Visual Arts Between Big Data And Singularities

It might at first seem surprising to investigate the relationship of Big Data and singularities with regard to the visual arts. Hearing the term Big Data, one automatically thinks of fields like computer science, the information technology (IT) industry, economics, business, or the natural and health sciences. When surveying the implications, applications, and concerns of Big Data, sociology, politics, or ethics tend to come to mind before the arts. Nevertheless, and precisely because of this, I would like to offer some considerations of the possible interconnections between these areas, including some examples of artists’ works and methods of creation, in the hope that I can shed some light on the nature of both Big Data and creative processes. At the same time, I would also like to introduce the reader to a broader interpretation of Big Data by examining it beyond its traditional meanings and appearances—ones that are often limited to IT-related areas. Therefore, in the following brief overview of the question, I will first discuss some considerations that are more distant from the strictly techn(olog) ical meaning of Big Data, then narrow it back, somewhat closer to its original sense.

Usually, we do not think of Big Data with regard to the fine and visual arts, perhaps because we are accustomed to the idea that in the arts, we need to celebrate singularity. The focus is upon the individual achievements and the special, personal style of the artist, and especially upon the launch of a new (art) form that may develop into a “school,” “movement,” or “ism”—an innovative solution to a pictorial problem, a novel approach to the representation of a topic, a bold standpoint with respect to a pressing issue, the making of a political statement through a unique artwork, and so on. Many of the creators who have been canonized as leading figures in the history of art—Giotto, Leonardo, Rembrandt, Cézanne, Picasso—are respected for their individual achievements, and can be connected to some of the aforementioned forms of innovation and singularity. Today’s emerging creators also aspire to become, literally, outstanding—i.e., to stand out from the huge mass of data and visual input and the overwhelming aesthetic offerings that contemporary viewers are constantly encountering.

Hence, in this first part of my examination of the connections between Big Data and the fine and visual arts, Big Data may in a sense refer to the massive amount of art production, from both historical periods and our present world, of which those who appreciate art are trying to get an overview, and which the artists themselves are working, struggling, and often even competing with. The appreciators strive to find their individual preferences, and to discover those works and genres that are the closest to their own tastes and ideals—of course, this personal taste will make them, as appreciators of art, singular too—while artists working on and for the free market hope to find a singular approach that will make their work become the favourite of galleries, museums, and collectors.

At the same time, however, seeing the question in a broader sense, there are other ways in which Big Data can be traced in art production and artistic processes. Here again, Big Data is not (solely) interpreted in the strict sense of having a large quantity of information collected, stored, and elaborated by machines based on specific instructions and algorithms, but is seen with respect to the creative, human working of the material—i.e., the creativity gained from the information. Seeing from this perspective, we can consider any and all types of influences, elaborations, re-interpretations, and re-visitations as part of working with the Big Data of the immense traditions of the global history of art.

Whenever an artist creates a new work with an earlier one in mind, or under the unconscious influence of previous works, the endless possibilities of the effect of those preceding works will arise. In this sense, the connection of the concepts of Big Data and singularity can be traced in the creative process of the artist—i.e., what he or she may choose from the endless options of the historical tradition, and how to transform it into a new, singular piece, with which and through which, ideally, the present viewer can both understand more of the original work and our contemporary world. Bringing forward this idea, we can even say that every work of art, once created, becomes part of the Big Data of human artistic tradition, and thus may also become the possible subject of future re-interpretations. Naturally, this re-working of a singular piece depends upon many factors—how widely the artwork is known, its artistic and aesthetic quality, in what ways it contributed to the defining of its era, whether it can be considered exemplary, and/or can and should it be questioned with regard to the social and political issues of its era. Naturally, many artworks will never be re-discovered and will be completely forgotten, while others have long-dormant periods of decades, even centuries, before  re-discovery, and yet others trigger an immediate reaction and lead to an incessant flow of re-interpretation and re-working right after they are completed.

At this point, we will mention pieces that are a part, or sub-category, of the above— works that are also parts of a larger set of investigation. This sub-category may include open-ended or never-ending works, unfinished and/or unfinishable pieces, and encyclopaedic collections of visual material and their re-elaboration. As examples, we can quote Ákos Czigány’s photographic series on the courtyards of Budapest, collected through his Lucien Hervé- and Rudolf Hervé-prize-winning images entitled Skies–Hommage á Hiroshi Sugimoto, in which the delicate outlines of roofs, seen from the middle of the buildings’ courtyards, frame a sky that appears in large, homogenous white areas, like the screens in Sugimoto’s movie series, to which I will return later in this article. In this way, the historicist and modernist architectural heritage of Budapest is not only surveyed and collected, but through a status change—from architectural into visual material—gets transformed, and becomes a constituent pictorial element in the new work.

