data art: from the aesthetic conceptualization of data to information critique
DESCRIPTION
In this particular essay, the focus is directed to the art world and the role that data plays in that particular sphere by discussing what is, currently labeled as, “data art” to understand the features which differentiate data visualization projects from artistic ones besides investigating possible common themes and methodologies among the latter.TRANSCRIPT
Data Art: From the Aesthetic Conceptualization of
Data to Information Critique
New Media Theories
Research Essay
Ana Crisostomo
Student n. 10397124
04/01/2013
1
1. Introduction
The current ubiquity of data populating every aspect of an individual’s digitally connected
existence [1], alongside the computational possibilities of harnessing the same to convert it
into distilled information, has introduced the theme of data as one of the most debated in
recent years in a variety of fields ranging from academia to business, from science to popular
media, and from politics to art.
In this particular essay, the focus is directed to the art world and the role that data plays in
that particular sphere by discussing what is, currently labeled as, “data art” to understand
the features which differentiate data visualization projects from artistic ones besides
investigating possible common themes and methodologies among the latter. If data art can
be affiliated to new media, does it enable, for instance, cognitive and perceptual
transformations [2]? Or does it operate solely on a more conceptual level? If “art attempts to
create new relationships between familiar and as yet unfamiliar data” (Jennings 3), what are
the particular connections that data art potentiates? In an era of excess of data, but often
scarcity of information and meaning [3], what are the alternatives proposed by data art? The
next pages will hopefully provide some (provisory) answers to these questions.
In terms of structure, the first two sections of the essay will briefly examine the concepts and
theories around data, databases and information making also references to knowledge,
meaning, interaction and interface. The following part moves forward to analyze aesthetic
aspects in an attempt to contextualize data art projects within a broader art movement.
The fifth section, prior to the conclusion, considers a selected set of projects as
representative of the diversity existing in the data art universe while illustrating some of the
theoretical arguments presented in previous sections.
[1] In this domain, Galloway refers to the present situation as a “culture of enforced interaction, the
militarization of connectivity” (Galloway, Lovink, Thacker 112).
[2] The theme of new media's potential for cognitive and perceptual transformation is developed by
Jennings in “The Production, Reproduction and Reception of the Work of Art.”
[3] As stated by Dean: “Excesses of information turn into a lack of the information most relevant to the
questions at hand” (Dean 19).
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2. From Data to Databases
One of the elements which have catapulted the current data popularity is the sheer amount
of data captured (reflected in the label “big data” commonly used in multiple spheres) – not
only in terms of breadth, but also depth – and, in many cases, made publicly available. The
terms in which these data can be made available and to whom can, just by itself, provide
discussion material for another parallel essay leading to issues surrounding information
control and power [4]. On a more pragmatic approach to this topic Manovich, for example,
refers to a new data divide as creating three “data classes” in contemporary society which can
be visualized in a classical pyramidal manner: those who create data (the larger group), those
who have the means to collect it (a smaller group), and those who have the expertise to
analyze it (the most restrict category of all) (Manovich, “Trending: The Promises and the
Challenges of Big Social Data”, 11) – a concept which raises several questions on a societal
level.
The potentialities hiding behind a vast set of detailed data produced and accessed mostly in
the period subsequent to the massified use of the internet, can be simultaneously daunting
and exert an unquestionable fascination and curiosity [5]. When referring to financial
systems, for instance, some authors refer to the internet as the source of a “fog of data”
(Terranova, “New Economy, Financialization and Social Production in Web 2.0.” 159) to
highlight the volatility created by the reflexivity processes triggered by the amount of data
being immediately and synchronously available. In the realm of academia, some authors
praise the research opportunities which data affords, declaring that we have already entered
the “post-theoretical age” [6]. Other enthusiastic voices claim more promptly that data
renders outdated many theories of human behavior since “with enough data, the numbers
speak for themselves” [7].
