Question-to-Source Guide: Data Sharing Practices and Biological Discovery in Scientific Research

Frame the question

The interplay between data sharing practices and biological discovery forms the core of this guide. Source [1] investigates microglia turnover in the human brain, while sources [2] and [3] examine data sharing infrastructure in scientific research. Source [4] contextualizes these practices within broader debates about public participation in science. These sources collectively address how data management frameworks shape biological research outcomes and societal engagement with scientific knowledge.

What the evidence shows

Source [1] establishes that microglia, unlike most hematopoietic lineages, exhibit slow turnover (median 28% per year) with some cells surviving over two decades. This challenges assumptions about cellular renewal in the CNS. Source [2] reveals that CENS researchers, despite willingness to share data, face systemic barriers: only 10% of funders require data deposition, and repositories for niche domains are scarce. Source [3] contrasts this by showcasing the 1000 Genomes Project's open-data model, which created tools for genetic variation analysis. Source [4] reframes these practices as part of a 'gift culture' of scholarship, where data sharing is relational rather than transactional. These findings collectively suggest that data sharing infrastructure directly impacts both scientific discovery and public engagement with research.

Follow the source trail

Source [1] provides biological context for understanding cellular turnover, while sources [2] and [3] offer contrasting models of data sharing. Source [4] synthesizes these practices within a broader sociological framework. The 1000 Genomes Project's open-data approach [3] contrasts with CENS's fragmented sharing practices [2], highlighting institutional differences in data management. Source [1]'s findings on microglia turnover could benefit from the 1000 Genomes Project's data tools, while source [4]'s citizen science framework might inform more inclusive data-sharing models. These connections reveal how institutional frameworks shape both biological research and public participation in science.

Use these sources well

For an essay on data sharing and biological discovery, integrate source [1]'s microglia turnover findings with source [3]'s open-data infrastructure to show how data accessibility enables biological research. Contrast this with source [2]'s CENS case to highlight institutional barriers. Use source [4] to contextualize these practices within broader debates about public participation. Avoid overstating correlations: while source [1] shows slow turnover, source [2] indicates that data sharing remains limited to interpersonal exchanges. Emphasize that source [3]'s tools for genetic variation analysis could enhance microglia research if adopted more widely. For follow-up, explore how citizen science frameworks [4] might address CENS's data-sharing limitations [2] or how open-data models [3] could improve microglia research.

What to search next

How might the 1000 Genomes Project's open-data model [3] address CENS's data-sharing limitations [2]? Could citizen science frameworks [4] enhance microglia research by democratizing data access? What are the ethical implications of slow microglia turnover [1] for neurodegenerative disease studies? How do institutional policies shape the balance between data sharing and intellectual property rights across these domains? These questions suggest that data management practices are not just technical but deeply intertwined with scientific discovery and societal engagement.

Verbatim source abstracts

[1] The Lifespan and Turnover of Microglia in the Human Brain — Cell Reports, 2017-07-01, doi:10.1016/j.celrep.2017.07.004

The hematopoietic system seeds the CNS with microglial progenitor cells during the fetal period, but the subsequent cell generation dynamics and maintenance of this population have been poorly understood. We report that microglia, unlike most other hematopoietic lineages, renew slowly at a median rate of 28% per year, and some microglia last for more than two decades. Furthermore, we find no evidence for the existence of a substantial population of quiescent long-lived cells, meaning that the microglia population in the human brain is sustained by continuous slow turnover throughout adult life. [1]

[2] If We Share Data, Will Anyone Use Them? Data Sharing and Reuse in the Long Tail of Science and Technology — PLoS ONE, 2013-07-23, doi:10.1371/journal.pone.0067332

