Studying Data Communities
Analytical Dimensions from and for Empirical Research
DOI:
https://doi.org/10.18357/kula.327Keywords:
data communities, data practices, studying communities, data repositories, biocuration, research dataAbstract
How can data communities be studied? In this paper, we combine existing literature with our own research spanning more than a decade to propose five dimensions and a series of guiding questions that can be used to analyze data communities. These dimensionsーdisciplinary domains, social orderings, material orderings, data uses, and data expertiseーillustrate the variability of data communities and offer starting points for future empirical research, infrastructure design, and policy activities. Analyzing data communities through the multidimensional perspectives that we propose encourages critical interrogation of these heterogeneous groups while highlighting the complex ways in which data practices constitute particular communities and how those communities in turn shape data. Studying data communities with the questions we propose provides ways to honor epistemic diversity, experiment with community-centric infrastructures and policies, and create and value different forms of expertise.
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Arnaboldi, Valerio, Daniela Raciti, Kimberly Van Auken, Juancarlos N. Chan, Hans-Michael Müller, and Paul W. Sternberg. 2020. “Text Mining Meets Community Curation: A Newly Designed Curation Platform to Improve Author Experience and Participation at WormBase.” Database 2020: 1–16. https://doi.org/10.1093/database/baaa006.
Birnholtz, Jeremy P., and Matthew J. Bietz. 2003. “Data at Work: Supporting Sharing in Science and Engineering.” In GROUP ’03: Proceedings of the 2003 International ACM SIGGROUP Conference on Supporting Group Work. Association for Computing Machinery. https://doi.org/10.1145/958160.958215.
Bodenreider, Olivier, and Robert Stevens. 2006. “Bio-ontologies: Current Trends and Future Directions.” Briefings in Bioinformatics 7 (3): 256–74. https://doi.org/10.1093/bib/bbl027.
Borgman, Christine L. 2012. “The Conundrum of Sharing Research Data.” Journal of the American Society for Information Science and Technology 63 (6): 1059–78. https://doi.org/10.1002/asi.22634.
Borgman, Christine L. 2015. Big Data, Little Data, No Data: Scholarship in the Networked World. The MIT Press. https://doi.org/10.7551/mitpress/9963.001.0001.
Borgman, Christine L., and Paul Groth. 2025. “From Data Creator to Data Reuser: Distance Matters.” Harvard Data Science Review 7 (2). https://doi.org/10.1162/99608f92.35d32cfc.
Bowker, Geoffrey C., and Susan Leigh Star. 1999. Sorting Things Out: Classification and Its Consequences. The MIT Press. https://doi.org/10.7551/mitpress/6352.001.0001.
Burge, Sarah, Teresa K. Attwood, Alex Bateman, Tanya Z. Berardini, Michael Cherry, Claire O’Donovan, Ioannis Xenarios, and Pascale Gaudet. 2012. “Biocurators and Biocuration: Surveying the 21st Century Challenges.” Database 2012: bar059. https://doi.org/10.1093/database/bar059.
Carroll, Stephanie Russo, Ibrahim Garba, Oscar L. Figueroa-Rodríguez, Jarita Holbrook, Raymond Lovett, Simeon Materechera, Mark Parsons, Kay Raseroka, Desi Rodriguez-Lonebear, Robyn Rowe, Rodrigo Sara, Jennifer D. Walker, Jane Anderson, and Maui Hudson. 2023. “The CARE Principles for Indigenous Data Governance.” In Open Scholarship Press Curated Volumes: Policy. https://openscholarshippress.pubpub.org/pub/xx3kj9rv.
Cavazzoni, Emma. 2026. “Data-Technology Communities: Collaboration and Diversity in Data- and Technology-Intensive Multidisciplinary Research.” BioSocieties (January). https://doi.org/10.1057/s41292-025-00379-w.
Cohen, Anthony P. (1985) 1993. The Symbolic Construction of Community. Key Ideas. Routledge.
Cooper, Danielle Miriam, and Rebecca Springer. 2019. “Data Communities: A New Model for Supporting STEM Data Sharing.” Ithaka S+R. https://doi.org/10.18665/sr.311396.
Darragh, Jen, Mikala R. Narlock, Halle Burns, Peter A. Cerda, Wind Cowles, Leslie Delserone, Seth Erickson, Joel Herndon, Heidi Imker, Lisa R. Johnston, Sherry Lake, Michael Lenard, Alicia Hofelich Mohr, Jennifer Moore, Jonathan Petters, Brandie Pullen, Shawna Taylor, and Briana Wham. 2024. “Institutional Data Repositories Are Vital.” Science 385 (6714): 1174. http://doi.org/10.1126/science.adr0789.
