Results for 'data'

966 found
Order:
  1. Data is the new gold, but efficiently mining it requires a philosophy of data.Data Thinkerr - 2023 - Data Thinking.
    Fixing the problem won’t be easy, but humans’ sharpened focus on an emerging philosophy of data might give us some clue about where we will be heading for.
    Download  
     
    Export citation  
     
    Bookmark  
  2. The 1 law of "absolute reality"." ~, , Data", , ", , Value", , = O. &Gt, Being", & Human - manuscript
    Download  
     
    Export citation  
     
    Bookmark  
  3. (1 other version)Open data, open review and open dialogue in making social sciences plausible.Quan-Hoang Vuong - 2017 - Nature: Scientific Data Updates 2017.
    Nowadays, protecting trust in social sciences also means engaging in open community dialogue, which helps to safeguard robustness and improve efficiency of research methods. The combination of open data, open review and open dialogue may sound simple but implementation in the real world will not be straightforward. However, in view of Begley and Ellis’s (2012) statement that, “the scientific process demands the highest standards of quality, ethics and rigour,” they are worth implementing. More importantly, they are feasible to work (...)
    Download  
     
    Export citation  
     
    Bookmark   15 citations  
  4. Brain Data in Context: Are New Rights the Way to Mental and Brain Privacy?Daniel Susser & Laura Y. Cabrera - 2023 - American Journal of Bioethics Neuroscience 15 (2):122-133.
    The potential to collect brain data more directly, with higher resolution, and in greater amounts has heightened worries about mental and brain privacy. In order to manage the risks to individuals posed by these privacy challenges, some have suggested codifying new privacy rights, including a right to “mental privacy.” In this paper, we consider these arguments and conclude that while neurotechnologies do raise significant privacy concerns, such concerns are—at least for now—no different from those raised by other well-understood (...) collection technologies, such as gene sequencing tools and online surveillance. To better understand the privacy stakes of brain data, we suggest the use of a conceptual framework from information ethics, Helen Nissenbaum’s “contextual integrity” theory. To illustrate the importance of context, we examine neurotechnologies and the information flows they produce in three familiar contexts—healthcare and medical research, criminal justice, and consumer marketing. We argue that by emphasizing what is distinct about brain privacy issues, rather than what they share with other data privacy concerns, risks weakening broader efforts to enact more robust privacy law and policy. (shrink)
    Download  
     
    Export citation  
     
    Bookmark   14 citations  
  5. Big data and their epistemological challenge.Luciano Floridi - 2012 - Philosophy and Technology 25 (4):435-437.
    Between 2006 and 2011, humanity accumulated 1,600 EB of data. As a result of this growth, there is now more data produced than available storage. This article explores the problem of “Big Data,” arguing for an epistemological approach as a possible solution to this ever-increasing challenge.
    Download  
     
    Export citation  
     
    Bookmark   36 citations  
  6. Big Data, epistemology and causality: Knowledge in and knowledge out in EXPOsOMICS.Stefano Canali - 2016 - Big Data and Society 3 (2).
    Recently, it has been argued that the use of Big Data transforms the sciences, making data-driven research possible and studying causality redundant. In this paper, I focus on the claim on causal knowledge by examining the Big Data project EXPOsOMICS, whose research is funded by the European Commission and considered capable of improving our understanding of the relation between exposure and disease. While EXPOsOMICS may seem the perfect exemplification of the data-driven view, I show how causal (...)
    Download  
     
    Export citation  
     
    Bookmark   10 citations  
  7. Clinical data wrangling using Ontological Realism and Referent Tracking.Werner Ceusters, Chiun Yu Hsu & Barry Smith - 2014 - In Ceusters Werner, Hsu Chiun Yu & Smith Barry (eds.), Proceedings of the Fifth International Conference on Biomedical Ontology (ICBO), Houston, 2014, (CEUR, 1327). pp. 27-32.
    Ontological realism aims at the development of high quality ontologies that faithfully represent what is general in reality and to use these ontologies to render heterogeneous data collections comparable. To achieve this second goal for clinical research datasets presupposes not merely (1) that the requisite ontologies already exist, but also (2) that the datasets in question are faithful to reality in the dual sense that (a) they denote only particulars and relationships between particulars that do in fact exist and (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  8. Big Data and Changing Concepts of the Human.Carrie Figdor - 2019 - European Review 27 (3):328-340.
    Big Data has the potential to enable unprecedentedly rigorous quantitative modeling of complex human social relationships and social structures. When such models are extended to nonhuman domains, they can undermine anthropocentric assumptions about the extent to which these relationships and structures are specifically human. Discoveries of relevant commonalities with nonhumans may not make us less human, but they promise to challenge fundamental views of what it is to be human.
    Download  
     
