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First discussed during a 2014 workshop dedicated to "overcoming data discovery and reuse obstacles," the [[Journal:The FAIR Guiding Principles for scientific data management and stewardship|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.<ref name="WilkinsonTheFAIR16">{{Cite journal |last=Wilkinson |first=Mark D. |last2=Dumontier |first2=Michel |last3=Aalbersberg |first3=IJsbrand Jan |last4=Appleton |first4=Gabrielle |last5=Axton |first5=Myles |last6=Baak |first6=Arie |last7=Blomberg |first7=Niklas |last8=Boiten |first8=Jan-Willem |last9=da Silva Santos |first9=Luiz Bonino |last10=Bourne |first10=Philip E. |last11=Bouwman |first11=Jildau |date=2016-03-15 |title=The FAIR Guiding Principles for scientific data management and stewardship |url=https://www.nature.com/articles/sdata201618 |journal=Scientific Data |language=en |volume=3 |issue=1 |pages=160018 |doi=10.1038/sdata.2016.18 |issn=2052-4463 |pmc=PMC4792175 |pmid=26978244}}</ref> The authors released the FAIR principles while recognizing that "one of the grand challenges of data-intensive science ... is to improve knowledge discovery through assisting both humans and their computational agents in the discovery of, access to, and integration and analysis of task-appropriate scientific data and other scholarly digital objects."<ref name="WilkinsonTheFAIR16" />
First discussed during a 2014 workshop dedicated to "overcoming data discovery and reuse obstacles," the [[Journal:The FAIR Guiding Principles for scientific data management and stewardship|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.<ref name="WilkinsonTheFAIR16">{{Cite journal |last=Wilkinson |first=Mark D. |last2=Dumontier |first2=Michel |last3=Aalbersberg |first3=IJsbrand Jan |last4=Appleton |first4=Gabrielle |last5=Axton |first5=Myles |last6=Baak |first6=Arie |last7=Blomberg |first7=Niklas |last8=Boiten |first8=Jan-Willem |last9=da Silva Santos |first9=Luiz Bonino |last10=Bourne |first10=Philip E. |last11=Bouwman |first11=Jildau |date=2016-03-15 |title=The FAIR Guiding Principles for scientific data management and stewardship |url=https://www.nature.com/articles/sdata201618 |journal=Scientific Data |language=en |volume=3 |issue=1 |pages=160018 |doi=10.1038/sdata.2016.18 |issn=2052-4463 |pmc=PMC4792175 |pmid=26978244}}</ref> The authors released the FAIR principles while recognizing that "one of the grand challenges of data-intensive science ... is to improve knowledge discovery through assisting both humans and their computational agents in the discovery of, access to, and integration and analysis of task-appropriate scientific data and other scholarly digital objects."<ref name="WilkinsonTheFAIR16" />


