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Big Data and the Arts

Miguel Ángel Medina, University of Málaga (Spain)

Abstract

Big Data has come and is here to stay pervading many human activities, including social, humanistic and natural sciences. This article briefly reviews the emergence of Big Data in Humanities and the Arts, as well as the opportunities and issues it opens.

1. Introduction

Big Data is a relatively recent term that has emerged as a widely recognized trend pervading many different human activities and attracting the attention from the industrial and commercial sectors, governments and academia (Hashem, Yaqoob, Anuar, Mokhtar, Gani & Khan, 2015). There is not a consensus definition for Big Data yet. Big Data is sometimes defined as “the amount of data just beyond technology’s capability to store, manage, and process efficiently” (Manika et al., 2011). Very recently, Big Data has been similarly defined as “a term utlized to refer to the increase in the volume of data that are difficult to store, process, and analyze thorugh traditional database technologies” (Hashem, Yaqoob, Anuar, Mokhtar, Gani & Khan, 2015). Introducing slight but interesting differntial tinges, Magoulas & Lorica introduce the Big Data concept “when the size and performance requirements for data management become significant design and decision factors for implementing a data management and analysis system” (Magoulas & Lorica, 2011). Others define Big Data as characterized by the size of data volume, variety, and acquisition velocity, altogether usually mentioned as “the three Vs” (Zikopoulos, Parasuraman, Deutsch, Giles & Corrigan, 2012; Berman, 2013). Some authors add a fourth essential and key V to the features defining Big Data, namely, V for value (Gantz & Reinsel, 2011; Chen, Mao & Liu, 2014).

It should be stressed that Big Data is a relative and moveable concept in terms of data “size”, taking into account both the actual historical moment and the human activity in which is going to be applied. It is clear that the amount of data to be considered “big” is not the same for the Information Technologies, Biology or History. And it is also clear that the maximal technological capability to manage data is continuosly increasing. A recent analysis carried out by CISCO revealed that from 1992 to 2012 the amount of data transmitted across the Internet hugely increased from 100 gigabytes per day to 12 terabytes a second (mentioned in the AHRC The Challenge of Big Data brochure published in July 2014). Up to the beginning of the current millenium, most of the available information was maintained stored in analog storage systems (books, photographs, drawings, maps, discs, tapes, and so on). In 2002, digital storage of information amounted for a half of the global information sotrage capacity, thus marking the beginning of the digital age. In only five years, by 2007 almost 94% of the totality of the accumulated information was already digitally stored. Furthermore, the trend to accumulate new data is continuously accelerating so fast that currently more than 90% of total data available in the world has been created in the last two years. Thus, currently the “size” of Big Data initiatives ranges from a few terabytes to many petabytes of data.

Although Big Data indeed refers to very large quantities of available data, now it seems clear that size is not the most relevant feature of Big Data, but rather the value of these data is what matters most. As mentioned in the presentation of the Big Data and Big Challenges for Law and Legal Information symposium held in 2013 to celebrate the 125 years of Georgetown Universtiy Law Library, this value of Big Data is related with our ability to discover meaning by connecting points of information electronically, across numerous, vast, and often unrelated stores of data (available in http://www.georgetown.edu/library/about/125/symposium/index.cfm). Therefore, the most relevant feature of Big Data is not its size, but its relationality to other data. And this is so because Big Data is essentially networked (Boyd & Crawford, 2011). In particular, Big Data coming from data tracking has introduced two new types of social networks, the so-called articulated and behavioral networks. In fact, networks are currently pervading all scientific, humanistic and social disciplines. For a review on networks and arts, see my essay on the issue recently published in Rupkatha (Medina, 2015)….Access Full Text of the Article

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