GenSyn2026

Call for papers

This 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:

• Methods, techniques, and algorithms to generate high-quality synthetic data for IS, including traditional frameworks, natural language process algorithms, and generative AI models.
• Synthetic data generation for databases and knowledge graphs, including queries and data integration.
• Process Automation and Mining with Synthetic Databy utilizing synthetic datasets to improve data-driven applications, process mining, and business process modeling and simulation.
• Synthetic datasets for real-time application by creating synthetic datasets to train 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.
• Producing novel synthetic dataset benchmarks for different application domains where data scarcity represents an issue, e.g., industry settings or healthcare.
• Evaluation of Synthetic Data in Real-world Contexts in particular methodologies to validate the quality, diversity, sustainability, and realism of existing synthetic datasets in business intelligence and industry-specific systems.
• Case studies and experience reports from academia and industry.

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

Papers should be submitted as PDF, following Springer’s LNCS format. Submissions not conforming to the LNCS format, the page limitations, or being obviously out of the scope of the workshop, will be rejected without review. For Springer’s LNCS format, see the guidelines provided at Springer’s site

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%.