Results for 'Big Data'

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  1. 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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  2. 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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  3.  32
    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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  4.  20
    Big Data Analytics and How to Buy an Election.Jakob Mainz, Jørn Sønderholm & Rasmus Uhrenfeldt - 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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  5. 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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  6. Etica Big Data în cercetare.Nicolae Sfetcu - manuscript
    Principalele probleme cu care se confruntă oamenii de știință în lucrul cu seturile mari de date (Big Data), evidențiind principale aspecte etice, luând în considerare inclusiv legislația din Uniunea Europeană. După o scurtă Introducere despre Big Data, secțiunea Tehnologia prezintă aplicațiile specifice în cercetare. Urmează o abordare a principalelor probleme filosofice specifice în Aspecte filosofice, și Aspecte legale cu evidențierea problemelor etice specifice din Regulamentul UE privind protecția datelor 2016/679 (General Data Protection Regulation, "GDPR"). Secțiunea Probleme etice (...)
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  7. 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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  8.  78
    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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  9.  75
    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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  10.  50
    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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  11.  56
    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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  12. Big Data Ethics in Research.Nicolae Sfetcu - manuscript
    The main problems faced by scientists in working with Big Data sets, highlighting the main ethical issues, taking into account the legislation of the European Union. After a brief Introduction to Big Data, the Technology section presents specific research applications. There is an approach to the main philosophical issues in Philosophical Aspects, and Legal Aspects with specific ethical issues in the EU Regulation on the protection of natural persons with regard to the processing of personal data and (...)
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  13.  70
    Procesarea Big Data.Nicolae Sfetcu - manuscript
    Datele trebuie procesate cu instrumente avansate de colectare și analiză, pe baza unor algoritmi prestabiliți, pentru a putea obține informații relevante. Algoritmii trebuie să ia în considerare și aspecte invizibile pentru percepțiile directe. Big Data în procesele guvernamentale cresc eficiența costurilor, productivitatea și inovația. Registrele civile sunt o sursă pentru Big Data. Datele prelucrate ajută în domenii critice de dezvoltare, cum ar fi îngrijirea sănătății, ocuparea forței de muncă, productivitatea economică, criminalitatea, securitatea și gestionarea dezastrelor naturale și a (...)
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  14. Big Data.Nicolae Sfetcu - 2019 - Drobeta Turnu Severin: MultiMedia Publishing.
    Odată cu creșterea volumului de date pe Internet, în media socială, cloud computing, dispozitive mobile și date guvernamentale, Big Data devine în același timp o amenințare și o oportunitate în ceea ce privește gestionarea și utilizarea acestor date, menținând în același timp drepturile persoanelor implicate. În fiecare zi, folosim și generăm tone de date, alimentând bazele de date ale agențiilor guvernamentale, companiilor private și chiar cetățenilor privați. Beneficiem în multe feluri de existența și utilizarea Big Data, dar trebuie (...)
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  15.  36
    Occam's Razor For Big Data?Birgitta Dresp-Langley - 2019 - Applied Sciences 3065 (9):1-28.
    Detecting quality in large unstructured datasets requires capacities far beyond the limits of human perception and communicability and, as a result, there is an emerging trend towards increasingly complex analytic solutions in data science to cope with this problem. This new trend towards analytic complexity represents a severe challenge for the principle of parsimony (Occam’s razor) in science. This review article combines insight from various domains such as physics, computational science, data engineering, and cognitive science to review the (...)
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  16. Medical Privacy and Big Data: A Further Reason in Favour of Public Universal Healthcare Coverage.Carissa Véliz - 2019 - In T. C. de Campos, J. Herring & A. M. Phillips (eds.), Philosophical Foundations of Medical Law. Oxford, U.K.: Oxford University Press. pp. 306-318.
    Most people are completely oblivious to the danger that their medical data undergoes as soon as it goes out into the burgeoning world of big data. Medical data is financially valuable, and your sensitive data may be shared or sold by doctors, hospitals, clinical laboratories, and pharmacies—without your knowledge or consent. Medical data can also be found in your browsing history, the smartphone applications you use, data from wearables, your shopping list, and more. At (...)