    Export citation  
     
    Bookmark  
  9. Data models, representation and adequacy-for-purpose.Alisa Bokulich & Wendy Parker - 2021 - European Journal for Philosophy of Science 11 (1):1-26.
    We critically engage two traditional views of scientific data and outline a novel philosophical view that we call the pragmatic-representational view of data. On the PR view, data are representations that are the product of a process of inquiry, and they should be evaluated in terms of their adequacy or fitness for particular purposes. Some important implications of the PR view for data assessment, related to misrepresentation, context-sensitivity, and complementary use, are highlighted. The PR view provides (...)
    Download  
     
    Export citation  
     
    Bookmark   19 citations  
  10. Sense-data and the philosophy of mind: Russell, James, and Mach.Gary Hatfield - 2002 - Principia 6 (2):203-230.
    The theory of knowledge in early twentieth-century Anglo American philosophy was oriented toward phenomenally described cognition. There was a healthy respect for the mind-body problem, which meant that phenomena in both the mental and physical domains were taken seriously. Bertrand Russell's developing position on sense-data and momentary particulars drew upon, and ultimately became like, the neutral monism of Ernst Mach and William James. Due to a more recent behaviorist and physicalist inspired "fear of the mental", this development has been (...)
    Download  
     
    Export citation  
     
    Bookmark   15 citations  
  11. A Theory of Sense-Data.Andrew Y. Lee - forthcoming - Analytic Philosophy.
    I develop and defend a sense-datum theory of perception. My theory follows the spirit of classic sense-datum theories: I argue that what it is to have a perceptual experience is to be acquainted with some sense-data, where sense-data are private particulars that have all the properties they appear to have, that are common to both perception and hallucination, that constitute the phenomenal characters of perceptual experiences, and that are analogous to pictures inside one’s head. But my theory also (...)
    Download  
     
    Export citation  
     
    Bookmark   2 citations  
  12. What is data ethics?Luciano Floridi & Mariarosaria Taddeo - 2016 - Philosophical Transactions of the Royal Society A 374 (2083):20160360.
    This theme issue has the founding ambition of landscaping Data Ethics as a new branch of ethics that studies and evaluates moral problems related to data (including generation, recording, curation, processing, dissemination, sharing, and use), algorithms (including AI, artificial agents, machine learning, and robots), and corresponding practices (including responsible innovation, programming, hacking, and professional codes), in order to formulate and support morally good solutions (e.g. right conducts or right values). Data Ethics builds on the foundation provided by (...)
    Download  
     
    Export citation  
     
    Bookmark   58 citations  
  13. Data Synthesis for Big Questions: From Animal Tracks to Ecological Models.Rose Trappes - 2024 - Philosophy, Theory, and Practice in Biology 16 (1):4.
    This paper addresses a relatively new mode of ecological research: data synthesis studies. Data synthesis studies involve reusing data to create a general model as well as a reusable, aggregated dataset. Using a case from movement ecology, I analyse the trade-offs and strategies involved in data synthesis. Like theoretical ecological modelling, I find that synthesis studies involve a modelling trade-off between generality, precision and realism; they deal with this trade-off by adopting a pragmatic kludging strategy. I (...)
    Download  
     
    Export citation  
     
    Bookmark  
  14. Data, Privacy, and the Individual.Carissa Véliz - 2020 - Center for the Governance of Change.
    The first few years of the 21st century were characterised by a progressive loss of privacy. Two phenomena converged to give rise to the data economy: the realisation that data trails from users interacting with technology could be used to develop personalised advertising, and a concern for security that led authorities to use such personal data for the purposes of intelligence and policing. In contrast to the early days of the data economy and internet surveillance, the (...)
    Download  
     
