Enhancing Data Quality in Large-Scale Software Systems for Industrial Automation-Reference-Cited by-同舟云学术

Enhancing Data Quality in Large-Scale Software Systems for Industrial Automation

Published:2023-12-04 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 3rd International Workshop on Software Engineering and AI for Data Quality in Cyber-Physical Systems/Internet of Things
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Author:

Golendukhina Valentina¹,Sonnleithner Lisa²,Felderer Michael³

Affiliation:

1. University of Innsbruck, Innsbruck, Austria

2. JKU Linz, Linz, Austria

3. DLR, Cologne, Germany

Funder

Austrian Research Promotion Agency

Austrian Federal Ministry for Digital and Economic Affairs

the National Foundation for Research, Technology and Development

Christian Doppler Research Association

Publisher

ACM

Reference13 articles.

1. 2003. IEC 62264: Enterprise-control system integration. International Electrotechnical Commission. https://www.iso.org/standard/31332.html Standard 2003. IEC 62264: Enterprise-control system integration. International Electrotechnical Commission. https://www.iso.org/standard/31332.html Standard

2. Data quality challenges in large-scale cyber-physical systems: A systematic review

3. Carlo Batini , Cinzia Cappiello , Chiara Francalanci , and Andrea Maurino . 2009. Methodologies for data quality assessment and improvement. ACM computing surveys (CSUR), 41, 3 ( 2009 ), 1–52. Carlo Batini, Cinzia Cappiello, Chiara Francalanci, and Andrea Maurino. 2009. Methodologies for data quality assessment and improvement. ACM computing surveys (CSUR), 41, 3 (2009), 1–52.

4. An approach for assessing industrial IoT data sources to determine their data trustworthiness

5. IEC. 2013. IEC 61131 - Programmable controllers Part 3: Programming languages: Edition 3.0. www.iec.ch IEC. 2013. IEC 61131 - Programmable controllers Part 3: Programming languages: Edition 3.0. www.iec.ch