Learning Health Systems · 2023 · 19 citations · 23 references
ComputingBiologyHealth Data StandardsMethod ValidationSystematicsData ArchivingData LineageData ProvenanceSample CollectionSpecimen CollectionSpecimen DocumentationBenefit-sharingData Lineage TrackingData ProcessingRegulatory RequirementsSpecimen Collection QualitySpecimen Metadata CaptureSpecimen Provenance DocumentationSpecimen Standardization
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.
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The FAIR Guiding Principles for scientific data management and stewardship
Mark D. Wilkinson, Michel Dumontier, IJsbrand Jan Aalbersberg et al. · Scientific Data · 2016 · 17.8K citations · Full text
Raise standards for preclinical cancer research
C. Glenn Begley, Lee M. Ellis · Nature · 2012 · 2.9K citations · Full text
Medicine, Cancer Biology, Oncology +12
A call for transparent reporting to optimize the predictive value of preclinical research
Story C. Landis, Susan Amara, Khusru Asadullah et al. · Nature · 2012 · 1.2K citations · Full text