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Sabina Leonelli
University of Exeter
  1. What’s so Special About Model Organisms?Rachel A. Ankeny & Sabina Leonelli - 2011 - Studies in History and Philosophy of Science Part A 42 (2):313-323.
    This paper aims to identify the key characteristics of model organisms that make them a specific type of model within the contemporary life sciences: in particular, we argue that the term “model organism” does not apply to all organisms used for the purposes of experimental research. We explore the differences between experimental and model organisms in terms of their material and epistemic features, and argue that it is essential to distinguish between their representational scope and representational target. We also examine (...)
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  2.  88
    Repertoires: A Post-Kuhnian Perspective on Scientific Change and Collaborative Research.Rachel A. Ankeny & Sabina Leonelli - 2016 - Studies in History and Philosophy of Science Part A 60:18-28.
  3. Scientific Understanding: Philosophical Perspectives.Henk de Regt, Sabina Leonelli & Kai Eigner (eds.) - 2008 - University of Pittsburgh Press.
    The chapters in this book highlight the multifaceted nature of the process of scientific research.
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  4.  44
    Re-Thinking Reproducibility as a Criterion for Research Quality.Sabina Leonelli - 2018 - Research in the History of Economic Thought and Methodology 36 (B):129-146.
    A heated debate surrounds the significance of reproducibility as an indicator for research quality and reliability, with many commentators linking a "crisis of reproducibility" to the rise of fraudulent, careless and unreliable practices of knowledge production. Through the analysis of discourse and practices across research fields, I point out that reproducibility is not only interpreted in different ways, but also serves a variety of epistemic functions depending on the research at hand. Given such variation, I argue that the uncritical pursuit (...)
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  5.  49
    What Distinguishes Data From Models?Sabina Leonelli - 2019 - European Journal for Philosophy of Science 9 (2):22.
    I propose a framework that explicates and distinguishes the epistemic roles of data and models within empirical inquiry through consideration of their use in scientific practice. After arguing that Suppes’ characterization of data models falls short in this respect, I discuss a case of data processing within exploratory research in plant phenotyping and use it to highlight the difference between practices aimed to make data usable as evidence and practices aimed to use data to represent a specific phenomenon. I then (...)
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  6. What Counts as Scientific Data? A Relational Framework.Sabina Leonelli - 2015 - Philosophy of Science 82 (5):810-821.
    This paper proposes an account of scientific data that makes sense of recent debates on data-driven and ‘big data’ research, while also building on the history of data production and use particularly within biology. In this view, ‘data’ is a relational category applied to research outputs that are taken, at specific moments of inquiry, to provide evidence for knowledge claims of interest to the researchers involved. They do not have truth-value in and of themselves, nor can they be seen as (...)
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  7. Classificatory Theory in Data-Intensive Science: The Case of Open Biomedical Ontologies.Sabina Leonelli - 2012 - International Studies in the Philosophy of Science 26 (1):47 - 65.
    Knowledge-making practices in biology are being strongly affected by the availability of data on an unprecedented scale, the insistence on systemic approaches and growing reliance on bioinformatics and digital infrastructures. What role does theory play within data-intensive science, and what does that tell us about scientific theories in general? To answer these questions, I focus on Open Biomedical Ontologies, digital classification tools that have become crucial to sharing results across research contexts in the biological and biomedical sciences, and argue that (...)
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  8.  78
    Integrating Data to Acquire New Knowledge: Three Modes of Integration in Plant Science.Sabina Leonelli - 2013 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 44 (4):503-514.
    This paper discusses what it means and what it takes to integrate data in order to acquire new knowledge about biological entities and processes. Maureen O’Malley and Orkun Soyer have pointed to the scientific work involved in data integration as important and distinct from the work required by other forms of integration, such as methodological and explanatory integration, which have been more successful in captivating the attention of philosophers of science. Here I explore what data integration involves in more detail (...)
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  9.  68
    Re-Thinking Organisms: The Impact of Databases on Model Organism Biology.Sabina Leonelli & Rachel A. Ankeny - 2012 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 43 (1):29-36.
