a>"},"page":"487-496","date_updated":"2025-12-17T09:05:53Z","oa":"1","author":[{"first_name":"Isabel","last_name":"Steinhardt","orcid":"https://orcid.org/0000-0002-2590-6189","full_name":"Steinhardt, Isabel","id":"90339"},{"full_name":"Röwert, Ronny","last_name":"Röwert","first_name":"Ronny"}],"main_file_link":[{"url":"https://www.nomos-elibrary.de/de/document/view/detail/uuid/cc4f88b8-f9a8-32ef-a706-a9134f224090","open_access":"1"}],"doi":"10.5771/9783748943334-487","type":"book_chapter","editor":[{"full_name":"Pasternack, Peer","last_name":"Pasternack","first_name":"Peer"},{"first_name":"Gabi","last_name":"Reinmann","full_name":"Reinmann, Gabi"},{"last_name":"Schneijderberg","full_name":"Schneijderberg, Christian ","first_name":"Christian "}],"status":"public","_id":"61237","user_id":"90339","department":[{"_id":"121"}],"file_date_updated":"2025-09-12T06:37:04Z","quality_controlled":"1","year":"2025","publisher":"Nomos","date_created":"2025-09-12T06:35:25Z","title":"Open Science","publication":"Hochschulforschung","abstract":[{"text":"In diesem Beitrag wird zunächst die historische Entstehung von Open Science kurz skizziert und definiert, was unter diesem Begriff zu verstehen ist. Daran anschließend werden die Open-Science-Praktiken Open Data, Open Access, Open Source, Open Methodology und Open Peer Review dargestellt und diskutiert, welche Forschungserkenntnisse zu Open Science vorhanden sind. Im Schluss werden Forschungsdesiderate aufgegriffen und die Implikationen von Open Science für die Wissenschaft erläutert.","lang":"ger"}],"file":[{"relation":"main_file","success":1,"content_type":"application/pdf","file_name":"2025 Steinhardt & Röwert Open Science.pdf","file_id":"61238","access_level":"closed","file_size":268261,"creator":"isste","date_created":"2025-09-12T06:37:04Z","date_updated":"2025-09-12T06:37:04Z"}],"ddc":["300"],"keyword":["Open Data","Open Access","Open Source","Open Methodology","Open Peer Review"],"language":[{"iso":"ger"}]},{"keyword":["Mathematical models","Estimation","Data models","Convolutional neural networks","Accuracy","Magnetic hysteresis","Magnetic cores","Temperature measurement","Magnetic domains","Temperature distribution","Convolutional neural network (CNN)","machine learning (ML)","magnetics"],"_id":"63498","user_id":"83383","department":[{"_id":"52"}],"status":"public","type":"journal_article","publication":"IEEE Transactions on Power Electronics","title":"HARDCORE: H-Field and Power Loss Estimation for Arbitrary Waveforms With Residual, Dilated Convolutional Neural Networks in Ferrite Cores","doi":"10.1109/TPEL.2024.3488174","date_updated":"2026-01-06T08:08:01Z","date_created":"2026-01-06T08:07:13Z","author":[{"first_name":"Wilhelm","last_name":"Kirchgässner","full_name":"Kirchgässner, Wilhelm"},{"first_name":"Nikolas","last_name":"Förster","full_name":"Förster, Nikolas"},{"first_name":"Till","last_name":"Piepenbrock","full_name":"Piepenbrock, Till"},{"first_name":"Oliver","last_name":"Schweins","full_name":"Schweins, Oliver"},{"full_name":"Wallscheid, Oliver","last_name":"Wallscheid","first_name":"Oliver"}],"volume":40,"year":"2025","citation":{"mla":"Kirchgässner, Wilhelm, et al. “HARDCORE: H-Field and Power Loss Estimation for Arbitrary Waveforms With Residual, Dilated Convolutional Neural Networks in Ferrite Cores.” <i>IEEE Transactions on Power Electronics</i>, vol. 40, no. 2, 2025, pp. 3326–35, doi:<a href=\"https://doi.org/10.1109/TPEL.2024.3488174\">10.1109/TPEL.2024.3488174</a>.","short":"W. 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HARDCORE: H-Field and Power Loss Estimation for Arbitrary Waveforms With Residual, Dilated Convolutional Neural Networks in Ferrite Cores. <i>IEEE Transactions on Power Electronics</i>, <i>40</i>(2), 3326–3335. <a href=\"https://doi.org/10.1109/TPEL.2024.3488174\">https://doi.org/10.1109/TPEL.2024.3488174</a>","chicago":"Kirchgässner, Wilhelm, Nikolas Förster, Till Piepenbrock, Oliver Schweins, and Oliver Wallscheid. “HARDCORE: H-Field and Power Loss Estimation for Arbitrary Waveforms With Residual, Dilated Convolutional Neural Networks in Ferrite Cores.” <i>IEEE Transactions on Power Electronics</i> 40, no. 2 (2025): 3326–35. <a href=\"https://doi.org/10.1109/TPEL.2024.3488174\">https://doi.org/10.1109/TPEL.2024.3488174</a>.","ieee":"W. Kirchgässner, N. Förster, T. Piepenbrock, O. Schweins, and O. Wallscheid, “HARDCORE: H-Field and Power Loss Estimation for Arbitrary Waveforms With Residual, Dilated Convolutional Neural Networks in Ferrite Cores,” <i>IEEE Transactions on Power Electronics</i>, vol. 40, no. 2, pp. 3326–3335, 2025, doi: <a href=\"https://doi.org/10.1109/TPEL.2024.3488174\">10.1109/TPEL.2024.3488174</a>.","ama":"Kirchgässner W, Förster N, Piepenbrock T, Schweins O, Wallscheid O. HARDCORE: H-Field and Power Loss Estimation for Arbitrary Waveforms With Residual, Dilated Convolutional Neural Networks in Ferrite Cores. <i>IEEE Transactions on Power Electronics</i>. 2025;40(2):3326-3335. doi:<a href=\"https://doi.org/10.1109/TPEL.2024.3488174\">10.1109/TPEL.2024.3488174</a>"},"page":"3326-3335","intvolume":"        40","issue":"2"},{"keyword":["bushing","experimental data","rubber-metal-bushing","Dataset suspension"],"user_id":"22109","department":[{"_id":"151"}],"_id":"64894","status":"public","abstract":[{"text":"This dataset contains experimental measurements of the radial dynamic and quasi-static characteristics of four different types of Rubber-Metal Bushings (RMBs) used in the suspension system of a passenger car under harmonic displacement excitation. For each bushing type, 2–3 individual specimens were tested.