User:Shawndouglas/sandbox/sublevel12

Sandbox begins below

[[File:|right|380px]] Title: What are the potential implications of the FAIR data principles to laboratory informatics applications?

Author for citation: Shawn E. Douglas

License for content: Creative Commons Attribution-ShareAlike 4.0 International

Publication date: May 2024

Introduction

This brief topical article will examine

Blah blah blah

• LIMS and FAIR: Journal:A roadmap for LIMS at NIST Material Measurement Laboratory
• ELNs and FAIR: Structure-based knowledge acquisition from electronic lab notebooks for research data provenance documentation
• Biomedical software and FAIR: https://www.nature.com/articles/s41597-023-02463-x
• Making software workflows FAIR: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10538699/
• AWS and FAIR for healthcare and life sciences: https://aws.amazon.com/blogs/industries/implement-fair-scientific-data-principles-when-building-hcls-data-lakes/
• APIs and FAIR data: https://www.labguru.com/blog/fair-data-principles-and-apis
• Bioinformatics LIMS and FAIR: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8425304/
• Labbit: https://labbit.com/fair-data-lims

• https://riojournal.com/article/96075/ Importance of metadata for FAIR data objects
• Deep talk about metadata: Journal:Shared metadata for data-centric materials science
• More metadata, for findability: "While descriptive metadata may not be available, support for generalized CRUD operations requires essential structural and administrative metadata to be captured, stored, and made available for requestors. Metadata capture must be highly automated and reliable, both in terms of technical reliability and ensured metadata quality." Journal:Making data and workflows findable for machines
• More metadat, for reusability: "make recommendations for assigning identifiers and metadata that supports sample tracking, integration, and reuse. Our goal is to provide a practical approach to sample management, geared towards ecosystem scientists who contribute and reuse sample data." Journal:Sample identifiers and metadata to support data management and reuse in multidisciplinary ecosystem sciences

• "The principles should be considered during development of informatics systems to further promote data discovery and reuse. In Table 1, we have correlated the various BRICS functional components to the FAIR principles to illustrate the extent to which each of the components contributes towards the principles." Journal:Development of an informatics system for accelerating biomedical research

Restricted or personal information while still being FAIR

• Journal:FAIR Health Informatics: A health informatics framework for verifiable and explainable data analysis
• Journal:Restricted data management: The current practice and the future

• Linking databases of data that haven't seen proper "FAIR-ification" and metadata handling won't be as useful.
• Further discussion on data quality in the scope of FAIR: Journal:Towards a contextual approach to data quality