In this article, we examine work with communal data in the context of clinical genetic testing. Drawing from prior research on digital research infrastructures and from the analysis of our empirical data on genetic testing, we describe how data generated in laboratories distributed all over the world are shared and re-used. Our research findings point to six different human-driven activities related to expanding, disambiguating, sanitizing and assessing the relevance, validity and combinability of data. We contribute to research within Health Informatics with a framework that foregrounds human-driven activities for data interoperability.
CinkoskyMFickettJGilnaP, et al. Electronic data publishing and GenBank. Science1991; 252(5010): 1273–1277.
2.
FriendSBorresenALBrodyL, et al. Breast cancer information on the web. Nat Genet1995; 11(3): 238–239.
3.
CerfVCameronALederbergJ, et al. National collaboratories: applying information technology for scientific research. Washington, DC: National Academy Press, 1993.
4.
GilbertW.Towards a paradigm shift in biology. Nature1991; 349(6305): 99.
5.
CouchFWeberBL.Mutations and polymorphisms in the familial early-onset breast cancer (BRCA1) gene. Hum Mutat1996; 8(1): 8–18.
6.
KouzesRTMyersJDWulfWA.Collaboratories: doing science on the Internet. Computer1996; 29(8): 40–46.
Frizzo-BarkerJChow-WhitePChartersA, et al. Genomic big data and privacy: challenges and opportunities for precision medicine. Comput Supp Cooper Work2016; 25(2–3): 115–136.
9.
OECD. Data-driven innovation for growth and well-being (STI policy note). Paris: OECD Publishing, 2015.
TolleKTansleySHeyA.The fourth paradigm: data-intensive scientific discovery. P IEEE2011; 99(8): 1334–1337.
12.
KitchinR.The data revolution: big data, open data, data infrastructures and their consequences. Thousand Oaks, CA: SAGE, 2014.
13.
VassilakopoulouPSkorveEAanestadM.Enabling openness of valuable information resources: curbing data subtractability and exclusion. Inform Syst J2019; 29: 768–786.
14.
TempiniN.Till data do us part: understanding data-based value creation in data-intensive infrastructures. Inf Organ2017; 27(4): 191–210.
15.
ZuboffS.In the age of the smart machine: the future of work and power. New York: Basic Books, 1988.
16.
BowersJ (ed.). The work to make a network work: studying CSCW in action. In: Proceedings of the ACM conference on computer supported cooperative work, Chapel Hill, NC, 22–26 October 1994. New York: ACM.
KarastiHBakerKSHalkolaE.Enriching the notion of data curation in e-science: data managing and information infrastructuring in the long term ecological research (LTER) network. Comput Supp Cooper Work2006; 15(4): 321–358.
19.
RibesD (ed.). The kernel of a research infrastructure. In: Proceedings of the 17th ACM conference on computer supported cooperative work & social computing, Baltimore, MD, 15–19 February 2014. New York: ACM.
20.
BakerKSMillerandF.Infrastructuring ecology: challenges in achieving data sharing. In: ParkerJNVermeulenNPendersB (eds) Collaboration in the new life sciences. Farnham: Ashgate, 2010, pp. 111–138.
21.
FanielIMJacobsenTE.Reusing scientific data: how earthquake engineering researchers assess the reusability of colleagues’ data. Comput Supp Cooper Work2010; 19(3–4): 355–375.
22.
HepsøVMonteiroERollandKHR. Ecologies of e-infrastructures. J AIS2009; 10(5): 430–446.
23.
KansaSWKansaE.Data publishing and archaeology’s information ecosystem. Near East Archaeol2014; 77(3): 223–227.
24.
De la FlorGJirotkaMLuffP, et al. Transforming scholarly practice: embedding technological interventions to support the collaborative analysis of ancient texts. Comput Supp Cooper Work2010; 19: 309–334.
25.
UreJHartswoodMWardlawJ, et al. The development of data infrastructures for ehealth: a sociotechnical perspective. J Assoc Inf Syst2009; 10(5): 415–429.
26.
RibesDBowkerGC.Between meaning and machine: learning to represent the knowledge of communities. Inf Organ2009; 19(4): 199–217.
27.
LeeCP.Boundary negotiating artifacts: unbinding the routine of boundary objects and embracing chaos in collaborative work. Comput Supp Cooper Work2007; 16(3): 307–339.
28.
EdwardsPMayernikMBatchellerA, et al. Science friction: data, metadata, and collaboration. Soc Stud Sci2011; 41: 667–690.
29.
JirotkaMLeeCPOlsonGM.Supporting scientific collaboration: methods, tools and concepts. Comput Supp Cooper Work2013; 22(4–6): 667–715.
30.
FlyvbjergB.Five misunderstandings about case-study research. Qualit Inq2006; 12(2): 219–245.
31.
SladeIRiddellDTurnbullC, et al. Development of cancer genetic services in the UK: a national consultation. Genome Med2015; 7(1): 18.
32.
WilkinsonMDDumontierMAalbersbergIJ, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data2016; 3: 160018.
33.
HartswoodMProcterRTaylorP, et al. Problems of data mobility and reuse in the provision of computer-based training for screening mammography. In: Proceedings of the SIGCHI conference on human factors in computing systems, Austin, TX, 5–10 May 2012. New York: ACM.
34.
McGilchristMSullivanFKalraD.Assuring the confidentiality of shared electronic health records. BMJ2007; 335(7632): 1223–1224.
35.
BorgmanCLWallisJCEnyedyN.Little science confronts the data deluge: habitat ecology, embedded sensor networks, and digital libraries. Int J Digit Libr2007; 7(1–2): 17–30.
36.
PhillipsN.Tool spots DNA errors in papers. Nature2017; 551: 422–423.
37.
ByrneJALabbéC.Striking similarities between publications from China describing single gene knockdown experiments in human cancer cell lines. Scientometrics2017; 110(3): 1471–1493.
38.
BakerKSChandlerCL.Enabling long-term oceanographic research: changing data practices, information management strategies and informatics. Deep Sea Res2008; 55(18): 2132–2142.
39.
Den DunnenJTAntonarakisSE. Mutation nomenclature extensions and suggestions to describe complex mutations: a discussion. Hum Mutat2000; 15(1): 7–12.
40.
KarastiHBakerKS.Digital data practices and the long term ecological research program growing global. Int J Digit Curat2008; 3(2): 42–58.
41.
GradyC.Enduring and emerging challenges of informed consent. N Engl J Med2015; 372(9): 855–862.
42.
Parra-CalderonCLKayeJMoreno-CondeA, et al. Desiderata for digital consent in genomic research. J Commun Genet2018; 9(2): 191–194.
43.
ArmstrongJToscanoMKotchkoN, et al. Utilization and outcomes of BRCA genetic testing and counseling in a national commercially insured population: the ABOUT study. JAMA Oncol2015; 1: 1251–1260.
WollersheimDSariARahayuW.Archetype-based electronic health records: a literature review and evaluation of their applicability to health data interoperability and access. Health Inf Manag2009; 38(2): 7–17.
46.
PatersonGIChristieSBonneyW, et al. Synoptic operative reports for spinal cord injury patients as a tool for data quality. Health Informatics J2016; 22(4): 984–991.
47.
MalinBSweeneyL.How (not) to protect genomic data privacy in a distributed network: using trail re-identification to evaluate and design anonymity protection systems. J Biomed Inform2004; 37(3): 179–192.
48.
GymrekMMcGuireALGolanD, et al. Identifying personal genomes by surname inference. Science2013; 339(6117): 321–324.
