Results for 'Data-Driven Science'

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  1. Beyond Categorical Definitions of Life: A Data-Driven Approach to Assessing Lifeness.Christophe Malaterre & Jean-François Chartier - 2019 - Synthese 198 (5):4543-4572.
    The concept of “life” certainly is of some use to distinguish birds and beavers from water and stones. This pragmatic usefulness has led to its construal as a categorical predicate that can sift out living entities from non-living ones depending on their possessing specific properties—reproduction, metabolism, evolvability etc. In this paper, we argue against this binary construal of life. Using text-mining methods across over 30,000 scientific articles, we defend instead a degrees-of-life view and show how these methods can contribute to (...)
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  2.  72
    Ihde’s Missing Sciences: Postphenomenology, Big Data, and the Human Sciences.Daniel Susser - 2016 - Techné: Research in Philosophy and Technology 20 (2):137-152.
    In Husserl’s Missing Technologies, Don Ihde urges us to think deeply and critically about the ways in which the technologies utilized in contemporary science structure the way we perceive and understand the natural world. In this paper, I argue that we ought to extend Ihde’s analysis to consider how such technologies are changing the way we perceive and understand ourselves too. For it is not only the natural or “hard” sciences which are turning to advanced technologies for help in (...)
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  3. Big Data, Epistemology and Causality: Knowledge in and Knowledge Out in EXPOsOMICS.Stefano Canali - 2016 - Big Data and Society 3 (2).
    Recently, it has been argued that the use of Big Data transforms the sciences, making data-driven research possible and studying causality redundant. In this paper, I focus on the claim on causal knowledge by examining the Big Data project EXPOsOMICS, whose research is funded by the European Commission and considered capable of improving our understanding of the relation between exposure and disease. While EXPOsOMICS may seem the perfect exemplification of the data-driven view, I show (...)
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  4. The Epistemological Foundations of Data Science: A Critical Analysis.Jules Desai, David Watson, Vincent Wang, Mariarosaria Taddeo & Luciano Floridi - manuscript
    The modern abundance and prominence of data has led to the development of “data science” as a new field of enquiry, along with a body of epistemological reflections upon its foundations, methods, and consequences. This article provides a systematic analysis and critical review of significant open problems and debates in the epistemology of data science. We propose a partition of the epistemology of data science into the following five domains: (i) the constitution of (...)
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  5. Annotating Affective Neuroscience Data with the Emotion Ontology.Janna Hastings, Werner Ceusters, Kevin Mulligan & Barry Smith - 2012 - In Third International Conference on Biomedical Ontology. ICBO. pp. 1-5.
    The Emotion Ontology is an ontology covering all aspects of emotional and affective mental functioning. It is being developed following the principles of the OBO Foundry and Ontological Realism. This means that in compiling the ontology, we emphasize the importance of the nature of the entities in reality that the ontology is describing. One of the ways in which realism-based ontologies are being successfully used within biomedical science is in the annotation of scientific research results in publicly available databases. (...)
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  6. The Fate of Explanatory Reasoning in the Age of Big Data.Frank Cabrera - 2021 - Philosophy and Technology 34 (4):645-665.
    In this paper, I critically evaluate several related, provocative claims made by proponents of data-intensive science and “Big Data” which bear on scientific methodology, especially the claim that scientists will soon no longer have any use for familiar concepts like causation and explanation. After introducing the issue, in Section 2, I elaborate on the alleged changes to scientific method that feature prominently in discussions of Big Data. In Section 3, I argue that these methodological claims are (...)
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  7. No Wisdom in the Crowd: Genome Annotation at the Time of Big Data - Current Status and Future Prospects.Antoine Danchin - 2018 - Microbial Biotechnology 11 (4):588-605.
    Science and engineering rely on the accumulation and dissemination of knowledge to make discoveries and create new designs. Discovery-driven genome research rests on knowledge passed on via gene annotations. In response to the deluge of sequencing big data, standard annotation practice employs automated procedures that rely on majority rules. We argue this hinders progress through the generation and propagation of errors, leading investigators into blind alleys. More subtly, this inductive process discourages the discovery of novelty, which remains (...)