\r\n \r\nQuasi-static measurements were performed at a constant excitation frequency of 0.05 Hz with varying displacement amplitudes. Dynamic measurements were conducted with displacement amplitudes ranging from 0.04 mm to 0.3 mm and excitation frequencies of 2, 5, 10, ..., up to 100 Hz.\r\n\r\nThe data is structured by bushing type, measurement mode, amplitude, and frequency, and is provided in *.csv  and *.hrm format. It is intended to support further research in modeling rubber-metal bushings and parameter identification techniques.","lang":"eng"}],"type":"research_data","doi":"10.5281/ZENODO.14851317","title":"Experimental Dataset: Force and Displacement Measurements of Four Rubber-Metal Bushing Types from a Passenger Car under Harmonic Displacement Excitation","author":[{"first_name":"Jan","last_name":"Schütte","orcid":"0000-0001-9025-9742","id":"22109","full_name":"Schütte, Jan"}],"date_created":"2026-03-11T10:22:01Z","publisher":"LibreCat University","date_updated":"2026-03-11T10:25:23Z","citation":{"short":"J. Schütte, Experimental Dataset: Force and Displacement Measurements of Four Rubber-Metal Bushing Types from a Passenger Car under Harmonic Displacement Excitation, LibreCat University, 2025.","bibtex":"@book{Schütte_2025, title={Experimental Dataset: Force and Displacement Measurements of Four Rubber-Metal Bushing Types from a Passenger Car under Harmonic Displacement Excitation}, DOI={<a href=\"https://doi.org/10.5281/ZENODO.14851317\">10.5281/ZENODO.14851317</a>}, publisher={LibreCat University}, author={Schütte, Jan}, year={2025} }","mla":"Schütte, Jan. <i>Experimental Dataset: Force and Displacement Measurements of Four Rubber-Metal Bushing Types from a Passenger Car under Harmonic Displacement Excitation</i>. LibreCat University, 2025, doi:<a href=\"https://doi.org/10.5281/ZENODO.14851317\">10.5281/ZENODO.14851317</a>.","apa":"Schütte, J. (2025). <i>Experimental Dataset: Force and Displacement Measurements of Four Rubber-Metal Bushing Types from a Passenger Car under Harmonic Displacement Excitation</i>. LibreCat University. <a href=\"https://doi.org/10.5281/ZENODO.14851317\">https://doi.org/10.5281/ZENODO.14851317</a>","chicago":"Schütte, Jan. <i>Experimental Dataset: Force and Displacement Measurements of Four Rubber-Metal Bushing Types from a Passenger Car under Harmonic Displacement Excitation</i>. LibreCat University, 2025. <a href=\"https://doi.org/10.5281/ZENODO.14851317\">https://doi.org/10.5281/ZENODO.14851317</a>.","ieee":"J. Schütte, <i>Experimental Dataset: Force and Displacement Measurements of Four Rubber-Metal Bushing Types from a Passenger Car under Harmonic Displacement Excitation</i>. LibreCat University, 2025.","ama":"Schütte J. <i>Experimental Dataset: Force and Displacement Measurements of Four Rubber-Metal Bushing Types from a Passenger Car under Harmonic Displacement Excitation</i>. LibreCat University; 2025. doi:<a href=\"https://doi.org/10.5281/ZENODO.14851317\">10.5281/ZENODO.14851317</a>"},"year":"2025"},{"publication_status":"unpublished","year":"2024","citation":{"apa":"Harder, H., &#38; Peitz, S. (n.d.). <i>Predicting PDEs Fast and Efficiently with Equivariant Extreme Learning Machines</i>.","bibtex":"@article{Harder_Peitz, title={Predicting PDEs Fast and Efficiently with Equivariant Extreme Learning Machines}, author={Harder, Hans and Peitz, Sebastian} }","mla":"Harder, Hans, and Sebastian Peitz. <i>Predicting PDEs Fast and Efficiently with Equivariant Extreme Learning Machines</i>.","short":"H. Harder, S. Peitz, (n.d.).","chicago":"Harder, Hans, and Sebastian Peitz. “Predicting PDEs Fast and Efficiently with Equivariant Extreme Learning Machines,” n.d.","ieee":"H. Harder and S. Peitz, “Predicting PDEs Fast and Efficiently with Equivariant Extreme Learning Machines.” .","ama":"Harder H, Peitz S. Predicting PDEs Fast and Efficiently with Equivariant Extreme Learning Machines."},"oa":"1","date_updated":"2024-04-30T08:45:24Z","date_created":"2024-04-30T08:43:14Z","author":[{"first_name":"Hans","id":"98879","full_name":"Harder, Hans","last_name":"Harder"},{"first_name":"Sebastian","full_name":"Peitz, Sebastian","id":"47427","last_name":"Peitz","orcid":"0000-0002-3389-793X"}],"title":"Predicting PDEs Fast and Efficiently with Equivariant Extreme Learning Machines","main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/2404.18530"}],"type":"preprint","abstract":[{"lang":"eng","text":"We utilize extreme learning machines for the prediction of partial differential equations (PDEs). Our method splits the state space into multiple windows that are predicted individually using a single model. Despite requiring only few data points (in some cases, our method can learn from a single full-state snapshot), it still achieves high accuracy and can predict the flow of PDEs over long time horizons. Moreover, we show how additional symmetries can be exploited to increase sample efficiency and to enforce equivariance."