    Export citation  
     
    Bookmark   3 citations  
  15. Data quality, experimental artifacts, and the reactivity of the psychological subject matter.Uljana Feest - 2022 - European Journal for Philosophy of Science 12 (1):1-25.
    While the term “reactivity” has come to be associated with specific phenomena in the social sciences, having to do with subjects’ awareness of being studied, this paper takes a broader stance on this concept. I argue that reactivity is a ubiquitous feature of the psychological subject matter and that this fact is a precondition of experimental research, while also posing potential problems for the experimenter. The latter are connected to the worry about distorted data and experimental artifacts. But what (...)
    Download  
     
    Export citation  
     
    Bookmark   6 citations  
  16. OPTIMIZING DATA SCIENCE WORKFLOWS IN CLOUD COMPUTING.Tummalachervu Chaitanya Kanth - 2024 - Journal of Science Technology and Research (JSTAR) 4 (1):71-76.
    This paper explores the challenges and innovations in optimizing data science workflows within cloud computing environments. It begins by highlighting the critical role of data science in modern industries and the pivotal contribution of cloud computing in enabling scalable and efficient data processing. The primary focus lies in identifying and analyzing the key challenges encountered in current data science workflows deployed in cloud infrastructures. These challenges include scalability issues related to handling large volumes of data, (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  17. AI training data, model success likelihood, and informational entropy-based value.Quan-Hoang Vuong, Viet-Phuong La & Minh-Hoang Nguyen - manuscript
    Since the release of OpenAI's ChatGPT, the world has entered a race to develop more capable and powerful AI, including artificial general intelligence (AGI). The development is constrained by the dependency of AI on the model, quality, and quantity of training data, making the AI training process highly costly in terms of resources and environmental consequences. Thus, improving the effectiveness and efficiency of the AI training process is essential, especially when the Earth is approaching the climate tipping points and (...)
    Download  
     
    Export citation  
     
    Bookmark  
  18. Big Data Analytics in Healthcare: Exploring the Role of Machine Learning in Predicting Patient Outcomes and Improving Healthcare Delivery.Federico Del Giorgio Solfa & Fernando Rogelio Simonato - 2023 - International Journal of Computations Information and Manufacturing (Ijcim) 3 (1):1-9.
    Healthcare professionals decide wisely about personalized medicine, treatment plans, and resource allocation by utilizing big data analytics and machine learning. To guarantee that algorithmic recommendations are impartial and fair, however, ethical issues relating to prejudice and data privacy must be taken into account. Big data analytics and machine learning have a great potential to disrupt healthcare, and as these technologies continue to evolve, new opportunities to reform healthcare and enhance patient outcomes may arise. In order to investigate (...)
    Download  
     
    Export citation  
     
    Bookmark  
  19. Data Science and Mass Media: Seeking a Hermeneutic Ethics of Information.Christine James - 2015 - Proceedings of the Society for Phenomenology and Media, Vol. 15, 2014, Pages 49-58 15 (2014):49-58.
    In recent years, the growing academic field called “Data Science” has made many promises. On closer inspection, relatively few of these promises have come to fruition. A critique of Data Science from the phenomenological tradition can take many forms. This paper addresses the promise of “participation” in Data Science, taking inspiration from Paul Majkut’s 2000 work in Glimpse, “Empathy’s Impostor: Interactivity and Intersubjectivity,” and some insights from Heidegger’s "The Question Concerning Technology." The description of Data Science (...)
    Download  
     
    Export citation  
     
    Bookmark  
  20. Data subject rights as a research methodology: A systematic literature review.Adamu Adamu Habu & Tristan Henderson - 2023 - Journal of Responsible Technology 16 (C):100070.
    Data subject rights provide data controllers with obligations that can help with transparency, giving data subjects some control over their personal data. To date, a growing number of researchers have used these data subject rights as a methodology for data collection in research studies. No one, however, has gathered and analysed different academic research studies that use data subject rights as a methodology for data collection. To this end, we conducted a systematic (...)
    Download  
     
