Social Networking Services provide services in return for rights to commercialize users’ personal data. We argue that what makes this transaction permissible is not users’ autonomous consent but the provision of sufficiently valuable opportunities to exchange data for services. We argue that the value of these opportunities should be assessed for both (a) a range of users with different decision-making abilities and (b) third parties. We conclude that regulation should shift from aiming to ensure autonomous consent towards ensuring (...) that users face options that they will use to advance individual and common interests. (shrink)

This paper examines classification practices in the domain of plant data semantics, and particularly methods used to label plant traits to foster the collection, management, linkage and analysis of data about crops across locations—which crucially inform research and interventions on plants and agriculture. The efforts required to share data place in sharp relief the forms of diversity characterizing the systems used to capture the biological and environmental characteristics of plant variants: particularly the biological, cultural, scientific and semantic (...) diversity affecting the identification and description of plant traits, the methods used to generate and process data, and the goals and skills of those with relevant expertise—including farmers and breeders. Through a study of the Crop Ontology (which explicitly recognizes and negotiates diversity) and its application to cassava breeding, I argue for a process-sensitive approach to the naming of plant traits that focuses on documenting environmental processes instead of biological products. I claim that this approach can foster reliable linkage and robust re-use of plant data, while at the same time facilitating dialogue between data scientists, plant researchers, breeders, and other relevant experts in ways that crucially inform agricultural interventions. I conclude that the study of data semantics and related descriptors constitutes a productive and underexplored way to think about the epistemic import of naming traits within plant science. The effort to articulate semantic differences among plant varieties and methods of data processing can generate newly inclusive ways to develop and communicate biological knowledge. In turn, such practices have the potential to defy existing understandings of systematisation and hierarchies of expertise in biology, thus bolstering the extent to which plant science can support biodiversity and sustainable agriculture. (shrink)

This series will include monographs and collections of studies devoted to the investigation and exploration of knowledge, information and data-processing systems of all kinds, no matter whether human, (other) animal or machine. Its scope is intended to span the full range of interests from classical problems in the philosophy of mind and phi losophical psychology through issues in cognitive psychology and socio biology (concerning the mental capabilities of other species) to ideas related to artificial intelligence and computer (...) science. While primary emphasis will be placed upon theoretical, conceptual and epistemologi cal aspects of these problems and domains, empirical, experimental and methodological studies will also appear from time to time. Among the most challenging and difficult projects within the scope of artificial intelligence is the development and implementation of com puter programs suitable for processing natural language. Our purpose in compiling the present volume has been to contribute to the foundations of this enterprise by bringing together classic papers devoted to crucial problems involved in understanding natural language, which range from issues of formal syntax and logical form to those of possible-worlds and situation semantics. The book begins with a comprehensive introduc tion composed by Jack Kulas, the senior editor of this work, which pro vides a systematic orientation to this complex field, and ends with a selected bibliography intended to promote further research. If our efforts assist others in dealing with these problems, they will have been worthwhile. J. H. F. (shrink)

The large-scale and intensive collection and analysis of digital data (commonly called “Big Data”) has become a common, popular, and consensual research method for the social sciences, as the automation of data collection, mathematization of analysis, and digital objectification reinforce both its efficiency and truth-value. This article opens with a critical review of the literature on data collection and analysis, and summarizes current ethical discussions focusing on these technologies. A semiotic model of data production and (...) circulation is then introduced to problematize the view that digital data has ceased to stand for a formalization method (a possible kind of representation among others), and effectively “becomes the world itself” (a direct presentation of the world outperforming all other modes of representation). Following Charles Sanders Peirce’s semiotics and pragmaticist philosophy, we characterize digitalization as a hypersymbolic semiotic process, and we highlight the naturalization of meaning, the illusion of iconicity, and rhetorical efficiency on which data’s truth value relies within the context of its large-scale, profit-driven, and results-oriented research uses. This outlines some epistemological and ethical implications of data’s visualization, use, and authority, and indicates avenues for critical semiotics of contemporary data science and analysis. (shrink)

The contributors set out to demonstrate the influence of the computer - not just in the philosophy of mind, but also in epistemology, metaphysics, logic and the philosophy of mathematics. Even ethics and ethical reasoning have been explored through the use of the computer.

