UniProt building community metrics for FAIR and TRUSTworthy resources

UniProt 为公平和值得信赖的资源构建社区指标

• 批准号: 10595850
• 负责人: Alex Bateman
• 金额: $ 19.8万
• 依托单位: EUROPEAN MOLECULAR BIOLOGY LABORATORY
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-18 至 2026-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10595850
• 关键词: Amino Acid Sequence; Awareness; Biomedical Research; Certification; Collection; Communities; Consensus; Data; Databases; Development; Educational workshop; Ensure; Evaluation; FAIR principles; Fostering; Funding; Funding Agency; Genes; Goals; Graph; Institutes; Legal patent; Literature; Measures; Metadata; Mission; Ontology; Paper; Process; Proteins; Publications; Research Infrastructure; Resources; Self Assessment; Source Code; TRUST principles; Time; United States National Institutes of Health; Work; base; biomedical resource; community building; data repository; data resource; data reuse; data standards; interest; knowledgebase; parent grant; tool; trustworthiness

PROJECT SUMMARY UNIPROT BUILDING COMMUNITY METRICS FOR FAIR AND TRUSTWORTHY RESOURCES- SUPPLEMENT REQUEST 2022 The mission of the Universal Protein Resource(UniProt) is to support biomedical research by providing a freely available, stable, comprehensive, richly and accurately annotated sequence knowledgebase. The overall goal of this Supplement application for the UniProt parent grant (U24HG007822) is to (i) support UniProt to assess and increase alignment with FAIR and TRUST principles, (ii) to provide a tool to enable data resources to help evaluate their usage, utility, and impact and (iii) advance the the evaluation of data reuse across data repositories. UniProt has been a leader in the provision of protein sequence and annotation data since its inception in 2002. As a large and central piece of the biomedical research infrastructure it has seen a progresive professionalisation and hardening of its processes and development. This has also happened to the field as a whole with the creation of sets of principles such as the FAIR and TRUST principles as well as a growing variety of certifications. UniProt was identified as an exemplar in the original publication describing the FAIR principles and was also an early adopter of the TRUST principles gaining CoreTrustSeal certification in May 2020. We will carry out a further self assessment of our FAIR and TRUST compliance as part of the project leading to a set of goals supporting our application for renewal of CoreTrustSeal certification in 2023. This work will help to ensure we remain well aligned with community standards for data and metadata as well as refresh our outlook for management processes of UniProt. We believe that we are at the forefront of developing biomedical resources and have developed a range of metrics for understanding the usage, impact and utility of UniProt. We will develop an interface in GoogleColab to enable the community to view metrics for UniProt or any other biomedical resource of interest in a rapid way based on publicly available APIs to literature and patent databases. We are aware that UniProt data is widely reused across other data resources and this reuse is extremely difficult to measure and can be considered the greatest gap in our understanding of the impact of biomedical data resources. We will hold a workshop with key stakeholders to discuss ways to measure reuse across NIH data resources.

项目总结 UniProt为公平和值得信赖的资源构建社区指标- 补充申请2022 全球蛋白质资源(UniProt)的使命是通过以下方式支持生物医学研究 提供免费可用的、稳定的、全面的、丰富和准确的注释序列 知识库。这份UniProt家长补助金补充申请的总体目标 (U24HG007822)是为了(I)支持UniProt评估并增加与公平和信任的一致性 原则；(Ii)提供工具，使数据资源能够帮助评估其使用情况、效用和 影响和(3)推进对跨数据存储库的数据重复使用的评估。UniProt已经成为 自2002年成立以来，在提供蛋白质序列和注释数据方面处于领先地位。作为一名 它是生物医学研究基础设施的重要核心部分，它已经取得了进展 其流程和开发的专业化和强化。这种情况也发生在 整个领域制定了一整套原则，如公平和信任原则 以及种类越来越多的认证。UniProt在原始版本中被确定为范例 描述公平原则的出版物，也是信托原则的早期采用者 于2020年5月获得CoreTrustSeal认证。我们将对我们的 作为项目的一部分，公平和可信的合规性导致了一系列支持我们的 申请于2023年续展CoreTrustSeal认证。这项工作将有助于确保我们 保持与社区数据和元数据标准的良好一致性，并更新我们的前景 用于UniProt的管理流程。我们相信，我们处于发展的前沿 生物医学资源，并开发了一系列指标来了解使用、影响 和UniProt的实用性。我们将在GoogleColab中开发一个界面，使社区能够查看 UniProt或任何其他感兴趣的生物医学资源的指标，基于公开的快速方式 提供文献和专利数据库的API。我们知道UniProt数据被广泛重复使用 跨其他数据资源，这种重用是非常难以衡量的，可以考虑 我们对生物医学数据资源影响的理解存在最大差距。我们将举行一场 与主要利益相关者举行研讨会，讨论如何衡量NIH数据资源的重用性。