Davies, Sarah R. 2025. “Working in Biocuration: Contemporary Experiences and Perspectives.” Database 2025 (January): baaf003. https://doi.org/10.1093/database/baaf003.
Davies, Sarah R., and Constantin Holmer. 2024. “Care, Collaboration, and Service in Academic Data Work: Biocuration as ‘Academia Otherwise.’” Information, Communication & Society 4: 683–701. https://doi.org/10.1080/1369118X.2024.2315285.
Egher, Claudia. 2023. Digital Healthcare and Expertise: Mental Health and New Knowledge Practices. Palgrave Macmillan. https://doi.org/10.1007/978-981-16-9178-2.
Federer, Lisa M. 2019. “Who, What, When, Where, and Why? Quantifying and Understanding Biomedical Data Reuse.” PhD diss., University of Maryland. https://doi.org/10.13016/60jd-9hux.
Fortun, Kim. 2009. “Scaling and Visualizing Multi-sited Ethnography.” In Multi-Sited Ethnography: Theory, Praxis and Locality in Contemporary Research, edited by Mark-Anthony Falzon. Routledge. https://doi.org/10.4324/9781315596389.
Gabrielsen, Ane Møller. 2024. “Gendering Data Care: Curators, Care, and Computers in Data-Centric Biology.” Science as Culture 33 (2): 256–80. https://doi.org/10.1080/09505431.2023.2260830.
Gregory, Kathleen, Paul Groth, Helena Cousijn, Andrea Scharnhorst, and Sally Wyatt. 2019. “Searching Data: A Review of Observational Data Retrieval Practices in Selected Disciplines.” Journal of the Association for Information Science and Technology 70 (5): 419–32. https://doi.org/10.1002/asi.24165.
Gregory, Kathleen M., Helena Cousijn, Paul Groth, Andrea Scharnhorst, and Sally Wyatt. 2019. “Understanding Data Search as a Socio-technical Practice.” Journal of Information Science 46 (4): 459–75. https://doi.org/10.1177/0165551519837182.
Gregory, Kathleen, Paul Groth, Andrea Scharnhost, and Sally Wyatt. 2020. “Lost or Found? Discovering Data Needed for Research.” Harvard Data Science Review (April). https://doi.org/10.1162/99608f92.e38165eb.
Gregory, Kathleen, Anton Ninkov, Chantal Ripp, Emma Roblin, Isabella Peters, and Stefanie Haustein. 2023. “Tracing Data: A Survey Investigating Disciplinary Differences in Data Citation.” Quantitative Science Studies 4 (3): 622–49. https://doi.org/10.1162/qss_a_00264.
Gregory, Kathleen, and Laura Koesten. 2023. “Opening Research Data.” Private report.
Gregory, Kathleen, Laura Koesten, Regina Schuster, Torsten Möller, and Sarah Davies. 2024. “Data Journeys in Popular Science: Producing Climate Change and COVID-19 Data Visualizations at Scientific American.” Harvard Data Science Review 6 (2). https://doi.org/10.1162/99608f92.141c99cf.
Gregory, Kathleen, Stefanie Haustein, Constance Poitras, Emma Roblin, Anton Ninkov, Chantal Ripp, Isabella Peters. 2026. “Digging Deeper into Data Citations: Recognizing and Rewarding Data Work.” Research Evaluation 35: rvag008, https://doi.org/10.1093/reseval/rvag008.
Grundmann, Reiner. 2017. “The Problem of Expertise in Knowledge Societies.” Minerva 55 (1): 25–48. https://doi.org/10.1007/s11024-016-9308-7.
Hammarfelt, Björn. 2019. “Discipline.” In ISKO Encyclopedia of Knowledge Organization, edited by Birger Hjørland and Claudio Gnoli. https://www.isko.org/cyclo/discipline.
Hilgartner, Stephen. 2000. Science on Stage: Expert Advice as Public Drama. Stanford University Press. https://doi.org/10.1515/9781503618220.
Hobbis, Stephanie Ketterer, and Geoffrey Hobbis. 2022. “Non-/Human Infrastructures and Digital Gifts: The Cables, Waves and Brokers of Solomon Islands Internet.” Ethnos 87 (5): 851–73. https://doi.org/10.1080/00141844.2020.1828969.
Holinski, Alexandra, Melissa L. Burke, Sarah L. Morgan, Peter McQuilton, and Patricia M. Palagi. 2020. “Biocuration - Mapping Resources and Needs.” F1000Research 9 (ELIXIR): 1094. https://doi.org/10.12688/f1000research.25413.2.