"Hegel's Philosophy of Nature was for a long time regarded as an outdated historical curiosity. Yet if systematic completeness is given up, the value of Hegelian arguments and of Hegelian logic generally becomes uncertain. In this book, John Burbidge reveals the abiding significance of the Philosophy of Nature as the intermediate movement in Hegel's system." "Burbidge looks at three specific texts in Hegel's work: the two chapters of the Science of Logic that deal with the concept of chemism, (...) and the section on chemical process in the Philosophy of Nature. Through his detailed commentary, he clarifies Hegel's distinction between a strictly theoretical philosophy and one that understands the natural world. He shows that Hegel does not presume to derive natural data a priori, nor is he simply dependent on the explanatory theories arrived at by chemists themselves. Experience provides the data, but thought sets the parameters. Burbidge sets Hegel's thought in context with sketches of what Kant, Fichte, and Schelling had to say about chemistry, and with background outlining the stage chemistry had reached at the time Hegel was writing. He also reveals how Hegel changed his mind as he revised each section for succeeding editions of his work, thus providing a fascinating case study of the development of Hegel's ideas."--BOOK JACKET.Title Summary field provided by Blackwell North America, Inc. All Rights Reserved. (shrink)

Privacy, Due process and the Computational Turn: The Philosophy of Law Meets the Philosophy of Technology engages with the rapidly developing computational aspects of our world including data mining, behavioural advertising, iGovernment, profiling for intelligence, customer relationship management, smart search engines, personalized news feeds, and so on in order to consider their implications for the assumptions on which our legal framework has been built. The contributions to this volume focus on the issue of privacy, which is often (...) equated with data privacy and data security, location privacy, anonymity, pseudonymity, unobservability, and unlinkability. Here, however, the extent to which predictive and other types of data analytics operate in ways that may or may not violate privacy is rigorously taken up, both technologically and legally, in order to open up new possibilities for considering, and contesting, how we are increasingly being correlated and categorizedin relationship with due process – the right to contest how the profiling systems are categorizing and deciding about us. (shrink)

Data science is not simply a method but an organising idea. Commitment to the new paradigm overrides concerns caused by collateral damage, and only a counterculture can constitute an effective critique. Understanding data science requires an appreciation of what algorithms actually do; in particular, how machine learning learns. The resulting ‘insight through opacity’ drives the observable problems of algorithmic discrimination and the evasion of due process. But attempts to stem the tide have not grasped the nature of (...) class='Hi'>data science as both metaphysical and machinic. Data science strongly echoes the neoplatonism that informed the early science of Copernicus and Galileo. It appears to reveal a hidden mathematical order in the world that is superior to our direct experience. The new symmetry of these orderings is more compelling than the actual results. Data science does not only make possible a new way of knowing but acts directly on it; by converting predictions to pre-emptions, it becomes a machinic metaphysics. The people enrolled in this apparatus risk an abstraction of accountability and the production of ‘thoughtlessness’. Susceptibility to data science can be contested through critiques of science, especially standpoint theory, which opposes the ‘view from nowhere’ without abandoning the empirical methods. But a counterculture of data science must be material as well as discursive. Karen Barad’s idea of agential realism can reconfigure data science to produce both non-dualistic philosophy and participatory agency. An example of relevant praxis points to the real possibility of ‘machine learning for the people’. (shrink)

This important book, which results from a series of presentations at American Philosophical Association conferences, explores the major ways in which computers ...

The analysis of video-recorded interaction consists of various professionalized ways of seeing participant behavior through multimodal, co-operative, or intercorporeal lenses. While these perspectives are often adopted simultaneously, each creates a different view of the human body and interaction. Moreover, microanalysis is often produced through local practices of sense-making that involve the researchers’ bodies. It has not been fully elaborated by previous research how adopting these different ways of seeing human behavior influences both what is seen from a video and how (...) it is seen, as well as the way the interpretation of the data ultimately unfolds in the interaction between researchers. In this article, we provide a theoretical-methodological discussion of the microanalytic research process. We explore how it differs from “seeing” affect in interaction either as a co-operative and multimodal action or as an intercorporeal experience. First, we introduce the multimodal conversation analytic, co-operative, and intercorporeal approaches to microanalysis. Second, we apply and compare these practices to a video-recorded interaction of a romantic couple. Furthermore, we examine a video-recorded episode of us, the researchers, reflecting on our analytic observations about this interaction. We suggest that adopting a multimodal and co-operative perspective constructs affect as co-produced and displayed through observable action, while an intercorporeal perspective produces affect as an embodied and experienced phenomenon. While the former enables locating affect in a specific moment and identifiable body parts, the latter facilitates recognizing the experienced side of affect. These different modes of professional vision complement one another in capturing affect in interaction while being fundamentally used in local interactions between the researchers. (shrink)

This cutting edge volume provides an overview of the dynamic new field of cyberphilosophy – the intersection of philosophy and computing.

