Amsterdam, September 17-19, 2024

SeMatS 2024

International Workshop on Semantic Materials Science

Harnessing the Power of Semantic Web Technologies in Materials Science

at SEMANTICS 2024

OVERVIEW

Advanced technological solutions play a vital role in leveraging the potential of data and driving innovative research. However, the compatibility issues arising from different formats and structures of scientific data hinder progress in data generation, organization, storage, and sharing. To address these challenges, interoperability and efficient data access and analysis automation are crucial. The Semantic Web emerges as a powerful solution to overcome these obstacles.

Observing conferences on Materials Sciences Engineering (MSE) domain e.g. FEMS Euromat [https://euromat2023.com/] and MSE [https://dgm.de/mse/2022/program] the number of Semantic Web applications on Materials Science Engineering is significantly increasing, counting on more than 10 presentations on 2022 and more than 20 on 2023 . Due to this growing adoption of Semantic Web by the Materials Science community, we aim to attract participants focusing on the intersection of both areas.

The Semantic Web has been widely adopted in various fields, particularly in life sciences, over the past few decades. Notable examples include the Gene Ontology (GO), a comprehensive source of gene information; the Disease Ontology, which integrates medical vocabularies; and COVIDPUBGRAPH, a valuable data resource for COVID-19 publications.

Expanding and adapting Semantic Web technologies to the Materials Science domain can significantly enhance research outcomes by enabling the uniform consideration, integration, and analysis of heterogeneous data from diverse sources and formats. Implementing these technologies can improve the traceability and reproducibility of scientific procedures, experiments, and simulations. It also facilitates automatable data management solutions and empowers researchers to answer scientific inquiries using semantic queries. Moreover, machine learning methods can benefit from enhanced data completeness and coherence.

The primary objective of this workshop is to comprehensively implement Semantic Web Technologies in Materials Science while highlighting the associated benefits and challenges. It is crucial to make these technologies accessible to a broader community, as they have the potential to revolutionize Materials Science research. Additionally, we propose that manufacturers of testing machines prescribe this data structure as a standardized output format. Formal ontological knowledge can also serve as a teaching tool to provide a fundamental understanding of characterization methods, data and metadata structures, and essential technological tools.

During our workshop, we will provide an overview of existing approaches and implementations of Semantic Web technology in Materials Science. We will identify and categorize relevant works and offer valuable insights based on practical examples. This conference aims to bring together Materials Science and Semantic Web stakeholders to foster collaboration, exchange ideas, and drive innovation.

Join us as we explore the transformative possibilities of Semantic Web Technologies in Materials Science and pave the way for a more interconnected and efficient research landscape.

Submission Guidelines

All papers must be original and not simultaneously submitted to another journal or conference. The following paper categories are welcome:

• Format

  Submissions must be in PDF, formatted in the style of the Springer Publications format for Lecture Notes in Computer Science (LNCS). For details on the LNCS style, see Springer's Author Instructions. 

   

  Full research papers (8-12 pages)

  Papers presenting negative results (8-12 pages) 

  In Use and experience papers (8-12 pages)

  Position and vision papers (6-8 pages)

  Short research papers (4-6 pages)

  System/demo/in practice papers (4-6 pages)

  Industrial statement papers (2 pages)

   (plus unlimited references)

  Review and Publication

  All papers have to be submitted electronically via EasyChair.

  The accepted contributions will be published in the proceedings of the workshop through CEUR-WS. Each accepted paper needs to be presented by one of the authors at the workshop. 

List of Topics

The workshop will cover topics within the intersection of the scope of the Web Semantic and the Materials Science and Engineering domain (MSE), including but not limited to:

• Knowledge Graph construction in MSE

• Ontology design and design methodologies in the MSE domain

• Efficient integration and communication of ontologies in MSE

• Data interoperability and data integration in MSE

• Data quality assurance and data governance in SW-based MSE systems

• Ontology-based reasoning and inference in MSE

• Semantic search and information retrieval in MSE

• Semantic annotation and metadata management in MSE

• Machine learning and AI techniques applied to MSE using SW technologies

• Natural Language Processing (NLP) applied to MSE data

• Large Language Models (LLM)

• Visualization techniques for MSE data

• Microscope and image processing applications in MSE using SW technologies

• Collaborative and distributed approaches for managing MSE data

• Retrieval Augmented Generation (RAG)

• Lessons learned and best practices for implementing SW applications in MSE systems

Important Dates

• Submission: June 14, 2024 (11:59 pm, AoE)

• Notifications: July 05, 2024 (11:59 pm, AoE)

• Camera Ready: TBA

• Event: Amsterdam, September 17-19, 2024

Committees

Program Committee

• Angelika Gedsun (Universität Freiburg, Germany)

• Martin Glauer (Otto von Guericke University Magdeburg, Germany)

• Gerhard Goldbeck (Goldbeck Consulting, UK) 

• Abril Azocar Guzman (Forschungszentrum Jülich (FZJ), Germany)

• Heiko Hafok (Fraunhofer Institut for Mechanics of Materials IWM, Germany)

• Thomas Hanke (Fraunhofer Institut for Mechanics of Materials IWM, Germany)

• Fabio Le Piane (National Research Council of Italy, Italy)

• Martin Thomas Horsch (Norwegian University of Life Sciences, Norway)

• Francesco Mercuri (National Research Council of Italy, Italy) 

• Thilo Muth (Bundesanstalt für Materialforschung und -prüfung (BAM), Germany)

• Axel-Cyrille Ngonga Ngomo (Universität Paderborn, Germany)

• Ebrahim Norouzi (FIZ Karlsruhe – Leibniz Institute for Information Infrastructure, Germany)

• María Poveda-Villalón (Universidad Politécnica de Madrid, Spain)

• Muhammad Saleem (AKSW-University Leipzig, Germany)

• Tommaso Soru (Serendipity AI | Liber AI,  UK)

• Jorg Waitelonis (FIZ Karlsruhe – Leibniz Institute for Information Infrastructure, Germany)

• Lan Yang (Insight SFI Research Centre for Data Analytics, University of Galway, Ireland)

• Ghezal Ahmad Zia (Bundesanstalt für Materialforschung und -prüfung (BAM), Germany)

• Maribel Acosta (Technical University of Munich, Germany)

Organizing committee

• Andre Valdestilhas (Bundesanstalt für Materialforschung und -prüfung (BAM) , Germany)

• Huanyu Li (Linköping University, Sweden)

• Patrick Lambrix (Linköping University, Sweden)

• Harald Sack (FIZ Karlsruhe, Leibniz Institute for Information Infrastructure, Germany)

Contact

Andre Valdestilhas

andre.valdestilhas@bam.de

or 

firmao@gmail.com