User:Shawndouglas/sandbox/sublevel12

This is sublevel12 of my sandbox, where I play with features and test MediaWiki code. If you wish to leave a comment for me, please see my discussion page instead.

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

First discussed during a 2014 workshop dedicated to "overcoming data discovery and reuse obstacles," the FAIR Guiding Principles were published by Wilkinson et al. in 2016 as a stakeholder collaboration driven to see research "objects" (i.e., research data and information of all shapes and formats) become more universally findable, accessible, interoperable and reusable (FAIR) by both machines and people.^[1]

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

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