Results for 'data'

999 found
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  1.  74
    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.
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  2. The 1 law of "absolute reality"." ~, , Data", , ", , Value", , = O. &Gt, Being", & Human - manuscript
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  3. Open data, open review and open dialogue in making social sciences plausible.Quan-Hoang Vuong - 2017 - Nature: Scientific Data Updates 2017.
    Nowadays, protecting trust in social sciences also means engaging in open community dialogue, which helps to safeguard robustness and improve efficiency of research methods. The combination of open data, open review and open dialogue may sound simple but implementation in the real world will not be straightforward. However, in view of Begley and Ellis’s (2012) statement that, “the scientific process demands the highest standards of quality, ethics and rigour,” they are worth implementing. More importantly, they are feasible to work (...)
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  4. Open data, open review and open dialogue in making social sciences plausible.Quan-Hoang Vuong - 2017 - Scientific Data 4.
    A growing awareness of the lack of reproducibility has undermined society’s trust and esteem in social sciences. In some cases, well-known results have been fabricated or the underlying data have turned out to have weak technical foundations.
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  5. 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 (...)
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  6. Big Data and Changing Concepts of the Human.Carrie Figdor - 2019 - European Review 27 (3):328-340.
    Big Data has the potential to enable unprecedentedly rigorous quantitative modeling of complex human social relationships and social structures. When such models are extended to nonhuman domains, they can undermine anthropocentric assumptions about the extent to which these relationships and structures are specifically human. Discoveries of relevant commonalities with nonhumans may not make us less human, but they promise to challenge fundamental views of what it is to be human.
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  7. 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 (...)
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  8. 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 (...)
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  9. What is data ethics?Luciano Floridi & Mariarosaria Taddeo - 2016 - Philosophical Transactions of the Royal Society A 374 (2083).
    This theme issue has the founding ambition of landscaping Data Ethics as a new branch of ethics that studies and evaluates moral problems related to data (including generation, recording, curation, processing, dissemination, sharing, and use), algorithms (including AI, artificial agents, machine learning, and robots), and corresponding practices (including responsible innovation, programming, hacking, and professional codes), in order to formulate and support morally good solutions (e.g. right conducts or right values). Data Ethics builds on the foundation provided by (...)
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  10. Data.Luciano Floridi - 2008 - In William A. Darity (ed.), International Encyclopedia of the Social Sciences.
    The word data (sing. datum) is originally Latin for “things given or granted”. Because of such a humble and generic meaning, the term enjoys considerable latitude both in its technical and in its common usage, for almost anything can be referred to as a “thing given or granted” (Cherry [1978]). With some reasonable approximation, four principal interpretations may be identified in the literature. The first three captures part of the nature of the concept and are discussed in the next (...)
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  11. 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 .
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  12. 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 (...)
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  13. Big Data Analytics and How to Buy an Election.Jakob Mainz, Rasmus Uhrenfeldt & Jorn Sonderholm - 2021 - Public Affairs Quarterly 32 (2):119-139.
    In this article, we show how it is possible to lawfully buy an election. The method we describe for buying an election is novel. The key things that make it possible to buy an election are the existence of public voter registration lists where one can see whether a given elector has voted in a particular election, and the existence of Big Data Analytics that with a high degree of accuracy can predict what a given elector will vote in (...)
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  14. 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 (...)
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  15. Data frauds, health risks, and the growing question of ethics during the COVID-19 pandemic.Vuong Quan-Hoang, Le Tam-Tri & Nguyen Minh-Hoang - manuscript
    In this essay, we advocate that the issue of health data ethics should no longer be considered on the level of individual scientists or research labs, but rather as a problem involving all stakeholders, from publishers, funders, ethical committees to governments, for the sake of research integrity.
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  16. 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 (...)
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  17. Data management practices and educational research effectiveness of university lecturers in South-South Nigeria.Valentine Joseph Owan, Francisca Nonyelum Odigwe & Bassey Asuquo Bassey - 2020 - Journal of Educational and Social Research 10 (3):24-34.
    The existing body of knowledge has witnessed gaps arising from the paucity of research literature on the quality of educational research output in higher education. This study shows how the management of data in higher education affects the quality of academic research conducted by university lecturers in South-South Nigeria. A sample of 602 lecturers were accessed during data collection and responded to two questionnaires (Data Management Practices Questionnaire – DMPQ and "Educational Research Effectiveness Questionnaire – EREQ). Multiple (...)