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  8. What is This Thing Called Philosophy of Science? A Computational Topic-Modeling Perspective, 1934–2015.Christophe Malaterre, Jean-François Chartier & Davide Pulizzotto - 2019 - Hopos: The Journal of the International Society for the History of Philosophy of Science 9 (2):215-249.
    What is philosophy of science? Numerous manuals, anthologies or essays provide carefully reconstructed vantage points on the discipline that have been gained through expert and piecemeal historical analyses. In this paper, we address the question from a complementary perspective: we target the content of one major journal of the field—Philosophy of Science—and apply unsupervised text-mining methods to its complete corpus, from its start in 1934 until 2015. By running topic-modeling algorithms over the full-text corpus, we identified 126 key (...)
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  9. 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, (...)
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  10. What Isn’T Obvious About ‘Obvious’: A Data-Driven Approach to Philosophy of Logic.Moti Mizrahi - 2019 - In Andrew Aberdein & Matthew Inglis (eds.), Advances in Experimental Philosophy of Logic and Mathematics. London: Bloomsbury Press. pp. 201-224.
    It is often said that ‘every logical truth is obvious’ (Quine 1970: 82), that the ‘axioms and rules of logic are true in an obvious way’ (Murawski 2014: 87), or that ‘logic is a theory of the obvious’ (Sher 1999: 207). In this chapter, I set out to test empirically how the idea that logic is obvious is reflected in the scholarly work of logicians and philosophers of logic. My approach is data-driven. That is to say, I propose (...)
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  11.  76
    The Bridge Between Philosophy and Information-Driven Science.Barry Smith - 2021 - Journal of Knowledge Structures and Systems 2 (2):47-55.
    This essay is a response to Luis M. Augusto’s intriguing paper on the rift between mainstream and formal ontology. I will show that there are in fact two questions at issue here: 1. concerning the links between mainstream and formal approaches within philosophy, and 2. concerning the application of philosophy (and especially philosophical ontology) in support of information-driven research for example in the life sciences.
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  12.  68
    Five Ethical Challenges for Data-Driven Policing.Jeremy Davis, Duncan Purves, Juan Gilbert & Schuyler Sturm - forthcoming - AI and Ethics.
    This paper synthesizes scholarship from several academic disciplines to identify and analyze five major ethical challenges facing data-driven policing. Because the term “data-driven policing” emcompasses a broad swath of technologies, we first outline several data-driven policing initiatives currently in use in the United States. We then lay out the five ethical challenges. Certain of these challenges have received considerable attention already, while others have been largely overlooked. In many cases, the challenges have been articulated (...)
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  13.  4
    Urban Scale Digital Twins in Data-Driven Society: Challenging Digital Universalism in Urban Planning Decision-Making.Marianna Charitonidou - 2022 - International Journal of Architectural Computing 19:1-16.
    The article examines the impact of the virtual public sphere on how urban spaces are experienced and conceived in our data-driven society. It places particular emphasis on urban scale digital twins, which are virtual replicas of cities that are used to simulate environments and develop scenarios in response to policy problems. The article also investigates the shift from the technical to the socio-technical perspective within the field of smart cities. Despite the aspirations of urban scale digital twins to (...)
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  14. Open Data, Open Review and Open Dialogue in Making Social Sciences Plausible.Quan-Hoang Vuong - 2017 - Nature: Scientific Data Updates 2017.
    Nowadays, protecting trust in social sciences also means engaging in open community dialogue, which helps to safeguard robustness and improve efficiency of research methods. The combination of open data, open review and open dialogue may sound simple but implementation in the real world will not be straightforward. However, in view of Begley and Ellis’s (2012) statement that, “the scientific process demands the highest standards of quality, ethics and rigour,” they are worth implementing. More importantly, they are feasible to work (...)
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  15. Open Data, Open Review and Open Dialogue in Making Social Sciences Plausible.Quan-Hoang Vuong - 2017 - Scientific Data 4.
    A growing awareness of the lack of reproducibility has undermined society’s trust and esteem in social sciences. In some cases, well-known results have been fabricated or the underlying data have turned out to have weak technical foundations.
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  16. Open Science, Open Data, and Open Scholarship: European Policies to Make Science Fit for the Twenty-First Century.Rene Von Schomberg, Jean-Claude Burgelman, Corina Pascu, Kataezyna Szkuta, Athanasios Karalopoulos, Konstantinos Repanas & Michel Schouppe - 2019 - Frontiers in Big Data 2:43.
