Publications
AI Explainability: Embedding Conceptual Models
Maass, W., Castellanos, A., Tremblay, M., Lukyanenko, R., & Storey, V.C.
ICIS 2022 Proceedings. 12
Introduces methods to embed conceptual models into AI for improved explainability.
AI meets Design Science – Towards Design Methods for AI Systems Development
Janzen, S., Stein, H., Öksüz-Köster, N., Maass, W.
In: International Conference on Information Systems (ICIS) 2022 TREOs. International Conference on Information Systems (ICIS-2022), December 9-14, Copenhagen, Denmark
Proposes design methods for AI systems development, bridging AI and design science.
AI-based Approach for Improving the Detection of Blood Doping in Sports
Rahman, M.R., Bejder, J., Bonne, T.C., Andersen, A.B., Huertas, J.R., Aikin, R., Nordsborg, N.B., & Maass, W.
arXiv:2203.00001
Presents an AI-based approach to enhance the detection of blood doping in sports.
Approaches for Automated Data Quality Analysis: Syntactic and Semantic Assessment
Ahiagble, A.P., Stein, H.
Annual conference of the Society for Computer Science (INFORMATIK-2022), September 26-30, Hamburg, Germany
Discusses automated methods for syntactic and semantic data quality analysis.
Bewertung von Unternehmensdatenbeständen: Wege zur Wertermittlung des wertvollsten immateriellen Vermögensgegenstandes
Stein, H., Groen in’t Woud, F., Holuch, M., Mulryan, D., Froese, T., Holst, L.
In: Wie aus Daten Wert entsteht: Band 1: Datenwirtschaft und Datentechnologie. Springer, 2022
Discusses methods for valuing corporate data assets in the context of intangible assets.
ConceptSuperimposition: Using Conceptual Modeling Method for Explainable AI
Maass, W., Castellanos, A., Tremblay, M.C., Lukyanenko, R., & Storey, V.C.
In AAAI Spring Symposium: MAKE (pp. 1-6)
Explores the use of conceptual modeling methods for enhancing explainable AI.
Contract-based Data-sharing for AI-based Decision Making on the Web
Maass, W.
55th Hawaii International Conference on System Sciences (HICSS-2022), January 4-7, Hawaii, Hawaii, United States. Springer
Proposes a contract-based framework for data-sharing to facilitate AI-driven decision-making.
Data Analytics for Uncovering Fraudulent Behaviour in Elite Sports
Rahman, M.R., Piper, T., Geyer, H., Equey, T., Baume, N., Aikin, R., Maass, W.
43rd International Conference on Information Systems (ICIS 22), Copenhagen, Denmark
Applies data analytics to uncover fraudulent behaviors in elite sports.
Data Management
Chua, C., Indulska, M., Lukyaneko, R., Maaß, W., Storey, V.C.
MIS Quarterly Research Curations
In our modern, digital world, the critical role of information technology makes data management an important research topic. This paper curates data management research at MIS Quarterly as it has progressed from its early context of understanding requirements of relatively simple information systems to the sophisticated and complex systems of today. In the following sections, we discuss the focus of this curation, the themes of data management, and the progression of research over time. We reviewed each paper published in MISQ since its inception, assessing the paper's relevance to the curation's theme. Because of the ubiquity of the word ‘data’ in MISQ papers, we performed this review manually rather than relying on keyword searches. We iteratively classified the relevant papers into 5 themes based on consensus. Our final curation includes 81 papers. To keep the text concise, we eschew citations from the paragraphs below and instead include them in the associated tables that follow.
In our modern, digital world, the critical role of information technology makes data management an important research topic. This paper curates data management research at MIS Quarterly as it has progressed from its early context of understanding requirements of relatively simple information systems to the sophisticated and complex systems of today. In the following sections, we discuss the focus of this curation, the themes of data management, and the progression of research over time. We reviewed each paper published in MISQ since its inception, assessing the paper's relevance to the curation's theme. Because of the ubiquity of the word ‘data’ in MISQ papers, we performed this review manually rather than relying on keyword searches. We iteratively classified the relevant papers into 5 themes based on consensus. Our final curation includes 81 papers. To keep the text concise, we eschew citations from the paragraphs below and instead include them in the associated tables that follow.
Data Sharing in German Food Industry – Empirical Insights
Stein, H., Rix, C., Effertz, A., Bergau, S., Maass, W.
In Proceedings of the Americas Conference on Information Systems (AMCIS)
Provides empirical insights into data sharing practices in the German food industry.
Detection of Erythropoietin in Blood to Uncover Doping in Sports using Machine Learning
Rahman, M.R., Bejder, J., Bonne, T.C., Andersen, A.B., Huertas, J.R., Aikin, R., Nordsborg, N.B., Maass, W.
In Proceedings of the IEEE International Conference on Digital Health (ICDH), pp. 193-201
Explores machine learning methods to detect erythropoietin in blood for uncovering doping in sports.
Explainable AI
Storey, V.C., Lukyanenko, R., Maass, W., & Parsons, J.
Communications of the ACM, 65(4), 27-29
Discusses the principles and challenges of explainable AI in various domains.
Explainable AI: Opening the Black Box or Pandora's Box?
Storey, V., Lukyanenko, R., Maass, W., Parsons, J.
Communications of the ACM (CACM)
Examines the challenges and opportunities in implementing explainable AI.
Explainable Unsupervised Multi-Sensor Industrial Anomaly Detection and Categorization
Ameli, M., Becker, P.A., Lankers, K., van Ackeren, M., Bähring, H., Maass, W.
In: International Conference on Machine Learning and Applications (ICMLA-2022), December 12-14, Paradise Island, The Bahamas
Explores unsupervised anomaly detection and categorization in industrial environments using explainable AI.
Impact of Covid-19 on the global orthopaedic research output
Wolf, M., Landgraeber, S., Maass, W., & Orth, P.
Frontiers in Surgery, 9
Analyzes the impact of Covid-19 on global orthopaedic research output.