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.