    Open science will make science more efficient, reliable, and responsive to societal challenges. The European Commission has sought to advance open science policy from its inception in a holistic and integrated way, covering all aspects of the research cycle from scientific discovery and review to sharing knowledge, publishing, and outreach. We present the steps taken with a forward-looking perspective on the challenges laying ahead, in particular the necessary change of the rewards and incentives system for researchers (for (...)
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  17. Wanting What We Don't Want to Want: Representing Addiction in Interoperable Bio-Ontologies.Janna Hastings, Nicolas Le Novère, Werner Ceusters, Kevin Mulligan & Barry Smith - 2012 - In Ronald Cornet & Robert Stevens (eds.), Proceeedings of the Third International Conference on Biomedical Ontology. CEUR. pp. 56-60.
    Ontologies are being developed throughout the biomedical sciences to address standardization, integration, classification and reasoning needs against the background of an increasingly data-driven research paradigm. In particular, ontologies facilitate the translation of basic research into benefits for the patient by making research results more discoverable and by facilitating knowledge transfer across disciplinary boundaries. Addressing and adequately treating mental illness is one of our most pressing public health challenges. Primary research across multiple disciplines such as psychology, psychiatry, biology, neuroscience (...)
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  18. From the Ground Up: Philosophy and Archaeology, 2017 Dewey Lecture.Alison Wylie - 2017 - Proceedings and Addresses of the American Philosophical Association 91:118-136.
    I’m often asked why, as a philosopher of science, I study archaeology. Philosophy is so abstract and intellectual, and archaeology is such an earth-bound, data-driven enterprise, what could the connection possibly be? This puzzlement takes a number of different forms. In one memorable exchange in the late 1970s when I was visiting Oxford as a graduate student an elderly don, having inquired politely about my research interests, tartly observed that archaeology isn’t a science, so I couldn’t (...)
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  19. On the Application of Formal Principles to Life Science Data: A Case Study in the Gene Ontology.Jacob Köhler, Anand Kumar & Barry Smith - 2004 - In Proceedings of DILS 2004 (Data Integration in the Life Sciences), (Lecture Notes in Bioinformatics 2994). Berlin: Springer. pp. 79-94.
    Formal principles governing best practices in classification and definition have for too long been neglected in the construction of biomedical ontologies, in ways which have important negative consequences for data integration and ontology alignment. We argue that the use of such principles in ontology construction can serve as a valuable tool in error-detection and also in supporting reliable manual curation. We argue also that such principles are a prerequisite for the successful application of advanced data integration techniques such (...)
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  20. Data models, representation and adequacy-for-purpose.Alisa Bokulich & Wendy Parker - 2021 - European Journal for Philosophy of Science 11 (1):1-26.
    We critically engage two traditional views of scientific data and outline a novel philosophical view that we call the pragmatic-representational view of data. On the PR view, data are representations that are the product of a process of inquiry, and they should be evaluated in terms of their adequacy or fitness for particular purposes. Some important implications of the PR view for data assessment, related to misrepresentation, context-sensitivity, and complementary use, are highlighted. The PR view provides (...)
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  21. Compressed Sensing - A New Mode of Measurement.Thomas Vogt - 2017 - In Nicola Mößner & Alfred Nordmann (eds.), Reasoning in Measurement: History and Philosophy of Technoscience Volume 9. New York, USA: Routledge.
    After introducing the concept of compressed sensing as a complementary measurement mode to the classical Shannon-Nyquist approach, I discuss some of the drivers, potential challenges and obstacles to its implementation. I end with a speculative attempt to embed compressed sensing as an enabling methodology within the emergence of data-driven discovery. As a consequence I predict the growth of non-nomological sciences where heuristic correlations will find applications but often bypass conventional pure basic and use-inspired basic research stages due to (...)
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  22. Data Science and Mass Media: Seeking a Hermeneutic Ethics of Information.Christine James - 2015 - Proceedings of the Society for Phenomenology and Media, Vol. 15, 2014, Pages 49-58 15 (2014):49-58.
