1st Workshop on Generation of Synthetic Datasets for Information Systems (GenSyn)
16-17 June 2025, Vienna, Austria
About The Event
In the age of advanced information systems, data is crucial for deploying and evaluating systems, but collecting usable benchmarks is challenging due to privacy, scarcity, and legal concerns. Synthetic datasets have become valuable for machine learning tasks, supporting data-driven applications, AI, IoT, Digital Twins, and business process models. The GenSyn workshop aims to discuss generative AI and classical techniques for creating synthetic datasets for AI and non-AI information systems, presenting state-of-the-art tools and approaches.
Where
Co-located with the 37th International Conference on Advanced Information Systems (CaiSE 2025)
When
June 16th-17th, 2025
Call for papers
Our workshop is a dedicated forum to encourage the exploration of how synthetic datasets can be integrated across diverse information system engineering (ISE) contexts, which is a developing field and a promising application area for AI, where many approaches are not mature enough yet for publication at the main track and are more exploratory. Areas of Interest include, but are not limited to:
- Synthetic data for AI and Machine Learning in ISE: Generating high-quality synthetic data to support machine learning applications within ISE, including deep learning, natural language processing, and generative AI models;
- Method, techniques, and algorithms to generate synthetic data for IS, spanning from AI/ML generative models to traditional frameworks, e.g., model-based tools;
- Synthetic data generation to support data management systems, e.g., DBMS and knowledge graphs;
- Process Automation and Mining with Synthetic Data: Utilizing synthetic datasets to improve data-driven applications, process mining, and business process modeling and simulation;
- Synthetic datasets for real-time application: Creating synthetic datasets to conceive digital twins, simulate real-time data streams in IoT systems, and data for advanced driver assistance systems (ADAS);
- Data-driven compliance and governance: Addressing regulatory and privacy concerns through synthetic data generation to support decision-making and compliance in sensitive systems, e.g., eGovernment and healthcare;
- Evaluation of Synthetic Data in Real-world Contexts: Developing benchmarks and methodologies to validate the quality, diversity, sustainability, and realism of synthetic datasets in business intelligence and industry-specific systems;
- Case studies and experience reports from academia and industry
Important dates
- Full paper submissions: March 7th, 2025
- Notification of acceptance: April 7th, 2025
- Camera-ready copies: April 14th, 2025
- Author registration: April 14th, 2025
- Workshop date: 16th June 2025
Submission process
Submissions to the presentation-oriented workshop must conform to the Springer LNCS/LNBIP format and the page limits includes references, figures, tables, and appendixes. Following the Springer guidelines, we accept the following types of submissions:
- Full papers up to 12 pages, to present mature works with a rigorous evaluation
- Short papers from 6 up to 8 pages, to present early-stage works with a ligh-weight evaluation or proof-of-concept
The results described in the submitted paper must be unpublished and must not be under review elsewhere. Three to five keywords characterizing the paper should be listed at the end of the abstract. The selected papers will be discussed on with the paper reviewers as well as during the program board meeting. As the review process is not blind, please indicate your name and affiliation when you submit. According to the Springer standards, the overall acceptance rate cannot exceed 45%-50%.
Organizers
Claudio Di Sipio
Post-doc researcher, University of l'AquilaArianna Fedeli
Post-doc researcher, Gran Sasso Science InstituteRiccardo Rubei
Post-doc researcher, University of l'AquilaEduard Kamburjan
Assistant professor, IT University of Copenhagen PC members
TBD
Program
TBD
Event Venue: TU Wien
Coming soon!