Abstract
Big Data has been one of the trending ideas in the information technology business in the recent years. It has (or already had) its place in the Gartner Hype Cycle for Emerging Technologies 1 and the phrase is notorious for oscillating between being used as a buzz word and being a meaningful technological concept. There is some broader interest in Big Data, as the many attempts to give an answer to the question " What is Big Data? " indicate. 2 The idea that when speaking of Big Data we are dealing with more than just one of the current coins in marketing jargon is also supported by the fact that the term has been admitted into venerable dictionaries like the Oxford English Dictionary and Merriam-Webster. The widespread interest in the nature of Big Data, though, also hints that there lie some difficulties in giving a concise and informative definition of the concept. This, of course, is not a distinctive feature of Big Data technologies, but is the case with modern technologies in general, especially with information and communications technologies: They evolve rapidly and sometimes are subject to technological leaps or redefinitions that transcend concepts in use at a time (the computer becoming a computer in a network, the mobile phone becoming the smart phone, glasses becoming augmented reality glasses, the automobile becoming the driverless car etc.). So what is Big Data? 3 Big Data is very large volumes of data of various types, collected massively from heterogenous sources (sensors, cell phones, social networks etc.). Big Data is also the new technologies (algorithms/software and hardware) used to collect, store and process this data with high degrees of velocity. Technology forecasters and marketers envision Big Data to allow for entirely new kinds of applications and products to be developed in the field of information and communications. Big Data is marketed as a solution to many problems in informatics that could not be tackled before, or only with high costs and effort. Big Data is said to promise an increase in efficiency and productivity, to lower costs in industry and business, to enable new methods and knowledge in science, and to enhance control and regulation in personal life and in governance. As regards those technologies as such it could seem that only technical disciplines would take an academic interest in them: It is a question for informatics whether envisioned Big Data applications actually are realizable, or whether they offer truly new approaches and solutions to classical problems. And it is a question for economics whether, for example, it would be economically rational to make use of Big Data technologies in business processes, or whether products built on them might find their markets. As regards ethics and the
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CITATION STYLE
Nerurkar, M., Wadephul, C., & Wiegerling, K. (2016). Ethics of Big Data: Introduction. The International Review of Information Ethics, 24. https://doi.org/10.29173/irie154
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