Scientific data supporting rational arguments for human-made causes of climate and environmental changes might be persuasive in some contexts. Law, policy, activism and The Earth Charter similarly appear insufficient to change attitudes and behaviours. Even biblical and theological arguments fail to move some Christians beyond apathy and climate denial. Decades of ecological theology and calls for ecological conversion suggest that appeals to reason and facts are limited without an affective epistemology that join knowledge and experience to produce worldview (...) transformation through emotions, such as awe.Contribution: Departing from appeal to scientific data and arguments alone, the primary claim is that ecological conversion is not singularly a rational act. For broader engagement and action to mitigate climate and environmental degradation, experiential and affective encounter with nature promise wider participation and transformation. (shrink)

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 straightforward representations of given phenomena. Rather, they are fungible objects defined by their portability and prospective usefulness as evidence. (shrink)

In recent months months the hashtag #overlyhonestmethods has steadily been gaining popularity. Posts under this hashtag—presumably by scientists—detail aspects of daily scientific research that differ considerably from the idealized interpretation of scientific experimentation as standardized, objective and reproducible. Over and above its entertainment value, the popularity of this hashtag raises two important points for those who study both science and scientists. Firstly, the posts highlight that the generation of data through experimentation is often far less standardized than (...) is commonly assumed. Secondly, the popularity of the hashtag together with its relatively blasé reception by the scientific community reveal that the actions reported in the tweets are far from shocking and indeed may be considered just “part of scientific research”. Such observations give considerable pause for thought, and suggest that current conceptions of data might be limited by failing to recognize this “inherent variability” within the actions of generation—and thus within data themselves. Is it possible, we must ask, that epistemic virtues such as standardization, consistency, reportability and reproducibility need to be reevaluated? Such considerations are, of course, of particular importance to data sharing discussions and the Open Data movement. This paper suggests that the notion of a “moral professionalism” for data generation and sharing needs to be considered in more detail if the inherent variability of data are to be addressed in any meaningful manner. (shrink)

Because of the many criticisms of the notion of a theory independent observation language, it is useful to look at a few actual examples of scientific data to see what theories might be implicit and in what way. There are several possibilities. The theories could be previously accepted, under active investigation, or of a kind that has never been systematically examined. The present study explores these possibilities in the data of several scientific journal articles. The conclusion (...) is that theories and regularities of all three kinds can be found as antecedent conditions of data statements. Any descriptive account of scientific inference must find room for such presuppositions. (shrink)

In a series of experiments done in wartime Nazi Germany, inmates of the Dachau concentration camp were exposed to cold by being immersed in ice water, or kept outside in freezing temperatures; their responses were measured, and various techniques were used in an attempt to revive them. The immediate application of these hypothermia studies was to the war effort, to try to protect or save soldiers exposed to cold water or air. An account of the procedures and results of these (...) experiments was written by an American officer, Major Leo Alexander, on the basis of his post-war discovery of documents and interviews in Germany. These reports reveal the ghastly and abominable details of the experiments.Recent scientific work in British Columbia has caused some ethical debate when it consulted the Alexander report and used some of the Nazi experimental data. The scientists in the Hypothermia Unit of the University of Victoria, unsurprisingly but reassuringly, have no intention of repeating the Nazi atrocities, and condemn them. The current controversy concerns the morality of their using the Alexander data in their study. This out-of-the-way case has some small intrinsic interest; but its consideration leads to broader concerns. (shrink)

Powerful interest groups have responded to evidence of environmental or health risks by manufacturing doubt, partially through attacks on scientists. The current legal standard for the admissibility of scientific evidence in court enables such strategies for generating doubt. In the face of attacks on their reputations and careers, researchers working on public interest science need the courage to speak the truth despite risk, which Michel Foucault described as the virtue of parrhesia. Parrhesia is also a Christian virtue shown in (...) the willingness to witness to truth in the face of risk because of one's confidence in God. This essay argues that Christianity possesses resources to form individuals in parrhesia in ways that support the dedication to scientific truth. (shrink)