Using speech act theory from the Philosophy of Language, this paper attempts to develop an ethical framework for the phenomenon of speech processing. We use the concepts of the illocutionary force and the illocutionary content of a speech act to explain the ethics of speech processing. By emphasizing the different stages involved in speech processing, we explore the distinct ethical issues that arise in relation to each stage. Input, processing, and output are the different ethically (...) relevant stages under which a spoken item or a speech navigates within the range of speech-processing modules. Employing the illocutionary force-content distinction, we specify and characterize the input-related ethical issues, the output-related ethical issues, and the processing-related ethical issues involved in speech processing. Together with illocutionary force-content distinction, we employ the data-information distinction to characterize the stage-wise ethical issues in the phenomenon of speech processing as the ethics of collecting (speech) data, the ethics of contextualizing (speech) data/information, and the ethics of releasing the con-textualized information (processed speech). Immediate ethical issues that arise from the range of speech processing modules are distinguished from distant ethical issues. We also indicate the nature of ethical issues that arise from Speaker Independent speech technologies. (shrink)

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 (...) insight into the common but little-discussed practices of iteratively reusing and repurposing data, which result in many datasets’ having a phylogeny—an origin and complex evolutionary history—that is relevant to their evaluation and future use. We relate these insights to the open-data and data-rescue movements, and highlight several future avenues of research that build on the PR view of data. (shrink)

Health professionals had difficulty choosing the right time to discuss life-sustaining treatments (LSTs) since the Korean Act was passed in 2018. This study aimed to understand how patients decide to undergo LSTs in clinical practice and to compare the perceptions of these decisions among health professionals, patients, and families with suggestions to support the self-directed decisions of patients. A retrospective observational study with electronic medical records (EMRs) and a descriptive survey was used. The data obtained from the EMRs included (...) all adult patients who died in end-of-life care at a university hospital in 2021. We also conducted a survey of 214 health professionals and 100 patients and their families (CNUH IRB approval no. 2022-07-006). Based on the EMR data of 916 patients in end-of-life care, 78.4% signed do-not-attempt-resuscitation consents, 5.6% completed the documents for LSTs, and 10.2% completed both forms. LST decisions were mostly made by family members (81.5%). Most survey participants agreed that meaningless LSTs should be suspended, and the decision should be made by patients. Patients and family members (42–56%) and health professionals (56–58%) recommended discussing LST suspension when the patient is still conscious but with predicted deterioration of their condition. The suffering experienced by the patient was considered to be a priority by most patients (58%) and families (54%) during the decision-making process, while health professionals considered “the possibility of the patient’s recovery” to be the highest priority (43–55%). There is still a significant discrepancy in the perceptions of LST decisions among health professionals, patients, and their families despite high awareness of the Act. This situation makes it challenging to implement the Act to ensure respect for the rights of patients to self-determination and dignified end-of-life. Further effort is needed to improve the awareness of LSTs and to clarify the ambiguity of document preparation timing. (shrink)

In response to calls to forget and unthink photography this article considers the computational environment and its consequences for the image making. What is there to know about images that are networked and generated with data processing techniques rather than with light and chemistry? How to analyse images and read what they are and what they represent, beyond what is visible in the picture? The article argues that glitches while aesthetically capturing errors in the machine point to broader (...) conditions of image making revealing systemic errors and not only its momentary technical failures. To explore digital images as affective phenomena to be sensed, the article looks at how glitch and its operations have been used by artists to generate digital images, and most importantly how they reveal computational systems as technical objects and affective infrastructures where discrimination is not an error but part of the system. (shrink)

As a reply to the commentary (Humphreys in Found Sci, 2012), we explore the methodological implications of seeing artificial neural networks as generic classification tools, we show in which sense the use of descriptions and models in data analysis is not equivalent to the original empirical use of epicycles in describing planetary motion, and we argue that agnostic science is essentially related to the type of problems we ask about a phenomenon and to the processes used to find answers.