    In recent years, the growing academic field called “Data Science” has made many promises. On closer inspection, relatively few of these promises have come to fruition. A critique of Data Science from the phenomenological tradition can take many forms. This paper addresses the promise of “participation” in Data Science, taking inspiration from Paul Majkut’s 2000 work in Glimpse, “Empathy’s Impostor: Interactivity and Intersubjectivity,” and some insights from Heidegger’s "The Question Concerning Technology." The description of (...)
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  23. Driven to Extinction? The Ethics of Eradicating Mosquitoes with Gene-Drive Technologies.Jonathan Pugh - 2016 - Journal of Medical Ethics 42 (9):578-581.
    Mosquito-borne diseases represent a significant global disease burden, and recent outbreaks of such diseases have led to calls to reduce mosquito populations. Furthermore, advances in ‘gene-drive’ technology have raised the prospect of eradicating certain species of mosquito via genetic modification. This technology has attracted a great deal of media attention, and the idea of using gene-drive technology to eradicate mosquitoes has been met with criticism in the public domain. In this paper, I shall dispel two moral objections that have been (...)
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  24. Form-Driven Vs. Content-Driven Arguments for Realism.Juha Saatsi - 2010 - In P. D. Magnus & Jacob Busch (eds.), New Waves in Philosophy of Science. Palgrave-Macmillan.
    I offer a meta-level analysis of realist arguments for the reliability of ampliative reasoning about the unobservable. We can distinguish form-driven and content-driven arguments for realism: form-driven arguments appeal to the form of inductive inferences, whilst content-driven arguments appeal to their specific content. After regimenting the realism debate in these terms, I will argue that the content-driven arguments are preferable. Along the way I will discuss how my analysis relates to John Norton’s recent, more general (...)
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  25. What is Data Ethics?Luciano Floridi & Mariarosaria Taddeo - 2016 - Philosophical Transactions of the Royal Society A 374 (2083).
    This theme issue has the founding ambition of landscaping Data Ethics as a new branch of ethics that studies and evaluates moral problems related to data (including generation, recording, curation, processing, dissemination, sharing, and use), algorithms (including AI, artificial agents, machine learning, and robots), and corresponding practices (including responsible innovation, programming, hacking, and professional codes), in order to formulate and support morally good solutions (e.g. right conducts or right values). Data Ethics builds on the foundation provided by (...)
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  26. Building Ontologies with Basic Formal Ontology.Robert Arp, Barry Smith & Andrew D. Spear - 2015 - Cambridge, MA: MIT Press.
    In the era of “big data,” science is increasingly information driven, and the potential for computers to store, manage, and integrate massive amounts of data has given rise to such new disciplinary fields as biomedical informatics. Applied ontology offers a strategy for the organization of scientific information in computer-tractable form, drawing on concepts not only from computer and information science but also from linguistics, logic, and philosophy. This book provides an introduction to the field of (...)
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  27. Privacy Versus Public Health? A Reassessment of Centralised and Decentralised Digital Contact Tracing.Lucie White & Philippe van Basshuysen - 2021 - Science and Engineering Ethics 27 (2):1-13.
    At the beginning of the COVID-19 pandemic, high hopes were placed on digital contact tracing. Digital contact tracing apps can now be downloaded in many countries, but as further waves of COVID-19 tear through much of the northern hemisphere, these apps are playing a less important role in interrupting chains of infection than anticipated. We argue that one of the reasons for this is that most countries have opted for decentralised apps, which cannot provide a means of rapidly informing users (...)
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  28. Practical and Philosophical Considerations for Defining Information as Well-Formed, Meaningful Data in the Information Sciences.Jesse David Dinneen & Christian Brauner - 2015 - Library Trends 63 (3):378-400.
    This paper demonstrates the practical and philosophical strengths of adopting Luciano Floridi’s “general definition of information” (GDI) for use in the information sciences (IS). Many definitions of information have been proposed, but little work has been done to determine which definitions are most coherent or useful. Consequently, doubts have been cast on the necessity and possibility of finding a definition. In response to these doubts, the paper shows how items and events central to IS are adequately described by Floridi’s conception (...)
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  29.  95
    Science Transformed?: Debating Claims of an Epochal Break.Alfred Nordmann, Hans Radder & Gregor Schiemann (eds.) - 2011 - University of Pittsburgh Press.