}],"status":"public","_id":"53793","user_id":"98879","keyword":["extreme learning machines","partial differential equations","data-driven prediction","high-dimensional systems"],"language":[{"iso":"eng"}]},{"_id":"55336","department":[{"_id":"151"}],"user_id":"54290","keyword":["retrofit","diagnosis","prognostics","RUL prediction","missing data","ball bearings"],"language":[{"iso":"eng"}],"publication":"Proceedings of the 2024 Prognostics and System Health Management Conference (PHM)","type":"conference","abstract":[{"text":"Predicting the remaining useful life of technical \r\nsystems has gained significant attention in recent years due to \r\nincreasing demands for extending the lifespan of degrading system \r\ncomponents. Therefore, already used systems are retrofitted by \r\nintegrating sensors to monitor their performance and \r\nfunctionality, enabling accurate diagnosis of their condition and \r\nprediction of their remaining useful life. One of the main \r\nchallenges in this field is identified in the missing data from the \r\ntime where the retrofitted system has already run but without \r\nbeing monitored by sensors. In this paper, a novel approach for \r\nthe combined diagnostics and prognostics of retrofitted systems is \r\nproposed. The methodology aims to provide an accurate diagnosis \r\nof the system’s health state and estimation of the remaining useful \r\nlife by a combination of a machine learning and expert knowledge. \r\nTo evaluate the effectiveness of the proposed methodology, a case \r\nstudy involving a retrofitted system in an industrial setting is \r\nselected and applied. It is demonstrated that the approach \r\neffectively diagnose the current system’s health state and \r\naccurately predict its remaining useful life, thereby enabling \r\npredictive maintenance and decision-making. Overall, our \r\nresearch contributes to advancing the field of condition \r\nmonitoring for retrofitted systems by providing a comprehensive \r\nmethodology that addresses the challenge of missing data.","lang":"eng"}],"status":"public","date_updated":"2024-07-22T09:29:26Z","publisher":"IEEE Computer Society","author":[{"first_name":"Amelie","last_name":"Bender","full_name":"Bender, Amelie","id":"54290"},{"last_name":"Aimiyekagbon","id":"9557","full_name":"Aimiyekagbon, Osarenren Kennedy","first_name":"Osarenren Kennedy"},{"first_name":"Walter","last_name":"Sextro","id":"21220","full_name":"Sextro, Walter"}],"date_created":"2024-07-22T09:27:57Z","title":"Diagnostics and Prognostics for Retrofitted Systems: A Comprehensive Approach for Enhanced System Health Assessment","doi":"10.1109/PHM61473.2024.00038","conference":{"start_date":"2024-05-28","name":"2024 Prognostics and System Health Management Conference (PHM)","location":"Stockholm, Schweden","end_date":"2024-05-31"},"publication_identifier":{"isbn":["979-8-3503-6058-5"]},"quality_controlled":"1","year":"2024","citation":{"short":"A. Bender, O.K. Aimiyekagbon, W. Sextro, in: Proceedings of the 2024 Prognostics and System Health Management Conference (PHM), IEEE Computer Society, 2024.","bibtex":"@inproceedings{Bender_Aimiyekagbon_Sextro_2024, title={Diagnostics and Prognostics for Retrofitted Systems: A Comprehensive Approach for Enhanced System Health Assessment}, DOI={<a href=\"https://doi.org/10.1109/PHM61473.2024.00038\">10.1109/PHM61473.2024.00038</a>}, booktitle={Proceedings of the 2024 Prognostics and System Health Management Conference (PHM)}, publisher={IEEE Computer Society}, author={Bender, Amelie and Aimiyekagbon, Osarenren Kennedy and Sextro, Walter}, year={2024} }","mla":"Bender, Amelie, et al. “Diagnostics and Prognostics for Retrofitted Systems: A Comprehensive Approach for Enhanced System Health Assessment.” <i>Proceedings of the 2024 Prognostics and System Health Management Conference (PHM)</i>, IEEE Computer Society, 2024, doi:<a href=\"https://doi.org/10.1109/PHM61473.2024.00038\">10.1109/PHM61473.2024.00038</a>.","apa":"Bender, A., Aimiyekagbon, O. K., &#38; Sextro, W. (2024). Diagnostics and Prognostics for Retrofitted Systems: A Comprehensive Approach for Enhanced System Health Assessment. <i>Proceedings of the 2024 Prognostics and System Health Management Conference (PHM)</i>. 2024 Prognostics and System Health Management Conference (PHM), Stockholm, Schweden. <a href=\"https://doi.org/10.1109/PHM61473.2024.00038\">https://doi.org/10.1109/PHM61473.2024.00038</a>","ama":"Bender A, Aimiyekagbon OK, Sextro W. Diagnostics and Prognostics for Retrofitted Systems: A Comprehensive Approach for Enhanced System Health Assessment. In: <i>Proceedings of the 2024 Prognostics and System Health Management Conference (PHM)</i>. IEEE Computer Society; 2024. doi:<a href=\"https://doi.org/10.1109/PHM61473.2024.00038\">10.1109/PHM61473.2024.00038</a>","ieee":"A. Bender, O. K. Aimiyekagbon, and W. Sextro, “Diagnostics and Prognostics for Retrofitted Systems: A Comprehensive Approach for Enhanced System Health Assessment,” presented at the 2024 Prognostics and System Health Management Conference (PHM), Stockholm, Schweden, 2024, doi: <a href=\"https://doi.org/10.1109/PHM61473.2024.00038\">10.1109/PHM61473.2024.00038</a>.","chicago":"Bender, Amelie, Osarenren Kennedy Aimiyekagbon, and Walter Sextro. “Diagnostics and Prognostics for Retrofitted Systems: A Comprehensive Approach for Enhanced System Health Assessment.” In <i>Proceedings of the 2024 Prognostics and System Health Management Conference (PHM)</i>. IEEE Computer Society, 2024. <a href=\"https://doi.org/10.1109/PHM61473.2024.00038\">https://doi.org/10.1109/PHM61473.2024.00038</a>."