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  18. Cloud Data Security Using Elliptic Curve Cryptography.Arockia Panimalars, N. Dharani, R. Aiswarya & Pavithra Shailesh - 2017 - International Research Journal of Engineering and Technology 9 (4).
    Data security is, protecting data from ill- conceived get to, utilize, introduction, intrusion, change, examination, recording or destruction. Cloud computing is a sort of Internet-based computing that grants conjoint PC handling resources and information to PCs what's more, different gadgets according to necessity. It is a model that empowers universal, on-request access to a mutual pool of configurable computing resources. At present, security has been viewed as one of the best issues in the improvement of Cloud Computing. The (...)
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  19. Data models, representation and adequacy-for-purpose.Alisa Bokulich & Wendy Parker - 2021 - European Journal for Philosophy of Science 11 (1):1-26.
    We critically engage two traditional views of scientific data and outline a novel philosophical view that we call the pragmatic-representational view of data. On the PR view, data are representations that are the product of a process of inquiry, and they should be evaluated in terms of their adequacy or fitness for particular purposes. Some important implications of the PR view for data assessment, related to misrepresentation, context-sensitivity, and complementary use, are highlighted. The PR view provides (...)
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  20. 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. Port Harcourt, Nigeria: 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 (...)
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  21. Clinical data wrangling using Ontological Realism and Referent Tracking.Werner Ceusters, Chiun Yu Hsu & Barry Smith - 2014 - In 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 (...)
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  22. Data Mining the Brain to Decode the Mind.Daniel Weiskopf - forthcoming - In Neural Mechanisms: New Challenges in the Philosophy of Neuroscience.
    In recent years, neuroscience has begun to transform itself into a “big data” enterprise with the importation of computational and statistical techniques from machine learning and informatics. In addition to their translational applications such as brain-computer interfaces and early diagnosis of neuropathology, these tools promise to advance new solutions to longstanding theoretical quandaries. Here I critically assess whether these promises will pay off, focusing on the application of multivariate pattern analysis (MVPA) to the problem of reverse inference. I argue (...)
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  23. ICTs, data and vulnerable people: a guide for citizens.Alexandra Castańeda, Andreas Matheus, Andrzej Klimczuk, Anna BertiSuman, Annelies Duerinckx, Christoforos Pavlakis, Corelia Baibarac-Duignan, Elisabetta Broglio, Federico Caruso, Gefion Thuermer, Helen Feord, Janice Asine, Jaume Piera, Karen Soacha, Katerina Zourou, Katherin Wagenknecht, Katrin Vohland, Linda Freyburg, Marcel Leppée, Marta CamaraOliveira, Mieke Sterken & Tim Woods - 2021 - Bilbao: Upv-Ehu.
    ICTs, personal data, digital rights, the GDPR, data privacy, online security… these terms, and the concepts behind them, are increasingly common in our lives. Some of us may be familiar with them, but others are less aware of the growing role of ICTs and data in our lives - and the potential risks this creates. These risks are even more pronounced for vulnerable groups in society. People can be vulnerable in different, often overlapping, ways, which place them (...)
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  24. 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 (...)
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  25. 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 (...)
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  26. 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 (...)
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  27. 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.
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  28. 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 (...)
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  29. Big Data, Scientific Research and Philosophy.Giovanni Landi - 2020 - Www.Intelligenzaartificialecomefilosofia.Com.
    What is the epistemological status of Big Data? Is there really place for them in a scientific search for new empirical laws?
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  30. Big Data Analytics in Project Management: A Key to Success.Tareq Obaid & Samy S. Abu-Naser - 2023 - International Journal of Academic Engineering Research (IJAER) 7 (7):1-8.
    This review delves into the influence of big data analytics on project management effectiveness and project success rates. By examining applications, accomplishments, hindrances, and emerging developments in the context of big data analytics and project management, this review provides insights into its transformative potential. Results indicate that big data analytics fosters improved project performance, more robust risk management, and heightened adaptability. However, challenges related to data quality, privacy, and project manager training remain to be addressed. This (...)
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  31. 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 (...)
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  32.  79
    Big Data and the Emergence of Zemblanity and Self-Fulfilling Prophecies.Ricardo Peraça Cavassane, Itala M. Loffredo D'Ottaviano & Felipe Sobreira Abrahão - manuscript
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  33. 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:1-12.
    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)
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  34. 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 (...)
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  35. 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 (...)
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  36. 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.
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  37. 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 (...)
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  38.  89
    Data, Representation, and Evidential Values in Biology.Jinyeong Gim - 2023 - Korean Journal for the Philosophy of Science 26 (2):31-58.