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  17. Cloud Computing and Big Data for Oil and Gas Industry Application in China.Yang Zhifeng, Feng Xuehui, Han Fei, Yuan Qi, Cao Zhen & Zhang Yidan - 2019 - Journal of Computers 1.
    The oil and gas industry is a complex data-driven industry with compute-intensive, data-intensive and business-intensive features. Cloud computing and big data have a broad application prospect in the oil and gas industry. This research aims to highlight the cloud computing and big data issues and challenges from the informatization in oil and gas industry. In this paper, the distributed cloud storage architecture and its applications for seismic data of oil and gas industry are focused on (...)
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  18.  64
    Philosophical Aspects of Big Data.Nicolae Sfetcu - manuscript
    Big Data can generate, through inferences, new knowledge and perspectives. The paradigm that results from using Big Data creates new opportunities. Big Data has great influence at the governmental level, positively affecting society. These systems can be made more efficient by applying transparency and open governance policies, such as Open Data. After developing predictive models for target audience behavior, Big Data can be used to generate early warnings for various situations. There is thus a positive (...)
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  19. Big Data Optimization in Machine Learning.Xiaocheng Tang - 2015 - Disertation 1.
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  20. An Ethics Framework for Big Data in Health and Research.Vicki Xafis, G. Owen Schaefer, Markus K. Labude, Iain Brassington, Angela Ballantyne, Hannah Yeefen Lim, Wendy Lipworth, Tamra Lysaght, Cameron Stewart, Shirley Sun, Graeme T. Laurie & E. Shyong Tai - 2019 - Asian Bioethics Review 11 (3):227-254.
    Ethical decision-making frameworks assist in identifying the issues at stake in a particular setting and thinking through, in a methodical manner, the ethical issues that require consideration as well as the values that need to be considered and promoted. Decisions made about the use, sharing, and re-use of big data are complex and laden with values. This paper sets out an Ethics Framework for Big Data in Health and Research developed by a working group convened by the Science, (...)
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  21. Improving Bayesian Statistics Understanding in the Age of Big Data with the Bayesvl R Package.Quan-Hoang Vuong, Viet-Phuong La, Minh-Hoang Nguyen, Manh-Toan Ho, Manh-Tung Ho & Peter Mantello - 2020 - Software Impacts 4 (1):100016.
    The exponential growth of social data both in volume and complexity has increasingly exposed many of the shortcomings of the conventional frequentist approach to statistics. The scientific community has called for careful usage of the approach and its inference. Meanwhile, the alternative method, Bayesian statistics, still faces considerable barriers toward a more widespread application. The bayesvl R package is an open program, designed for implementing Bayesian modeling and analysis using the Stan language’s no-U-turn (NUTS) sampler. The package combines the (...)
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  22. Precision Medicine and Big Data: The Application of an Ethics Framework for Big Data in Health and Research.G. Owen Schaefer, E. Shyong Tai & Shirley Sun - 2019 - Asian Bioethics Review 11 (3):275-288.
    As opposed to a ‘one size fits all’ approach, precision medicine uses relevant biological, medical, behavioural and environmental information about a person to further personalize their healthcare. This could mean better prediction of someone’s disease risk and more effective diagnosis and treatment if they have a condition. Big data allows for far more precision and tailoring than was ever before possible by linking together diverse datasets to reveal hitherto-unknown correlations and causal pathways. But it also raises ethical issues relating (...)
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  23. Legal Aspects of Big Data - GDPR.Nicolae Sfetcu - manuscript
    The use of Big Data presents significant legal problems, especially in terms of data protection. The existing legal framework of the European Union based in particular on the Directive no. 46/95/EC and the General Regulation on the Protection of Personal Data provide adequate protection. But for Big Data, a comprehensive and global strategy is needed. The evolution over time was from the right to exclude others to the right to control their own data and, at (...)