    Export citation  
     
    Bookmark  
  21. Data Mining in the Context of Legality, Privacy, and Ethics.Amos Okomayin, Tosin Ige & Abosede Kolade - 2023 - International Journal of Research and Innovation in Applied Science 10 (Vll):10-15.
    Data mining possess a significant threat to ethics, privacy, and legality, especially when we consider the fact that data mining makes it difficult for an individual or consumer (in the case of a company) to control accessibility and usage of his data. Individuals should be able to control how his/ her data in the data warehouse is being access and utilize while at the same time providing enabling environment which enforces legality, privacy and ethicality on (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  22. ADVANCE DATA SECURITY IN CLOUD NETWORK SYSTEMS.Tummalachervu Chaitanya Kanth - 2023 - Journal of Science Technology and Research (JSTAR) 4 (1):29-36.
    This research presents a novel and efficient public key cryptosystem known as the Enhanced Schmidt Samoa (ESS) cryptosystem, proposed to safeguard the data of a single owner in cloud computing environments. Data storage is a one-time process in the cloud, while data retrieval is a frequent operation. Experimental results demonstrate that the ESS cryptosystem offers robust data confidentiality in the cloud, surpassing the security provided by traditional cryptosystems. The research also introduces a secure cloud framework designed (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  23. Data Analytics in Higher Education: Key Concerns and Open Questions.Alan Rubel & Kyle M. L. Jones - 2017 - University of St. Thomas Journal of Law and Public Policy 1 (11):25-44.
    “Big Data” and data analytics affect all of us. Data collection, analysis, and use on a large scale is an important and growing part of commerce, governance, communication, law enforcement, security, finance, medicine, and research. And the theme of this symposium, “Individual and Informational Privacy in the Age of Big Data,” is expansive; we could have long and fruitful discussions about practices, laws, and concerns in any of these domains. But a big part of the audience (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  24. Big Data Ethics in Education and Research.Nicolae Sfetcu - 2023 - It and C 2 (3):26-35.
    Big data ethics involves adherence to the concepts of right and wrong behavior regarding data, especially personal data. Big Data ethics focuses on structured or unstructured data collectors and disseminators. Big data ethics is supported, at EU level, by extensive documentation, which seeks to find concrete solutions to maximize the value of big data without sacrificing fundamental human rights. The European Data Protection Supervisor (EDPS) supports the right to privacy and the right (...)
    Download  
     
    Export citation  
     
    Bookmark  
  25. Data management practices in Educational Research.Valentine Joseph Owan & Bassey Asuquo Bassey - 2019 - In P. N. Ololube & G. U. Nwiyi (eds.), Encyclopedia of institutional leadership, policy, and management: A handbook of research in honour of Professor Ozo-Mekuri Ndimele. pp. 1251-1265.
    Data is very important in any research experiment because it occupies a central place in making decisions based on findings resulting from the analysis of such data. Given its central role, it follows that such an important asset as data, deserve effective management in order to protect the integrity and provide an opportunity for effective problem-solving. The main thrust of this paper was to examine data management practices that should be adopted by scholars in maintaining the (...)
    Download  
     
    Export citation  
     
    Bookmark   7 citations  
  26. Data’ in the Royal Society's Philosophical Transactions, 1665–1886.Chris Meyns - 2019 - Notes and Records: The Royal Society Journal of the History of Science.
    Was there a concept of data before the so-called ‘data revolution’? This paper contributes to the history of the concept of data by investigating uses of the term ‘data’ in texts of the Royal Society's Philosophical Transactions for the period 1665–1886. It surveys how the notion enters the journal as a technical term in mathematics, and charts how over time it expands into various other scientific fields, including Earth sciences, physics and chemistry. The paper argues that (...)
    Download  
     
    Export citation  
     
    Bookmark  
  27. Using models to correct data: paleodiversity and the fossil record.Alisa Bokulich - 2018 - Synthese 198 (Suppl 24):5919-5940.
    Despite an enormous philosophical literature on models in science, surprisingly little has been written about data models and how they are constructed. In this paper, I examine the case of how paleodiversity data models are constructed from the fossil data. In particular, I show how paleontologists are using various model-based techniques to correct the data. Drawing on this research, I argue for the following related theses: first, the ‘purity’ of a data model is not a (...)
    Download  
     
    Export citation  
     
    Bookmark   29 citations  
  28.  91
    Efficient Data Center Management: Advanced SLA-Driven Load Balancing Solutions.M. Arul Selvan - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):368-376.
    In modern data centers, managing the distribution of workloads efficiently is crucial for ensuring optimal performance and meeting Service Level Agreements (SLAs). Load balancing algorithms play a vital role in this process by distributing workloads across computing resources to avoid overloading any single resource. However, the effectiveness of these algorithms can be significantly enhanced through the integration of advanced optimization techniques. This paper proposes an SLA-driven load balancing algorithm optimized using methods such as genetic algorithms, particle swarm optimization, and (...)
    Download  
     
