Abstract
This paper is divided into two parts. In the first, I shall briefly analyse the phenomenon of “big data”, and argue that the real epistemological challenge posed by the zettabyte era is small patterns. The valuable undercurrents in the ocean of data that we are accumulating are invisible to the computationally-naked eye, so more and better technology will help. However, because the problem with big data is small patterns, ultimately, the game will be won by those who “know how to ask and answer questions” (Plato, Cratylus, 390c). This introduces the second part, concerning information quality (IQ): which data may be useful and relevant, and so worth collecting, curating, and querying, in order to exploit their valuable (small) patterns? I shall argue that the standard way of seeing IQ in terms of fit-for-purpose is correct but needs to be complemented by a methodology of abstraction, which allows IQ to be indexed to different purposes. This fundamental step can be taken by adopting a bi-categorical approach. This means distinguishing between purpose/s for which some information is produced (P-purpose) and purpose/s for which the same information is consumed (C-purpose). Such a bi-categorical approach in turn allows one to analyse a variety of so-called IQ dimensions, such as accuracy, completeness, consistency, and timeliness. I shall show that the bi-categorical approach lends itself to simple visualisations in terms of radar charts.
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Fracking (hydraulic fracturing) is a technique in which a liquid (usually water), mixed with sand and chemicals, is injected underground at high pressure in order to cause small fractures (typically less than 1 mm), along which fluids such as gas (especially shale gas), petroleum and brine water can surface.
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See more recently United States. Congress. House. Committee on Government Reform. Subcommittee on Regulatory Affairs (2006).
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Borges, “The Analytical Language of John Wilkins”, originally published in 1952, English translation in Borges (1964).
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Floridi, L. (2014). Big Data and Information Quality. In: Floridi, L., Illari, P. (eds) The Philosophy of Information Quality. Synthese Library, vol 358. Springer, Cham. https://doi.org/10.1007/978-3-319-07121-3_15
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DOI: https://doi.org/10.1007/978-3-319-07121-3_15
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