Intensified and extensive data production and data storage are characteristics of contemporary western societies. Health data sharing is increasing with the growth of Information and Communication Technology platforms devoted to the collection of personal health and genomic data. However, the sensitive and personal nature of health data poses ethical challenges when data is disclosed and shared even if for scientific research purposes. With this in mind, the Science and Values Working Group of the COST (...) Action CHIP ME ‘Citizen's Health through public-private Initiatives: Public health, Market and Ethical perspectives’ identified six core values they considered to be essential for the ethical sharing of health data using ICT platforms. We believe that using this ethical framework will promote respectful scientific practices in order to maintain individuals’ trust in research. We use these values to analyse five ICT platforms and explore how emerging data sharing platforms are reconfiguring the data sharing experience from a range of perspectives. We discuss which types of values, rights and responsibilities they entail and enshrine within their philosophy or outlook on what it means to share personal health information. Through this discussion we address issues of the design and the development process of personal health data and patient-oriented infrastructures, as well as new forms of technologically-mediated empowerment. (shrink)

Das Ziel der Begriffsgeschichte ist es, eine kritische und moglichst vollstandige Ubersicht uber den Bedeutungswandel von Begriffen durch die Jahrzehnte zu geben, so Gustav Teichmuller in der Vorrede zu seinen Studien zur Geschichte der Begriffe. Ein solches Unterfangen bringt Uberlappungen mit der Terminologiegeschichte, der Wortgeschichte, der Problemgeschichte, der Ideengeschichte und der Sachgeschichte mit sich, denn alle diese Disziplinen untersuchen letztlich den philosophischen Diskurs und seine Wandlungen in der Zeit. Erst die Verdeutlichung ihrer geschichtlichen Wirksamkeit macht Begriffe fur die philosophische Reflexion (...) brauchbar und schafft den ausreichend begrundeten Ruckhalt fur ihre stringente Anwendung. Die Basis dafur bietet der lexikographische Ansatz des Lessico Intellettuale Europeo, das heute das grosste Repositorium von lemmatisierten Texten der Philosophie- und Wissenschaftsgeschichte ist. Der von Riccardo Pozzo und Marco Sgarbi herausgegebene Band gliedert sich in drei Teile, die sich mit den neuen Entwicklungen in der Methodologie der Geschichte der Philosophie im 21. Jahrhundert befassen. Wahrend der erste Teil die methodischen Aspekte von Begriffs-, Problem- und Ideengeschichte thematisiert und der zweite Teil die Anwendung dieser Methoden auf die neuen Informationstechnologien zeigt, enthalt der dritte und letzte Teil einige Beispiele, an denen die Notwendigkeit der Verschrankung zwischen Begriffs-, Problem- und Ideengeschichte deutlich wird. (shrink)

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 argue that whether a set of objects functions as data or models does not depend on intrinsic differences in their physical properties, level of abstraction or the degree of human intervention involved in generating them, but rather on their distinctive roles towards identifying and characterizing the targets of investigation. The paper thus proposes a characterization of data models that builds on Suppes’ attention to data practices, without however needing to posit a fixed hierarchy of data and models or a highly exclusionary definition of data models as statistical constructs. (shrink)

What is data? That question is the fundamental investigation of this dissertation. I have developed a methodology from social-scientific processes to explore how different people understand the concept of data, rather than to rely on my own philosophical intuitions or thought experiments about the “nature” of data. The evidence I have gathered as to different individuals' constructions of data can be used to inform further inquiry of data and the design of information systems. My research (...) demonstrates that people have different constructions of data. The methodology of the SDFN, created for this dissertation, has proven able to probe those understandings. The SDFN, loosely based on a DFD and combined with ideas from SNA, provides a way of discovering practical definitions of hard-to-operationalize terms like data. The process of repeatedly categorizing various items as data allows the methodology to explore how participants actually use the term, rather than relying on theoretical dictionary-based definitions. Analysis of the interviews found three different constructions of data: data as communications, a container for meaning; data as subjective observations, sense-impressions filtered by knowledge; and data as objective facts, measurements revealing the relationships of reality. (shrink)

Georgios Pentzaropoulos continues his investigation undertaken in 'Generating Stable Knowledge via Reduction in Entropy' (Philosophy Pathways Issue 167, 28 November 2011) looking at knowledge not as something we 'possess' -- the knowledge contained in a book, for example -- but rather as an active, or interactive process of increasing understanding through the judicious sifting and processing of raw information. As Macmurray argued in his Gifford Lectures, 'All knowledge is for the sake of action.' Instead of seeking to define (...) some abstract notion of knowledge in a vacuum, what philosophers should be getting to grips with is the notion of actionable knowledge. - Geoffrey Klempner, Editor. (shrink)

This article 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 reuse from modeling and experimental practices in biology, I then argue that Dt affects (...) how researchers select and interpret data as evidence and identify and understand phenomena. (shrink)

