Publications
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.
MANGQ: Towards Natural Language Interfaces for Knowledge Graphs
Harig, A., Janzen, S., Maass, W.
32nd Workshop on Information Technologies and Systems (WITS-2022), Copenhagen, Denmark
Proposes MANGQ, a framework for building natural language interfaces for knowledge graphs.
MISQ Research Curation on Data Management
Chua, C., Indulska, M., Lukyanenko, R., Maass, W., & Storey, V.C.
MIS Quarterly, 1-12
Curates research findings on data management, highlighting trends and challenges.
Requirements for Data Valuation Methods
Stein, H., & Maass, W.
55th Hawaii International Conference on System Sciences (HICSS-2022), January 4-7, Hawaii, Hawaii, United States. Springer
Discusses the requirements for data valuation methods in AI and data-driven systems.
Towards A Data Quality Index for Data Valuation In the Data Economy
Dokic, D., Stein, H.
Annual Conference of the Society for Computer Science (INFORMATIK), September 2022, Hamburg, Germany
Proposes a data quality index for evaluating data valuation in the data economy.
Trust in artificial intelligence: From a Foundational Trust Framework to emerging research opportunities
Lukyanenko, R., Maass, W., & Storey, V.C.
Electronic Markets, 1-28
Proposes a foundational trust framework for AI and identifies emerging research opportunities.
Unsupervised Multi-Sensor Anomaly Localization with Explainable AI
Ameli, M., Pfanschilling, V., Amirli, A., Maass, W., Kersting, K.
In: IFIP Artificial Intelligence Applications and Innovations (AIAI-2022), June 17-20, Crete, Greece
Explores unsupervised anomaly localization techniques using explainable AI in multi-sensor environments.
Conceptualizing Data Ecosystems for Industrial Food Production
Rix, C., Stein, H., Chen, Q., Frank, J., & Maass, W.
23rd IEEE International Conference on Business Informatics. IEEE Conference on Business Informatics (CBI-2021), Leading the Digital Transformation, September 1-3, Bolzano/Virtual, Italy. Springer.
Investigates the conceptualization of data ecosystems for enhancing industrial food production.
From Mental Models to Machine Learning Models via Conceptual Models
Maass, W., Storey, V. C., & Lukyanenko, R.
In Enterprise, Business-Process and Information Systems Modeling (pp. 293–300). Cham: Springer International Publishing.
Explores how conceptual models can bridge the gap between mental models and machine learning models.
From Qualitative to Quantitative Data Valuation in Manufacturing Companies
Stein, H., Holst, L., Stich, V., & Maass, W.
In A. Dolgui, A. Bernard, D. Lemoine, G. von Cieminski, & D. Romero (Eds.), Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems (pp. 172–180). Cham: Springer International Publishing.
Describes a framework for transitioning from qualitative to quantitative data valuation in manufacturing.
Monetäre Bewertung von Daten im Kontext der Rechnungslegung – Ansätze zur Datenbilanzierung
Stein, H., & Maass, W.
In D. Trauth, T. Bergs, & W. Prinz (Eds.), Monetarisierung von technischen Daten (pp. 115–130). Springer.
Discusses approaches to the monetary valuation of data in the context of accounting.
Pairing conceptual modeling with machine learning
Maass, W., & Storey, V.
Data & Knowledge Engineering, 134, 101909.
Presents a methodology for integrating conceptual modeling with machine learning techniques.
Smart Resilience Services for Industrial Production
Janzen, S., Öksüz, N., Sporkmann, J., Schlappa, M., Gerhard, J., Ortjohann, L., & Becker, P.
22. VDI-Kongress AUTOMATION 2021 – Navigating towards resilient production. VDI Automatisierungskongress (AUTOMATION-2021), June 29-30, Virtual, Germany. VDI.
Explores smart resilience services designed for industrial production environments.
Towards an Artificial Intelligence based Approach for Manufacturing Resilience
Öksüz, N., Bouschery, S., Schlappa, M., Unterberg, M., & Sporkmann, J.
22. VDI-Kongress AUTOMATION 2021 – Navigating towards resilient production. VDI Automatisierungskongress (AUTOMATION-2021), June 29-30, Virtual, Germany. VDI.
Proposes AI-based methods to enhance resilience in manufacturing processes.