    Export citation  
     
    Bookmark  
  29. Data and the Good?Daniel Susser - 2022 - Surveillance and Society 20 (3):297-301.
    Surveillance studies scholars and privacy scholars have each developed sophisticated, important critiques of the existing data-driven order. But too few scholars in either tradition have put forward alternative substantive conceptions of a good digital society. This, I argue, is a crucial omission. Unless we construct new “sociotechnical imaginaries,” new understandings of the goals and aspirations digital technologies should aim to achieve, the most surveillance studies and privacy scholars can hope to accomplish is a less unjust version of the technology (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  30. Retractions Data Mining #1.Quan-Hoang Vuong & Viet-Phuong La - 2019 - Open Science Framework 2019 (2):1-3.
    Motivation: • Breaking barriers in publishing demands a proactive attitude • Open data, open review and open dialogue in making social sciences plausible .
    Download  
     
    Export citation  
     
    Bookmark  
  31. Reframing data ethics in research methods education: a pathway to critical data literacy.Javiera Atenas, Leo Havemann & Cristian Timmermann - 2023 - International Journal of Educational Technology in Higher Education 20:11.
    This paper presents an ethical framework designed to support the development of critical data literacy for research methods courses and data training programmes in higher education. The framework we present draws upon our reviews of literature, course syllabi and existing frameworks on data ethics. For this research we reviewed 250 research methods syllabi from across the disciplines, as well as 80 syllabi from data science programmes to understand how or if data ethics was taught. We (...)
    Download  
     
    Export citation  
     
    Bookmark  
  32. When data drive health: an archaeology of medical records technology.Colin Koopman, Paul D. G. Showler, Patrick Jones, Mary McLevey & Valerie Simon - 2022 - Biosocieties 17 (4):782-804.
    Medicine is often thought of as a science of the body, but it is also a science of data. In some contexts, it can even be asserted that data drive health. This article focuses on a key piece of data technology central to contemporary practices of medicine: the medical record. By situating the medical record in the perspective of its history, we inquire into how the kinds of data that are kept at sites of clinical encounter (...)
    Download  
     
    Export citation  
     
    Bookmark  
  33.  87
    Optimizing Data Center Operations with Enhanced SLA-Driven Load Balancing".S. Yoheswari - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):368-376.
    The research introduces a novel framework that incorporates real-time monitoring, dynamic resource allocation, and adaptive threshold settings to ensure consistent SLA adherence while optimizing computing performance. Extensive simulations are conducted using synthetic and real-world datasets to evaluate the performance of the proposed algorithm. The results demonstrate that the optimized load balancing approach outperforms traditional algorithms in terms of SLA compliance, resource utilization, and energy efficiency. The findings suggest that the integration of optimization techniques into load balancing algorithms can significantly enhance (...)
    Download  
     
    Export citation  
     
    Bookmark  
  34. Big Data: truth, quasi-truth or post-truth?Ricardo Peraça Cavassane & M. Loffredo D'ottaviano Itala - 2020 - Acta Scientiarum. Human and Social Sciences 42 (3):1-7.
    In this paper we investigate if sentences presented as the result of the application of statistical models and artificial intelligence to large volumes of data – the so-called ‘Big Data’ – can be characterized as semantically true, or as quasi-true, or even if such sentences can only be characterized as probably quasi-false and, in a certain way, post-true; that is, if, in the context of Big Data, the representation of a data domain can be configured as (...)
    Download  
     
    Export citation  
     
    Bookmark  
  35. Sense-data and the mind–body problem.Gary Hatfield - 2004 - In Ralph Schumacher (ed.), Perception and Reality: From Descartes to the Present. Mentis. pp. 305--331.
    The first two sections of the paper characterize the nineteenth century respect for the phenomenal by considering Helmholtz’s position and James’ and Russell’s move to neutral monism. The third section displays a moment’s sympathy with those who recoiled from the latter view -- but only a moment’s. The recoil overshot what was a reasonable response, and denied the reality of the phenomenal, largely in the name of the physical or the material. The final two sections of the paper develop a (...)
    Download  
     