}},{"page":"617-625","citation":{"apa":"Kulkarni, P. J., Tissen, D., Bernijazov, R., &#38; Dumitrescu, R. (2024). Towards Automated Design: Automatically Generating Modeling Elements with Prompt Engineering and Generative Artificial Intelligence. In J. Malmqvist, M. Candi, R. Saemundsson, F. Bystrom, &#38; O. Isaksson (Eds.), <i>DS 130: Proceedings of NordDesign 2024</i> (pp. 617–625). <a href=\"https://doi.org/10.35199/NORDDESIGN2024.66\">https://doi.org/10.35199/NORDDESIGN2024.66</a>","mla":"Kulkarni, Pranav Jayant, et al. “Towards Automated Design: Automatically Generating Modeling Elements with Prompt Engineering and Generative Artificial Intelligence.” <i>DS 130: Proceedings of NordDesign 2024</i>, edited by J. Malmqvist et al., 2024, pp. 617–25, doi:<a href=\"https://doi.org/10.35199/NORDDESIGN2024.66\">10.35199/NORDDESIGN2024.66</a>.","bibtex":"@inproceedings{Kulkarni_Tissen_Bernijazov_Dumitrescu_2024, title={Towards Automated Design: Automatically Generating Modeling Elements with Prompt Engineering and Generative Artificial Intelligence}, DOI={<a href=\"https://doi.org/10.35199/NORDDESIGN2024.66\">10.35199/NORDDESIGN2024.66</a>}, booktitle={DS 130: Proceedings of NordDesign 2024}, author={Kulkarni, Pranav Jayant and Tissen, Denis and Bernijazov, Ruslan and Dumitrescu, Roman}, editor={Malmqvist, J. and Candi, M. and Saemundsson, R. and Bystrom, F. and Isaksson, O.}, year={2024}, pages={617–625} }","short":"P.J. Kulkarni, D. Tissen, R. Bernijazov, R. Dumitrescu, in: J. Malmqvist, M. Candi, R. Saemundsson, F. Bystrom, O. Isaksson (Eds.), DS 130: Proceedings of NordDesign 2024, 2024, pp. 617–625.","chicago":"Kulkarni, Pranav Jayant, Denis Tissen, Ruslan Bernijazov, and Roman Dumitrescu. “Towards Automated Design: Automatically Generating Modeling Elements with Prompt Engineering and Generative Artificial Intelligence.” In <i>DS 130: Proceedings of NordDesign 2024</i>, edited by J. Malmqvist, M. Candi, R. Saemundsson, F. Bystrom, and O. Isaksson, 617–25, 2024. <a href=\"https://doi.org/10.35199/NORDDESIGN2024.66\">https://doi.org/10.35199/NORDDESIGN2024.66</a>.","ieee":"P. J. Kulkarni, D. Tissen, R. Bernijazov, and R. Dumitrescu, “Towards Automated Design: Automatically Generating Modeling Elements with Prompt Engineering and Generative Artificial Intelligence,” in <i>DS 130: Proceedings of NordDesign 2024</i>, Reykjavik, 2024, pp. 617–625, doi: <a href=\"https://doi.org/10.35199/NORDDESIGN2024.66\">10.35199/NORDDESIGN2024.66</a>.","ama":"Kulkarni PJ, Tissen D, Bernijazov R, Dumitrescu R. Towards Automated Design: Automatically Generating Modeling Elements with Prompt Engineering and Generative Artificial Intelligence. In: Malmqvist J, Candi M, Saemundsson R, Bystrom F, Isaksson O, eds. <i>DS 130: Proceedings of NordDesign 2024</i>. ; 2024:617-625. doi:<a href=\"https://doi.org/10.35199/NORDDESIGN2024.66\">10.35199/NORDDESIGN2024.66</a>"},"year":"2024","related_material":{"link":[{"relation":"confirmation","url":"https://www.designsociety.org/publication/47658/Towards+Automated+Design%3A+Automatically+Generating+Modeling+Elements+with+Prompt+Engineering+and+Generative+Artificial+Intelligence"}]},"publication_identifier":{"unknown":["978-1-912254-21-7"]},"publication_status":"epub_ahead","conference":{"location":"Reykjavik","end_date":"2024-08-14","start_date":"2024-08-12","name":"NordDesign Conference 2024"},"doi":"10.35199/NORDDESIGN2024.66","title":"Towards Automated Design: Automatically Generating Modeling Elements with Prompt Engineering and Generative Artificial Intelligence","author":[{"last_name":"Kulkarni","id":"86782","full_name":"Kulkarni, Pranav Jayant","first_name":"Pranav Jayant"},{"first_name":"Denis","last_name":"Tissen","full_name":"Tissen, Denis","id":"44458"},{"first_name":"Ruslan","id":"36312","full_name":"Bernijazov, Ruslan","last_name":"Bernijazov"},{"first_name":"Roman","full_name":"Dumitrescu, Roman","id":"16190","last_name":"Dumitrescu"}],"date_created":"2024-09-17T09:56:43Z","date_updated":"2024-09-17T09:57:07Z","status":"public","editor":[{"first_name":"J.","full_name":"Malmqvist, J.","last_name":"Malmqvist"},{"first_name":"M.","last_name":"Candi","full_name":"Candi, M."},{"full_name":"Saemundsson, R.","last_name":"Saemundsson","first_name":"R."},{"full_name":"Bystrom, F.","last_name":"Bystrom","first_name":"F."},{"first_name":"O.","full_name":"Isaksson, O.","last_name":"Isaksson"}],"abstract":[{"lang":"eng","text":"Developing Intelligent Technical Systems (ITS) involves a complex process encompassing planning, analysis, design, production, and maintenance. Model-Based Systems Engineering (MBSE) is a key methodology for systematic systems engineering. Designing models for ITS requires harmonious interaction of various elements, posing a challenge in MBSE. Leveraging Generative Artificial Intelligence, we generated a dataset for modeling, using prompt engineering on large language models. The generated artifacts can aid engineers in MBSE design or serve as synthetic training data for AI assistants."}],"publication":"DS 130: Proceedings of NordDesign 2024","type":"conference","language":[{"iso":"eng"}],"keyword":["Data Driven Design","Design Automation","Systems Engineering (SE)","Artificial Intelligence (AI)"],"user_id":"86782","_id":"56166"},{"publisher":"European Society for Composite Materials (ESCM)","date_updated":"2026-02-27T06:46:21Z","volume":3,"date_created":"2025-11-04T12:47:06Z","author":[{"first_name":"Johannes","orcid":"0000-0002-0169-8602","last_name":"Gerritzen","id":"105344","full_name":"Gerritzen, Johannes"},{"full_name":"Hornig, Andreas","last_name":"Hornig","first_name":"Andreas"},{"first_name":"Peter","full_name":"Winkler, Peter","last_name":"Winkler"},{"full_name":"Gude, Maik","last_name":"Gude","first_name":"Maik"}],"title":"Direct parameter identification for highly nonlinear strain rate dependent constitutive models using machine learning","doi":"10.60691/yj56-np80","publication_identifier":{"isbn":["978-2-912985-01-9"]},"year":"2024","intvolume":"         3","page":"1252–1259","citation":{"ieee":"J. Gerritzen, A. Hornig, P. Winkler, and M. Gude, “Direct parameter identification for highly nonlinear strain