International Society for Biocuration. 2026. “Biocuration Generic Job Description.” https://www.biocuration.org/community/biocuration-generic-job-description/.
Jetten, Mijke, Marjan Grootveld, Annemie Mordant, Mascha Jansen, Margreet Bloemers, Margriet Miedema, and Celia W. G. Van Gelder. 2021. “Professionalising Data Stewardship in the Netherlands. Competences, Training and Education. Dutch Roadmap Towards National Implementation of FAIR Data Stewardship.” March 19, 2021. Zenodo. https://doi.org/10.5281/zenodo.4623713.
Kastenhofer, Karen, and Susan Molyneux-Hodgson, eds. 2021. Community and Identity in Contemporary Technosciences. Sociology of the Sciences Yearbook 31. Springer. https://doi.org/10.1007/978-3-030-61728-8.
Khan, Nushrat, Mike Thelwall, and Kayvan Kousha. 2023. “Data Sharing and Reuse Practices: Disciplinary Differences and Improvements Needed.” Online Information Review 47 (6): 1036–64. https://doi.org/10.1108/OIR-08-2021-0423.
Knorr Cetina, Karin. 1999. Epistemic Cultures: How the Sciences Make Knowledge. Harvard University Press. Koesten, Laura M., Emilia Kacprzak, Jenifer F. A. Tennison, and Elena Simperl. 2017. “The Trials and Tribulations of Working with Structured Data: A Study on Information Seeking Behaviour.” In CHI ’17: Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems. https://doi.org/10.1145/3025453.3025838.
Koesten, Laura, Jude Yew, and Kathleen Gregory. 2025. “Human-Data Interaction: Thinking Beyond Individual Datasets.” Interactions 32 (1): 34–38. https://doi.org/10.1145/3705537.
Latour, Bruno, and Steve Woolgar. 1986. Laboratory Life: The Construction of Scientific Facts. Princeton University Press. https://doi.org/10.2307/j.ctt32bbxc.
Lave, Jean, and Etienne Wenger. 1991. Situated Learning: Legitimate Peripheral Participation. Cambridge University Press.
Law, John. 2017. “STS as Method.” In The Handbook of Science and Technology Studies, 4th ed., edited by Ulrike Felt, Rayvon Fouché, Clark A. Miller, and Laurel Smith-Doerr. The MIT Press.
Lean, Oliver M. 2021. “Are Bio-ontologies Metaphysical Theories?” Synthese 199: 11587–11608. https://doi.org/10.1007/s11229-021-03303-4.
Leonelli, Sabina. 2016. Data-Centric Biology: A Philosophical Study. University of Chicago Press. https://doi.org/10.7208/chicago/9780226416502.001.0001.
Leonelli, Sabina, and Rachel A. Ankeny. 2015. “Repertoires: How to Transform a Project into a Research Community.” BioScience 65 (7): 701–8. https://doi.org/10.1093/biosci/biv061.
Levallois, Clement, Stephanie Steinmetz, and Paul Wouters. 2013. “Sloppy Data Floods or Precise Social Science Methodologies? Dilemmas in the Transition to Data-Intensive Research in Sociology and Economics.” In Virtual Knowledge: Experimenting in the Humanities and the Social Sciences, edited by Paul Wouters, Anne Beaulieu, Andrea Scharnhorst, and Sally Wyatt. The MIT Press. https://doi.org/10.7551/mitpress/9274.003.0007.
Metzler, Ingrid, Lisa-Maria Ferent, and Ulrike Felt. 2023. “On Samples, Data, and Their Mobility in Biobanking: How Imagined Travels Help to Relate Samples and Data.” Big Data & Society 10 (1): 1–13. https://doi.org/10.1177/20539517231158635.
Oliver, Gillian, Jocelyn Cranefield, Spencer Lilley, and Matthew Lewellen. 2023. “Data Cultures: A Scoping Literature Review.” Information Research 28 (1): 3–29. https://doi.org/10.47989/irpaper950.
Ottinger, Gwen. 2010. “Buckets of Resistance: Standards and the Effectiveness of Citizen Science.” Science, Technology & Human Values 35 (2): 244–70. https://doi.org/10.1177/0162243909337121.
Ottinger, Gwen. 2022. “Misunderstanding Citizen Science: Hermeneutic Ignorance in U.S. Environmental Regulation.” Science as Culture 34 (1): 504–29. https://doi.org/10.1080/09505431.2022.2035710.
Ottinger, Gwen. 2023. “Responsible Epistemic Innovation: How Combatting Epistemic Injustice Advances Responsible Innovation (and Vice Versa).” Journal of Responsible Innovation 10 (1): 1–19. https://doi.org/10.1080/23299460.2022.2054306.