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  24.  59
    La technologie des mégadonnées (big data).Nicolae Sfetcu - manuscript
    Le terme big data désigne l'extraction, la manipulation et l'analyse des ensembles de données trop volumineux pour être traités de manière routinière. Pour cette raison, des logiciels spéciaux sont utilisés et, dans de nombreux cas, des ordinateurs et du matériel informatiques dédiés. Généralement, ces données sont analysées de manière statistique. Les données doivent être traitées avec des outils de collecte et d'analyse avancés, basés sur des algorithmes prédéterminés, afin d'obtenir des informations pertinentes. Les algorithmes doivent également prendre en compte (...)
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  25. Ethics of Identity in the Time of Big Data.James Brusseau - 2019 - First Monday 24 (5-6):00-11.
    Compartmentalizing our distinct personal identities is increasingly difficult in big data reality. Pictures of the person we were on past vacations resurface in employers’ Google searches; LinkedIn which exhibits our income level is increasingly used as a dating web site. Whether on vacation, at work, or seeking romance, our digital selves stream together. One result is that a perennial ethical question about personal identity has spilled out of philosophy departments and into the real world. Ought we possess one, unified (...)
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  26. L’éthique des mégadonnées (Big Data) en recherche.Nicolae Sfetcu - 2020 - Drobeta Turnu Severin: MultiMedia Publishing.
    Les principaux problèmes rencontrés par les scientifiques qui travaillent avec des ensembles de données massives (mégadonnées, Big Data), en soulignant les principaux problèmes éthiques, tout en tenant compte de la législation de l'Union européenne. Après une brève Introduction au Big Data, la section Technologie présente les applications spécifiques de la recherche. Il suit une approche des principales questions philosophiques spécifiques dans Aspects philosophiques, et Aspects juridiques en soulignant les problèmes éthiques spécifiques du règlement de l'UE sur la protection (...)
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  27. The Fate of Explanatory Reasoning in the Age of Big Data.Frank Cabrera - 2021 - Philosophy and Technology 34 (4):645-665.
    In this paper, I critically evaluate several related, provocative claims made by proponents of data-intensive science and “Big Data” which bear on scientific methodology, especially the claim that scientists will soon no longer have any use for familiar concepts like causation and explanation. After introducing the issue, in Section 2, I elaborate on the alleged changes to scientific method that feature prominently in discussions of Big Data. In Section 3, I argue that these methodological claims are in (...)
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  28. Status of Big Data In Internet of Things: A Comprehensive Overview.Peter Alphonce & Lusekelo Kibona - 2018 - International Journal of Academic Multidisciplinary Research (IJAMR) 2 (3):5-9.
    Abstract: Reports suggests that total amount of data generated everyday reaches 2.5 quintillion bytes [9], annual global IP traffic run rate in 2016 was 1.2 zettabytes and will reach 3.3 zettabytes by 2021 [12]. According to Gartner [25], Internet of Things excluding personal computers, tablets and smartphones will grow to 26 billion units of installed devices in year 2020. This results from penetration of digital applications which highly motivated by smart societies which can be defined as to when a (...)
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  29. The Qualitative Role of Big Data and Internet of Things for Future Generation-A Review.M. Arun Kumar & A. Manoj Prabaharan - 2021 - Turkish Online Journal of Qualitative Inquiry (TOJQI) 12 (3):4185-4199.
    The Internet of Things (IoT) wireless LAN in healthcare has moved away from traditional methods that include hospital visits and continuous monitoring. The Internet of Things allows the use of certain means, including the detection, processing and transmission of physical and biomedical parameters. With powerful algorithms and intelligent systems, it will be available to provide unprecedented levels of critical data for real-time life that are collected and analyzed to guide people in research, management and emergency care. This chapter provides (...)
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  30. 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 (...)
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  31. La Ricerca Scientifica nell'Era dei Big Data.Sabina Leonelli - 2018 - Meltemi.
    "Scientific Research in the Era of Big Data" - this book was also published in French (Mimesis) in 2019 and in Portuguese in 2022 (FIOCRUZ editors).