Recent proposals for a return to introspective methods make it necessary to review the central problems that led psychologists to abandon those methods as sources of scientific data in the early twentieth century. These problems and other related challenges to verbal reports collected during the cognitive revolution during the 1960s and 1970s were discussed in Ericsson and Simon's proposal for a theoretically motivated procedure to elicit valid and non- reactive concurrent verbalization of thoughts while subjects were performing tasks. (...) The same proposal explains why other verbal reports, such as introspections, detailed descriptions or explanations, require additional cognitive activity that often leads to reactivity and invalid reports. Finally, a new proposal is sketched for how the generation of introspective reports might be incorporated within a framework for non-reactive and valid verbalization of thoughts. (shrink)

Many studies in big data focus on the uses of data available to researchers, leaving without treatment data that is on the servers but of which researchers are unaware. We call this dark data, and in this article, we present and discuss it in the context of high-performance computing facilities. To this end, we provide statistics of a major HPC facility in Europe, the High-Performance Computing Center Stuttgart. We also propose a new position tailor-made for coping (...) with dark data and general data management. We call it the scientific data officer and we distinguish it from other standard positions in HPC facilities such as chief data officers, system administrators, and security officers. In order to understand the role of the SDO in HPC facilities, we discuss two kinds of responsibilities, namely, technical responsibilities and ethical responsibilities. While the former are intended to characterize the position, the latter raise concerns—and proposes solutions—to the control and authority that the SDO would acquire. (shrink)

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 mediating global market exchange, thus achieving a prominent social and economic status well beyond science itself. At the same time, calls to make all such data publicly and freely available have garnered strength and visibility, most prominently in the form of the Open Data movement. I discuss these developments by considering the conditions under which data journey across the communities and institutions implicated in globalized biology and biomedicine, and what this indicates about how Internet-based communication and the use of online databases affect scientific research and its role within contemporary society. (shrink)

ArgumentMost social scientists today think of data sharing as an ethical imperative essential to making social science more transparent, verifiable, and replicable. But what moved the architects of some of the U.S.’s first university-based social scientific research institutions, the University of Michigan’s Institute for Social Research, and its spin-off, the Inter-university Consortium for Political and Social Research, to share their data? Relying primarily on archived records, unpublished personal papers, and oral histories, I show that Angus Campbell, Warren (...) Miller, Philip Converse, and others understood sharing data not as an ethical imperative intrinsic to social science but as a useful means to the diverse ends of financial stability, scholarly and institutional autonomy, and epistemological reproduction. I conclude that data sharing must be evaluated not only on the basis of the scientific ideals its supporters affirm, but also on the professional objectives it serves. (shrink)

Big data biology—bioinformatics, computational biology, systems biology (including ‘omics’), and synthetic biology—raises a number of issues for the philosophy of science. This article deals with several such: Is data-intensive biology a new kind of science, presumably post-reductionistic? To what extent is big data biology data-driven? Can data ‘speak for themselves?’ I discuss these issues by way of a reflection on Carl Woese’s worry that “a society that permits biology to become an engineering discipline, that allows (...) that science to slip into the role of changing the living world without trying to understand it, is a danger to itself.” And I argue that scientific perspectivism, a philosophical stance represented prominently by Giere, Van Fraassen, and Wimsatt, according to which science cannot as a matter of principle transcend our human perspective, provides the best resources currently at our disposal to tackle many of the philosophical issues implied in the modeling of complex, multilevel/multiscale phenomena. (shrink)

This article responds to two problems confronting social and human sciences: how to relate to digital data, inasmuch as it challenges established social science methods; and how to relate to life sciences, insofar as they produce knowledge that impinges on our own ways of knowing. In a case study of proteomics, we explore how digital devices grapple with large-scale multiples – of molecules, databases, machines and people. We analyse one particular visual device, a cluster-heatmap, produced by scientists by mining (...) data from a large number of experiments on human blood plasma proteins. These proteins make up a myriad multiple whose identity shifts in many ways. Rather than displaying data about proteins, the heatmap constructs a view of the differences and similarities between experiments. We find this attempt to construct a view on many things at once instructive in thinking about multiples more generally. Instead of flattening molecular ‘life itself’, this visual device superimposes layers of digital devices and techniques from a wide variety of disciplines. This layering suggests a different way of relating to the life sciences more generally: rather than what they know, how they know might be of use to social and human sciences when attending to multiplicities. (shrink)

What is the epistemological status of Big Data? Is there really place for them in a scientific search for new empirical laws?

