Re-thinking organisms: The impact of databases on model organism biology

Leonelli, Sabina; Ankeny, Rachel A.

doi:10.1016/j.shpsc.2011.10.003

Cited by 144 publications

(83 citation statements)

References 20 publications

(18 reference statements)

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“…Interoperability strategies include imposing or embedding common standards, such as what counts as reliable evidence, acceptable research methods, and data management practices (Bowker, 2005;Leonelli & Ankeny, 2012). Infrastructure can also foster norms of behavior that encourage greater openness within a scientific community, including openness around data (Leonelli, 2010).…”

Section: Gaining Access To Extant Datamentioning

confidence: 99%

“…Contributions to a database can, in turn, encourage greater willingness to contribute to a database, resulting in a self-reinforcing cycle of increased data availability and normative shifts towards greater data openness. Databases can help encourage the circulation of types of data that the database does not support by creating expectations that scientists will share data when asked (Leonelli & Ankeny, 2012). Kelty (2012) discusses how scientific newsletters in biology not only constituted an infrastructure to build communities around particular organisms, but also promoted sharing of research objects by requiring openness of researchers as a condition of receiving the newsletter (and thus continued membership of the community).…”

Section: Gaining Access To Extant Datamentioning

confidence: 99%

“…A second way to maximize scientific work is to aggregate and integrate existing data more effectively (Leonelli & Ankeny, 2012;Meyer, 2009), for instance by embedding common standards within or across domains (Bowker, 2005;Leonelli & Ankeny, 2012) or by building links between members of the domain and fostering norms of data sharing and openness across this domain (Kelty, 2012;Leonelli, 2010). The C-DEBI data infrastructure exists to foster collaboration among other deep subseafloor biosphere researchers, and to assemble and circulate data produced by distributed domain scientists.…”

Section: How Domains Share or Build Their Own Infrastructuresmentioning

confidence: 99%

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Ship space to database: emerging infrastructures for studies of the deep subseafloor biosphere

Darch

Borgman

2016

PeerJ Computer Science

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Background. An increasing array of scientific fields face a ''data deluge.'' However, in many fields data are scarce, with implications for their epistemic status and ability to command funding. Consequently, they often attempt to develop infrastructure for data production, management, curation, and circulation. A component of a knowledge infrastructure may serve one or more scientific domains. Further, a single domain may rely upon multiple infrastructures simultaneously. Studying how domains negotiate building and accessing scarce infrastructural resources that they share with other domains will shed light on how knowledge infrastructures shape science. Methods. We conducted an eighteen-month, qualitative study of scientists studying the deep subseafloor biosphere, focusing on the Center for Dark Energy Biosphere Investigations (C-DEBI) and the Integrated Ocean Drilling Program (IODP) and its successor, the International Ocean Discovery Program (IODP2). Our methods comprised ethnographic observation, including eight months embedded in a laboratory, interviews (n = 49), and document analysis. Results. Deep subseafloor biosphere research is an emergent domain. We identified two reasons for the domain's concern with data scarcity: limited ability to pursue their research objectives, and the epistemic status of their research. Domain researchers adopted complementary strategies to acquire more data. One was to establish C-DEBI as an infrastructure solely for their domain. The second was to use C-DEBI as a means to gain greater access to, and reconfigure, IODP/IODP2 to their advantage. IODP/IODP2 functions as infrastructure for multiple scientific domains, which creates competition for resources. C-DEBI is building its own data management infrastructure, both to acquire more data from IODP and to make better use of data, once acquired. Discussion. Two themes emerge. One is data scarcity, which can be understood only in relation to a domain's objectives. To justify support for public funding, domains must demonstrate their utility to questions of societal concern or existential questions about humanity. The deep subseafloor biosphere domain aspires to address these questions in a more statistically intensive manner than is afforded by the data to which it currently has access. The second theme is the politics of knowledge infrastructures. A single scientific domain may build infrastructure for itself and negotiate access to multi-domain infrastructure simultaneously. C-DEBI infrastructure was designed both as a response to scarce IODP/IODP2 resources, and to configure the data allocation processes of IODP/IODP2 in their favor.

