• This record comes from PubMed

Enhancing Reuse of Data and Biological Material in Medical Research: From FAIR to FAIR-Health

. 2018 Apr ; 16 (2) : 97-105. [epub] 20180123

Language English Country United States Media print-electronic

Document type Journal Article, Review

Grant support
001 World Health Organization - International

The known challenge of underutilization of data and biological material from biorepositories as potential resources for medical research has been the focus of discussion for over a decade. Recently developed guidelines for improved data availability and reusability-entitled FAIR Principles (Findability, Accessibility, Interoperability, and Reusability)-are likely to address only parts of the problem. In this article, we argue that biological material and data should be viewed as a unified resource. This approach would facilitate access to complete provenance information, which is a prerequisite for reproducibility and meaningful integration of the data. A unified view also allows for optimization of long-term storage strategies, as demonstrated in the case of biobanks. We propose an extension of the FAIR Principles to include the following additional components: (1) quality aspects related to research reproducibility and meaningful reuse of the data, (2) incentives to stimulate effective enrichment of data sets and biological material collections and its reuse on all levels, and (3) privacy-respecting approaches for working with the human material and data. These FAIR-Health principles should then be applied to both the biological material and data. We also propose the development of common guidelines for cloud architectures, due to the unprecedented growth of volume and breadth of medical data generation, as well as the associated need to process the data efficiently.

See more in PubMed

Problems with scientific research: How science goes wrong. The Economist 2013:13 https://www.economist.com/news/leaders/21588069-scientific-research-has-changed-world-now-it-needs-change-itself-how-science-goes-wrong (accessed December29, 2017)

Wilkinson MD, Dumontier M, Aalbersberg IJ, et al. . The FAIR Guiding Principles for scientific data management and stewardship. Sci Data 2016;3:160018. PubMed PMC

Moore R. Towards a theory of digital preservation. Int J Digit Curation 2008;3:63–75

Pennock M. Digital Curation: A life-cycle approach to managing and preserving usable digital information. For publication in Library & Archives Journal, Issue 1, 2007. www.researchgate.net/profile/Maureen_Pennock/publication/228770335_Digital_ curation_A_life-cycle_approach_to_managing_and_preserving_usable_digital_information/links/5606535d08aeb5718ff29465.pdf (accessed December29, 2017)

Albert P, Alpi K, Baxter P, et al. . Digital research data curation: Overview of issues, current activities, and opportunities for the Cornell University Library. A report of the Cornell University Library (CUL) Data Working Group (DaWG). 2008. https://ecommons.cornell.edu/handle/1813/10903 (accessed December29, 2017)

Freedman LP, Cockburn IM, Simcoe TS. The economics of reproducibility in preclinical research. PLoS Biol 2015;13:e1002165. PubMed PMC

Prinz F, Schlange T, Asadullah K. Believe it or not: How much can we rely on published data on potential drug targets? Nat Rev Drug Discov 2011;10:712. PubMed

Begley CG, Ellis LM. Drug development: Raise standards for preclinical cancer research. Nature 2012;483:531–533 PubMed

Begley CG. Reproducibility: Six red flags for suspect work. Nature 2013;497:433–434 PubMed

AC't Hoen P, Friedländer MR, Almlöf J, et al. . Reproducibility of high-throughput mRNA and small RNA sequencing across laboratories. Nat Biotechnol 2013;31:1015–1022 PubMed

Bissell M. Reproducibility: The risks of the replication drive. Nature 2013;503:333–334 PubMed

Mobley A, Linder SK, Braeuer R, et al. . A survey on data reproducibility in cancer research provides insights into our limited ability to translate findings from the laboratory to the clinic. PLoS One 2013;8:e63221. PubMed PMC

Morrison SJ. Time to do something about reproducibility. eLife 2014;3:e03981 PubMed PMC

Sandve GK, Nekrutenko A, Taylor J, et al. . Ten simple rules for reproducible computational research. PLoS Comput Biol 2013;9:e1003285. PubMed PMC

Fomel S, Claerbout JF. Guest editors' introduction: Reproducible research. Comput Sci Eng 2009;11:5–7

Curcin V, Miles S, Danger R, et al. . Implementing interoperable provenance in biomedical research. Future Gener Comput Syst 2014;34:1–16

Kap M, Sieuwerts AM, Kubista M, et al. . The influence of tissue procurement procedures on RNA integrity, gene expression, and morphology in porcine and human liver tissue. Biopreserv Biobank 2015;13:200–206 PubMed

CEN/TS 16826-1:2015. Molecular in vitro diagnostic examinations—Specifications for pre-examination processes for snap frozen tissue—Part 1: Isolated RNA. 2015

Mager S, Oomen MH, Morente MM, et al. . Standard operating procedure for the collection of fresh frozen tissue samples. Eur J Cancer 2007;43:828–834 PubMed

Colledge F, Elger B, Howard HC. A review of the barriers to sharing in biobanking. Biopreserv Biobank 2013;11:339–346 PubMed

Colledge F, Persson K, Elger B, et al. . Sample and data sharing barriers in biobanking: Consent, committees, and compromises. Ann Diagn Pathol 2014;18:78–81 PubMed