rate dependent constitutive models using machine learning,” in <i>ECCM21 - Proceedings of the 21st European Conference on Composite Materials</i>, 2024, vol. 3, pp. 1252–1259, doi: <a href=\"https://doi.org/10.60691/yj56-np80\">10.60691/yj56-np80</a>.","chicago":"Gerritzen, Johannes, Andreas Hornig, Peter Winkler, and Maik Gude. “Direct Parameter Identification for Highly Nonlinear Strain Rate Dependent Constitutive Models Using Machine Learning.” In <i>ECCM21 - Proceedings of the 21st European Conference on Composite Materials</i>, 3:1252–1259. European Society for Composite Materials (ESCM), 2024. <a href=\"https://doi.org/10.60691/yj56-np80\">https://doi.org/10.60691/yj56-np80</a>.","ama":"Gerritzen J, Hornig A, Winkler P, Gude M. Direct parameter identification for highly nonlinear strain rate dependent constitutive models using machine learning. In: <i>ECCM21 - Proceedings of the 21st European Conference on Composite Materials</i>. Vol 3. European Society for Composite Materials (ESCM); 2024:1252–1259. doi:<a href=\"https://doi.org/10.60691/yj56-np80\">10.60691/yj56-np80</a>","apa":"Gerritzen, J., Hornig, A., Winkler, P., &#38; Gude, M. (2024). Direct parameter identification for highly nonlinear strain rate dependent constitutive models using machine learning. <i>ECCM21 - Proceedings of the 21st European Conference on Composite Materials</i>, <i>3</i>, 1252–1259. <a href=\"https://doi.org/10.60691/yj56-np80\">https://doi.org/10.60691/yj56-np80</a>","bibtex":"@inproceedings{Gerritzen_Hornig_Winkler_Gude_2024, title={Direct parameter identification for highly nonlinear strain rate dependent constitutive models using machine learning}, volume={3}, DOI={<a href=\"https://doi.org/10.60691/yj56-np80\">10.60691/yj56-np80</a>}, booktitle={ECCM21 - Proceedings of the 21st European Conference on Composite Materials}, publisher={European Society for Composite Materials (ESCM)}, author={Gerritzen, Johannes and Hornig, Andreas and Winkler, Peter and Gude, Maik}, year={2024}, pages={1252–1259} }","short":"J. Gerritzen, A. Hornig, P. Winkler, M. Gude, in: ECCM21 - Proceedings of the 21st European Conference on Composite Materials, European Society for Composite Materials (ESCM), 2024, pp. 1252–1259.","mla":"Gerritzen, Johannes, et al. “Direct Parameter Identification for Highly Nonlinear Strain Rate Dependent Constitutive Models Using Machine Learning.” <i>ECCM21 - Proceedings of the 21st European Conference on Composite Materials</i>, vol. 3, European Society for Composite Materials (ESCM), 2024, pp. 1252–1259, doi:<a href=\"https://doi.org/10.60691/yj56-np80\">10.60691/yj56-np80</a>."},"_id":"62078","project":[{"name":"TRR 285:  Methodenentwicklung zur mechanischen Fügbarkeit in wandlungsfähigen Prozessketten","_id":"130"},{"name":"TRR 285 - Subproject A03","_id":"137"},{"name":"TRR 285 - Project Area A","_id":"131"}],"user_id":"105344","keyword":["Direct parameter identification","Machine learning","Convolutional neural networks","Strain rate dependency","Fiber reinforced plastics","woven composites","segmentation","synthetic training data","x-ray computed tomography"],"language":[{"iso":"eng"}],"publication":"ECCM21 - Proceedings of the 21st European Conference on Composite Materials","type":"conference","abstract":[{"text":"Fiber reinforced plastics (FRP) exhibit strongly non-linear deformation behavior. To capture this in simulations, intricate models with a variety of parameters are typically used. The identification of values for such parameters is highly challenging and requires in depth understanding of the model itself. Machine learning (ML) is a promising approach for alleviating this challenge by directly predicting parameters based on experimental results. So far, this works mostly for purely artificial data. In this work, two approaches to generalize to experimental data are investigated: a sequential approach, leveraging understanding of the constitutive model and a direct, purely data driven approach. This is exemplary carried out for a highly non-linear strain rate dependent constitutive model for the shear behavior of FRP.The sequential model is found to work better on both artificial and experimental data. It is capable of extracting well suited parameters from the artificial data under realistic conditions. For the experimental data, the model performance depends on the composition of the experimental curves, varying between excellently suiting and reasonable predictions. Taking the expert knowledge into account for ML-model training led to far better results than the purely data driven approach. Robustifying the model predictions on experimental data promises further improvement. ","lang":"eng"}],"status":"public"},{"has_accepted_license":"1","citation":{"ama":"Khedkar M, Bodden E. Toward an Android Static Analysis Approach for Data Protection. In: <i>Proceedings of the IEEE/ACM 11th International Conference on Mobile Software Engineering and Systems (MOBILESoft ’24). Association for Computing Machinery, New York, NY, USA, 65–68.</i> ; 2024. doi:<a href=\"https://doi.org/10.1145/3647632.3651389\">10.1145/3647632.3651389</a>","ieee":"M. Khedkar and E. Bodden, “Toward an Android Static Analysis Approach for Data Protection,” presented at the 11th International Conference on Mobile Software Engineering and Systems 2024, Lisbon, Portugal, 2024, doi: <a href=\"https://doi.org/10.1145/3647632.3651389\">10.1145/3647632.3651389</a>.","chicago":"Khedkar, Mugdha, and Eric Bodden. “Toward an Android Static Analysis Approach for Data Protection.” In <i>Proceedings of the IEEE/ACM 11th International Conference on Mobile Software Engineering and Systems (MOBILESoft ’24). Association for Computing Machinery, New York, NY, USA, 65–68.