SISFAI2021: Semantic Interoperability of Sensitive Data in Federated AI October 25, 2021 |
Conference website | https://sisfai.github.io |
Submission link | https://easychair.org/conferences/?conf=sisfai2021 |
Submission deadline | June 18, 2021 |
Background and Goals
In the Industry 4.0 era, digital enterprises generate and use vast amounts of data that are captured and stored at different locations to improve their business models by leveraging Artificial Intelligence (AI). AI systems that rely on central data processing are not suitable in most applications since central data processing leads to issues on data accessibility, standardization, privacy, and trustworthiness. Furthermore, semantic interoperability plays a fundamental role in applications where data have become increasingly diverse and complex. AI systems may have biased or even potentially dangerous results if the meaning of data is not well understood.
This workshop aims to address the semantic interoperability of federated data integration approaches for advanced analytics provided by AI applications that rely on different conditions for data accessibility. These approaches may include AI concerns on privacy, trust, resilience, digital ethics, law, and human rights and should follow the FAIR principles to foster not only higher levels of semantic interoperability but also findability, accessibility, and reusability.
Topics
The topics of interest include, but are not limited to, the following:
- Semantic data sharing and sovereignty
- Semantic interoperability for machine learning
- Federated data integration
- Federated learning with linked data
- Responsible process mining
- Service-oriented architectures with event-driven semantic data
- Service choreography in different data jurisdictions
- Event-driven privacy for process data
- Responsible event mining
- Process mining in sensitive data
- Distributed FAIR workflows and software
- Reproducibility of machine learning notebooks
- Trustworthiness in distributed AI systems
Submission and Publication
Submitted papers should be in PDF format and follow the IEEE Proceedings Formatting Guideline (6-10 pages). The papers will be evaluated based on their scientific and technical contribution as well as their appropriateness, significance, and clarity by at least two members of the Program Committee. Each accepted paper that will be presented at the workshop must have one of its authors registered to EDOC’21 before the camera-ready deadline. Accepted and presented papers will be published by the IEEE Computer Society Press in a workshop proceedings and made available through IEEE Xplore and the IEEE Digital Library. Selected papers will be invited to submit an extended version to the special issue on Privacy, Trust and Fairness in Data of MDPI's Applied Science journal.
Committees
Program Committee
- Hans Weigand (Tilburg University, the Netherlands);
- Henderik Proper (Luxembourg Institute of Science and Technology, Luxembourg);
- Paul Johannesson (Stockholm University, Sweden);
- Zaharah Bukhsh (Eindhoven University of Technology, the Netherlands);
- Marten van Sinderen (University of Twente, the Netherlands);
- Luís Ferreira Pires (University of Twente, the Netherlands);
- Luiz Olavo Bonino da Silva Santos (University of Twente, the Netherlands);
- Tiago Prince Sales (Free University of Bolzano-Bozen, Italy)
Organizing committee
- João Moreira (University of Twente, the Netherlands);
- Faiza Bukhsh (University of Twente, the Netherlands)
Venue
The workshop will be a mixed physical/virtual workshop in the University of Twente, Enschede, the Netherlands. The workshop will be held in conjunction with the EDOC 2021 Enterprise Computing conference.
Contact
All questions about submissions should be emailed to m.j.vansinderen@utwente.nl.