Social media data hold considerable potential for predicting health-related conditions. Recent studies suggest that machine-learning models may accurately predict depression and other mental health-related conditions based on Instagram photos and Tweets. In this article, it is argued that individuals should have a sui generis right not to be subjected to AI profiling based on publicly available data without their explicit informed consent. The article (1) develops three basic arguments for a right to protection of personal data trading (...) on the notions of social control and stigmatization, (2) argues that a number of features of AI profiling make individuals more exposed to social control and stigmatization than other types of data processing (the exceptionalism of AI profiling), (3) considers a series of other reasons for and against protecting individuals against AI profiling based on publicly available data, and finally (4) argues that the EU General Data Protection Regulation does not ensure that individuals have a right not to be AI profiled based on publicly available data. (shrink)

The current behavioral consultation case demonstrates how functional behavioral assessment (FBA) data, basic and applied research, teacher preferences, and contextual variables contribute to the decision making process when developing classroom intervention procedures. A male, African-American, fifth-grade general education student was initially referred for his inappropriate vocalizations duringtime designated for independent seatwork. FBA data suggested that this behavior was being reinforced with teacher attention. Additional data showed that he was failing to complete his assignments. An intervention was implemented (...) where the student was given assignments one a time. He was instructed to solicit teacher attention and his next assignment after completing each assignment. Analysis ofteacher ratings for inappropriate vocalizations and assignment performance data suggest that the intervention was effective in increasing assignment completion and decreasing inappropriate verbalizations. Discussion focuses on how the various data playa role in the development and implementation of classroom intervention procedures. (shrink)

This groundbreaking, open access volume analyses and compares data practices across several fields through the analysis of specific cases of data journeys. It brings together leading scholars in the philosophy, history and social studies of science to achieve two goals: tracking the travel of data across different spaces, times and domains of research practice; and documenting how such journeys affect the use of data as evidence and the knowledge being produced. The volume captures the opportunities, (...) challenges and concerns involved in making data move from the sites in which they are originally produced to sites where they can be integrated with other data, analysed and re-used for a variety of purposes. The in-depth study of data journeys provides the necessary ground to examine disciplinary, geographical and historical differences and similarities in data management, processing and interpretation, thus identifying the key conditions of possibility for the widespread data sharing associated with Big and Open Data. The chapters are ordered in sections that broadly correspond to different stages of the journeys of data, from their generation to the legitimisation of their use for specific purposes. Additionally, the preface to the volume provides a variety of alternative “roadmaps” aimed to serve the different interests and entry points of readers; and the introduction provides a substantive overview of what data journeys can teach about the methods and epistemology of research. (shrink)

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 and with a focus on the role of data-sharing tools, like online databases, in facilitating this process; and I point to the philosophical implications of focusing on data as a unit of analysis. I then analyse three cases of data integration in the field of plant science, each of which highlights a different mode of integration: inter-level integration, which involves data documenting different features of the same species, aims to acquire an interdisciplinary understanding of organisms as complex wholes and is exemplified by research on Arabidopsis thaliana; cross-species integration, which involves data acquired on different species, aims to understand plant biology in all its different manifestations and is exemplified by research on Miscanthus giganteus; and translational integration, which involves data acquired from sources within as well as outside academia, aims at the provision of interventions to improve human health and is exemplified by research on Phytophtora ramorum. Recognising the differences between these efforts sheds light on the dynamics and diverse outcomes of data dissemination and integrative research; and the relations between the social and institutional roles of science, the development of data-sharing infrastructures and the production of scientific knowledge. (shrink)

Educational research is dominated by a particular model: data is gathered and analysed. Much literature on methods concerns either ways of processing data, or ethical issues regarding its collection and handling. The present paper looks beyond these matters to the taken‐for‐granted idea of data itself. What can be meant by ‘data’? How does this connect with ideas of the given? What is the place of giving in education—in teaching and learning, in research itself? These issues (...) are explored in the light of information technology’s impact on research, uncovering ethical dimensions that the seeming naturalness of data otherwise obscures. (shrink)

BackgroundEthics review is the process of assessing the ethics of research involving humans. The Ethics Review Committee (ERC) is the key oversight mechanism designated to ensure ethics review. Whether or not this governance mechanism is still fit for purpose in the data-driven research context remains a debated issue among research ethics experts.Main textIn this article, we seek to address this issue in a twofold manner. First, we review the strengths and weaknesses of ERCs in ensuring ethical oversight. Second, we (...) map these strengths and weaknesses onto specific challenges raised by big data research. We distinguish two categories of potential weakness. The first category concerns persistent weaknesses, i.e., those which are not specific to big data research, but may be exacerbated by it. The second category concerns novel weaknesses, i.e., those which are created by and inherent to big data projects. Within this second category, we further distinguish between purview weaknesses related to the ERC’s scope (e.g., how big data projects may evade ERC review) and functional weaknesses, related to the ERC’s way of operating. Based on this analysis, we propose reforms aimed at improving the oversight capacity of ERCs in the era of big data science.ConclusionsWe believe the oversight mechanism could benefit from these reforms because they will help to overcome data-intensive research challenges and consequently benefit research at large. (shrink)

The distinction between data and phenomena introduced by Bogen and Woodward (Philosophical Review 97(3):303–352, 1988) was meant to help accounting for scientific practice, especially in relation with scientific theory testing. Their article and the subsequent discussion is primarily viewed as internal to philosophy of science. We shall argue that the data/phenomena distinction can be used much more broadly in modelling processes in philosophy.