Scientific reasoning represents complex argumentation patterns that eventually lead to scientific discoveries. Social epistemology of science provides a perspective on the scientific community as a whole and on its collective knowledge acquisition. Different techniques have been employed with the goal of maximization of scientific knowledge on the group level. These techniques include formal models and computer simulations of scientific reasoning and interaction. Still, these models have tested mainly abstract hypothetical scenarios. The present thesis instead presents (...) data-driven approaches in social epistemology of science. A data-driven approach requires data collection and curation for its further usage, which can include creating empirically calibrated models and simulations of scientific inquiry, performing statistical analyses, or employing data- mining techniques and other procedures. -/- We present and analyze in detail three co-authored research projects on which the thesis’ author was engaged during her PhD. The first project sought to identify optimal team composition in high energy physics laboratories using data-mining techniques. The results of this project are published in (Perović et al. 2016), and indicate that projects with smaller numbers of teams and team members outperform bigger ones. In the second project, we attempted to determine whether there is an epistemic saturation point in experimentation in high energy physics. The initial results from this project are published in (Sikimić et al. 2018). In the thesis, we expand on this topic by using computer simulations to test for biases that could induce scientists to invest in projects beyond their epistemic saturation point. Finally, in previous examples of data-driven analyses, citations are used as a measure of epistemic efficiency of projects in high energy physics. In order to additionally justify and analyze the usage of this parameter in their data-driven research, in the third project Perović & Sikimić (2019) analyzed and compared inductive patterns in experimental physics and biology with the reliability of citation records in these fields. They conclude that while citations are a relatively reliable measure of efficiency in high energy physics research, the same does not hold for the majority of research in experimental biology. -/- Additionally, contributions of the author that are for the first time published in this theses are: (a) an empirically calibrated model of scientific interaction of research groups in biology, (b) a case study of irregular argumentation patterns in some pathogen discoveries, and (c) an introductory discussion of the benefits and limitations of data- driven approaches to the social epistemology of science. Using computer simulations of an empirically calibrated model, we demonstrate that having several levels of hierarchy and division into smaller research sub-teams is epistemically beneficial for researchers in experimental biology. We also show that argumentation analysis in biology represents a good starting point for further data-driven analyses in the field. Finally, we conclude that a data-driven approach is informative and useful for science policy, but requires careful considerations about data collection, curation, and interpretation. (shrink)

The paper discusses the problems in the detection of security information in legal and other administrative data. The authors analyse the prospects of the use of datamining in the solution of two key problems: abundance and indirectness of these data. Security research uses two kinds of data. The first one is scientific data, designed and gathered specially for the verification of certain security theories. They are the data of criminological, sociological, psychological surveys, experimental (...) class='Hi'>data, etc. The second kind is data that are not designed for security research. Most of the data are the by-products of the national legal system, especially its criminal justice, of national and local institutions responsible for the maintenance of public order, and of other public agencies. All the data provide huge amounts of information destined to control and direct the activities of these institutions. There are two kinds of problems in the use of this information in security study. First, this information has to be ‘decoded’ from data describing the activities of related institutions. Second, data on security are lost in huge amounts of other public data. Thus, they have to be ‘mined’. The paper discusses the prospects of the modern information proceeding method—data-mining in the solution of both problems. A new concept of data mining as a meta-procedure is proposed. The object of this meta-procedure is supposed to be the integration of multiple current theories (for example, criminal security) and related statistical procedures. A general algorithm of such data-mining is proposed. (shrink)