    Advancements in computing, instrumentation, robotics, digital imaging, and simulation modeling have changed science into a technology-driven institution. Government, industry, and society increasingly exert their influence over science, raising questions of values and objectivity. These and other profound changes have led many to speculate that we are in the midst of an epochal break in scientific history. -/- This edited volume presents an in-depth examination of these issues from philosophical, historical, social, and cultural perspectives. It offers arguments both (...)
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  30. Is an Archaeological Contribution to the Theory of Social Science Possible? Archaeological Data and Concepts in the Dispute Between Jean-Claude Gardin and Jean-Claude Passeron.Sébastien Plutniak - 2017 - Palethnologie 9:7-21.
    The issue of the definition and position of archaeology as a discipline is examined in relation to the dispute which took place from 1980 to 2009 between the archaeologist Jean-Claude Gardin and the sociologist Jean-Claude Passeron. This case study enables us to explore the actual conceptual relationships between archaeology and the other sciences (as opposed to those wished for or prescribed). The contrasts between the positions declared by the two researchers and the rooting of their arguments in their disciplines are (...)
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  31. Using Models to Correct Data: Paleodiversity and the Fossil Record.Alisa Bokulich - 2018 - Synthese 198 (Suppl 24):5919-5940.
    Despite an enormous philosophical literature on models in science, surprisingly little has been written about data models and how they are constructed. In this paper, I examine the case of how paleodiversity data models are constructed from the fossil data. In particular, I show how paleontologists are using various model-based techniques to correct the data. Drawing on this research, I argue for the following related theses: first, the ‘purity’ of a data model is not (...)
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  32. Theory-Laden Experimentation.Samuel Schindler - 2013 - Studies in History and Philosophy of Science Part A 44 (1):89-101.
    The thesis of theory-ladenness of observations, in its various guises, is widely considered as either ill-conceived or harmless to the rationality of science. The latter view rests partly on the work of the proponents of New Experimentalism who have argued, among other things, that experimental practices are efficient in guarding against any epistemological threat posed by theory-ladenness. In this paper I show that one can generate a thesis of theory-ladenness for experimental practices from an influential New Experimentalist account. The (...)
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  33. Towards a Taxonomy of the Model-Ladenness of Data.Alisa Bokulich - forthcoming - PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association.
    Model-data symbiosis is the view that there is an interdependent and mutually beneficial relationship between data and models, whereby models are not only data-laden, but data are also model-laden or model filtered. In this paper I elaborate and defend the second, more controversial, component of the symbiosis view. In particular, I construct a preliminary taxonomy of the different ways in which theoretical and simulation models are used in the production of data sets. These include (...) conversion, data correction, data interpolation, data scaling, data fusion, data assimilation, and synthetic data. Each is defined and briefly illustrated with an example from the geosciences. I argue that model-filtered data are typically more accurate and reliable than the so-called raw data, and hence beneficially serve the epistemic aims of science. By illuminating the methods by which raw data are turned into scientifically useful data sets, this taxonomy provides a foundation for developing a more adequate philosophy of data. (shrink)
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  34. Science’s Immunity to Moral Refutation.Alex Barber - 2013 - Australasian Journal of Philosophy 91 (4):633-653.
    Our moral convictions cannot, on the face of it, count in evidence against scientific claims with which they happen to conflict. Moral anti-realists of whatever stripe can explain this easily: science is immune to moral refutation because moral discourse is defective as a trustworthy source of true and objective judgments. Moral realists, they can add, are unable to explain this immunity. After describing how anti-realists might implement this reasoning, the paper argues that the only plausible realist comeback turns on (...)
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  35.  15
    Data.Luciano Floridi - 2008 - In William A. Darity (ed.), International Encyclopedia of the Social Sciences.
    The word data (sing. datum) is originally Latin for “things given or granted”. Because of such a humble and generic meaning, the term enjoys considerable latitude both in its technical and in its common usage, for almost anything can be referred to as a “thing given or granted” (Cherry [1978]). With some reasonable approximation, four principal interpretations may be identified in the literature. The first three captures part of the nature of the concept and are discussed in the next (...)
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  36.  42
    Enabling Posthumous Medical Data Donation: An Appeal for the Ethical Utilisation of Personal Health Data.Jenny Krutzinna, Mariarosaria Taddeo & Luciano Floridi - 2019 - Science and Engineering Ethics 25 (5):1357-1387.
