EDMA2020 has been postponed until Sept. 2021 due to the COVID-19 Crisis

This year the 4th InternationalĀ Engineering Data- and Model-Driven Applications Workshop (EDMA-2020) will be heldĀ in conjunction with UKCI 2020 at Aberystwyth University.

EDMA paper submissions should be made at: https://easychair.org/conferences/?conf=edma2020

‘Important dates’ are not the same as those for UKCI – see below for further detail

About EDMA:

We are witnessing a dramatic increase of large engineering data resource availability and accessibility. Data-driven technologies, sensors connected through the Internet of Things (IoT) and big data capabilities nowadays show sustained development throughout the life cycle, from R&D testing to manufacturing, use and retirement.

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 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 data assessment, mining, 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 efficient aggregation, integration, analysis and governance of data and models, 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), which need to retain relevance and context of the underlying business process that needs to be addressed and augmented via such tools.

The 4th EDMA International Workshop calls for industry and academic experts and researchers working across computing and engineering divide to share their views, experiences and best practices on the use of knowledge discovery, 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.

EDMA Workshop Topics

This 4th EDMA International Workshop (in a series started in 2017) aims to provide a forum for presentations and discussions sharing insights of current challenges, knowledge, expertise and solutions regarding trends and technologies for the use of data and models for dealing with the evolving complexity in systems, within an extended Industry 4.0 context. The workshop committee members invite contributions from across engineering and data science researchers on data (Knowledge Discovery, Machine Learning, Big Data Analytics) and engineering model-based methods to deliver effective and efficient solutions to current challenges of handling complexity in real-world engineering and industrial applications.

The 4th EDMA International Workshop Committee Members invite original contributions (reviews and surveys, technical and research papers) from industry and academia experts and researchers on case studies, methodologies, formalisms, algorithms and solutions for the following topics and related areas:

  • Knowledge-enabled Machine Learning frameworks and case studies;
  • Scientific Machine Learning for Engineering and Industrial Applications;
  • Data-driven approaches for the resilience 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;
  • Computational Modelling Techniques for industrial processes and workflows, as well as applied to biophysical, mathematical modelling of pathophysiology; 
  • Software Tools and Verification, Model Validation for Engineered Cyber-Physical Systems;
  • Knowledge discovery from unstructured and semi-structured data;
  • Knowledge engineering based on knowledge graphs and Machine Learning for automatic learning from data streams;  
  • Advanced Machine Learning methods for hybrid diagnostics and prognostics and automated healthcare assessment, with industrial and medical applications;

As in previous years, a prominent industry expert will deliver an agenda setting keynote to the workshop.

Paper Submissions

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 2020 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: 1.505).

Paper Submission Guidelines

All papers will be submitted electronically in PDF format through the 

EasyChair EDMA-2020 international workshop submission:

https://easychair.org/conferences/?conf=edma2020

More details are available from: https://ukci2020.dcs.aber.ac.uk/edma/

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 2020 website.

Important Dates

Paper Submission Deadline: 1 June 2020

Authors Notification: 20 June 2020

Early Registration Due: 6 July 2020

Camera-Ready Paper Due: 13 July 2020

Conference Date: 9-11 September 2020

Organising Committee

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

Technical Committee:

Dr Alberto Cabri, University of Genoa, Italy

Professor Gongde Guo, Fujian Normal University, China

Dr Jon Hall, Open University, UK

Professor Francesco Masulli, University of Genoa, Italy

Professor Vasile Palade, Coventry University, UK

Dr Luca Parisi, University of Bradford, UK

Professor Stefano Rovetta, University of Genoa, Italy

Professor Hissam Tawfik, Leeds Beckett University, UK

Dr Paul Trundle, University of Bradford, UK

Dr Longhzi Yang, Northumbria University, UK

Previous EDMA Workshops

2019: 3rd EDMA Workshop in conjunction with 19th Annual UK Workshop on Computational Intelligence, 4-5thSeptember 2019, Portsmouth, https://www.ukci2019.port.ac.uk/erma-workshop/

2018: 2nd EDMA Workshop in conjunction with 4th IEEE International Conference on Data Science & Systems, 28-30 June 2018, Exeter, http://cse.stfx.ca/~dss2018/WSS.php

2017: 1st EDMA Workshop in conjunction with the 10th IEEE International Conference on Cyber, Physical and Social Computing (IEEE CPSCom-2017) http://cse.stfx.ca/~CPSCom2017/WSS.php