</i>, 2024. <a href=\"https://doi.org/10.1145/3647632.3651389\">https://doi.org/10.1145/3647632.3651389</a>.","bibtex":"@inproceedings{Khedkar_Bodden_2024, title={Toward an Android Static Analysis Approach for Data Protection}, DOI={<a href=\"https://doi.org/10.1145/3647632.3651389\">10.1145/3647632.3651389</a>}, booktitle={Proceedings of the IEEE/ACM 11th International Conference on Mobile Software Engineering and Systems (MOBILESoft ’24). Association for Computing Machinery, New York, NY, USA, 65–68.}, author={Khedkar, Mugdha and Bodden, Eric}, year={2024} }","mla":"Khedkar, Mugdha, and Eric Bodden. “Toward an Android Static Analysis Approach for Data Protection.” <i>Proceedings of the IEEE/ACM 11th International Conference on Mobile Software Engineering and Systems (MOBILESoft ’24). Association for Computing Machinery, New York, NY, USA, 65–68.</i>, 2024, doi:<a href=\"https://doi.org/10.1145/3647632.3651389\">10.1145/3647632.3651389</a>.","short":"M. Khedkar, E. Bodden, in: Proceedings of the IEEE/ACM 11th International Conference on Mobile Software Engineering and Systems (MOBILESoft ’24). Association for Computing Machinery, New York, NY, USA, 65–68., 2024.","apa":"Khedkar, M., &#38; Bodden, E. (2024). Toward an Android Static Analysis Approach for Data Protection. <i>Proceedings of the IEEE/ACM 11th International Conference on Mobile Software Engineering and Systems (MOBILESoft ’24). Association for Computing Machinery, New York, NY, USA, 65–68.</i> 11th International Conference on Mobile Software Engineering and Systems 2024, Lisbon, Portugal. <a href=\"https://doi.org/10.1145/3647632.3651389\">https://doi.org/10.1145/3647632.3651389</a>"},"date_updated":"2026-03-04T08:11:48Z","author":[{"last_name":"Khedkar","full_name":"Khedkar, Mugdha","id":"88024","first_name":"Mugdha"},{"first_name":"Eric","id":"59256","full_name":"Bodden, Eric","last_name":"Bodden","orcid":"0000-0003-3470-3647"}],"doi":"10.1145/3647632.3651389","conference":{"location":"Lisbon, Portugal","end_date":"2024-04-15","start_date":"2024-04-14","name":"11th International Conference on Mobile Software Engineering and Systems 2024"},"type":"conference","status":"public","_id":"52235","department":[{"_id":"76"}],"user_id":"88024","file_date_updated":"2024-03-03T14:39:08Z","year":"2024","date_created":"2024-03-03T14:37:53Z","title":"Toward an Android Static Analysis Approach for Data Protection","publication":"Proceedings of the IEEE/ACM 11th International Conference on Mobile Software Engineering and Systems (MOBILESoft '24). Association for Computing Machinery, New York, NY, USA, 65–68.","abstract":[{"lang":"eng","text":"Android applications collecting data from users must protect it according to the current legal frameworks. Such data protection has become even more important since the European Union rolled out the General Data Protection Regulation (GDPR). Since app developers are not legal experts, they find it difficult to write privacy-aware source code. Moreover, they have limited tool support to reason about data protection throughout their app development process.\r\nThis paper motivates the need for a static analysis approach to diagnose and explain data protection in Android apps. The analysis will recognize personal data sources in the source code, and aims to further examine the data flow originating from these sources. App developers can then address key questions about data manipulation, derived data, and the presence of technical measures. Despite challenges, we explore to what extent one can realize this analysis through static taint analysis, a common method for identifying security vulnerabilities. This is a first step towards designing a tool-based approach that aids app developers and assessors in ensuring data protection in Android apps, based on automated static program analysis. "}],"file":[{"creator":"khedkarm","date_created":"2024-03-03T14:39:08Z","date_updated":"2024-03-03T14:39:08Z","access_level":"closed","file_id":"52236","file_name":"2402.07889v1.pdf","file_size":530812,"content_type":"application/pdf","relation":"main_file","success":1}],"external_id":{"arxiv":["2402.07889"]},"keyword":["static program analysis","data protection and privacy","GDPR compliance"],"ddc":["006"],"language":[{"iso":"eng"}]},{"file":[{"content_type":"application/pdf","success":1,"relation":"main_file","date_updated":"2024-11-18T12:10:09Z","creator":"awerning","date_created":"2024-11-18T12:10:09Z","file_size":183539,"file_id":"57200","access_level":"closed","file_name":"Eusipco__Target_specific_Dataset_Pruning_for_Compression_of_Audio_Tagging_Models.pdf"}],"status":"public","abstract":[{"lang":"eng","text":"Large audio tagging models are usually trained or pre-trained on AudioSet, a dataset that encompasses a large amount of different sound classes and acoustic environments. Knowledge distillation has emerged as a method to compress such models without compromising their effectiveness. There are many different applications for audio tagging, some of which require a specialization to a narrow domain of sounds to be classified. For these scenarios, it is beneficial to distill the large audio tagger with respect to a specific subset of sounds of interest. A method to prune a general dataset with respect to a target dataset is presented. By distilling with such a specialized pruned dataset, we obtain a compressed model with better classification accuracy in the specific target domain than with target-agnostic distillation."