Parasie, Sylvain. 2015. “Data-Driven Revelation?: Epistemological Tensions in Investigative Journalism in the Age of ‘Big Data.’” Digital Journalism 3 (3): 364–80. https://doi.org/10.1080/21670811.2014.976408.
Pink, Sarah. 2021. “The Ethnographic Hunch.” In Experimenting with Ethnography: A Companion to Analysis, edited by Andrea Ballestero and Brit Ross Winthereik. Duke University Press. https://doi.org/10.1515/9781478091691-005.
Poirier, Lindsay. 2023. “Attending to the Cultures of Data Science Work.” Data Science Journal 22 (6): 1–7. https://doi.org/10.5334/dsj-2023-006.
Poirier, Lindsay, and Brandon Costelloe-Kuehn. 2019. “Data Sharing at Scale: A Heuristic for Affirming Data Cultures.” Data Science Journal 18 (48): 1–7. https://doi.org/10.5334/dsj-2019-048.
Robinson-García, Nicolas, Evaristo Jiménez-Contreras, and Daniel Torres-Salinas. 2016. “Analyzing Data Citation Practices Using the Data Citation Index.” Journal of the Association for Information Science and Technology 67 (12): 2964–75. https://doi.org/10.1002/asi.23529.
Springer, Rebecca, and Danielle Cooper. 2020. “Data Communities: Empowering Researcher-Driven Data Sharing in the Sciences.” International Journal of Digital Curation 15 (1): 1–8. https://doi.org/10.2218/ijdc.v15i1.695.
Traweek, Sharon. (1988) 1992. Beamtimes and Lifetimes: The World of High Energy Physicists. Harvard University Press.
UNESCO. 2021. UNESCO Recommendation on Open Science. UNESCOC Digital Library. https://doi.org/10.54677/MNMH8546.
Wenger, Etienne. 1998. Communities of Practice: Learning, Meaning, and Identity. Cambridge University Press.
Wilkinson, Mark D., Michel Dumontier, IJsbrand Jan Aalbersberg, Gabrielle Appleton, Myles Axton, Arie Baak, Niklas Blomberg, Jan-Willem Boiten, Luiz Bonino da Silva Santos, Philip E. Bourne, Jildau Bouwman, Anthony J. Brookes, Tim Clark, Mercè Crosas, Ingrid Dillo, Olivier Dumon, Scott Edmunds, Chris T. Evelo, Richard Finkers, Alejandra Gonzalez-Beltran, Alasdair J. G. Gray, Paul Groth, Carole Goble, Jeffrey S. Grethe, Jaap Heringa, Peter A. C ’t Hoen, Rob Hooft, Tobias Kuhn, Ruben Kok, Joost Kok, Scott J. Lusher, Maryann E. Martone, Albert Mons, Abel L. Packer, Bengt Persson, Philippe Rocca-Serra, Marco Roos, Rene van Schaik, Susanna-Assunta Sansone, Erik Schultes, Thierry Sengstag, Ted Slater, George Strawn, Morris A. Swertz, Mark Thompson, Johan van der Lei, Erik van Mulligen, Jan Velterop, Andra Waagmeester, PeteWittenburg, Katherine Wolstencroft, Jun Zhao, and Barend Mons. 2016. “The FAIR Guiding Principles for Scientific Data Management and Stewardship.” Scientific Data 3 (160018). https://doi.org/10.1038/sdata.2016.18.
Wofford, Morgan F., and Andrea K. Thomer. 2023. “Curating for Contrarian Communities: Data Practices of Anthropogenic Climate Change Skeptics.” Proceedings of the Association for Information Science and Technology 60 (1): 442–55. https://doi.org/10.1002/pra2.802.
Wood-Charlson, Elisha M., Zachary Crockett, Chris Erdmann, Adam P. Arkin, and Carly B. Robinson. 2022. “Ten Simple Rules for Getting and Giving Credit for Data.” PLoS Computional Biology 18 (9): e1010476. https://doi.org/10.1371/journal.pcbi.1010476.
Wyatt, Sally. 2003. “Non-Users Also Matter: The Construction of Users and Non-Users of the Internet.” In How Users Matter: The Co-Construction of Users and Technology, edited by Nelly Oudshoorn and Trevor Pinch. The MIT Press. https://doi.org/10.7551/mitpress/3592.003.0006.
Zeng, Tong, Longfeng Wu, Sarah Bratt, and Daniel E. Acuna. 2020. “Assigning Credit to Scientific Datasets Using Article Citation Networks.” Journal of Informetrics 14 (2): 1–25. https://doi.org/10.1016/j.joi.2020.101013.
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