    Export citation  
     
    Bookmark   12 citations  
  36. The Sense-Data Language and External World Skepticism.Jared Warren - 2024 - In Uriah Kriegel (ed.), Oxford Studies in Philosophy of Mind Vol 4. Oxford University Press.
    We face reality presented with the data of conscious experience and nothing else. The project of early modern philosophy was to build a complete theory of the world from this starting point, with no cheating. Crucial to this starting point is the data of conscious sensory experience – sense data. Attempts to avoid this project often argue that the very idea of sense data is confused. But the sense-data way of talking, the sense-data language, (...)
    Download  
     
    Export citation  
     
    Bookmark   1 citation  
  37. Reconciling Data Actionability and Accountability in Global Health Research.Nathanael Sheehan & Sabina Leonelli - manuscript
    All too often, the requirements for actionability and accountability of data infrastructures are conceptualised as incompatible and leading to a trade-off situation where increasing one will unavoidably decrease the other. Through a comparative analysis of two data infrastructures used to share genomic data about the SARS-COV-2 virus, we argue that making data actionable for knowledge development involves a commitment to ensuring that the data in question are representative of the phenomena being studied and accountable to (...)
    Download  
     
    Export citation  
     
    Bookmark  
  38. Critical Provocations for Synthetic Data.Daniel Susser & Jeremy Seeman - 2024 - Surveillance and Society 22 (4):453-459.
    Training artificial intelligence (AI) systems requires vast quantities of data, and AI developers face a variety of barriers to accessing the information they need. Synthetic data has captured researchers’ and industry’s imagination as a potential solution to this problem. While some of the enthusiasm for synthetic data may be warranted, in this short paper we offer critical counterweight to simplistic narratives that position synthetic data as a cost-free solution to every data-access challenge—provocations highlighting ethical, political, (...)
    Download  
     
    Export citation  
     
    Bookmark  
  39. Why Data Privacy is Key To a Smart Energy Future.Carissa Véliz & Philipp Grunewald - 2018 - Nature Energy 3:702-704.
    The ability to collect fine-grained energy data from smart meters has benefits for utilities and consumers. However, a proactive approach to data privacy is necessary to maximize the potential of these data to support low-carbon energy systems, and innovative business models.
    Download  
     
    Export citation  
     
    Bookmark  
  40.  90
    A Data Collection for Studying What Makes Readers love a fiction book?Minh-Hoang Nguyen, Ni Putu Wulan Purnama Sari, Minh-Phuong Thi Duong, ManhTung Ho, Thi Mai Anh Tran, Dan Li, Phuong-Tri Nguyen, Hong-Hoa Thi Nguyen & Viet-Phuong La - 2025
    This data collection comprises of Amazon reviews of the book titled “Wild Wise Weird.” These reviews will be analyzed and updated to identify factors driving people to love a fiction book. Wild Wise Weird is a collection of 42 fables that blends traditional storytelling with modern sensibilities, weaving together life lessons, humor, and social commentary.
    Download  
     
    Export citation  
     
    Bookmark  
  41. Data and Afrofuturism: an emancipated subject?Aisha Paulina Lami Kadiri - 2021 - Internet Policy Review 10 (4):1-26.
    The concept of an individual, liberal data subject, who was traditionally at the centre of data protection efforts has recently come under scrutiny. At the same time, the particularly destructive effect of digital technology on Black people establishes the need for an analysis that not only considers but brings racial dimensions to the forefront. I argue that because Afrofuturism situates the Black struggle in persistent, yet continuously changing structural disparities and power relations, it offers a powerful departure point (...)
    Download  
     
    Export citation  
     
    Bookmark  
  42. How Data Governance Principles Influence Participation in Biodiversity Science.Beckett Sterner & Steve Elliott - 2023 - Science as Culture.
    Biodiversity science is in a pivotal period when diverse groups of actors—including researchers, businesses, national governments, and Indigenous Peoples—are negotiating wide-ranging norms for governing and managing biodiversity data in digital repositories. These repositories, often called biodiversity data portals, are a type of organization for which governance can address or perpetuate the colonial history of biodiversity science and current inequities. Researchers and Indigenous Peoples are developing and implementing new strategies to examine and change assumptions about which agents should count (...)
    Download  
     