Ethicists differ considerably in their reasons for using empirical data. This paper presents a brief overview of four traditional approaches to the use of empirical data: “the prescriptive applied ethicists,” “the theorists,” “the critical applied ethicists,” and “the particularists.” The main aim of this paper is to introduce a fifth approach of more recent date (i.e. “integrated empirical ethics”) and to offer some methodological directives for research in integrated empirical ethics. All five approaches are presented in a table (...) for heuristic purposes. The table consists of eight columns: “view on distinction descriptive-prescriptive sciences,” “location of moral authority,” “central goal(s),” “types of normativity,” “use of empirical data,” “method,” “interaction empirical data and moral theory,” and “cooperation with descriptive sciences.” Ethicists can use the table in order to identify their own approach. Reflection on these issues prior to starting research in empirical ethics should lead to harmonization of the different scientific disciplines and effective planning of the final research design. Integrated empirical ethics (IEE) refers to studies in which ethicists and descriptive scientists cooperate together continuously and intensively. Both disciplines try to integrate moral theory and empirical data in order to reach a normative conclusion with respect to a specific social practice. IEE is not wholly prescriptive or wholly descriptive since IEE assumes an interdepence between facts and values and between the empirical and the normative. The paper ends with three suggestions for consideration on some of the future challenges of integrated empirical ethics. (shrink)

The cogency of a scientific study utilizing historical data tends to be, unfortunately, very largely a matter of the methodological presuppositions of the reader. Indeed, the barriers to a more general and thorough scientific use of history are, for the most part, methodological. There are two such barriers: the uncertainty as to the validity of an intensive scientific investigation of historical problems, and the lack of a clear delineation of the fields of research.Concerning the first, two (...) problems must be considered: on the one hand, the nature of historical knowledge and on the other, the nature of scientific knowledge. The predictive assumption of the present discussion is that to understand the essential identity of historical and scientific knowledge is to justify the scientific manipulation of data which are unquestionably historical. The thesis which is being argued here is that all data are historical, that all reality—whatever its level or type—is event-structured, that events have an existential dependence on one another, that therefore relationships of relevance and causation may be established, and that the determination of such relationships is the function of scientific research in any field. (shrink)

Scientific disagreements sometimes persist even if scientists fully share results of their research. In this paper we develop an agent-based model to study the impact of diverging diagnostic values scientists may assign to the evidence, given their different background assumptions, on the emergence of polarization in the scientific community. Scientists are represented as Bayesian updaters for whom the diagnosticity of evidence is given by the Bayes factor. Our results suggest that an initial disagreement on the diagnostic value of (...) evidence can, but does not necessarily, lead to polarization, depending on the sample size of the performed studies and the confidence interval within which scientists share their opinions. In particular, the more data scientists share,the more likely it is that the community will end up polarized. (shrink)

A scientific community can be modeled as a collection of epistemic agents attempting to answer questions, in part by communicating about their hypotheses and results. We can treat the pathways of scientific communication as a network. When we do, it becomes clear that the interaction between the structure of the network and the nature of the question under investigation affects epistemic desiderata, including accuracy and speed to community consensus. Here we build on previous work, both our own and (...) others’, in order to get a firmer grasp on precisely which features of scientific communities interact with which features of scientific questions in order to influence epistemic outcomes. (shrink)

Using the Schwarzschild calculation of the Relativistic bending of starlight near the sun as an illustration, it is shown that the relationship between theory and data requires a hierarchy of structures of different logical type. An essential feature of this hierarchy is the use of idealizations and approximate truths. On the basis of a counterfactual analysis of these concepts, it is shown that confirmation is possible even though statistical measures of goodness of fit are not satisfied. The consequences of (...) this view of confirmation and hierarchical structure for scientific realism are then considered. (shrink)

There is an increasing push by journals to ensure that data and products related to published papers are shared as part of a cultural move to promote transparency, reproducibility, and trust in the scientific literature. Yet few journals commit to evaluating their effectiveness in implementing reporting standards aimed at meeting those goals (1, 2). Similarly, though the vast majority of journals endorse peer review as an approach to ensure trust in the literature, few make their peer review (...) class='Hi'>data available to evaluate effectiveness toward achieving concrete measures of quality, including consistency and completeness in meeting reporting standards. Remedying these apparent disconnects is critical for closing the gap between guidance recommendations and actual reporting behavior. We see this as a collective action problem requiring leadership and investment by publishers, who can be incentivized through mechanisms that allow them to manage reputational risk and through continued innovation in journal assessment. (shrink)