    Community databases have become crucial to the collection, ordering and retrieval of data gathered on model organisms, as well as to the ways in which these data are interpreted and used across a range of research contexts. This paper analyses the impact of community databases on research practices in model organism biology by focusing on the history and current use of four community databases: FlyBase, Mouse Genome Informatics, WormBase and The Arabidopsis Information Resource. We discuss the standards used by the (...)
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  10.  16
    What Distinguishes Data From Models?Sabina Leonelli - 2019 - European Journal for Philosophy of Science 9 (2):22.
    I propose a framework that explicates and distinguishes the epistemic roles of data and models within empirical inquiry through consideration of their use in scientific practice. After arguing that Suppes’ characterization of data models falls short in this respect, I discuss a case of data processing within exploratory research in plant phenotyping and use it to highlight the difference between practices aimed to make data usable as evidence and practices aimed to use data to represent a specific phenomenon. I then (...)
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  11.  60
    Data Interpretation in the Digital Age.Sabina Leonelli - 2014 - Perspectives on Science 22 (3):397-417.
    Scientific knowledge production is currently affected by the dissemination of data on an unprecedented scale. Technologies for the automated production and sharing of vast amounts of data have changed the way in which data are handled and interpreted in several scientific domains, most notably molecular biology and biomedicine. In these fields, the activity of data gathering has become increasingly technology-driven, with machines such as next generation genome sequencers and mass spectrometers generating billions of data points within hours, and with little (...)
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  12.  27
    Focusing on Scientific Understanding.Henk W. de Regt, Sabina Leonelli & K. Eigner - 2009 - In Henk De Regt, Sabina Leonelli & Kai Eigner (eds.), Scientific Understanding: Philosophical Perspectives. University of Pittsburgh Press.
  13.  80
    On the Locality of Data and Claims About Phenomena.Sabina Leonelli - 2009 - Philosophy of Science 76 (5):737-749.
    Bogen and Woodward characterized data as embedded in the context in which they are produced (‘local’) and claims about phenomena as retaining their significance beyond that context (‘nonlocal’). This view does not fit sciences such as biology, which successfully disseminate data via packaging processes that include appropriate labels, vehicles, and human interventions. These processes enhance the evidential scope of data and ensure that claims about phenomena are understood in the same way across research communities. I conclude that the degree of (...)
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  14.  67
    Performing Abstraction: Two Ways of Modelling Arabidopsis Thaliana.Sabina Leonelli - 2008 - Biology and Philosophy 23 (4):509-528.
    What is the best way to analyse abstraction in scientific modelling? I propose to focus on abstracting as an epistemic activity, which is achieved in different ways and for different purposes depending on the actual circumstances of modelling and the features of the models in question. This is in contrast to a more conventional use of the term ‘abstract’ as an attribute of models, which I characterise as black-boxing the ways in which abstraction is performed and to which epistemological advantage. (...)
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  15.  40
    The Time of Data: Timescales of Data Use in the Life Sciences.Sabina Leonelli - 2018 - Philosophy of Science 85 (5):741-754.
    This paper considers the temporal dimension of data processing and use, and the ways in which it affects the production and interpretation of knowledge claims. I start by distinguishing the time at which data collection, dissemination and analysis occur from the time in which the phenomena for which data serve as evidence operate. Building on the analysis of two examples of data re-use from modelling and experimental practices in biology, I then argue that Dt affects how researchers select and interpret (...)
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  16.  7
    How Does One “Open” Science? Questions of Value in Biological Research.Sabina Leonelli & Nadine Levin - 2017 - Science, Technology, and Human Values 42 (2):280-305.
    Open Science policies encourage researchers to disclose a wide range of outputs from their work, thus codifying openness as a specific set of research practices and guidelines that can be interpreted and applied consistently across disciplines and geographical settings. In this paper, we argue that this “one-size-fits-all” view of openness sidesteps key questions about the forms, implications, and goals of openness for research practice. We propose instead to interpret openness as a dynamic and highly situated mode of valuing the research (...)