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Section: Gaining Access To Extant Datamentioning

confidence: 99%

Section: Gaining Access To Extant Datamentioning

confidence: 99%

Section: How Domains Share or Build Their Own Infrastructuresmentioning

confidence: 99%

See 1 more Smart Citation

Ship space to database: emerging infrastructures for studies of the deep subseafloor biosphere

Darch

Borgman

2016

PeerJ Computer Science

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“…While often reviled as boring routine by the classical cell and molecular biologist favouring detailed functional study, the isolation of disease genes required original strategies and resourceful tinkering, large-scale collaboration and competition, the development of massive data analysis and sharing infrastructures, and data-intensive analysis and interpretation across several model systems (Leonelli & Ankeny, 2012;Makałowski et al, 2014;Smith & Porter, 2014). The study of human genetic disease and non-F o r R e v i e w O n l y human organisms has highlighted the existence of many novel genetic mechanisms, the impact of which could never have been conceived otherwise.…”

Section: Model Systems Functional Genomics and Epigeneticsmentioning

confidence: 99%

Human Genome Project, Personalised Medicine and Future Health Care

Tempini

Leonelli

2015

Encyclopedia of Life Sciences

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Abstract:At the turn of the millennium, the Human Genome Project and the upcoming publication of the human genome sequence promised to open an entirely new approach to healthcare, based on the genotype of the individual. This approach was dubbed personalised medicine (PM). However, the analysis of sequencing results revealed that the complexity of the biological world had been underestimated. The major project of revolutionizing medicine through genomics requires a more sophisticated and multilevel understanding of living systems, which in turn demands new data, models and modes of intervention on humans as well as non-human organisms. Thus, the most advanced applications of PM involve a complex interweaving of biological and medical knowledge, as well as increasing attention to the technical systems through which data about any specific individual could be processed. Further, the development of PM needs to include consideration of several key ethical issues, ranging from privacy and data control to the risk that dependence on sophisticated technologies will widen the gap between haves and have-nots both globally and within any one country. AbstractAt the turn of the millennium, the Human Genome Project and the upcoming publication of the human genome sequence promised to open an entirely new approach to healthcare, based on the genotype of the individual. This approach was dubbed personalised medicine (PM). However, the analysis of sequencing results revealed that the complexity of the biological world had been underestimated. The major project of revolutionizing medicine through genomics requires a more sophisticated and multilevel understanding of living systems, which in turn demands new data, models and modes of intervention on humans as well as nonhuman organisms. Thus, the most advanced applications of PM involve a complex interweaving of biological and medical knowledge, as well as increasing attention to the technical systems through which data about any Keywords: human genome project; healthcare; personalised medicine; precision medicine; pharmacogenomics; data-intensive science; translational medicine. Key Concepts-Personalised medicine describes the direction medical solutions are expected to evolve, towards personalisation and individual tailoring of therapies and treatment regimes that will cut and divide through patient populations. The motor of this promised innovation will be genomic profiling techniques, of nuclear DNA but also ones of latter development such as proteomics, metabolomics, transcriptomics, and so on.-Biomedicine is an interdisciplinary space involving biological and medical knowledge/expertise as well as IT, where scientific knowledge about biological phenomena is mobilized in order to devise solutions to medical problems.-Data-intensive science describes the mode of scientific research that is emerging as paramount in an age characterised by the increasing reliance and dependence of researchers on the development of complex, distributed infrastructures for data sharing and anal...

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“…I shall base my philosophical analysis on historical and ethnographic research that I carried out in the areas of model organism biology, bioinformatics and plant science over the last eight years (documented in detail in Leonelli 2010a, Ankeny 2012 andLeonelli 2012a). In particular, I will use three case studies in contemporary plant science as exemplary for the forms of integration that I wish to discuss: (1) the research activities centered around data gathered on model organism Arabidopsis thaliana; (2) the efforts to integrate Arabidopsis data with data gathered on the perennial crop family Miscanthus; and (3) current investigations of the biology of Phytophtora ramorum, a plant parasite that is wreaking havoc in the forests of the South-West of the UK, where I live.…”

Section: Introductionmentioning

confidence: 99%

Re-thinking organisms: The impact of databases on model organism biology

Cited by 144 publications

References 20 publications

Ship space to database: emerging infrastructures for studies of the deep subseafloor biosphere

Ship space to database: emerging infrastructures for studies of the deep subseafloor biosphere

Human Genome Project, Personalised Medicine and Future Health Care

Integrating data to acquire new knowledge: Three modes of integration in plant science

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