Neuroimaging technology is the most widely used tool to study human cognition. While originally a promising tool for mapping the content of cognitive theories onto the structures of the brain, recently developed tools for the analysis, handling and sharing of data have changed the theoretical landscape of cognitive neuroscience. Even with these advancements philosophical analyses of evidence in neuroimaging remain skeptical of the promise of neuroimaging technology. These views often treat the analysis techniques used to make sense of (...) class='Hi'>data produced in a neuroimaging experiment as one, attributing the inferential limitations of analysis pipelines to the technology as a whole. Situated against the neuroscientists own critical assessment of their methods and the limitations of those methods, this skepticism appears based on a misunderstanding of the role data analysis techniques play in neuroimaging research. My project picks up here, examining how data analysis techniques, such as pattern classification analysis, are used to assess the evidential value of neuroimaging data. The project takes the form of three papers. In the first I identify the use of multiple data analysis techniques as an important aspect of the data interpretation process that is overlooked by critics. In the second I develop an account of inferences in neuroimaging research that is sensitive to this use of data analysis techniques, arguing that interpreting neuroimaging data is a process of isolating and explaining a variety of data patterns. In the third I argue that the development and uptake of new techniques for analyzing data must be accompanied by changes in research practices and standards of evidence if they are to promote knowledge generation. My approach to this work is both traditionally philosophical, insofar as it involves reading and analyzing the work of philosophers and neuroscientists, and embedded insofar as most of the research was conducted while engaged in attending lab meetings and participating in the work of those scientists whose work is the object of my research. (shrink)

The current behavioral consultation case demonstrates how functional behavioral assessment (FBA) data, basic and applied research, teacher preferences, and contextual variables contribute to the decision making process when developing classroom intervention procedures. A male, African-American, fifth-grade general education student was initially referred for his inappropriate vocalizations duringtime designated for independent seatwork. FBA data suggested that this behavior was being reinforced with teacher attention. Additional data showed that he was failing to complete his assignments. An intervention was implemented (...) where the student was given assignments one a time. He was instructed to solicit teacher attention and his next assignment after completing each assignment. Analysis ofteacher ratings for inappropriate vocalizations and assignment performance data suggest that the intervention was effective in increasing assignment completion and decreasing inappropriate verbalizations. Discussion focuses on how the various data playa role in the development and implementation of classroom intervention procedures. (shrink)

BackgroundIncreasingly, hospitals and research institutes are developing technical solutions for sharing patient data in a privacy preserving manner. Two of these technical solutions are homomorphic encryption and distributed ledger technology. Homomorphic encryption allows computations to be performed on data without this data ever being decrypted. Therefore, homomorphic encryption represents a potential solution for conducting feasibility studies on cohorts of sensitive patient data stored in distributed locations. Distributed ledger technology provides a permanent record on all transfers and (...) processing of patient data, allowing data custodians to audit access. A significant portion of the current literature has examined how these technologies might comply with data protection and research ethics frameworks. In the Swiss context, these instruments include the Federal Act on Data Protection and the Human Research Act. There are also institutional frameworks that govern the processing of health related and genetic data at different universities and hospitals. Given Switzerland’s geographical proximity to European Union (EU) member states, the General Data Protection Regulation (GDPR) may impose additional obligations.MethodsTo conduct this assessment, we carried out a series of qualitative interviews with key stakeholders at Swiss hospitals and research institutions. These included legal and clinical data management staff, as well as clinical and research ethics experts. These interviews were carried out with two series of vignettes that focused on data discovery using homomorphic encryption and data erasure from a distributed ledger platform.ResultsFor our first set of vignettes, interviewees were prepared to allow data discovery requests if patients had provided general consent or ethics committee approval, depending on the types of data made available. Our interviewees highlighted the importance of protecting against the risk of reidentification given different types of data. For our second set, there was disagreement amongst interviewees on whether they would delete patient data locally, or delete data linked to a ledger with cryptographic hashes. Our interviewees were also willing to delete data locally or on the ledger, subject to local legislation.ConclusionOur findings can help guide the deployment of these technologies, as well as determine ethics and legal requirements for such technologies. (shrink)