Since 2016, other research stakeholders have taken to publishing their thoughts about how the FAIR principles apply to their fields of study and practice<ref name="NIHPubMedSearch">{{cite web |url=https://pubmed.ncbi.nlm.nih.gov/?term=fair+data+principles |title=fair data principles |work=PubMed Search |publisher=National Institutes of Health, National Library of Medicine |accessdate=30 April 2024}}</ref>, including in ways beyond what perhaps was originally imagined by Wilkinson ''et al.''. For example, multiple authors have examined whether or not the software used in scientific endeavors itself can be considered a research object worth being developed and managed in tandem with the FAIR data principles.<ref>{{Cite journal |last=Hasselbring |first=Wilhelm |last2=Carr |first2=Leslie |last3=Hettrick |first3=Simon |last4=Packer |first4=Heather |last5=Tiropanis |first5=Thanassis |date=2020-02-25 |title=From FAIR research data toward FAIR and open research software |url=https://www.degruyter.com/document/doi/10.1515/itit-2019-0040/html |journal=it - Information Technology |language=en |volume=62 |issue=1 |pages=39–47 |doi=10.1515/itit-2019-0040 |issn=2196-7032}}</ref><ref name="GruenpeterFAIRPlus20">{{Cite web |last=Gruenpeter, M. |date=23 November 2020 |title=FAIR + Software: Decoding the principles |url=https://www.fairsfair.eu/sites/default/files/FAIR%20%2B%20software.pdf |format=PDF |publisher=FAIRsFAIR “Fostering FAIR Data Practices In Europe” |accessdate=30 April 2024}}</ref><ref>{{Cite journal |last=Barker |first=Michelle |last2=Chue Hong |first2=Neil P. |last3=Katz |first3=Daniel S. |last4=Lamprecht |first4=Anna-Lena |last5=Martinez-Ortiz |first5=Carlos |last6=Psomopoulos |first6=Fotis |last7=Harrow |first7=Jennifer |last8=Castro |first8=Leyla Jael |last9=Gruenpeter |first9=Morane |last10=Martinez |first10=Paula Andrea |last11=Honeyman |first11=Tom |date=2022-10-14 |title=Introducing the FAIR Principles for research software |url=https://www.nature.com/articles/s41597-022-01710-x |journal=Scientific Data |language=en |volume=9 |issue=1 |pages=622 |doi=10.1038/s41597-022-01710-x |issn=2052-4463 |pmc=PMC9562067 |pmid=36241754}}</ref><ref>{{Cite journal |last=Patel |first=Bhavesh |last2=Soundarajan |first2=Sanjay |last3=Ménager |first3=Hervé |last4=Hu |first4=Zicheng |date=2023-08-23 |title=Making Biomedical Research Software FAIR: Actionable Step-by-step Guidelines with a User-support Tool |url=https://www.nature.com/articles/s41597-023-02463-x |journal=Scientific Data |language=en |volume=10 |issue=1 |pages=557 |doi=10.1038/s41597-023-02463-x |issn=2052-4463 |pmc=PMC10447492 |pmid=37612312}}</ref><ref>{{Cite journal |last=Du |first=Xinsong |last2=Dastmalchi |first2=Farhad |last3=Ye |first3=Hao |last4=Garrett |first4=Timothy J. |last5=Diller |first5=Matthew A. |last6=Liu |first6=Mei |last7=Hogan |first7=William R. |last8=Brochhausen |first8=Mathias |last9=Lemas |first9=Dominick J. |date=2023-02-06 |title=Evaluating LC-HRMS metabolomics data processing software using FAIR principles for research software |url=https://link.springer.com/10.1007/s11306-023-01974-3 |journal=Metabolomics |language=en |volume=19 |issue=2 |pages=11 |doi=10.1007/s11306-023-01974-3 |issn=1573-3890}}</ref> Researchers quickly recognized that any planning around updating processes and systems to make research objects more FAIR would have to be tailored to specific research contexts, recognize that digital research objects go beyond data and information, and recognize "the specific nature of software" and not consider it "just data."<ref name="GruenpeterFAIRPlus20" /> A 2019 survey by Europe's FAIRsFAIR found that researchers seeking and re-using relevant research software on the internet faced multiple challenges, including understanding and/or maintaining the necessary software environment and its dependencies, finding sufficient documentation, struggling with accessibility and licensing issues, having the time and skills to install and/or use the software, finding quality control of the source code lacking, and having a sufficient software sustainability and management plan.<ref name="GruenpeterFAIRPlus20" /> These challenges highlight the importance of software to researchers and other stakeholders, and the roll FAIR has in better ensuring such software is findable, interoperable, and reusable to better ensure their software-driven research is repeatable (by the same research team, with the same experimental setup), reproducible (by a different research team, with the same experimental setup), and replicable (by a different research team, with a different experimental setup).<ref name="GruenpeterFAIRPlus20" />
Since 2016, other research stakeholders have taken to publishing their thoughts about how the FAIR principles apply to their fields of study and practice<ref name="NIHPubMedSearch">{{cite web |url=https://pubmed.ncbi.nlm.nih.gov/?term=fair+data+principles |title=fair data principles |work=PubMed Search |publisher=National Institutes of Health, National Library of Medicine |accessdate=30 April 2024}}</ref>, including in ways beyond what perhaps was originally imagined by Wilkinson ''et al.''. For example, multiple authors have examined whether or not the software used in scientific endeavors itself can be considered a research object worth being developed and managed in tandem with the FAIR data principles.<ref>{{Cite journal |last=Hasselbring |first=Wilhelm |last2=Carr |first2=Leslie |last3=Hettrick |first3=Simon |last4=Packer |first4=Heather |last5=Tiropanis |first5=Thanassis |date=2020-02-25 |title=From FAIR research data toward FAIR and open research software |url=https://www.degruyter.com/document/doi/10.1515/itit-2019-0040/html |journal=it - Information Technology |language=en |volume=62 |issue=1 |pages=39–47 |doi=10.1515/itit-2019-0040 |issn=2196-7032}}</ref><ref name="GruenpeterFAIRPlus20">{{Cite web |last=Gruenpeter, M. |date=23 November 2020 |title=FAIR + Software: Decoding the principles |url=https://www.fairsfair.eu/sites/default/files/FAIR%20%2B%20software.pdf |format=PDF |publisher=FAIRsFAIR “Fostering FAIR Data Practices In Europe” |accessdate=30 April 2024}}</ref><ref>{{Cite journal |last=Barker |first=Michelle |last2=Chue Hong |first2=Neil P. |last3=Katz |first3=Daniel S. |last4=Lamprecht |first4=Anna-Lena |last5=Martinez-Ortiz |first5=Carlos |last6=Psomopoulos |first6=Fotis |last7=Harrow |first7=Jennifer |last8=Castro |first8=Leyla Jael |last9=Gruenpeter |first9=Morane |last10=Martinez |first10=Paula Andrea |last11=Honeyman |first11=Tom |date=2022-10-14 |title=Introducing the FAIR Principles for research software |url=https://www.nature.com/articles/s41597-022-01710-x |journal=Scientific Data |language=en |volume=9 |issue=1 |pages=622 |doi=10.1038/s41597-022-01710-x |issn=2052-4463 |pmc=PMC9562067 |pmid=36241754}}</ref><ref>{{Cite journal |last=Patel |first=Bhavesh |last2=Soundarajan |first2=Sanjay |last3=Ménager |first3=Hervé |last4=Hu |first4=Zicheng |date=2023-08-23 |title=Making Biomedical Research Software FAIR: Actionable Step-by-step Guidelines with a User-support Tool |url=https://www.nature.com/articles/s41597-023-02463-x |journal=Scientific Data |language=en |volume=10 |issue=1 |pages=557 |doi=10.1038/s41597-023-02463-x |issn=2052-4463 |pmc=PMC10447492 |pmid=37612312}}</ref><ref>{{Cite journal |last=Du |first=Xinsong |last2=Dastmalchi |first2=Farhad |last3=Ye |first3=Hao |last4=Garrett |first4=Timothy J. |last5=Diller |first5=Matthew A. |last6=Liu |first6=Mei |last7=Hogan |first7=William R. |last8=Brochhausen |first8=Mathias |last9=Lemas |first9=Dominick J. |date=2023-02-06 |title=Evaluating LC-HRMS metabolomics data processing software using FAIR principles for research software |url=https://link.springer.com/10.1007/s11306-023-01974-3 |journal=Metabolomics |language=en |volume=19 |issue=2 |pages=11 |doi=10.1007/s11306-023-01974-3 |issn=1573-3890}}</ref> Researchers quickly recognized that any planning around updating processes and systems to make research objects more FAIR would have to be tailored to specific research contexts, recognize that digital research objects go beyond data and information, and recognize "the specific nature of software" and not consider it "just data."<ref name="GruenpeterFAIRPlus20" />  
 