    Export citation  
     
    Bookmark  
  43. Data and Safety Monitoring Board and the Ratio Decidendi of the Trial.Roger Stanev - 2015 - Journal of Philosophy, Science and Law 15:1-26.
    Decision-making by a Data and Safety Monitoring Board (DSMB) regarding clinical trial conduct and termination is intricate and largely limited by cases and rules. Decision-making by legal jury is also intricate and largely constrained by cases and rules. In this paper, I argue by analogy that legal decision-making, which strives for a balance between competing demands of conservatism and innovation, supplies a good basis to the logic behind DSMB decision-making. Using the doctrine of precedents in legal reasoning as my (...)
    Download  
     
    Export citation  
     
    Bookmark  
  44. Classificatory Theory in Data-intensive Science: The Case of Open Biomedical Ontologies.Sabina Leonelli - 2012 - International Studies in the Philosophy of Science 26 (1):47 - 65.
    Knowledge-making practices in biology are being strongly affected by the availability of data on an unprecedented scale, the insistence on systemic approaches and growing reliance on bioinformatics and digital infrastructures. What role does theory play within data-intensive science, and what does that tell us about scientific theories in general? To answer these questions, I focus on Open Biomedical Ontologies, digital classification tools that have become crucial to sharing results across research contexts in the biological and biomedical sciences, and (...)
    Download  
     
    Export citation  
     
    Bookmark   27 citations  
  45. From data to semantic information.Luciano Floridi - 2003 - Entropy 5:125–145.
    There is no consensus yet on the definition of semantic information. This paper contributes to the current debate by criticising and revising the Standard Definition of semantic Information as meaningful data, in favour of the Dretske-Grice approach: meaningful and well-formed data constitute semantic information only if they also qualify as contingently truthful. After a brief introduction, SDI is criticised for providing necessary but insufficient conditions for the definition of semantic information. SDI is incorrect because truth-values do not supervene (...)
    Download  
     
    Export citation  
     
    Bookmark   3 citations  
  46. Big Data Ethics.Nicolae Sfetcu - manuscript
    Big Data ethics involves adherence to the concepts of right and wrong behavior regarding data, especially personal data. Big Data ethics focuses on structured or unstructured data collectors and disseminators. Big Data ethics is supported, at EU level, by extensive documentation, which seeks to find concrete solutions to maximize the value of Big Data without sacrificing fundamental human rights. The European Data Protection Supervisor (EDPS) supports the right to privacy and the right (...)
    Download  
     
    Export citation  
     
    Bookmark  
  47. Big Data - Aspecte filosofice.Nicolae Sfetcu - manuscript
    Big Data poate genera, prin inferențe, noi cunoașteri și perspective. Paradigma care rezultă din utilizarea Big Data generează noi oportunități. Un motiv de îngrijorare majoră în cazul Big Data se datorează faptului că oamenii de știință de date tind să lucreze cu date despre subiectele pe care nu le cunosc și cu care nu au fost niciodată în contact, fiind înstrăinați de produsul final al activității lor (aplicarea analizelor). Un studiu recent afirmă că ceasta poate fi motivul (...)
    Download  
     
    Export citation  
     
    Bookmark  
  48. Asking about data: exploring different realities of data via the social data flow network methodology.Brian Ballsun-Stanton - unknown
    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 (...)
    Download  
     
    Export citation  
     
    Bookmark  
  49. Big Data technology.Nicolae Sfetcu - manuscript
    Big Data must be processed with advanced collection and analysis tools, based on predetermined algorithms, in order to obtain relevant information. Algorithms must also take into account invisible aspects for direct perceptions. Big Data issues is multi-layered. A distributed parallel architecture distributes data on multiple servers (parallel execution environments) thus dramatically improving data processing speeds. Big Data provides an infrastructure that allows for highlighting uncertainties, performance, and availability of components. DOI: 10.13140/RG.2.2.12784.00004 .
    Download  
     
    Export citation  
     
    Bookmark  
  50. Taxonomy for Humans or Computers? Cognitive Pragmatics for Big Data.Beckett Sterner & Nico M. Franz - 2017 - Biological Theory 12 (2):99-111.
    Criticism of big data has focused on showing that more is not necessarily better, in the sense that data may lose their value when taken out of context and aggregated together. The next step is to incorporate an awareness of pitfalls for aggregation into the design of data infrastructure and institutions. A common strategy minimizes aggregation errors by increasing the precision of our conventions for identifying and classifying data. As a counterpoint, we argue that there are (...)
    Download  
     
    Export citation  
     
    Bookmark   4 citations  
1 — 50 / 966