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  32.  39
    NEUTROSOPHIC THEORY AND SENTIMENT ANALYSIS TECHNIQUE FOR MINING AND RANKING BIG DATA FROM ONLINE EVALUATION.C. Manju Priya - 2022 - Journal of Science Technology and Research (JSTAR) 3 (1):124-142.
    A huge amount of data is being generated everyday through different transactions in industries, social networking, communication systems etc. Big data is a term that represents vast volumes of high speed, complex and variable data that require advanced procedures and technologies to enable the capture, storage, management, and analysis of the data. Big data analysis is the capacity of representing useful information from these large datasets. Due to characteristics like volume, veracity, and velocity, big (...) analysis is becoming one of the most challenging research problems. Semantic analysis is method to better understand the implied or practical meaning of the input dataset. It is mostly applied with ontology to analyze content mainly in web resources. This field of research combines text analysis and Semantic Web technologies. The use semantic knowledge is to aid sentiment analysis of queries like emotion mining, popularity analysis, recommendation systems, user profiling, etc. A new method has been proposed to extract semantic relationships between different data attributes of big data which can be applied to a decision system. (shrink)
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  33.  83
    Aspecte legale în lucrul cu Big Data.Nicolae Sfetcu - manuscript
    Utilizarea Big Data prezintă probleme juridice semnificative, în special din punctul de vedere al protecției datelor. Cadrul juridic existent al Uniunii Europene, bazat în special pe Directiva nr. 46/95/CE și Regulamentul general privind protecția datelor cu caracter personal, oferă o protecție corespunzătoare. Dar, pentru Big Data este necesară o strategie cuprinzătoare și globală. Evoluția în timp a fost de la dreptul de a exclude pe alții la dreptul la controlul propriilor date și, în prezent, la regândirea dreptului la (...)
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  34. No Wisdom in the Crowd: Genome Annotation at the Time of Big Data - Current Status and Future Prospects.Antoine Danchin - 2018 - Microbial Biotechnology 11 (4):588-605.
    Science and engineering rely on the accumulation and dissemination of knowledge to make discoveries and create new designs. Discovery-driven genome research rests on knowledge passed on via gene annotations. In response to the deluge of sequencing big data, standard annotation practice employs automated procedures that rely on majority rules. We argue this hinders progress through the generation and propagation of errors, leading investigators into blind alleys. More subtly, this inductive process discourages the discovery of novelty, which remains essential in (...)
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  35. Online Misinformation and “Phantom Patterns”: Epistemic Exploitation in the Era of Big Data.Megan Fritts & Frank Cabrera - 2022 - Southern Journal of Philosophy 60 (1):57-87.
    In this paper, we examine how the availability of massive quantities of data i.e., the “Big Data” phenomenon, contributes to the creation, spread, and harms of online misinformation. Specifically, we argue that a factor in the problem of online misinformation is the evolved human instinct to recognize patterns. While the pattern-recognition instinct is a crucial evolutionary adaptation, we argue that in the age of Big Data, these capacities have, unfortunately, rendered us vulnerable. Given the ways in which (...)
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  36. Deleuze’s Postscript on the Societies of Control Updated for Big Data and Predictive Analytics.James Brusseau - 2020 - Theoria 67 (164):1-25.
    In 1990, Gilles Deleuze published Postscript on the Societies of Control, an introduction to the potentially suffocating reality of the nascent control society. This thirty-year update details how Deleuze’s conception has developed from a broad speculative vision into specific economic mechanisms clustering around personal information, big data, predictive analytics, and marketing. The central claim is that today’s advancing control society coerces without prohibitions, and through incentives that are not grim but enjoyable, even euphoric because they compel individuals to obey (...)
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  37. Probleme etice în lucrul cu Big Data.Nicolae Sfetcu - manuscript
    Etica Big Data presupune aderarea la conceptele de comportament corect și greșit în ceea ce privește datele, în special datele cu caracter personal. Etica Big Data pune accentul pe colectorii și diseminatorii de date structurate sau nestructurate. Etica Big Data este susținută, la nivelul UE, de o amplă documentație, prin care se încearcă să se găsească soluții concrete pentru maximizarea valorii Big Data fără a sacrifica drepturile fundamentale ale omului. Autoritatea Europeană pentru Protecția Datelor (AEPD) sprijină (...)