A 2019 survey by Europe's FAIRsFAIR found that researchers seeking and re-using relevant research software on the internet faced multiple challenges, including understanding and/or maintaining the necessary software environment and its dependencies, finding sufficient documentation, struggling with accessibility and licensing issues, having the time and skills to install and/or use the software, finding quality control of the source code lacking, and having a sufficient software sustainability and management plan.<ref name="GruenpeterFAIRPlus20" /> These challenges highlight the importance of software to researchers and other stakeholders, and the roll FAIR has in better ensuring such software is findable, interoperable, and reusable, which in turn better ensures researchers' software-driven research is repeatable (by the same research team, with the same experimental setup), reproducible (by a different research team, with the same experimental setup), and replicable (by a different research team, with a different experimental setup).<ref name="GruenpeterFAIRPlus20" />


*LIMS and FAIR: [[Journal:A roadmap for LIMS at NIST Material Measurement Laboratory]]
*LIMS and FAIR: [[Journal:A roadmap for LIMS at NIST Material Measurement Laboratory]]

Revision as of 18:36, 30 April 2024

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

FAIRResourcesGraphic AustralianResearchDataCommons 2018.png

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] The authors released the FAIR principles while recognizing that "one of the grand challenges of data-intensive science ... is to improve knowledge discovery through assisting both humans and their computational agents in the discovery of, access to, and integration and analysis of task-appropriate scientific data and other scholarly digital objects."[1]

