A5031565236- Research Data Management Practices
- Scientific Computing and Data Management
- Biomedical Text Mining and Ontologies
- Semantic Web and Ontologies
- Data Quality and Management
- Genetics, Bioinformatics, and Biomedical Research
- Medical Coding and Health Information
- Big Data and Business Intelligence
- Libraries and Information Services
University of Oxford
2019-2023
The FAIR principles have been widely cited, endorsed and adopted by a broad range of stakeholders since their publication in 2016. By intention, the 15 guiding do not dictate specific technological implementations, but provide guidance for improving Findability, Accessibility, Interoperability Reusability digital resources. This has likely contributed to adoption principles, because individual stakeholder communities can implement own solutions. However, it also resulted inconsistent...
Abstract The notion that data should be Findable, Accessible, Interoperable and Reusable, according to the FAIR Principles, has become a global norm for good stewardship prerequisite reproducibility. Nowadays, guides policy actions professional practices in public private sectors. Despite such endorsements, however, Principles are aspirational, remaining elusive at best, intimidating worst. To address lack of practical guidance, help with capability gaps, we developed Cookbook, an open,...
Abstract Transparent evaluations of FAIRness are increasingly required by a wide range stakeholders, from scientists to publishers, funding agencies and policy makers. We propose scalable, automatable framework evaluate digital resources that encompasses measurable indicators, open source tools, participation guidelines, which come together accommodate domain relevant community-defined FAIR assessments. The components the are: (1) Maturity Indicators – community-authored specifications...
The Investigation/Study/Assay (ISA) Metadata Framework is an established and widely used set of open source community specifications software tools for enabling discovery, exchange, publication metadata from experiments in the life sciences. original ISA suite provided a user-facing Java creating manipulating information structured ISA-Tab-a now tabular format. To make framework more accessible to machines enable programmatic manipulation experiment metadata, JSON serialization ISA-JSON was...
Community-developed minimum information checklists are designed to drive the rich and consistent reporting of metadata, underpinning reproducibility reuse data. These guidelines, however, usually in form narratives intended for human consumption. Modular reusable machine-readable versions also needed. Firstly, provide necessary quantitative verifiable measures degree which metadata descriptors meet these community requirements, a requirement FAIR Principles. Secondly, encourage creation...
Abstract Transparent evaluations of FAIRness are increasingly required by a wide range stakeholders, from scientists to publishers, funding agencies and policy makers. We propose scalable, automatable framework evaluate digital resources that encompasses measurable indicators, open source tools, participation guidelines, which come together accommodate domain relevant community-defined FAIR assessments. The components the are: (1) Maturity Indicators - community-authored specifications...
Thousands of community-developed (meta)data guidelines, models, ontologies, schemas and formats have been created implemented by several thousand data repositories knowledge-bases, across all disciplines. These resources are necessary to meet government, funder publisher expectations greater transparency access preservation related research publications. This obligates researchers ensure their is FAIR, share using the appropriate standards, store in sustainable community-adopted...