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  38. Ethics of Identity in the Time of Big Data - Delivered at 25th Annual International Vincentian Business Ethics Conference (IVBEC), 2018, St. John’s University, New York.James Brusseau - manuscript
    According to Facebook’s Mark Zuckerberg, big data reality means, “The days of having a different image for your co-workers and for others are coming to an end, which is good because having multiple identities represents a lack of integrity.” Two sets of questions follow. One centers on technology and asks how big data mechanisms collapse our various selves (work-self, family-self, romantic-self) into one personality. The second question set shifts from technology to ethics by asking whether we want the (...)
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  39. Engaging the Public in Ethical Reasoning About Big Data.Justin Anthony Knapp - 2016 - In Soren Adam Matei & Jeff Collman (eds.), Ethical Reasoning in Big Data: An Exploratory Analysis. Springer. pp. 43-52.
    The public constitutes a major stakeholder in the debate about, and resolution of privacy and ethical The public constitutes a major stakeholder in the debate about, and resolution of privacy and ethical about Big Data research seriously and how to communicate messages designed to build trust in specific big data projects and the institution of science in general. This chapter explores the implications of various examples of engaging the public in online activities such as Wikipedia that contrast with (...)
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  40. A Survey of Business Intelligence Solutions in Banking Industry and Big Data Applications.Elaheh Radmehr & Mohammad Bazmara - 2017 - International Journal of Mechatronics, Electrical and Computer Technology 7 (23):3280-3298.
    Nowadays, the economic and social nature of contemporary business organizations chiefly banks binds them to face with the sheer volume of data and information and the key to commercial success in this area is the proper use of data for making better, faster and flawless decisions. To achieve this goal organizations requires strong and effective tools to enable them in automating task analysis, decision-making, strategy formulation and risk prediction to prevent bankruptcy and fraud .Business Intelligence is a set (...)
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  41.  58
    Development of Keyword Trend Prediction Models for Obesity Before and After the COVID-19 Pandemic Using RNN and LSTM: Analyzing the News Big Data of South Korea.Gayeong Eom & Haewon Byeon - 2022 - Frontiers in Public Health 10:894266.
    The Korea National Health and Nutrition Examination Survey (2020) reported that the prevalence of obesity (≥19 years old) was 31.4% in 2011, but it increased to 33.8% in 2019 and 38.3% in 2020, which confirmed that it increased rapidly after the outbreak of COVID-19. Obesity increases not only the risk of infection with COVID-19 but also severity and fatality rate after being infected with COVID-19 compared to people with normal weight or underweight. Therefore, identifying the difference in potential factors for (...)
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  42.  49
    The Canary in the Gold Mine: Ethics, Privacy, and Big Data Analytics.William H. Harwood - 2019 - Dialogue and Universalism 29 (3):141-150.
    This paper offers a sketch of the complicated conflicts which arise—and metastasize seemingly daily—in the era of Big Data. Given the public’s ubiquitous-yet-ostensibly-voluntary data surrender, and industry’s ubiquitous-yet-ostensibly-anodyne collection of the same, inaction is not an option for any near-just society. By revisiting the philosophical basis for Panoptic apparatus, sketching the tumultuous history of US contract law trying to protect the public from itself, and comparing existing industry codes for similarly-situated—read: terrifyingly invasive—fields, the paper will provide a preliminary (...)
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  43. Correlation Isn’T Good Enough: Causal Explanation and Big Data[REVIEW]Frank Cabrera - 2021 - Metascience 30 (2):335-338.
    A review of Gary Smith and Jay Cordes: The Phantom Pattern Problem: The Mirage of Big Data. New York: Oxford University Press, 2020.
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  44. Hacking the Social Life of Big Data.Tobias Blanke, Mark Coté & Jennifer Pybus - 2015 - Big Data and Society 2 (2).