A different intention motivates Gregory Buchakjian—to document the civil-war-torn city of Beirut and its fascinating constructions. In 2009 he started to document over 700 buildings, forming an impressive inventory of the dilapidated and abandoned interiors of the capital through tens of thousands of photographs, while at the same time, parallel to this documentary collection, he was also creating artistic pieces in which some of these spaces reappear as a polyvalent hosting environment for staged photographs investigating his personal attachment and response to the decaying space. Another “encyclopaedic” collection we recall is Milorad Krstic’s Das Anatomische Theater. This time, however, the starting point is not architectural heritage, but the history of the 20th century. In Krstic’s collection of detailed visual analyses of the figures, movements, and events—as well as their interwoven connections—of modern times, he manages to create a critical visual encyclopaedia of the history and art history of the 20th century, where at the end it is the century itself lying on the dissection table.

Getting closer to the original and narrower sense of Big Data, we can mention another of its important connections to the world of the arts—those works, especially contemporary pieces, that contain and use a large amount of visual and/or digital information and its elaboration. Some of these are created with techniques and media that by now seem classical, like analogue photography. Just think, for example, of Hiroshi Sugimoto’s fascinating series made in movie theatres, where the exposure time is the same as the film’s length, hence the final photograph, even if it looks like a bright screen, nevertheless “contains” the entire film. Another example, this time created through the medium of digital photography, is Ádám Magyar’s Stainless series, in which the artist meticulously collects a huge amount of digital data with his camera for the creation of every piece in his series by “scanning” metro trains arriving from a tunnel with a special recording technique he developed, for which the final result will be a seemingly sterile, pure, engineer-like rendering of the vehicle, that at the same time successfully attempts to poetically analyze various aspects of contemporary urban reality through high-resolution details.

Towards the end of our overview, and arriving at the original sense of Big Data, I shall mention works that not only operate with large amounts of data—previous artworks, subject matters, or motives inherited as visual (re)sources to get inspired by, and to re-interpret in the creation of novel pieces—but that explicitly visualize Big Data itself, creating fascinating and, at the same time, singular pieces that investigate the flow and nature of Big Data. Some of the artists working in this direction are principally interested in making manifest the otherwise abstract nature of Big Data by, for example, using its raw material in creating a piece with a sublime effect. Ryoji Ikeda, whose large-scale installations and computer animations with the series title “data-verse” not only show Big Data, but create an overwhelming experience of it. The strange sublimity of his work comes not only from the ways of experiencing the data, but also from the difficulties of making sense of it. And it is exactly here where the thrilling appeal of his work is traceable: Data that was originally collected to understand a certain phenomenon becomes so abundant and overwhelming that it fills our mind to the point that we have to give up attempting to understand it, and instead try to enjoy the flow of the visual and mathematical information that we perceive, but are unable to elaborate.

Claude Closky uses visual information, and the visuality of information, in another way in his 2003 work “Untitled (NASDAQ),” for which an entire gallery wall was covered with wallpaper designed by Closky that contained stock exchange data. Needless to say, the numbers lost their significance, not only because one could not perceive the immense quantity of them, but because they also lost their actuality, since in our high-paced economy it is always the latest value that counts. In Closky’s case, we have a large segment of Big Data taken out of its context and used for its pure visuality, to create a decorative pattern. The artist thus manages to both impress the viewer with the unusual “use” of numbers and information, and at the same time implicitly mocks the often-hyped commercial aspects of the global art world and its infrastructure.

Needless to say, this has only been a brief overview of the myriad of possible interconnections between Big Data and singularities with regard to the fine and visual arts. I have provided just a few singular examples from the Big Data of artwork that use the immense historical traditions of art, investigating and re-working this material or directly using and visualizing Big Data for the creation of a new artwork. In each of these examples, however, the singularity of artwork dominates—i.e., the unique way in which the artist uses these influences, working with all of the available material in order to make a new piece, one that gives a new interpretation of our contemporary reality.