}],"type":"conference","publication":"32nd European Signal Processing Conference (EUSIPCO 2024)","file_date_updated":"2024-11-18T12:10:09Z","language":[{"iso":"eng"}],"ddc":["000"],"keyword":["data pruning","knowledge distillation","audio tagging"],"user_id":"62152","department":[{"_id":"54"}],"project":[{"name":"WestAI - AI Service Center West","_id":"512"}],"_id":"57160","citation":{"ama":"Werning A, Haeb-Umbach R. Target-Specific Dataset Pruning for Compression of Audio Tagging Models. In: <i>32nd European Signal Processing Conference (EUSIPCO 2024)</i>. ; 2024.","chicago":"Werning, Alexander, and Reinhold Haeb-Umbach. “Target-Specific Dataset Pruning for Compression of Audio Tagging Models.” In <i>32nd European Signal Processing Conference (EUSIPCO 2024)</i>, 2024.","ieee":"A. Werning and R. Haeb-Umbach, “Target-Specific Dataset Pruning for Compression of Audio Tagging Models,” presented at the 32nd European Signal Processing Conference, Lyon, 2024.","apa":"Werning, A., &#38; Haeb-Umbach, R. (2024). Target-Specific Dataset Pruning for Compression of Audio Tagging Models. <i>32nd European Signal Processing Conference (EUSIPCO 2024)</i>. 32nd European Signal Processing Conference, Lyon.","bibtex":"@inproceedings{Werning_Haeb-Umbach_2024, title={Target-Specific Dataset Pruning for Compression of Audio Tagging Models}, booktitle={32nd European Signal Processing Conference (EUSIPCO 2024)}, author={Werning, Alexander and Haeb-Umbach, Reinhold}, year={2024} }","short":"A. Werning, R. Haeb-Umbach, in: 32nd European Signal Processing Conference (EUSIPCO 2024), 2024.","mla":"Werning, Alexander, and Reinhold Haeb-Umbach. “Target-Specific Dataset Pruning for Compression of Audio Tagging Models.” <i>32nd European Signal Processing Conference (EUSIPCO 2024)</i>, 2024."},"year":"2024","has_accepted_license":"1","quality_controlled":"1","conference":{"name":"32nd European Signal Processing Conference","location":"Lyon"},"title":"Target-Specific Dataset Pruning for Compression of Audio Tagging Models","author":[{"first_name":"Alexander","last_name":"Werning","id":"62152","full_name":"Werning, Alexander"},{"first_name":"Reinhold","id":"242","full_name":"Haeb-Umbach, Reinhold","last_name":"Haeb-Umbach"}],"date_created":"2024-11-18T09:29:16Z","date_updated":"2025-11-28T13:22:00Z"},{"status":"public","abstract":[{"text":"Despite the widespread use of machine learning algorithms, their effectiveness is limited by a phenomenon known as algorithm aversion. Recent research concluded that unobserved variables can cause algorithm aversion. However, the impact of an unobserved variable on algorithm aversion remains unclear. Previous studies focused on situations where humans had more variables available than algorithms. We extend this research by conducting an online experiment with 94 participants, systematically varying the number of observable variables to the advisor and the advisor type. Surprisingly, our results did not confirm that an unobserved variable had a negative effect on advice-taking. Instead, we found a positive impact in an algorithm appreciation scenario. This study provides new insights into the paradoxical behavior in which people weigh advice more despite having fewer variables, as they correct for the advisor's errors. Practitioners should consider this behavior when designing algorithms and account for user correction behavior.","lang":"eng"}],"publication":"Wirtschaftsinformatik Conference","type":"conference","language":[{"iso":"eng"}],"keyword":["Algorithm aversion","Data","Decision-making","Advice-taking","Human-Computer Interaction"],"department":[{"_id":"196"}],"user_id":"51271","_id":"50118","citation":{"apa":"Leffrang, D. (2023). The Broken Leg of Algorithm Appreciation: An Experimental Study on the Effect of Unobserved Variables on Advice Utilization. <i>Wirtschaftsinformatik Conference</i>, <i>19</i>.","bibtex":"@inproceedings{Leffrang_2023, title={The Broken Leg of Algorithm Appreciation: An Experimental Study on the Effect of Unobserved Variables on Advice Utilization}, number={19}, booktitle={Wirtschaftsinformatik Conference}, author={Leffrang, Dirk}, year={2023} }","short":"D. Leffrang, in: Wirtschaftsinformatik Conference, 2023.","mla":"Leffrang, Dirk. “The Broken Leg of Algorithm Appreciation: An Experimental Study on the Effect of Unobserved Variables on Advice Utilization.” <i>Wirtschaftsinformatik Conference</i>, no. 19, 2023.","ieee":"D. Leffrang, “The Broken Leg of Algorithm Appreciation: An Experimental Study on the Effect of Unobserved Variables on Advice Utilization,” in <i>Wirtschaftsinformatik Conference</i>, Paderborn, 2023, no. 19.","chicago":"Leffrang, Dirk. “The Broken Leg of Algorithm Appreciation: An Experimental Study on the Effect of Unobserved Variables on Advice Utilization.” In <i>Wirtschaftsinformatik Conference</i>, 2023.","ama":"Leffrang D. The Broken Leg of Algorithm Appreciation: An Experimental Study on the Effect of Unobserved Variables on Advice Utilization. In: <i>Wirtschaftsinformatik Conference</i>. ; 2023."