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Ontologies4Cat: investigating the landscape of ontologies for catalysis research data management
Journal of Cheminformatics ( IF 8.6 ) Pub Date : 2024-02-07 , DOI: 10.1186/s13321-024-00807-2
Alexander S. Behr , Hendrik Borgelt , Norbert Kockmann

As scientific digitization advances it is imperative ensuring data is Findable, Accessible, Interoperable, and Reusable (FAIR) for machine-processable data. Ontologies play a vital role in enhancing data FAIRness by explicitly representing knowledge in a machine-understandable format. Research data in catalysis research often exhibits complexity and diversity, necessitating a respectively broad collection of ontologies. While ontology portals such as EBI OLS and BioPortal aid in ontology discovery, they lack deep classification, while quality metrics for ontology reusability and domains are absent for the domain of catalysis research. Thus, this work provides an approach for systematic collection of ontology metadata with focus on the catalysis research data value chain. By classifying ontologies by subdomains of catalysis research, the approach is offering efficient comparison across ontologies. Furthermore, a workflow and codebase is presented, facilitating representation of the metadata on GitHub. Finally, a method is presented to automatically map the classes contained in the ontologies of the metadata collection against each other, providing further insights on relatedness of the ontologies listed. The presented methodology is designed for its reusability, enabling its adaptation to other ontology collections or domains of knowledge. The ontology metadata taken up for this work and the code developed and described in this work are available in a GitHub repository at: https://github.com/nfdi4cat/Ontology-Overview-of-NFDI4Cat .

中文翻译:

Ontologies4Cat:调查催化研究数据管理本体的前景

随着科学数字化的进步,确保机器可处理数据的可查找、可访问、可互操作和可重用 (FAIR) 势在必行。本体通过以机器可理解的格式明确表示知识,在增强数据公平性方面发挥着至关重要的作用。催化研究中的研究数据通常表现出复杂性和多样性,需要分别广泛的本体论集合。虽然 EBI OLS 和 BioPortal 等本体门户有助于本体发现,但它们缺乏深度分类,而催化研究领域则缺乏本体可重用性和领域的质量指标。因此,这项工作提供了一种系统收集本体元数据的方法,重点关注催化研究数据价值链。通过按催化研究的子领域对本体进行分类,该方法提供了跨本体的有效比较。此外,还提供了工作流程和代码库,有助于在 GitHub 上表示元数据。最后,提出了一种方法来自动将元数据集合的本体中包含的类相互映射,从而提供对列出的本体的相关性的进一步见解。所提出的方法是为了可重用性而设计的,使其能够适应其他本体集合或知识领域。本工作中使用的本体元数据以及本工作中开发和描述的代码可在 GitHub 存储库中找到:https://github.com/nfdi4cat/Ontology-Overview-of-NFDI4Cat。
更新日期:2024-02-08
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