The 4th International Workshop on Engineering Data- & Model-driven Applications
in conjunction with the
20th UK Workshop on Computational Intelligence (UKCI 2021)
We are witnessing a dramatic increase of large engineering data resource availability and accessibility across the lifecycles of most engineered systems. Data-driven, data-enabled technologies, and computational model-driven capabilities show nowadays sustained development in all industrial areas, from manufacturing and supply chains to transportation and healthcare. On the other hand, developments with autonomous systems are becoming increasingly common across the field of engineered systems, from cars, drones, manufacturing systems and medical devices, and, concurrently, have an increasing and more diversified consumer demand. These technologies address prevailing societal challenges, such as Industry 4.0, autonomous cars, digital healthcare, which demand augmented decision making based on electronic records data mining, assessments, diagnostics and prognostics, and knowledge discovery to address complex contextual requirements. Such systems are expected to have proven capabilities for resilience and self-management / self-certification against risks affecting the mission goals, to learn from relatively new ways of storing data industrially, such as data lakes and graph databases, to be scalable for integration in big data processing systems involving data streams and to demonstrate this behaviour to stakeholders and users in a transparent and explainable manner. This demands new research for the efficient aggregation, integration, analysis and governance of data and models, and the development and validation of advanced data- and model-driven approaches that support decision making throughout the life cycle of systems.
Delivering to these challenges and opportunities requires deep interdisciplinary collaboration and research to achieve a deep integration of the data science and machine learning research (data-driven methodologies), with the underlying science and engineering knowledge and computational models (model-driven approaches).
The UK Automotive Council Digitalisation Roadmap (https://roadmap.ide.uk/) launched in March 2021 by the Institute of Digital Engineering (IDE), outlines pathways for research and development across sectors to significantly enhance the effectiveness of engineering, product and service development through digitalisation. We are delighted to have the support of the IDE for our EDMA workshop this year, including a keynote address outlining the digitalisation technology roadmap to 2040 for the automotive industry and beyond.
This 4th EDMA International Workshop calls for industry and academic experts and researchers working across the computing and engineering divide to share their views, experiences and best practices on the use of knowledge discovery and computational science and engineering models, to handle processing systems complexity, including big data analytics, in industrial, engineering, cyber-physical systems, industry 4.0 and related domains.
As in previous years, prominent industry experts will deliver an agenda setting keynotes to the workshop.
The 4th EDMA International Workshop Committee Members invite original contributions (reviews and surveys, technical and research papers) from industry and academic experts and researchers, describing case studies, methodologies, formalisms, algorithms and solutions for topics including but not limited to:
- Industrial, real-world case studies of application of hybrid model- and data-driven Machine Learning methods to solve engineering and technology problems;
- Scientific Machine Learning for Engineering and Industrial Applications;
- Model-based and data-driven approaches for the resilience, safety and reliability of autonomous features and systems;
- Data and Model Governance, Data Analytics and Visualisation, Patterns and Data Modelling for complex industrial and engineering systems;
- Software Tools and Verification, Model Validation for Engineered Cyber-Physical Systems;
- Knowledge discovery and knowledge engineering based on knowledge graphs and Machine Learning for automatic learning from engineering data streams;
- Applications of advanced Machine Learning methods for diagnostics and prognostics and integrated systems healthcare management.
Regular and short papers are welcome. All submissions will be peer-reviewed; all accepted papers will be included and published by Springer as a volume of Advances in Intelligent Systems and Computing as UKCI 2021 conference proceedings. At least one of the authors of any accepted paper is requested to register the paper at the conference.
Selected papers in substantially extended form will be considered for publication in a special issue of Expert Systems: The Journal of Knowledge Engineering (IF: 1.546).
Paper Submission Guidelines
All papers will be submitted electronically in PDF format through the
EasyChair EDMA-2020 international workshop submission here>>
More details are available here>>
The material submitted should not be published or under review elsewhere. Each paper is limited to 6 pages (short papers) or 12 pages (regular paper) using Springer conference proceedings guidelines available from the UKCI 2021 website.
Paper Submission Deadline: 7 June 2021
Authors Notification: 28 June 2021
Early Registration Due: 6 July 2021
Camera-Ready Paper Due: 16 July 2021
Conference Date: 8-10 September 2021
Dr Amr Abdullatif, University of Bradford, UK
Professor Felician Campean, University of Bradford, UK
Professor David Delaux, Valeo
Professor Daniel Neagu, University of Bradford, UK
Dr Emanuele Angiolini, Jaguar Land Rover, UK
Dr Alberto Cabri, University of Genoa, Italy
Dr Cuong Dao, Univeristy of Bradford, UK
Samuele De Guido, Institute of Digital Engineering, Loughborough University, UK
Dr Oscar Garcia-Afonso, Universidad de La Laguna, Spain
Professor Gongde Guo, Fujian Normal University, China
Dr Jon Hall, Open University, UK
Dr Jose I Aizpurua Unanue, Mondragon University, Spain
Dr Sohag Kabir, University of Bradford, UK
Dr Raluca Lefticaru, University of Bradford, UK
Navein Madhavan, Institute of Digital Engineering, Loughborough University UK
Professor Francesco Masulli, University of Genoa, Italy
Dr Geev Mokryani, University of Bradford, UK
Dr Paula Palade, Jaguar Land Rover, UK
Professor Vasile Palade, Coventry University, UK
Dr Luca Parisi, University of Bradford, UK
Professor Stefano Rovetta, University of Genoa, Italy
Dr Daniele Scrimieri, University of Bradford, UK
Professor Hissam Tawfik, Leeds Beckett University, UK
Prof Longhzi Yang, Northumbria University, UK
Dr Kit Qichun Zhang, University of Bradford, UK
Previous EDMA Workshops
2019 - 3rd EDMA Workshop in conjunction with 19th Annual UK Workshop on Computational Intelligence, 4-5th September 2019, Portsmouth.
2018 - 2nd EDMA Workshop in conjunction with 4th IEEE International Conference on Data Science & Systems, 28-30 June 2018, Exeter
2017 - 1st EDMA Workshop in conjunction with the 10th IEEE International Conference on Cyber, Physical and Social Computing (IEEE CPSCom-2017), 21-23 June 2017, Exeter.
Programme will be available shortly