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1st International Workshop on Graph-Driven Scientific Knowledge Architectures (GDSKA'26)

Co-located with IEEE eScience 2026

Call for Papers

Graph-based technologies, including knowledge graphs, ontologies, graph databases, graph analytics, and graph machine learning, are emerging as powerful unifying abstractions across all stages of the scientific research lifecycle.

This workshop explores how these technologies can be applied to represent and integrate knowledge, model workflow dependencies, enable semantic interoperability across heterogeneous datasets, and support resource discovery, reasoning, and orchestration in distributed computing environments, including HPC, Cloud, Edge, and IoT infrastructures spanning the computing continuum.

Topics of Interest

Topics of interest include, but are not limited to:

  • Knowledge graph construction, population, and querying in scientific contexts
  • Ontologies and linked data for FAIR data principles and reproducibility
  • Graph-based provenance tracking and data lineage
  • Graph-driven workflow modeling and pipeline orchestration
  • Knowledge graphs for resource description and scheduling across distributed infrastructures
  • Graph databases and big data analytics for large-scale data management
  • Graph reasoning (graph neural networks and graph analytics) applied to scientific datasets and infrastructure problems
  • Scalable graph processing for large-scale workloads
  • Federated knowledge graphs across institutions and research domains

Beyond infrastructure and middleware concerns, the workshop welcomes contributions from any domain of science that employs graph-based methods as a primary tool for data integration, analysis, or knowledge discovery. This includes, but is not limited to, life sciences and biomedical research, climate and Earth sciences, high-energy physics and astronomy, materials science and chemistry, social sciences, and digital humanities.

Important Dates

  • Paper submission: July 14th, 2026 (AoE)
  • Notification of Acceptance: August 1st, 2026

  • Camera-ready paper due: August 7th, 2026

  • Submission link

Submission Guidelines

Authors submitting papers for GDSKA'26 must do so via the EasyChair submission web page. Upon accessing the submission page, authors should click on "make a new submission" and then select the track "The 1st Workshop on Graph Data Science-Driven Knowledge Analysis" from the list of available tracks.

Authors are invited to submit technical papers of no more than 8 pages in PDF format, including figures and references. The papers should be formatted according to the IEEE 8.5x11 manuscript guidelines.

Submitted papers must contain original work that has not appeared in and is not under consideration for another conference, journal, or workshop. Each paper will receive up to 3 reviews from experts in the area. There will be no revision rebuttal process and the review will be one-pass.

Publication

Accepted papers will be published in the IEEE eScience 2026 Workshop Proceedings and presented at the workshop.

Organization

Workshop Chairs

  • Gabriele Morabito, University of Messina, Italy
  • Dante D. Sánchez-Gallegos, University Carlos III of Madrid, Spain
  • Yannis Tzitzikas, University of Crete, Greece

Program Committee

  • TBA