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  17.  18
    Documenting the Emergence of Bio-Ontologies: Or, Why Researching Bioinformatics Requires HPSSB.Sabina Leonelli - 2010 - History and Philosophy of the Life Sciences 32 (1).
  18.  4
    Data Shadows: Knowledge, Openness, and Absence.Gail Davies, Brian Rappert & Sabina Leonelli - 2017 - Science, Technology, and Human Values 42 (2):191-202.
    This editorial critically engages with the understanding of openness by attending to how notions of presence and absence come bundled together as part of efforts to make open. This is particularly evident in contemporary discourse around data production, dissemination, and use. We highlight how the preoccupations with making data present can be usefully analyzed and understood by tracing the related concerns around what is missing, unavailable, or invisible, which unvaryingly but often implicitly accompany debates about data and openness.
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  19.  37
    Bio-Ontologies as Tools for Integration in Biology.Sabina Leonelli - 2008 - Biological Theory 3 (1):7-11.
  20.  39
    Growing Weed, Producing Knowledge An Epistemic History of Arabidopsis Thaliana.Sabina Leonelli - 2007 - History and Philosophy of the Life Sciences 29 (2):193 - 223.
    Arabidopsis is currently the most popular and well-researched model organism in plant biology. This paper documents this plant's rise to scientific fame by focusing on two interrelated aspects of Arabidopsis research. One is the extent to which the material features of the plant have constrained research directions and enabled scientific achievements. The other is the crucial role played by the international community of Arabidopsis researchers in making it possible to grow, distribute and use plant specimen that embody these material features. (...)
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  21.  4
    Why the Current Insistence on Open Access to Scientific Data? Big Data, Knowledge Production, and the Political Economy of Contemporary Biology.Sabina Leonelli - 2013 - Bulletin of Science, Technology and Society 33 (1-2):6-11.
    The collection and dissemination of data on human and nonhuman organisms has become a central feature of 21st-century biology and has been endorsed by funding agencies in the United States and Europe as crucial to translating biological research into therapeutic and agricultural innovation. Large molecular data sets, often referred to as “big data,” are increasingly incorporated into digital databases, many of which are freely accessible online. These data have come to be seen as resources that play a key role in (...)
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  22.  41
    Classificatory Theory in Biology.Sabina Leonelli - 2013 - Biological Theory 7 (4):338-345.
    Scientific classification has long been recognized as involving a specific style of reasoning and doing research, and as occasionally affecting the development of scientific theories. However, the role played by classificatory activities in generating theories has not been closely investigated within the philosophy of science. I argue that classificatory systems can themselves become a form of theory, which I call classificatory theory, when they come to formalize and express the scientific significance of the elements being classified. This is particularly evident (...)
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  23.  18
    Understanding in Biology: The Impure Nature of Biological Knowledge.Sabina Leonelli - 2009 - In Henk De Regt, Sabina Leonelli & Kai Eigner (eds.), Scientific Understanding: Philosophical Perspectives. University of Pittsburgh Press. pp. 189--209.
  24.  27
    ‘Extreme’ Organisms and the Problem of Generalization: Interpreting the Krogh Principle.Sara Green, Michael R. Dietrich, Sabina Leonelli & Rachel A. Ankeny - 2018 - History and Philosophy of the Life Sciences 40 (4):65.
    Many biologists appeal to the so-called Krogh principle when justifying their choice of experimental organisms. The principle states that “for a large number of problems there will be some animal of choice, or a few such animals, on which it can be most conveniently studied”. Despite its popularity, the principle is often critiqued for implying unwarranted generalizations from optimal models. We argue that the Krogh principle should be interpreted in relation to the historical and scientific contexts in which it has (...)
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  25.  10
    How to Choose Your Research Organism.Michael R. Dietrich, Rachel A. Ankeny, Nathan Crowe, Sara Green & Sabina Leonelli - 2020 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 80:101227.
