Wittner Rudolf, Holub Petr, Mascia Cecilia, Frexia Francesca, Müller Heimo, Plass Markus, Allocca Clare, Betsou Fay, Burdett Tony, Cancio Ibon, Chapman Adriane, Chapman Martin, Courtot Mélanie, Curcin Vasa, Eder Johann, Elliot Mark, Exter Katrina, Goble Carole, Golebiewski Martin, Kisler Bron, Kremer Andreas, Leo Simone, Lin-Gibson Sheng, Marsano Anna, Mattavelli Marco, Moore Josh, Nakae Hiroki, Perseil Isabelle, Salman Ayat, Sluka James, Soiland-Reyes Stian, Strambio-De-Castillia Caterina, Sussman Michael, Swedlow Jason R, Zatloukal Kurt, Geiger Jörg
BBMRI-ERIC Graz Austria.
Institute of Computer Science & Faculty of Informatics Masaryk University Brno Czechia.
Learn Health Syst. 2023 Apr 18;8(1):e10365. doi: 10.1002/lrh2.10365. eCollection 2024 Jan.
Open and practical exchange, dissemination, and reuse of specimens and data have become a fundamental requirement for life sciences research. The quality of the data obtained and thus the findings and knowledge derived is thus significantly influenced by the quality of the samples, the experimental methods, and the data analysis. Therefore, a comprehensive and precise documentation of the pre-analytical conditions, the analytical procedures, and the data processing are essential to be able to assess the validity of the research results. With the increasing importance of the exchange, reuse, and sharing of data and samples, procedures are required that enable cross-organizational documentation, traceability, and non-repudiation. At present, this information on the provenance of samples and data is mostly either sparse, incomplete, or incoherent. Since there is no uniform framework, this information is usually only provided within the organization and not interoperably. At the same time, the collection and sharing of biological and environmental specimens increasingly require definition and documentation of benefit sharing and compliance to regulatory requirements rather than consideration of pure scientific needs. In this publication, we present an ongoing standardization effort to provide trustworthy machine-actionable documentation of the data lineage and specimens. We would like to invite experts from the biotechnology and biomedical fields to further contribute to the standard.
样本和数据的开放且实用的交流、传播及再利用已成为生命科学研究的一项基本要求。所获取数据的质量,以及由此得出的研究结果和知识,会受到样本质量、实验方法及数据分析的显著影响。因此,对分析前条件、分析程序及数据处理进行全面而精确的记录,对于评估研究结果的有效性至关重要。随着数据和样本的交流、再利用及共享的重要性日益增加,需要有能实现跨组织记录、可追溯性及不可否认性的程序。目前,关于样本和数据来源的此类信息大多要么稀少、不完整,要么不连贯。由于没有统一的框架,此类信息通常仅在组织内部提供,无法实现互操作。与此同时,生物和环境样本的收集与共享越来越需要对利益共享进行定义和记录,并遵守监管要求,而不仅仅是考虑纯粹的科学需求。在本出版物中,我们展示了一项正在进行的标准化工作,以提供关于数据谱系和样本的可信且机器可操作的文档。我们诚邀生物技术和生物医学领域的专家为该标准做出进一步贡献。