The application of the latest technologies in biology and medicine has brought them to a qualitatively new level of possibilities. Worldwide, biobanking is actively developing through the creation of biobanks of various types and purposes, whose resources are used to solve therapeutic or scientific problems. Legal science remains an open question concerning the boundary that runs between the right to data protection and the scope of disclosure of data needed for medical purposes. In this article, the author (...) considers peculiarities of data processing in the context of biobanking activity on the example of Austria and its national legislation. In addition, the article reveals features of the approaches of the European Court of Human Rights (ECtHR) and the Council of Europe to the issue of biobanking in general, its characteristics in the context of data, and legal regulation of this phenomenon in the national law of states. The author devoted an important part of the study to the role of Austria’s experience in the context of data processing for scientific purposes and the development of biobanking for a number of other European states. The aim of the article is to analyze the Austrian legislation on data processing for scientific research and biobanking, the attitude of the Council of Europe to this phenomenon, and the practice of the ECtHR, as well as to consider the impact of the current world situation on these activities. The leading method of research used in the article is the formal-legal method. The article analyzes the Austrian law in the context of data processing in medical research, the relationship of the specifics of personal data protection, and the need to disclose them for scientific purposes. The author pays special attention to the influence of Austrian law on the legislation of other countries, which is reflected in the conclusions to the article. In addition, based on an analysis of the application of the Austrian experience to the legislation of Poland and Ukraine, the author points out the necessary changes that should be made in the laws of these countries. (shrink)

The aim of the article is to explain the relationship between the ethical evaluation of scientific research involving personal data and the assessment of compliance with data protection law. The article presents the mutual relationship between the protection of personal data and scientific activity from a dogmatic perspective, the legal regulation of the processing of personal data in scientific research, and the so-called research exceptions that apply when data are processed for (...) class='Hi'>scientific research. It also covers the importance of meeting the ethical requirements of scientific research in order to profit from the indicated exceptions. Finally, it provides a comparison between the ethical and the legal systems of personal data protection in research (objectives, criteria, authorities, and procedures). (shrink)

In this article, interviewing from a descriptive, phenomenological, human scientific perspective is examined. Methodological issues are raised in relation to evaluative criteria as well as reflective matters that concern the phenomenological researcher. The data collection issues covered are 1) the selection of participants, 2) the number of participants in a study, 3) the interviewer and the questions, and 4) data collection procedures. Certain conclusions were drawn indicating that phenomenological research methods cannot be evaluated on the basis of (...) an empiricist theory of science, but must be critiqued from within a phenomenological theory of science. Some reflective matters, experienced by the phenomenological researcher, are also elaborated upon. (shrink)

Isaac Newton's Scientific Method examines Newton's argument for universal gravity and his application of it to resolve the problem of deciding between geocentric and heliocentric world systems by measuring masses of the sun and planets. William L. Harper suggests that Newton's inferences from phenomena realize an ideal of empirical success that is richer than prediction. Any theory that can achieve this rich sort of empirical success must not only be able to predict the phenomena it purports to explain, but (...) also have those phenomena accurately measure the parameters which explain them. Harper explores the ways in which Newton's method aims to turn theoretical questions into ones which can be answered empirically by measurement from phenomena, and to establish that propositions inferred from phenomena are provisionally accepted as guides to further research. This methodology, guided by its rich ideal of empirical success, supports a conception of scientific progress that does not require construing it as progress toward Laplace's ideal limit of a final theory of everything, and is not threatened by the classic argument against convergent realism. Newton's method endorses the radical theoretical transformation from his theory to Einstein's. Harper argues that it is strikingly realized in the development and application of testing frameworks for relativistic theories of gravity, and very much at work in cosmology today. (shrink)

The author critiques one of the arguments commonly used by opponents of scientific realism—namely, the thesis that scientific theories are underdetermined by empirical data.

The curse of dimensionality is one of the most prominent challenge that data scientists face when trying to make valuable inferences. It is an epistemic problem that hits particularly hard in "Big Data" research contexts, where the volume of the data set is particularly large. The way in which we tackle with this problem sheds light on the notion of scientific evidence. Yet, it is virtually absent from the current philosophical literature. In this paper, I aim (...) to broaden the focus of that literature by showing that the dimensions in which the data are embedded are an integral part of scientific evidence. This is an aspect of scientific evidence that is often hidden behind the traditional observation/theory dichotomy that we often encounter in philosophy of science. Dimensions are abstract objects. They are not observables like tables and chairs, nor are they entries in a data set. Ultimately, I aim to show that empirical adequacy is not merely a matter of finding the model that best fit the relevant observational data. It is also a matter of finding the model that best fit the relevant observational data inside the relevant dimensions. (shrink)