    This paper builds off the Our Data Ourselves research project, which examined ways of understanding and reclaiming the data that young people produce on smartphone devices. Here we explore the growing usage and centrality of mobiles in the lives of young people, questioning what data-making possibilities exist if users can either uncover and/or capture what data controllers such as Facebook monetize and share about themselves with third-parties. We outline the MobileMiner, an app we created to consider (...)
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  45.  74
    Hey, Google, leave those kids alone: Against hypernudging children in the age of big data.James Smith & Tanya de Villiers-Botha - forthcoming - AI and Society:1-11.
    Children continue to be overlooked as a topic of concern in discussions around the ethical use of people’s data and information. Where children are the subject of such discussions, the focus is often primarily on privacy concerns and consent relating to the use of their data. This paper highlights the unique challenges children face when it comes to online interferences with their decision-making, primarily due to their vulnerability, impressionability, the increased likelihood of disclosing personal information online, and their (...)
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  46.  99
    Ihde’s Missing Sciences: Postphenomenology, Big Data, and the Human Sciences.Daniel Susser - 2016 - Techné: Research in Philosophy and Technology 20 (2):137-152.
    In Husserl’s Missing Technologies, Don Ihde urges us to think deeply and critically about the ways in which the technologies utilized in contemporary science structure the way we perceive and understand the natural world. In this paper, I argue that we ought to extend Ihde’s analysis to consider how such technologies are changing the way we perceive and understand ourselves too. For it is not only the natural or “hard” sciences which are turning to advanced technologies for help in carrying (...)
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  47. Gründe Geben. Maschinelles Lernen Als Problem der Moralfähigkeit von Entscheidungen. Ethische Herausforderungen von Big-Data.Andreas Kaminski, Michael Nerurkar, Christian Wadephul & Klaus Wiegerling - 2020 - In Klaus Wiegerling, Michael Nerurkar, Christian Wadephul (Hg.): Ethische Herausforderungen von Big-Data. Bielefeld: Transcript. pp. 151-174.
    Entscheidungen verweisen in einem begrifflichen Sinne auf Gründe. Entscheidungssysteme bieten eine probabilistische Verlässlichkeit als Rechtfertigung von Empfehlungen an. Doch nicht für alle Situationen mögen Verlässlichkeitsgründe auch angemessene Gründe sein. Damit eröffnet sich die Idee, die Güte von Gründen von ihrer Angemessenheit zu unterscheiden. Der Aufsatz betrachtet an einem Beispiel, einem KI-Lügendetektor, die Frage, ob eine (zumindest aktuell nicht gegebene) hohe Verlässlichkeit den Einsatz rechtfertigen kann. Gleicht er nicht einem Richter, der anhand einer Statistik Urteile fällen würde?
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  48. A Review Paper on Scope of Big Data Analysis in Heath Informatics.Kazi Md Shahiduzzaman, Lusekelo Kibona & Hassana Ganame - 2018 - International Journal of Engineering and Information Systems (IJEAIS) 2 (5):1-8.
    Abstract— The term Health Informatics represent a huge volume of data that is collected from different source of health sector. Because of its’ diversity in nature, quite a big number of attributes, numerous amount data, health informatics can be considered as Big Data. Therefore, different techniques used for analyzing Big Data will also fit for Health Informatics. In recent years, implementation of Data Mining on Health Informatics brings a lot of fruitful outcomes that improve the (...)
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    Theory of Signs and Statistical Approach to Big Data in Assessing the Relevance of Clinical Biomarkers of Inflammation and Oxidative Stress.Pietro Ghezzi, Kevin Davies, Aidan Delaney & Luciano Floridi - 2018 - Proceedings of the National Academy of Sciences of the United States of America 115 (10):2473-2477.
    Biomarkers are widely used not only as prognostic or diagnostic indicators, or as surrogate markers of disease in clinical trials, but also to formulate theories of pathogenesis. We identify two problems in the use of biomarkers in mechanistic studies. The first problem arises in the case of multifactorial diseases, where different combinations of multiple causes result in patient heterogeneity. The second problem arises when a pathogenic mediator is difficult to measure. This is the case of the oxidative stress (OS) theory (...)
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  50. 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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