    This article argues that personal medical data should be made available for scientific research, by enabling and encouraging individuals to donate their medical records once deceased, similar to the way in which they can already donate organs or bodies. This research is part of a project on posthumous medical data donation developed by the Digital Ethics Lab at the Oxford Internet Institute at the University of Oxford. Ten arguments are provided to support the need to foster posthumous medical (...)
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  37. How Non-Epistemic Values Can Be Epistemically Beneficial in Scientific Classification.Soohyun Ahn - 2020 - Studies in History and Philosophy of Science Part A 84:57-65.
    The boundaries of social categories are frequently altered to serve normative projects, such as social reform. Griffiths and Khalidi argue that the value-driven modification of categories diminishes the epistemic value of social categories. I argue that concerns over value-modified categories stem from problematic assumptions of the value-free ideal of science. Contrary to those concerns, non-epistemic value considerations can contribute to the epistemic improvement of a scientific category. For example, the early history of the category infantile autism shows how (...)
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  38. The Science of Belief: A Progress Report.Nicolas Porot & Eric Mandelbaum - forthcoming - WIREs Cognitive Science 1.
    The empirical study of belief is emerging at a rapid clip, uniting work from all corners of cognitive science. Reliance on belief in understanding and predicting behavior is widespread. Examples can be found, inter alia, in the placebo, attribution theory, theory of mind, and comparative psychological literatures. Research on belief also provides evidence for robust generalizations, including about how we fix, store, and change our beliefs. Evidence supports the existence of a Spinozan system of belief fixation: one that is (...)
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  39.  84
    Towards a Contextual Approach to Data Quality.Stefano Canali - 2020 - Data 4 (5):90.
    In this commentary, I propose a framework for thinking about data quality in the context of scientific research. I start by analyzing conceptualizations of quality as a property of information, evidence and data and reviewing research in the philosophy of information, the philosophy of science and the philosophy of biomedicine. I identify a push for purpose dependency as one of the main results of this review. On this basis, I present a contextual approach to data quality (...)
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  40. The History of Science as a Graveyard of Theories: A Philosophers’ Myth?Moti Mizrahi - 2016 - International Studies in the Philosophy of Science 30 (3):263-278.
    According to the antirealist argument known as the pessimistic induction, the history of science is a graveyard of dead scientific theories and abandoned theoretical posits. Support for this pessimistic picture of the history of science usually comes from a few case histories, such as the demise of the phlogiston theory and the abandonment of caloric as the substance of heat. In this article, I wish to take a new approach to examining the ‘history of science as a (...)
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  41. Ontology-Based Fusion of Sensor Data and Natural Language.Erik Thomsen & Barry Smith - 2018 - Applied Ontology 13 (4):295-333.
    We describe a prototype ontology-driven information system (ODIS) that exploits what we call Portion of Reality (POR) representations. The system takes both sensor data and natural language text as inputs and composes on this basis logically structured POR assertions. The goal of our prototype is to represent both natural language and sensor data within a single framework that is able to support both axiomatic reasoning and computation. In addition, the framework should be capable of discovering and representing (...)
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  42.  59
    Crowdsourced Science: Sociotechnical Epistemology in the E-Research Paradigm.David Watson & Luciano Floridi - 2018 - Synthese 195 (2):741-764.
    Recent years have seen a surge in online collaboration between experts and amateurs on scientific research. In this article, we analyse the epistemological implications of these crowdsourced projects, with a focus on Zooniverse, the world’s largest citizen science web portal. We use quantitative methods to evaluate the platform’s success in producing large volumes of observation statements and high impact scientific discoveries relative to more conventional means of data processing. Through empirical evidence, Bayesian reasoning, and conceptual analysis, we show (...)
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  43. The Tool Box of Science: Tools for the Building of Models with a Superconductivity Example.Nancy Cartwright, Towfic Shomar & Mauricio Suárez - 1995 - Poznan Studies in the Philosophy of the Sciences and the Humanities 44:137-149.
    We call for a new philosophical conception of models in physics. Some standard conceptions take models to be useful approximations to theorems, that are the chief means to test theories. Hence the heuristics of model building is dictated by the requirements and practice of theory-testing. In this paper we argue that a theory-driven view of models can not account for common procedures used by scientists to model phenomena. We illustrate this thesis with a case study: the construction of one (...)
