Legal Big Data (Legal Big Data)
In: Custers B.H.M. & Leeuw F. (2017), Legal big data: Toepassingen voor de rechtspraktijk en juridisch onderzoek, Nederlands Juristenblad 2017(34): 2449-2456.
In: Custers B.H.M. & Leeuw F. (2017), Legal big data: Toepassingen voor de rechtspraktijk en juridisch onderzoek, Nederlands Juristenblad 2017(34): 2449-2456.
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Working paper
In: Aus Politik und Zeitgeschichte 65.2015,11/12
Enth. u.a.: "Ich habe doch nichts zu verbergen"/ E. Morozov. - Politikfeld Big Data/ C. Stöcker. - Von Big zu Smart: zu Sustainable?/ R. Kreibich. - Dr. Algorithmus? Big Data in der Medizin/ P. Langkafel. - Big Data und die Macht des Marktes/ Y. Hofstetter
In: Cambridge elements. Elements in the philosophy of science
Big Data and methods for analyzing large data sets such as machine learning have in recent times deeply transformed scientific practice in many fields. However, an epistemological study of these novel tools is still largely lacking. After a conceptual analysis of the notion of data and a brief introduction into the methodological dichotomy between inductivism and hypothetico-deductivism, several controversial theses regarding big data approaches are discussed. These include, whether correlation replaces causation, whether the end of theory is in sight and whether big data approaches constitute entirely novel scientific methodology. In this Element, I defend an inductivist view of big data research and argue that the type of induction employed by the most successful big data algorithms is variational induction in the tradition of Mill's methods. Based on this insight, the before-mentioned epistemological issues can be systematically addressed.
In: Routledge research in information technology and society 21
In: Milan S. (2021) Big Data. In: Harris P., Bitonti A., Fleisher C.S., Skorkjær Binderkrantz A. (eds) The Palgrave Encyclopedia of Interest Groups, Lobbying and Public Affairs. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-030-13895-0_103-1
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In: Wiley & SAS business series
Unique insights to implement big data analytics and reap big returns to your bottom line Focusing on the business and financial value of big data analytics, respected technology journalist Frank J. Ohlhorst shares his insights on the newly emerging field of big data analytics in Big Data Analytics . This breakthrough book demonstrates the importance of analytics, defines the processes, highlights the tangible and intangible values and discusses how you can turn a business liability into actionable material that can be used to redefine markets, improve profits and identify new business opportunities. Reveals big data analytics as the next wave for businesses looking for competitive advantage Takes an in-depth look at the financial value of big data analytics Offers tools and best practices for working with big data Once the domain of large on-line retailers such as eBay and Amazon, big data is now accessible by businesses of all sizes and across industries. From how to mine the data your company collects, to the data that is available on the outside, Big Data Analytics shows how you can leverage big data into a key component in your business's growth strategy.
In: Graham, M., and Shelton, T. (2013) Geography and the Future of Big Data, Big Data and the Future of Geography. Dialogues in Human Geography 3(3) 255-261
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The project assesses the use of Big Data in teaching in the social sciences.
In: Zwitter , A 2014 , ' Big Data ethics ' , Big Data & Society , vol. 1 , no. 2 , pp. 1-6 . https://doi.org/10.1177/2053951714559253
The speed of development in Big Data and associated phenomena, such as social media, has surpassed the capacity of the average consumer to understand his or her actions and their knock-on effects. We are moving towards changes in how ethics has to be perceived: away from individual decisions with specific and knowable outcomes, towards actions by many unaware that they may have taken actions with unintended consequences for anyone. Responses will require a rethinking of ethical choices, the lack thereof and how this will guide scientists, governments, and corporate agencies in handling Big Data. This essay elaborates on the ways Big Data impacts on ethical conceptions.
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In: Routledge Research in Information Technology and Society 21
Intro -- Half Title -- Title Page -- Copyright -- Contents -- Notes on contributors -- Acknowledgements -- 1 The politics of Big Data: principles, policies, practices -- Our focus and goal -- Big Data - does it exist, and if so, what is it? -- Politics as a perspective on Big Data -- The volume in brief -- Notes -- References -- PART I Principles and paradigms: questioning the tenets of Big Data -- 2 The haystack fallacy, or why Big Data provides little security -- Introduction -- Setting chapter parameters -- What are data? -- What makes data 'big'? -- What are Big Data good for, given how they are created, processed, and used? -- Because petabytes -- [Causal] models are moot -- Theory is irrelevant -- Numbers speak for themselves -- Correlation is enough -- Results show unprecedented accuracy -- So what? -- In conclusion -- Notes -- References -- 3 Grasping the ethics and politics of algorithms -- Introduction -- Opening black boxes is not enough -- Some things cannot be done right -- Discrimination and bias are no accident -- Human experts are not necessarily better -- The algorithm is just one part of the puzzle -- Superhuman artificial intelligence is not the main issue -- Conclusion -- Notes -- References -- 4 Big Data - within the tides of securitisation? -- Introduction -- A new data pragmatism? -- Uncertainty, predictability and interpretation -- Securitisation and (surveillance) technology -- Big Data as a tool of (in)securitisation -- Increasing power asymmetries and technology dependencies -- Summary and conclusions -- Acknowledgement -- Notes -- References -- 5 Surveillance as a critical paradigm for Big Data? -- Introduction -- Big Data and dataveillance -- Epistemic issues in Big Data -- Amending the epistemic critique: critical issues of Big Data as surveillance -- The decoupling of generation and analysis of data
In: Criminology at the edge
In: Wiley & SAS business series
In: The Data Revolution: Big Data, Open Data, Data Infrastructures & Their Consequences, S. 67-79
In: Big Data & Society 2014 1: DOI: 10.1177/2053951714559253
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In: Peripherie: Politik, Ökonomie, Kultur, Band 38, Heft 3-2018, S. 483-487
ISSN: 2366-4185