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  26.  29
    Making Organisms Model Human Behavior: Situated Models in North-American Alcohol Research, Since 1950.Rachel A. Ankeny, Sabina Leonelli, Nicole C. Nelson & Edmund Ramsden - 2014 - Science in Context 27 (3):485-509.
    ArgumentWe examine the criteria used to validate the use of nonhuman organisms in North-American alcohol addiction research from the 1950s to the present day. We argue that this field, where the similarities between behaviors in humans and non-humans are particularly difficult to assess, has addressed questions of model validity by transforming the situatedness of non-human organisms into an experimental tool. We demonstrate that model validity does not hinge on the standardization of one type of organism in isolation, as often the (...)
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  27.  34
    Introduction: On the Philosophy of Science in Practice. [REVIEW]Marcel Boumans & Sabina Leonelli - 2013 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 44 (2):259-261.
  28.  20
    Where Health and Environment Meet: The Use of Invariant Parameters in Big Data Analysis.Sabina Leonelli & Niccolò Tempini - 2018 - Synthese 198 (Suppl 10):1-20.
    The use of big data to investigate the spread of infectious diseases or the impact of the built environment on human wellbeing goes beyond the realm of traditional approaches to epidemiology, and includes a large variety of data objects produced by research communities with different methods and goals. This paper addresses the conditions under which researchers link, search and interpret such diverse data by focusing on “data mash-ups”—that is the linking of data from epidemiology, biomedicine, climate and environmental science, which (...)
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  29.  3
    How Do Scientists Define Openness? Exploring the Relationship Between Open Science Policies and Research Practice.John Dupré, David Castle, Dagmara Weckowska, Sabina Leonelli & Nadine Levin - 2016 - Bulletin of Science, Technology and Society 36 (2):128-141.
    This article documents how biomedical researchers in the United Kingdom understand and enact the idea of “openness.” This is of particular interest to researchers and science policy worldwide in view of the recent adoption of pioneering policies on Open Science and Open Access by the U.K. government—policies whose impact on and implications for research practice are in need of urgent evaluation, so as to decide on their eventual implementation elsewhere. This study is based on 22 in-depth interviews with U.K. researchers (...)
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  30.  66
    Infrared Metaphysics: Radiation and Theory-Choice. Part 2.Hasok Chang & Sabina Leonelli - 2005 - Studies in History and Philosophy of Science Part A 36 (4):687-706.
    We continue our discussion of the competing arguments in favour of the unified theory and the pluralistic theory of radiation advanced by three nineteenth-century pioneers: Herschel, Melloni, and Draper. Our narrative is structured by a consideration of the epistemic criteria relevant to theory-choice; the epistemic focus highlights many little-known aspects of this relatively well-known episode. We argue that the acceptance of light-heat unity in this period cannot be credibly justified on the basis of common evaluative criteria such as simplicity and (...)
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  31.  30
    Infrared Metaphysics: The Elusive Ontology of Radiation. Part 1.Hasok Chang & Sabina Leonelli - 2005 - Studies in History and Philosophy of Science Part A 36 (3):477-508.
    Hardly any ontological result of modern science is more firmly established than the fact that infrared radiation differs from light only in wavelength; this is part of the modern conception of the continuous spectrum of electromagnetic radiation reaching from radio waves to gamma radiation. Yet, like many such evident truths, the light-infrared unity was an extremely difficult thing to establish. We examine the competing arguments in favour of the unified and pluralistic theories of radiation, as put forward in the first (...)
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  32.  28
    Symposium Issue: Philosophy of Biology in Flanders and the Netherlands.Sabina Leonelli & Thomas Reydon - 2005 - Acta Biotheoretica 53 (2):55-56.
  33.  24
    Bioethics Authorship in Context: How Trends in Biomedicine Challenge Bioethics.Rachel A. Ankeny & Sabina Leonelli - 2011 - American Journal of Bioethics 11 (10):22 - 24.