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  44. The Case Study Method in Philosophy of Science: An Empirical Study.Moti Mizrahi - 2020 - Perspectives on Science 28 (1):63-88.
    There is an ongoing methodological debate in philosophy of science concerning the use of case studies as evidence for and/or against theories about science. In this paper, I aim to make a contribution to this debate by taking an empirical approach. I present the results of a systematic survey of the PhilSci-Archive, which suggest that a sizeable proportion of papers in philosophy of science contain appeals to case studies, as indicated by the occurrence of the indicator words (...)
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  45.  37
    Ontology (Science).Barry Smith - 2008 - In Carola Eschenbach & Mike Grüninger (eds.), Formal Ontology in Information Systems. Proceedings of the Fifth International Conference (FOIS 2008). Amsterdam: IOS Press. pp. 21-35.
    Increasingly, in data-intensive areas of the life sciences, experimental results are being described in algorithmically useful ways with the help of ontologies. Such ontologies are authored and maintained by scientists to support the retrieval, integration and analysis of their data. The proposition to be defended here is that ontologies of this type – the Gene Ontology (GO) being the most conspicuous example – are a part of science. Initial evidence for the truth of this proposition (which some (...)
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  46.  33
    Science Meets Philosophy: Metaphysical Gap & Bilateral Brain.Hermann G. W. Burchard - 2020 - Philosophy Study 10 (10):599-614.
    The essay brings a summation of human efforts seeking to understand our existence. Plato and Kant & cognitive science complete reduction of philosophy to a neural mechanism, evolved along elementary Darwinian principles. Plato in his famous Cave Allegory explains that between reality and our experience of it there exists a great chasm, a metaphysical gap, fully confirmed through particle-wave duality of quantum physics. Kant found that we have two kinds of perception, two senses: By the spatial outer sense we (...)
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  47.  48
    Information Quality, Data and Philosophy.Luciano Floridi & Phyllis Illari - 2014 - In Phyllis Illari & Luciano Floridi (eds.), The Philosophy of Information Quality. Switzerland: Springer International Publishing. pp. 5–23.
    In this opening chapter, we review the literature on information quality. Our major aim is to introduce the issues, and trace some of the history of the debates, with a view to situating the chapters in this volume – whose authors come from different disciplines – to help make them accessible to readers with different backgrounds and expertise. We begin in this section by tracing some influential analyses of IQ in computer science. This is a useful basis for examining (...)
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  48. Computer Simulation and the Features of Novel Empirical Data.Greg Lusk - 2016 - Studies in History and Philosophy of Science Part A 56:145-152.
    In an attempt to determine the epistemic status of computer simulation results, philosophers of science have recently explored the similarities and differences between computer simulations and experiments. One question that arises is whether and, if so, when, simulation results constitute novel empirical data. It is often supposed that computer simulation results could never be empirical or novel because simulations never interact with their targets, and cannot go beyond their programming. This paper argues against this position by examining whether, (...)
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  49. Big Data and Changing Concepts of the Human.Carrie Figdor - 2019 - European Review 27 (3):328-340.
    Big Data has the potential to enable unprecedentedly rigorous quantitative modeling of complex human social relationships and social structures. When such models are extended to nonhuman domains, they can undermine anthropocentric assumptions about the extent to which these relationships and structures are specifically human. Discoveries of relevant commonalities with nonhumans may not make us less human, but they promise to challenge fundamental views of what it is to be human.
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  50. Comparative Views on Research Productivity Differences Between Major Social Science Fields in Vietnam: Structured Data and Bayesian Analysis, 2008-2018.Quan-Hoang Vuong, La Viet Phuong, Vuong Thu Trang, Ho Manh Tung, Nguyen Minh Hoang & Manh-Toan Ho - manuscript
    Since Circular 34 from the Ministry of Science and Technology of Vietnam required the head of the national project to have project results published in ISI/Scopus journals in 2014, the field of economics has been dominating the number of nationally-funded projects in social sciences and humanities. However, there has been no scientometric study that focuses on the difference in productivity among fields in Vietnam. Thus, harnessing the power of the SSHPA database, a comprehensive dataset of 1,564 Vietnamese authors (854 (...)
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