Background Sharing anonymized/de-identified clinical trial data and publishing research outcomes in scientific journals, or presenting them at conferences, is key to data-driven scientific exchange. However, when data from scientific publications are linked to other publicly available personal information, the risk of reidentification of trial participants increases, raising privacy concerns. Therefore, we defined a set of criteria allowing us to determine and minimize the risk of data reidentification. We also implemented a review process at (...) Takeda for clinical publications prior to submission for publication in journals or presentation at medical conferences. Methods Abstracts, manuscripts, posters, and oral presentations containing study participant information were reviewed and the potential impact on study participant privacy was assessed. Our focus was on direct and indirect identifiers, such as sex, age or geographical indicators in rare disease studies or studies with small sample size treatment groups. Risk minimization was sought using a generalized presentation of identifier-relevant information and decision-making on data sharing for further research. Additional risk identification was performed based on study participant/personnel parameters present in materials destined for the public domain. The potential for participant/personnel identification was then calculated to facilitate presentation of meaningful but de-identified information. Results The potential for reidentification was calculated using a risk ratio of the exposed versus available individuals, with a value above the threshold of 0.09 deemed an unacceptable level of reidentification risk. We found that in 13% of Takeda clinical trial publications reviewed, either individuals could potentially be reidentified or inappropriate data sharing plans could pose a data privacy risk to study participants. In 1/110 abstracts, 58/275 manuscripts, 5/87 posters and 3/58 presentations, changes were necessary due to data privacy concerns/rules. Despite the implementation of risk-minimization measures prior to release, direct and indirect identifiers were found in 11% and 34% of the analysed documents, respectively. Conclusions Risk minimization using de-identification of clinical trial data presented in scientific publications and controlled data sharing conditions improved privacy protection for study participants. Our results also suggest that additional safeguards should be implemented to ensure that higher data privacy standards are met. (shrink)

Throughout the history of science, novel ideas that diverge from mainstream thought have often been met with condemnation, derision, and ad hominem attacks. These reactions have sometimes led to the premature rejection of such ideas, only for them to be later revived and even accepted as the prevailing paradigm. While robust debate is essential in science, the use of derogatory language is unethical, for it discourages research on existing hypotheses, deters funders, corrupts the scientific record, and delays or prevents (...) the advancement of science. In this article, I discuss the case of unethical language repeatedly used against proponents of the hypothesis that an extraterrestrial impact event triggered the Younger Dryas cool period. (shrink)

Defense of Scientific Hypothesis: From Reproducibility Crisis to Big Data sets out to explain and defend the scientific hypothesis. Alger's mission is to counteract the misinformation and misunderstanding about the hypothesis that even seasoned scientists have concerning its nature and place in modern science. Most biological scientists receive little or no formal training in scientific thinking. Further, the hypothesis is under attack by critics who claim that it is irrelevant to science. In order to appreciate and (...) evaluate scientific controversies like global climate change, vaccine safety, etc., the public first needs to understand the hypothesis. Defense of Scientific Hypothesis begins by describing and analyzing the scientific hypothesis in depth and examining its relationships to various kinds of science. Alger then guides readers through a review of the hypothesis in the context of the Reproducibility Crisis and presents survey data on how scientists perceive and employ hypotheses. He assesses cognitive factors that influence our ability to use the hypothesis and makes practical and policy recommendations for teaching and learning about it. Finally, Alger considers two possible futures of the hypothesis in science as the Big Data revolution looms: in one scenario, the hypothesis is displaced by the Big Data Mindset that forgoes understanding in favor of correlation and prediction. In the other, robotic science incorporates the hypotheses into mechanized laboratories guided by artificial intelligence. But in his illuminating epilogue, Alger envisions a third way, the Centaur Scientist, a symbiotic relationship between human scientists and computers. (shrink)