Research on practices to share and reuse data will inform the design of infrastructure to support data collection, management, and discovery in the long tail of science and technology. These are research domains in which data tend to be local in character, minimally structured, and minimally documented. We report on a ten-year study of the Center for Embedded Network Sensing (CENS), a National Science Foundation Science and Technology Center. We found that CENS researchers are willing to share their data, but few are asked to do so, and in only a few domain areas do their funders or journals require them to deposit data. Few repositories exist to accept data in CENS research areas.. Data sharing tends to occur only through interpersonal exchanges. CENS researchers obtain data from repositories, and occasionally from registries and individuals, to provide context, calibration, or other forms of background for their studies. Neither CENS researchers nor those who request access to CENS data appear to use external data for primary research questions or for replication of studies. CENS researchers are willing to share data if they receive credit and retain first rights to publish their results. Practices of releasing, sharing, and reusing of data in CENS reaffirm the gift culture of scholarship, in which goods are bartered between trusted colleagues rather than treated as commodities. [2]

[3] The 1000 Genomes Project: data management and community access — Nature Methods, 2012-04-27, doi:10.1038/nmeth.1974

The 1000 Genomes Project was launched as one of the largest distributed data collection and analysis projects ever undertaken in biology. In addition to the primary scientific goals of creating both a deep catalog of human genetic variation and extensive methods to accurately discover and characterize variation using new sequencing technologies, the project makes all of its data publicly available. Members of the project data coordination center have developed and deployed several tools to enable widespread data access. [3]

[4] “Citizen Science”? Rethinking Science and Public Participation — Science & Technology Studies, 2018-10-30, doi:10.23987/sts.60425

Since the late twentieth century, “citizen science” has become an increasingly fashionable label for a growing number of participatory research activities. This paper situates the origins and rise of the term “citizen science” and contextualises “citizen science” within the broader history of public participation in science. It analyses critically the current promises — democratisation, education, discoveries — emerging within the “citizen science” discourse and offers a new framework to better understand the diversity of epistemic practices involved in these participatory projects. Finally, it maps a number of historical, political, and social questions for future research in the critical studies of “citizen science”. [4]

Source dossiers

Reference cards for every cited source, using only verified record metadata.

[1] The Lifespan and Turnover of Microglia in the Human Brain

• Authors: Pedro Réu, Azadeh Khosravi, Samuel Bernard, Jeff E. Mold, Mehran Salehpour, Kanar Alkass, Shira Perl, John F. Tisdale, Göran Possnert, Henrik Druid, Jonas Frisén
• Venue: Cell Reports
• Published: 2017-07-01
• DOI: 10.1016/j.celrep.2017.07.004
• Citation count: 510
• Institutions: Stockholm University; University of Coimbra; Karolinska Institutet; Lyon 1 Université; Centre National de la Recherche Scientifique; Institut Camille Jordan; Uppsala University; National Institutes of Health
• Topics: Neuroinflammation and Neurodegeneration Mechanisms, Neurogenesis and neuroplasticity mechanisms, Immune cells in cancer, Microglia, Biology, Progenitor cell, Population, Haematopoiesis, Neuroscience, Progenitor
• License/access: cc-by (open access)
• Record: https://doi.org/10.1016/j.celrep.2017.07.004
• Abstract (verbatim): "The hematopoietic system seeds the CNS with microglial progenitor cells during the fetal period, but the subsequent cell generation dynamics and maintenance of this population have been poorly understood. We report that microglia, unlike most other hematopoietic lineages, renew slowly at a median rate of 28% per year, and some microglia last for more than two decades. Furthermore, we find no evidence for the existence of a substantial population of quiescent long-lived cells, meaning that the microglia population in the human brain is sustained by continuous slow turnover throughout adult life." [1]

[2] If We Share Data, Will Anyone Use Them? Data Sharing and Reuse in the Long Tail of Science and Technology

