17 November, 2022 – Singapore – Online/In presence Workshop
The 2nd International Workshop on Software Engineering and AI for Data Quality in Cyber-Physical Systems/Internet of Things at the ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC / FSE)
Cyber-physical systems (CPS)/Internet of Things (IoT) are omnipresent in many industrial sectors and application domains in which the quality of the data acquired and used for decision support is a common factor. Data quality can deteriorate due to factors such as sensor faults and failures due to operating in harsh and uncertain environments.
How can software engineering and artificial intelligence (AI) help manage and tame data quality issues in CPS/IoT?
This is the question we aim to investigate in this workshop SEA4DQ. Emerging trends in software engineering need to take data quality management seriously as CPS/IoT are increasingly data-centric in their approach to acquiring and processing data along the edge-fog-cloud continuum. This workshop will provide researchers and practitioners a forum for exchanging ideas, experiences, understanding of the problems, visions for the future, and promising solutions to the problems in data quality in CPS/IoT.
Cyber-Physical Systems/Internet of Things at the ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC / FSE)
Keynotes
Prof. Dr. Andreas Metzger
Head of Adaptive Systems and Big Data Applications,
University of Duisburg-Essen, Germany
Title: “Data Quality Issues in Online Reinforcement Learning for Self-adaptive Systems”
Prof. Foutse Khomh
Head of SoftWare Analytics and Technologies (SWAT) Lab,
University of Montréal, Canada
Title: “Data Quality and Model Under-Specification Issues”
Organization Committee
Phu Nguyen (Main Contact)
General Chair
SINTEF, Norway
Sagar Sen (Main Contact)
Co-Program Chair
SINTEF, Norway
Maria Chiara Magnanini
Co-Program Chair
Politecnico di Milano, Italy
Beatriz Cassoli
Moderator, Co-Web Chair
TU Darmstadt, Germany
Nicolas Jourdan
Moderator, Co-Web Chair
TU Darmstadt, Germany
Mikel Armendia
Publicity Chair
Tekniker, Spain
Topics of Interest
- Software/hardware architectures and frameworks for data quality management in CPS/IoT
- Software engineering and AI to pre-process and clean data
- Software engineering and AI to detect and repair anomalies in CPS/IoT data
- Software engineering and AI to cluster data as events
- Software tools for data quality management, testing, and profiling
- Public sensor datasets from CPS/IoT (manufacturing, digital health, energy,…)
- Distributed ledger and blockchain technologies for quality tracking
- Quantification of data quality hallmarks and uncertainty in data repair
- Sensor data fusion techniques for improving data quality and prediction
- Augmented data quality
- Case studies that have evaluated an existing technique or tool on real systems, not only toy problems, to manage data quality in cyber-physical systems in different sectors.
- Certification and standardization of data quality in CPS/IoT
- Approaches for secure and trusted data sharing, especially for data quality, management, and governance in CPS/IoT
- Trade-offs between data quality and data security in CPS/IoT
Accepted Papers
- Data Quality as a Microservice – an ontology and rule based approach for quality assurance of sensor data in manufacturing machines | Full Paper
Jørgen Stang, Dirk Walther, Per Myrseth - Effect of Time Patterns in Mining Process Invariants for Industrial Control Systems: An Experimental Study | Full Paper
Muhammad Azmi Umer, Aditya Mathur and Muhammad Taha Jilani - Preliminary Findings on the Occurrence and Causes of Data Smells in a Real-World Business Travel Data Processing Pipeline | WIP Paper
Valentina Golendukhina, Harald Foidl, Michael Felderer and Rudolf Ramler - Data Quality Issues for Vibration Sensors: A Case Study in Ferrosilicon Production | Short Paper
Maryna Waszak, Terje Moen, Sølve Eidnes, Alexander Stasik, Anders Hansen, Gregory Bouquet, Antoine Pultier, Xiang Ma, Idar Tørlen, Bjørn Rune Henriksen, Arianeh Aamodt, Dumitru Roman - Data Quality Issues in Solar Panels Installations: A Case Study | Short Paper
Dumitru Roman, Antoine Pultier, Xiang Ma, Ahmet Soylu, Alexander G.Ulyashin
Program Committee
- Andreas Metzger, University of Duisburg-Essen, Germany
- Donghwan Shin, University of Luxembourg, Luxembourg
- David Lo, Singapore Management University, Singapore
- Jean-Yves Tigli, Université Côte d’Azur, France
- Helena Holmström Olsson, Malmö University, Sweden
- Frank Alexander Kraemer, NTNU, Norway
- Hong-Linh Truong, Aalto University, Finland
- Cyril Cecchinel, DataThings, Luxembourg
- Dumitru Roman, SINTEF / University of Oslo, Norway
- Felix Mannhardt, KIT-AR, Germany
- Dimitra Politaki, INLECOM, Greece
- Amina Ziegenbein, Technische Universität Darmstadt, Germany
- Flavien Peysson, PREDICT, France
- Karl John Pedersen, DNV AS, Norway
- Helge Spieker, Simula Research Laboratory, Norway
- Dusica Marijan, Simula Research Laboratory, Norway
- Marc Roper, University of Strathclyde, UK
- Jan Nygård, Cancer Registry of Norway, Norway
- Freddy Munoz, Compass Inc., USA
- Stefano Borgia, Holonix, Italy
- Katinka Wolter, Free University of Berlin, Germany
- Sudipto Ghosh, Colorado State University, USA
- Luke Todhunter, University of Nottingham, UK
- Debmalya Biswas, Darwin Digital, Switzerland
- Enrique Garcia Ceja, Optimeering, Oslo
* PC members list is in an arbitrary order.
The SEA4DQ 2022 Workshop is sponsored by the research projects InterQ and DAT4.Zero that are funded by the European Union’s Horizon 2020 Research and Innovation programme.