Smarter Extraction of Scholarly Metadata using Knowledge Graphs and Language Models (SESAME). The mission statement of SESAME is to bring together researchers and practitioners to explore how AI-driven curation approaches leveraging large language models and knowledge graphs to strengthen digital libraries infrastructures. The proposed workshop is intended for a broader spectrum of participants within the JCDL community, including researchers, data curators, and policy makers.

1st SESAME-2025 workshop, to be held on 15-19, December 2025 at JCDL 2025 (Virtual Event)

Submission Guidelines

The workshop invites original papers and not simultaneously submitted to another journal or conference or workshop. The workshop call focuses on three categories listed below. Each submission will be reviewed by domain experts according to the JCDL guidelines.

• Long papers: 6–8 pages (excluding references)
• Short papers: 2–4 pages (excluding references)
• Demos / Data / Position: 2–4 pages (excluding references)

List of Topics

• Research Artifacts Metadata Modeling and Granularity
  • Metadata of scholarly publications, datasets, software, and models
  • Metadata quality assessment, enrichment, and curation
  • Research artifacts provenance across digital libraries
  • Cross-disciplinary metadata interoperability
• Large Language Models (LLMs) and NLP for Metadata
  • Research artifacts metadata extraction using LLMs
  • Prompt engineering, fine-tuning for scholarly information extraction
  • Evaluation, reliability and issues for LLM-generated metadata
  • Comparative studies of LLM-based vs traditional methods
  • LLMs for metadata curation and normalization
  • AI-driven curation, preservation at scale, and long-term accessibility
• Knowledge Graphs and Linked Data
  • Construction of scholarly knowledge graphs from heterogeneous metadata
  • Linking and aligning entities across repositories and infrastructures
  • Applications of KGs for discovery, recommendation, and impact
• Digital Libraries and Infrastructure
  • Integration of metadata workflows into digital library systems
  • Benchmarks, datasets, and shared tasks for metadata extraction and modeling
  • System design for metadata-intensive digital library applications
• Societal, Ethical Impact and Future Policy Directions
  • Ethical implications of AI-driven metadata generation and curation
  • Metadata for open science, reproducibility, and research integrity
  • Societal impacts of metadata granularity on scholarly evaluation and equity
  • Policy frameworks and governance for interoperable metadata infrastructures

Committees

Program Committee

• To be announced 

Organizing committee

• Dr. Muhammad Asif Suryani
• Dr. Brigitte Mathiak
• Dr. Florian Reitz 
• Dr. Florian Jäckel
• Prof. Dr. Ansgar Scherp

Contact

All questions about submissions should be emailed to asif.suryani@gesis.org