    The American Journal of Bioethics, Volume 11, Issue 10, Page 22-24, October 2011.
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  34. Model Organisms.Rachel Ankeny & Sabina Leonelli - 2021 - Cambridge University Press.
    This Element presents a philosophical exploration of the concept of the 'model organism' in contemporary biology. Thinking about model organisms enables us to examine how living organisms have been brought into the laboratory and used to gain a better understanding of biology, and to explore the research practices, commitments, and norms underlying this understanding. We contend that model organisms are key components of a distinctive way of doing research. We focus on what makes model organisms an important type of model, (...)
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  35.  12
    Intellectual Directions for History and Philosophy of the Life Sciences, 2019–2023.Giovanni Boniolo & Sabina Leonelli - 2019 - History and Philosophy of the Life Sciences 41 (3):28.
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  36.  20
    An Epistemology of the Concrete: Twentieth-Century Histories of Life.Sabina Leonelli - 2011 - International Studies in the Philosophy of Science 25 (4):420-422.
    International Studies in the Philosophy of Science, Volume 25, Issue 4, Page 420-422, December 2011.
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  37. Data Journeys in the Sciences.Sabina Leonelli & Niccolò Tempini (eds.) - 2020 - Springer.
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  38. Naar een open dialoog tussen de wetenschap en de wetenschapsstudies.Sabina Leonelli - 2007 - Algemeen Nederlands Tijdschrift voor Wijsbegeerte 3.
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  39.  47
    Ordinary Genomes: Science, Citizenship and Genetic Identities. [REVIEW]Sabina Leonelli - 2012 - Acta Biotheoretica 60 (3):319-322.
    Karen-Sue Taussig: Ordinary Genomes: Science, Citizenship and Genetic Identities Content Type Journal Article Category Book Review Pages 1-4 DOI 10.1007/s10441-012-9150-8 Authors Sabina Leonelli, Department of Sociology and Philosophy, ESRC Centre for Genomics in Society, University of Exeter, Exeter, Devon, UK Journal Acta Biotheoretica Online ISSN 1572-8358 Print ISSN 0001-5342.
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  40.  39
    The Crucial Role of Models in Science: Natasha Myers: Rendering Life Molecular: Models, Modelers, and Excitable Matter. Durham and London: Duke University Press, 2015, 328pp, $94.95 Cloth, $26.95 PB.Sabina Leonelli - 2017 - Metascience 26 (1):99-101.
  41.  11
    The Scientific Importance of Asking Questions at Meetings: Why Virtual Debate is Not Enough.Maureen A. O'Malley & Sabina Leonelli - 2011 - Bioessays 33 (1):35-37.
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  42. Open science, data sharing and solidarity: who benefits?Ciara Staunton, Carlos Andrés Barragán, Stefano Canali, Calvin Ho, Sabina Leonelli, Matthew Mayernik, Barbara Prainsack & Ambroise Wonkham - 2021 - History and Philosophy of the Life Sciences 43 (4):1-8.
    Research, innovation, and progress in the life sciences are increasingly contingent on access to large quantities of data. This is one of the key premises behind the “open science” movement and the global calls for fostering the sharing of personal data, datasets, and research results. This paper reports on the outcomes of discussions by the panel “Open science, data sharing and solidarity: who benefits?” held at the 2021 Biennial conference of the International Society for the History, Philosophy, and Social Studies (...)
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  43. From FAIR Data to Fair Data Use: Methodological Data Fairness in Health-Related Social Media Research.Hywel Williams, Lora Fleming, Benedict W. Wheeler, Rebecca Lovell & Sabina Leonelli - 2021 - Big Data and Society 8 (1).
    The paper problematises the reliability and ethics of using social media data, such as sourced from Twitter or Instagram, to carry out health-related research. As in many other domains, the opportunity to mine social media for information has been hailed as transformative for research on well-being and disease. Considerations around the fairness, responsibilities and accountabilities relating to using such data have often been set aside, on the understanding that as long as data were anonymised, no real ethical or scientific issue (...)
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