Since 2016, other research stakeholders have taken to publishing their thoughts about how the FAIR principles apply to their fields of study and practice[2], including in ways beyond what perhaps was originally imagined by Wilkinson et al.. For example, multiple authors have examined whether or not the software used in scientific endeavors itself can be considered a research object worth being developed and managed in tandem with the FAIR data principles.[3][4][5][6][7] Researchers quickly recognized that any planning around updating processes and systems to make research objects more FAIR would have to be tailored to specific research contexts, recognize that digital research objects go beyond data and information, and recognize "the specific nature of software" and not consider it "just data."[4]

A 2019 survey by Europe's FAIRsFAIR found that researchers seeking and re-using relevant research software on the internet faced multiple challenges, including understanding and/or maintaining the necessary software environment and its dependencies, finding sufficient documentation, struggling with accessibility and licensing issues, having the time and skills to install and/or use the software, finding quality control of the source code lacking, and having a sufficient software sustainability and management plan.[4] These challenges highlight the importance of software to researchers and other stakeholders, and the roll FAIR has in better ensuring such software is findable, interoperable, and reusable, which in turn better ensures researchers' software-driven research is repeatable (by the same research team, with the same experimental setup), reproducible (by a different research team, with the same experimental setup), and replicable (by a different research team, with a different experimental setup).[4]

Restricted or personal information while still being FAIR

Conclusion

References

  1. ↑ 1.0 1.1 Wilkinson, Mark D.; Dumontier, Michel; Aalbersberg, IJsbrand Jan; Appleton, Gabrielle; Axton, Myles; Baak, Arie; Blomberg, Niklas; Boiten, Jan-Willem et al. (15 March 2016). "The FAIR Guiding Principles for scientific data management and stewardship" (in en). Scientific Data 3 (1): 160018. doi:10.1038/sdata.2016.18. ISSN 2052-4463. PMC PMC4792175. PMID 26978244. https://www.nature.com/articles/sdata201618. 
  2. ↑ "fair data principles". PubMed Search. National Institutes of Health, National Library of Medicine. https://pubmed.ncbi.nlm.nih.gov/?term=fair+data+principles. Retrieved 30 April 2024. 
  3. ↑ Hasselbring, Wilhelm; Carr, Leslie; Hettrick, Simon; Packer, Heather; Tiropanis, Thanassis (25 February 2020). "From FAIR research data toward FAIR and open research software" (in en). it - Information Technology 62 (1): 39–47. doi:10.1515/itit-2019-0040. ISSN 2196-7032. https://www.degruyter.com/document/doi/10.1515/itit-2019-0040/html. 
  4. ↑ 4.0 4.1 4.2 4.3 Gruenpeter, M. (23 November 2020). "FAIR + Software: Decoding the principles" (PDF). FAIRsFAIR “Fostering FAIR Data Practices In Europe”. https://www.fairsfair.eu/sites/default/files/FAIR%20%2B%20software.pdf. Retrieved 30 April 2024. 
  5. ↑ Barker, Michelle; Chue Hong, Neil P.; Katz, Daniel S.; Lamprecht, Anna-Lena; Martinez-Ortiz, Carlos; Psomopoulos, Fotis; Harrow, Jennifer; Castro, Leyla Jael et al. (14 October 2022). "Introducing the FAIR Principles for research software" (in en). Scientific Data 9 (1): 622. doi:10.1038/s41597-022-01710-x. ISSN 2052-4463. PMC PMC9562067. PMID 36241754. https://www.nature.com/articles/s41597-022-01710-x. 
  6. ↑ Patel, Bhavesh; Soundarajan, Sanjay; Ménager, Hervé; Hu, Zicheng (23 August 2023). "Making Biomedical Research Software FAIR: Actionable Step-by-step Guidelines with a User-support Tool" (in en). Scientific Data 10 (1): 557. doi:10.1038/s41597-023-02463-x. ISSN 2052-4463. PMC PMC10447492. PMID 37612312. https://www.nature.com/articles/s41597-023-02463-x. 
  7. ↑ Du, Xinsong; Dastmalchi, Farhad; Ye, Hao; Garrett, Timothy J.; Diller, Matthew A.; Liu, Mei; Hogan, William R.; Brochhausen, Mathias et al. (6 February 2023). "Evaluating LC-HRMS metabolomics data processing software using FAIR principles for research software" (in en). Metabolomics 19 (2): 11. doi:10.1007/s11306-023-01974-3. ISSN 1573-3890. https://link.springer.com/10.1007/s11306-023-01974-3. 
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