Software Engineering and AI for Data Quality in Cyber-Physical Systems/Internet of Things - SEA4DQ'22 Report

Abstract

Cyber-physical systems (CPS)/lntemet 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. Because of things like sensor failures and defects brought on by working in harsh and unreliable conditions, data quality might suffer. How can software engineering and artificial intelligence (AI) help manage and tame data quality issues in CPS/IoT? Data quality is of paramount importance for CPS/loT. This workshop series stemmed from the common interest in data quality of the Zero-Defect Manufacturing (ZDM) Research and Innovation projects under the Horizon 2020 Framework Programme such as InterQ (https://interqproject.eu/) and DAT4.Zero (https://dat4zero.eu/). Not only for ZDM, but also in general, emerging trends in software engineering need to take data quality management seriously as CPS/loT are increasingly data-centric in their approach to acquiring and processing data along the edge-fog-cloud continuum. This workshop provides 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/loT. SEA4DQ 2022 took place on November 171h, 2022 and collocated with the ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC / FSE) 2022 in Singapore. The workshop featured two great keynotes, six excellent presentations, and concluded on a high note with an extensive panel discussion.