The paper defines units of cognition from data, through; information, concept, knowledge, and to wisdom, applying the Semantic Ladder. This concept is later used in describing different levels of computer information systems and defining a process of decision-making. Finally, the Semantic Ladder is applied in understanding art, where certain compositions reflect different units of cognition, including the simplest and most complex ones. This study implies that wisdom as the ultimate unit of cognition is the result of hierarchical processing (...) of data, information, concept, and knowledge. What does it mean for civilization? The more we know, the more we want; and we may be in more trouble! Can we overcome knowledge that we created and become wiser? (shrink)

Unprecedented advances in the ability to store, analyze, and retrieve data is the hallmark of the information age. Along with enhanced capability to identify meaningful patterns in large data sets, contemporary data science renders many classical models of privacy protection ineffective. Addressing these issues through privacy-sensitive design is insufficient because advanced data science is mutually exclusive with preserving privacy. The special privacy problem posed by data analysis has so far escaped even leading accounts of informational (...) privacy. Here, I argue that accounts of privacy must include norms about information processing in addition to norms about information flow. Ultimately, users need the resources to control how and when personal information is processed and the knowledge to make information decisions about that control. While privacy is an insufficient design constraint, value-sensitive design around control and transparency can support privacy in the information age. (shrink)

Big data represents a significant challenge for the social sciences. From a philosophy-of-science perspective, it is important to reflect on related theories and processes for developing them. In this paper, we start by examining different views on the role of theories in big data-related social research. Then, we try to show how big data is related to standards for evaluating theories. We also outline how big data affects theory- and data-based research approaches and the (...) process of theory building. Discussions include a summary of lines of reasoning, limitations, and a proposal for future developmental steps. (shrink)

The contribution of the data paper publishing paradigm to the knowledge generation and validation processes is becoming substantial and pivotal. In this paper, through the information-processing perspective of Mindsponge Theory, we discuss how the data article publishing system serves as a filtering mechanism for quality control of the increasingly chaotic datasphere. The overemphasis on machine-actionality and technical standards presents some shortcomings and limitations of the data article publishing system, such as the lack of consideration of humanistic (...) values, radical race for big data, and inadequate use of expertise in data evaluation. Without addressing the shortcomings and limitations, the reusability of data will be hindered, and scientific investment to facilitate data sharing will be wasted. Thus, we suggest that the current data paper publishing paradigm needs to be updated with a new philosophy of data. (shrink)

Omitting experimental data is often considered a violation of scientific integrity. If we consider experimental inquiry as a questioning process, omitting data is seen to be merely an example of tentatively rejecting (‘bracketing’) some of nature’s answers. Such bracketing is not only occasionally permissible; sometimes it is mandated by optimal interrogative strategies. When to omit data is therefore a strategic rather than ethical question. These points are illustrated by reference to Millikan’s oil drop experiment.

Since the second half of the twentieth century, biomedical research has made increasing use of epidemiological methods to establish empirical evidence on a population level. This paper is about practices with data in epidemiological research, based on a case study in Denmark. I propose an epistemology of record linkage that invites exploration of epidemiological studies as heterogeneous assemblages. Focusing on data collecting, sampling and linkage, I examine how data organisation and processing become productive beyond the context (...) of their collection. The case study looks at how a local population database established in 1976 to investigate possibilities for the prevention of cardiovascular disease is used thirty years later to test hypotheses on the aetiology of breast cancer. For two breast cancer investigations based on the same core data set, I follow the underlying record linkage practice and describe how research objects such as molecular markers become relevant with respect to public health through information networking. Epidemiological association studies function as tools that performatively enrol different contexts into statistical risk estimation, thereby configuring options for research as well as for clinical testing and public health policy. (shrink)

This paper is concerned with the kind of non-linear causation that lies behind the production and comprehension of speech in discourse, where multiple input data typically act in concert towards a determinate output. To this end Whitehead's philosophy of Process - in particular his theory of prehensions — is applied to the analysis of pragmatic implication and inference in a short literary excerpt, which involves the most complex kind of prehension, the `intuitive judgment'. This leads to a number (...) of conclusions concerning the way in which patterns of linguistic behaviour can be evoked out of mere potentiality by contextually embedded prehensions that constrain and modulate the expression of intended discourse acts. Some of these constraints are attributable to the nature of focal consciousness itself. An extension of the Whiteheadian notion of subjective aim (usually understood to preside over a single actual occasion) will be necessitated, since in discourse this can clearly both be suspended and divided into subordinate sub-aims while the overall aim, still unfulfilled, is inherited from occasion to occasion. (shrink)