    Leonelli (2016) suggested a relational view of data against a representational view by emphasizing data-centric biology rather than the theory-centric tradition in the philosophy of science. This is because the first view allows for data journeys across laboratories using public database resources, whereas the second does not. This paper examines Leonelli’s strategies to defend the relational view of data. Contrary to Leonelli’s intention, it indicates that her strategies led to unnecessary misunderstandings of the relationships among (...), representation, and evidential values. It will be argued that evidential values of data are inevitably based on a representational feature and that it is better to reconcile both views of data as complementary rather than contrasting. (shrink)
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  39. 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 (...)
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  40.  53
    Secure and Scalable Data Mining Technique over a Restful Web Services.Solar Francesco & Oliver Smith - forthcoming - International Journal of Research and Innovation in Applied Science.
    Scalability, efficiency, and security had been a persistent problem over the years in data mining, several techniques had been proposed and implemented but none had been able to solve the problem of scalability, efficiency and security from cloud computing. In this research, we solve the problem scalability, efficiency and security in data mining over cloud computing by using a restful web services and combination of different technologies and tools, our model was trained by using different machine learning algorithm, (...)
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  41. 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 (...)
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  42. 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 (...)
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  43. 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 .
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  44. Big Data and the Emergence of Zemblanity and Self-Fulfilling Prophecies.Ricardo Peraça Cavassane, Felipe S. Abrahão & Itala M. L. D'Ottaviano - manuscript
    In this paper, we argue that both zemblanity and self-fulfilling prophecy may emerge from the application of Big Data models in society due to the presence of feedback loops.
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  45.  98
    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 (...)
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  46. Research Data Preservation Practices of Library and Information Science Faculties.A. Subaveerapandiyan & Anuradha Maurya - 2022 - Defence Journal of Library and Information Science Technology 42 (4):259-264.
    Digitisation of research data is widely increasing all around the world because it needs more and development of enormous digital technologies. Data curation services are starting to offer many libraries. Research data curation is the collective invaluable and reusable information of the researchers. Collected data preservation is more important. The majority of the higher education institutes preserved the research data for their students and researchers. It is stored for a long time using various formats. It (...)
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  47. Big Data - Aspects philosophiques.Nicolae Sfetcu - manuscript
    Le big data peut générer, par inférences, de nouvelles connaissances et perspectives. Le paradigme qui résulte de l'utilisation du big data crée de nouvelles opportunités. L'une des principales préoccupations dans le cas du big data est que les scientifiques des données ont tendance à travailler avec des données sur des sujets qu'ils ne connaissent pas et n'ont jamais été en contact, étant éloignés du produit final de leur activité (l'application des analyses). Une étude récente (Tanner 2014) indique (...)
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  48. Microethics for healthcare data science: attention to capabilities in sociotechnical systems.Mark Graves & Emanuele Ratti - 2021 - The Future of Science and Ethics 6:64-73.
    It has been argued that ethical frameworks for data science often fail to foster ethical behavior, and they can be difficult to implement due to their vague and ambiguous nature. In order to overcome these limitations of current ethical frameworks, we propose to integrate the analysis of the connections between technical choices and sociocultural factors into the data science process, and show how these connections have consequences for what data subjects can do, accomplish, and be. Using healthcare (...)
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  49. ITS for Data Manipulation Language (DML) Commands Using SQLite.Mahmoud Jamal Abu Ghali & Samy S. Abu-Naser - 2019 - International Journal of Engineering and Information Systems (IJEAIS) 3 (3):57-92.
    In many areas, technology has facilitated many things, diagnosing diseases, regulating traffic and teaching students in schools rely on Intelligent systems to name a few. At present, traditional classroom-based education is no longer the most appropriate in schools. From here, the idea of intelligent e-learning for students to increase their culture and keep them updated in life began. E-learning has become an ideal solution, relying on artificial intelligence, which has a footprint in this through the development of systems based on (...)
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  50. Big Data.Nicolae Sfetcu - manuscript
    Termenul Big Data se referă la extragerea, manipularea și analiza unor seturi de date care sunt prea mari pentru a fi tratate în mod obișnuit. Din această cauză se utilizează software special și, în multe cazuri, și calculatoare și echipamente hardware special dedicate. În general la aceste date analiza se face statistic. Pe baza analizei datelor respective se fac de obicei predicții ale unor grupuri de persoane sau alte entități, pe baza comportamentului acestora în diverse situații și folosind tehnici (...)
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