},"year":"2023","issue":"19","conference":{"name":"Wirtschaftsinformatik","location":"Paderborn"},"main_file_link":[{"url":"https://aisel.aisnet.org/wi2023/19 "}],"title":"The Broken Leg of Algorithm Appreciation: An Experimental Study on the Effect of Unobserved Variables on Advice Utilization","date_created":"2024-01-03T09:50:06Z","author":[{"full_name":"Leffrang, Dirk","id":"51271","last_name":"Leffrang","orcid":"0000-0001-9004-2391","first_name":"Dirk"}],"date_updated":"2024-01-10T09:53:24Z"},{"abstract":[{"text":"Megatrends, such as digitization or sustainability, are confronting the product management of manufacturing companies with a variety of challenges regarding the design of future products, but also the management of the actual products. To successfully position their products in the market, product managers need to gather and analyze comprehensive information about customers, developments in the products’ environment, product usage, and more. The digitization of all aspects of life is making data on these topics increasingly available – via social media, documents, or the internet of things from the products themselves. The systematic collection and analysis of these data enable the exploitation of new potentials for the adaption of existing products and the creation of the products of tomorrow. However, there are still no insights into the main concepts and cause-effect relationships in exploiting data-driven approaches for product management. Therefore, this paper aims to identify the main concepts and advantages of data-driven product management. To answer the corresponding research questions a comprehensive systematic literature review is conducted. From its results, a detailed description of the main concepts of data-driven product management is derived. Furthermore, a taxonomy for the advantages of data-driven product management is presented. The main concepts and the taxonomy allow for a deeper understanding of the topic while highlighting necessary future actions and research needs.","lang":"eng"}],"status":"public","type":"conference","publication":"2023 IEEE International Conference on Technology Management, Operations and Decisions (ICTMOD)","keyword":["Product Lifecyle Management (PLM)","Data Analytics","Data-driven Design","Engineering Management","Lifecycle Data"],"language":[{"iso":"eng"}],"_id":"52369","user_id":"66731","department":[{"_id":"563"}],"year":"2023","citation":{"ieee":"T. Fichtler, K. Grigoryan, C. Koldewey, and R. Dumitrescu, “Towards a Data-Driven Product Management – Concepts, Advantages, and Future Research,” presented at the IEEE International Conference on Technology Management, Operations and Decisions (ICTMOD), Rabat, Morocco, 2023, doi: <a href=\"https://doi.org/10.1109/ictmod59086.2023.10438135\">10.1109/ictmod59086.2023.10438135</a>.","chicago":"Fichtler, Timm, Khoren Grigoryan, Christian Koldewey, and Roman Dumitrescu. “Towards a Data-Driven Product Management – Concepts, Advantages, and Future Research.” In <i>2023 IEEE International Conference on Technology Management, Operations and Decisions (ICTMOD)</i>. IEEE, 2023. <a href=\"https://doi.org/10.1109/ictmod59086.2023.10438135\">https://doi.org/10.1109/ictmod59086.2023.10438135</a>.","ama":"Fichtler T, Grigoryan K, Koldewey C, Dumitrescu R. Towards a Data-Driven Product Management – Concepts, Advantages, and Future Research. In: <i>2023 IEEE International Conference on Technology Management, Operations and Decisions (ICTMOD)</i>. IEEE; 2023. doi:<a href=\"https://doi.org/10.1109/ictmod59086.2023.10438135\">10.1109/ictmod59086.2023.10438135</a>","mla":"Fichtler, Timm, et al. “Towards a Data-Driven Product Management – Concepts, Advantages, and Future Research.” <i>2023 IEEE International Conference on Technology Management, Operations and Decisions (ICTMOD)</i>, IEEE, 2023, doi:<a href=\"https://doi.org/10.1109/ictmod59086.2023.10438135\">10.1109/ictmod59086.2023.10438135</a>.","bibtex":"@inproceedings{Fichtler_Grigoryan_Koldewey_Dumitrescu_2023, title={Towards a Data-Driven Product Management – Concepts, Advantages, and Future Research}, DOI={<a href=\"https://doi.org/10.1109/ictmod59086.2023.10438135\">10.1109/ictmod59086.2023.10438135</a>}, booktitle={2023 IEEE International Conference on Technology Management, Operations and Decisions (ICTMOD)}, publisher={IEEE}, author={Fichtler, Timm and Grigoryan, Khoren and Koldewey, Christian and Dumitrescu, Roman}, year={2023} }","short":"T. Fichtler, K. Grigoryan, C. Koldewey, R. Dumitrescu, in: 2023 IEEE International Conference on Technology Management, Operations and Decisions (ICTMOD), IEEE, 2023.","apa":"Fichtler, T., Grigoryan, K., Koldewey, C., &#38; Dumitrescu, R. (2023). Towards a Data-Driven Product Management – Concepts, Advantages, and Future Research. <i>2023 IEEE International Conference on Technology Management, Operations and Decisions (ICTMOD)</i>. IEEE International Conference on Technology Management, Operations and Decisions (ICTMOD), Rabat, Morocco. <a href=\"https://doi.org/10.1109/ictmod59086.2023.10438135\">https://doi.org/10.1109/ictmod59086.2023.10438135</a>"},"publication_status":"published","title":"Towards a Data-Driven Product Management – Concepts, Advantages, and Future Research","doi":"10.1109/ictmod59086.2023.10438135","conference":{"end_date":"2023-11-24","location":"Rabat, Morocco","name":"IEEE International Conference on Technology Management, Operations and Decisions (ICTMOD)","start_date":"2023-11-22"},"publisher":"IEEE","date_updated":"2024-03-07T18:17:34Z","author":[{"first_name":"Timm","orcid":"https://orcid.org/0000-0001-6034-4399","last_name":"Fichtler","full_name":"Fichtler, Timm","id":"66731"},{"first_name":"Khoren","full_name":"Grigoryan, Khoren","last_name":"Grigoryan"},{"first_name":"Christian","last_name":"Koldewey","orcid":"https://orcid.org/0000-0001-7992-6399","id":"43136","full_name":"Koldewey, Christian"},{"first_name":"Roman","id":"16190","full_name":"Dumitrescu, Roman","last_name":"Dumitrescu"}],"date_created":"2024-03-07T18:13:47Z"}]