• Authors: Jillian C. Wallis, Elizabeth Rolando, Christine L. Borgman
• Venue: PLoS ONE
• Published: 2013-07-23
• DOI: 10.1371/journal.pone.0067332
• Citation count: 499
• Institutions: University of California, Los Angeles
• Topics: Research Data Management Practices, Scientific Computing and Data Management, Data Quality and Management, Data sharing, Context (archaeology), Scholarship, Reuse, Publication, Data management, Data science
• License/access: cc-by (open access)
• Record: https://doi.org/10.1371/journal.pone.0067332
• Abstract (verbatim): "Research on practices to share and reuse data will inform the design of infrastructure to support data collection, management, and discovery in the long tail of science and technology. These are research domains in which data tend to be local in character, minimally structured, and minimally documented. We report on a ten-year study of the Center for Embedded Network Sensing (CENS), a National Science Foundation Science and Technology Center. We found that CENS researchers are willing to share their data, but few are asked to do so, and in only a few domain areas do their funders or journals require them to deposit data. Few repositories exist to accept data in CENS research areas.. Data sharing tends to occur only through interpersonal exchanges. CENS researchers obtain data from repositories, and occasionally from registries and individuals, to provide context, calibration, or other forms of background for their studies. Neither CENS researchers nor those who request access to CENS data appear to use external data for primary research questions or for replication of studies. CENS researchers are willing to share data if they receive credit and retain first rights to publish their results. Practices of releasing, sharing, and reusing of data in CENS reaffirm the gift culture of scholarship, in which goods are bartered between trusted colleagues rather than treated as commodities." [2]

[3] The 1000 Genomes Project: data management and community access

• Authors: Laura Clarke, Xiangqun Zheng-Bradley, Richard Smith, Eugene Kulesha, Chunlin Xiao, Iliana Toneva, Brendan Vaughan, Don Preuss, Rasko Leinonen, Martin Shumway, Stephen T. Sherry, Paul Flicek
• Venue: Nature Methods
• Published: 2012-04-27
• DOI: 10.1038/nmeth.1974
• Citation count: 484
• Institutions: European Bioinformatics Institute; Wellcome Trust; National Institutes of Health; National Center for Biotechnology Information
• Topics: Genomics and Phylogenetic Studies, Genomics and Rare Diseases, Gene expression and cancer classification, Data science, Data management, Genome, Computer science, Variation (astronomy), 1000 Genomes Project, World Wide Web
• License/access: cc-by-nc-sa (open access)
• Record: https://doi.org/10.1038/nmeth.1974
• Abstract (verbatim): "The 1000 Genomes Project was launched as one of the largest distributed data collection and analysis projects ever undertaken in biology. In addition to the primary scientific goals of creating both a deep catalog of human genetic variation and extensive methods to accurately discover and characterize variation using new sequencing technologies, the project makes all of its data publicly available. Members of the project data coordination center have developed and deployed several tools to enable widespread data access." [3]

[4] “Citizen Science”? Rethinking Science and Public Participation

• Authors: Bruno J. Strasser, Jérôme Baudry, Dana Mahr, Gabriela Sánchez, Élise Tancoigne
• Venue: Science & Technology Studies
• Published: 2018-10-30
• DOI: 10.23987/sts.60425
• Citation count: 430
• Institutions: University of Geneva
• Topics: Species Distribution and Climate Change, Citizen science, Democratization, Citizen journalism, Diversity (politics), Political science, Politics, Sociology, Public participation, Science education
• License/access: cc-by (open access)
• Record: https://doi.org/10.23987/sts.60425
• Abstract (verbatim): "Since the late twentieth century, “citizen science” has become an increasingly fashionable label for a growing number of participatory research activities. This paper situates the origins and rise of the term “citizen science” and contextualises “citizen science” within the broader history of public participation in science. It analyses critically the current promises — democratisation, education, discoveries — emerging within the “citizen science” discourse and offers a new framework to better understand the diversity of epistemic practices involved in these participatory projects. Finally, it maps a number of historical, political, and social questions for future research in the critical studies of “citizen science”." [4]