In Processes of Knowledge, George Towner analyzes the actual ways that human knowledge is accumulated and organized, both in science and in everyday life. He places the processes of knowledge within their social context, examining the basic ways that communication lets people share ideas. Towner traces the development of language, writing, and data processing, demonstrating their different effects on theorizing. He also develops an evolutionary view of group thinking, examining the ways that human groups use specific types of (...) theories to achieve social cohesion and showing how these theories change over time. The result is a dynamic view of intellectual history, based on the inherent processes by which knowledge grows. (shrink)

Systematic sampling of communities gives rise to large contingency tables summing up possible changes in the assemblages' structure. Such tables are generally analysed by multivariate statistical methods, which are ill-suited for simultaneously analysing rare and common species (Field et al., 1982). In order to separately process species belonging to either of these categories, we propose a statistical method to select common species in a sequence of ecological surveys. It is based on a precise definition of rarity, and depends on a (...) rarity parameter. In this work, this parameter will be optimised so that the sub-table of common species captures the essential features of the complete table as well as possible. In this way we analysed the spatio-temporal evolution of macrobenthic communities from the Algiers harbour to study the pollution influence during a year. The examination of the communities' structuring was done through Principal Components Analysis (PCA) of the species proportions table. Environmental variables were simultaneously sampled. We show that the data structure can be explained by about 25% of the total number of present species. Two environmental gradients were brought to the fore inside the harbour, the first one representing pollution, and the second one representing hydrological instabilities. (shrink)

This paper presents a cognitive account of the process of evaluating scientific data. Our account assumes that when individuals evaluate data, they construct a mental model of a data-interpretation package, in which the data and theoretical interpretations of the data are integrated. We propose that individuals attempt to discount data by seeking alternative explanations for events within the mental model; data-interpretation packages are accepted when the individual cannot find alternative accounts for these events. (...) Our analysis indicates that there are many levels at which data-interpretation packages can be accepted or denied. (shrink)

The exponential accumulation, processing and accrual of big data in healthcare are only possible through an equally rapidly evolving field of big data analytics. The latter offers the capacity to rationalize, understand and use big data to serve many different purposes, from improved services modelling to prediction of treatment outcomes, to greater patient and disease stratification. In the area of infectious diseases, the application of big data analytics has introduced a number of changes in the (...) information accumulation models. These are discussed by comparing the traditional and new models of data accumulation. Big data analytics is fast becoming a crucial component for the modelling of transmission—aiding infection control measures and policies—emergency response analyses required during local or international outbreaks. However, the application of big data analytics in infectious diseases is coupled with a number of ethical impacts. Four key areas are discussed in this paper: automation and algorithmic reliance impacting freedom of choice, big data analytics complexity impacting informed consent, reliance on profiling impacting individual and group identities and justice/fair access and increased surveillance and population intervention capabilities impacting behavioural norms and practices. Furthermore, the extension of big data analytics to include information derived from personal devices, such as mobile phones and wearables as part of infectious disease frameworks in the near future and their potential ethical impacts are discussed. Considered together, the need for a constructive and transparent inclusion of ethical questioning in this rapidly evolving field becomes an increasing necessity in order to provide a moral foundation for the societal acceptance and responsible development of the technological advancement. (shrink)

This paper explores some key discrepancies between two sets of normative requirements applicable to the research use of personal data and human biological materials: the data protection regime which follows the application of the European Union General Data Protection Regulation, and the Declaration of Helsinki, CIOMS guidelines and other research ethics regulations. One source of this controversy is that the GDPR requires consent to process personal data to be clear, concise, specific and granular, freely given and (...) revocable and therefore has challenged the concept of ‘broad consent’, which has been widely applied in the context of biobanking. Another source of controversy is the interplay between regulations of research ethics and protection of personal data related to the secondary use of personal data and biological materials. In this case, the GDPR ‘research condition’ provides an alternative to re-consent for the use of previously collected personal data and biological materials. Although the mentioned controversies have been raised in the legal literature, they have not been explicitly addressed from the research ethics perspective. Should consent be regarded as a priority legal basis for personal data processing in health data research? Can broad consent still be a suitable legal ground for biobanking? What should be the role of research ethics provisions that differ from the GDPR standards, and what should be the role and function of research ethics committees in the changing environment of health data research? These are the ongoing controversies to be explored in the paper. (shrink)