In an increasingly data-driven world, the question of data – or metadata – veracity is now a central issue not only in the world of information but also in the legal one. Data veracity describes a closeness to truth on a higher level than a measure such as accuracy does. High veracity data is data that can be relied upon when making decisions, thus reducing the risk of basing choices on untrue information. The article uses (...) epistemic logic to model structured metadata automatically extracted from legal papers, and the tools of metaontology to propose a definition of veracity as truthmaker. (shrink)

A model of inductive inquiry is defined within a first-order context. Intuitively, the model pictures inquiry as a game between Nature and a scientist. To begin the game, a nonlogical vocabulary is agreed upon by the two players along with a partition of a class of structures for that vocabulary. Next, Nature secretly chooses one structure ("the real world") from some cell of the partition. She then presents the scientist with a sequence of atomic facts about the chosen structure. With (...) each new datum the scientist announces a guess about the cell to which the chosen structure belongs. To succeed in his inquiry, the scientist's successive conjectures must be correct all but finitely often, that is, the conjectures must converge in the limit to the correct cell. A special kind of scientist selects his hypotheses on the basis of a belief revision operator. We show that reliance on belief revision allows scientists to solve a wide class of problems. (shrink)

We present two case studies from contemporary biology in which we observe conflicts between established and emerging approaches. The first case study discusses the relation between molecular biology and systems biology regarding the explanation of cellular processes, while the second deals with phylogenetic systematics and the challenge posed by recent network approaches to established ideas of evolutionary processes. We show that the emergence of new fields is in both cases driven by the development of high-throughput data generation technologies and (...) the transfer of modeling techniques from other fields. New and emerging views are characterized by different philosophies of nature, i.e. by different ontological and methodological assumptions and epistemic values and virtues. This results in a kind of conflict we call “epistemic competition” that manifests in two ways: On the one hand, opponents engage in mutual critique and defense of their fundamental assumptions. On the other hand, they compete for the acceptance and integration of the knowledge they provide by a broader scientific community. Despite an initial rhetoric of replacement, the views as well as the respective audiences come to be seen as more clearly distinct during the course of the debate. Hence, we observe—contrary to many other accounts of scientific change—that conflict results in the formation of new niches of research, leading to co-existence and perceived complementarity of approaches. Our model thus contributes to the understanding of the pluralization of the scientific landscape. (shrink)

A powerful movement is afoot to create a national computerized system of health records. Advocates claim it could save the health delivery system billions of dollars and improve the quality of health services. According to Lawrence Gostin, a leading commentator on privacy and health records, this new infrastructure is “already under way and [has] an aura of inevitability.” When it is in place, almost any information that is viewed as relevant to a decision in the health care delivery system would (...) be available to a large and yet undetermined number of individuals. The transformation of the collection and communication of health information from texts housed by health care providers and facilities to data electronically transmitted through networks of linked computers has significant implications for confidentiality and for data collection in scientific research. The best evidence clearly indicates that most people in the United States consider confidentiality for health information important and worry that the increased computerization of health records will result in inappropriate disclosure. (shrink)

Irregularities in data/results of scientific research might be spotted pre-publication by co-workers and reviewers, or post-publication by readers typically with vested interest. The latter might consist of fellow researchers in the same subject area who would naturally pay closer attention to a published paper. However, it is increasingly apparent that there are readers who interrogate papers in detail with a primary intention to identify potential problems with the work. Here, we consider post-publication peer review (PPPR) by individuals, or (...) groups of individuals, who perform PPPRs with a perceptible intention to actively identify irregularities in published data/results and to expose potential research fraud or misconduct, or intentional misconduct exposing (IME)-PPPR. On one hand, such activities, when done anonymously or pseudonymously with no formal discourse, have been deemed as lacking in accountability, or perceived to incur some degree of maleficence, and have been labelled as vigilantism. On the other, these voluntary works have unravelled many instances of research misconduct and have helped to correct the literature. We explore the tangible benefits of IME-PPPR in detecting errors in published papers and from the perspectives of moral permissibility, research ethics, and the sociological perspective of science. We posit that the benefits of IME-PPPR activities that uncover clear evidence of misconduct, even when performed anonymously or pseudonymously, outweigh their perceived deficiencies. These activities contribute to a vigilant research culture that manifests the self-correcting nature of science, and are in line with the Mertonian norms of scientific ethos. (shrink)