Katz DS, Smith AM. Transitive credit and JSON-LD. J Open Res Softw 2015;3:e7

The Editor. Human variome microattribution reviews. Nat Genet 2008;40:1

Giardine B, Borg J, Higgs DR, et al. . Systematic documentation and analysis of human genetic variation in hemoglobinopathies using the microattribution approach. Nat Genet 2011;43:295–301 PubMed PMC

Cambon-Thomsen A, Thorisson GA, Mabile L, et al. . The role of a bioresource research impact factor as an incentive to share human bioresources. Nat Genet 2011;43:503–504 PubMed

Bravo E, Calzolari A, De Castro P, et al. . Developing a guideline to standardize the citation of bioresources in journal articles (CoBRA). BMC Med 2015;13:1. PubMed PMC

Institute of Medicine (IOM). Sharing Clinical Trial Data: Maximizing Benefits, Minimizing Risk. Washington, DC: The National Academies Press; 2015 PubMed

EU Regulation. 2016/679 of the European Parliament and of the Council of 27 April 2016 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data, and repealing Directive 95/46/EC (General Data Protection Regulation). Adopted by the Council on April 8, 2016. 2016

PISA Consortium. Handbook of privacy and privacy-enhancing technologies. In: Van Blarkom G, Borking J, Olk J. (eds). College bescherming persoonsgegevens, The Netherlands: The Hague, 2003. http://andrewpatrick.ca/pisa/handbook/Handbook_Privacy_and_PET_final.pdf

El Emam K, Rodgers S, Malin B. Anonymising and sharing individual patient data. BMJ 2015;350:h1139. PubMed PMC

Eder J, Gottweis H, Zatloukal K. IT solutions for privacy protection in biobanking. Public Health Genomics 2012;15:254–262 PubMed

Prasser F, Kohlmayer F. Putting statistical disclosure control into practice: The ARX data anonymization tool. In: Medical Data Privacy Handbook. Springer: Charm Heidelberg New York Dordrecht, London; 2015: 111–148

Rubinstein I, Hartzog W. Anonymization and risk. Available at SSRN 2646185 2015

Sun X, Sun L, Wang H. Extended k-anonymity models against sensitive attribute disclosure. Comput Commun 2011;34:526–535

Dwork C, Roth A. The algorithmic foundations of differential privacy. Theor Comput Sci 2013;9:211–407

Heatherly R, Denny JC, Haines JL, et al. . Size matters: How population size influences genotype-phenotype association studies in anonymized data. J Biomed Inform 2014;52:243–250 PubMed PMC

Burr WE, Dodson DF, Newton EM, et al. . Electronic Authentication Guideline. NIST Special Publication 800-63-2. 2013. DOI: http://dx.doi.org/10.6028/NIST.SP.800-63-2 http://nvlpubs.nist.gov/nistpubs/SpecialPublications/NIST.SP.800-63-2.pdf (accessed December29, 2017)

Nenadic A, Zhang N, Yao L, et al. . Levels of authentication assurance: An investigation. In: Third International Symposium on Information Assurance and Security. IEEE 2007: 155–160

Feldman EA. The Genetic Information Nondiscrimination Act (GINA): Public policy and medical practice in the age of personalized medicine. J Gen Intern Med 2012;27:743–746 PubMed PMC

Armbrust M, Fox A, Griffith R, et al. . A view of cloud computing. Commun ACM 2010;53:50–58

Mell P, Grance T. NIST SP 800-145, The NIST definition of cloud computing. 2011. DOI: 10.6028/NIST.SP.800 http://nvlpubs.nist.gov/nistpubs/Legacy/SP/nistspecialpublication800-145.pdf (accessed December29, 2017) DOI

Zhou M, Zhang R, Xie W, et al. . Security and privacy in cloud computing: A survey. In: Semantics Knowledge and Grid (SKG), 2010 Sixth International Conference on. 2010: 105–112. DOI: 10.1109/SKG.2010.19 DOI

Ryan MD. Cloud computing privacy concerns on our doorstep. Commun ACM 2011;54:36–38

ISO/IEC 27018:2014—Information technology—Security techniques—Code of practice for protection of personally identifiable information (PII) in public clouds acting as PII processors. 2014

Litton JE. We must urgently clarify data-sharing rules. Nature 2017;541:437. PubMed

W3C Working Group. PROV-Overview—An Overview of the PROV Family of Documents. Ed. by Groth, P and Moreau, L. 2013. www.w3.org/TR/prov-overview (accessed December29, 2017)

ISO/TS 8000-60:2017–Data quality–Part 60: Data quality management: Overview. 2017

Pfitzmann A, Hansen M. A terminology for talking about privacy by data minimization: Anonymity, unlinkability, undetectability, unobservability, pseudonymity, and identity management. Version v0.34. 2010. https://dud.inf.tu-dresden.de/literatur/Anon_Terminology_v0.34.pdf (accessed December29, 2017)

ISO/TS 25237:2008—Health informatics—Pseudonymization. 2008

Find record

Citation metrics

Loading data ...

Archiving options

Loading data ...