[4] On a more conceptual approach to this matter, it might be relevant to read Postscript on the
Societies of Control by Deleuze and its references to the new “numerical language of control [is] made
of codes that mark access to information, or reject it” (Deleuze 3) and the description of society of
control.
[5] Whitelaw refers a tendency towards data mysticism where “data (…) becomes a reservoir of
potential, a field of the unknown and emergent” (Whitelaw).
[6] As stated by Associate Professor Dan Edelstein in The New York Times article “Digital Keys for
Unlocking the Humanities’ Riches” by Patricia Cohen.
[7] According to Chris Anderson, editor in chief of Wired, in “The End of Theory: The Data Deluge
Makes the Scientific Method Obsolete.”
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There is no unanimity on the matter, but perhaps most authors would agree on the fact that
what is mostly interesting in the present “big data” wave is not necessarily the size of data,
but the type of data captured and its relational character. According to some, “big data”
allows the combination of “surface data” with “deep data” (Manovich, “Trending: The
Promises and the Challenges of Big Social Data” 2) and the possibility of establishing various
connections between sets of data (Boyd, Crawford 1) unveiling patterns which were
previously not visible. Such patterns might serve as pointers in the path to meaningful
information, but that is not necessarily the case in every occasion as, the same authors point
out, they can equally instigate “the practice of apophenia: seeing patterns where none
actually exist” (Boyd, Crawford 2).
Another aspect which is worth exploring relates to the objective character which is frequently
associated with data as well as a condition of pre-existence: seeing data as an independent
entity which exists beyond and regardless of any (human) intervention. But, as Manovich
writes, “data does not just exist — it has to be generated” (Manovich, “Database as a
Symbolic Form” 7) [8]. Being this the case, it is then adequate to complement this idea with
the one from Bowker stating that: “raw data is both an oxymoron and a bad idea; to the
contrary, data should be cooked with care.”
If one is to consider data as a primary ingredient provided with a certain degree of plasticity,
then further steps are required to produce a final recipe. These steps could be denominated
as the assemblage of data into databases which includes the selection (inclusion and
exclusion) and organization of items into particular structures. Different data organization
models create different types of databases [9]. Additionally, a tool to efficiently explore such
structures is also required and, in most cases, this querying mechanism takes the form of an
algorithm. In most of the web 2.0 platforms (regardless of their, more or less, accentuated
social nature) and even beyond those, there is a symbiotic relationship between both
elements [10].
[8] To complement this idea, Whitelaw adds that “data always comes from somewhere: it is produced
by the process that generates it, and as such it encodes that process, as much as anything else”
(Whitelaw).
[9] As stated by Manovich in the 1998 article on Database as a Symbolic Form (Manovich, “Database
as a Symbolic Form” 1).
[10] According to Manovich “Algorithms and data structures have a symbiotic relationship” (Manovich,
“Database as a Symbolic Form” 6). This is also noted by Fuller and Goffey when writing about one of
the Evil Media stratagems (Know Your Data): “algorithms without data structures are useless” (Fuller,
Goffey 150).
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While the efficiency of the algorithms may convey the notion of machinic objectivity to the
user [11], there are innumerous debates on the workings of these complex mechanisms which
some authors claim to “produce not barometric readings but hieroglyphs” (Gillespie 710) to
highlight the black boxed criteria involved in their processes. In some circumstances, it may
be a matter of intentionally concealing the principles being applied, but in others it is
possibly the pure abstract complexity of the algorithm which does not allow a linear
reconciliation between data and results. As explained by Rieder and Rohle: “certain
techniques imported from the computer sciences may never be understood in the same way
we understand statistical concepts like variance or regression because there no longer is a
'manual' equivalent of the automated approach” (Rieder, Rohle 76).
The referred degree of complexity [12] and level of opacity involved should not stand as an
unsurpassable hurdle in the way of a critical approach on data, databases and information.
The path which carries methods and data from computer sciences to other fields is not
linear. In what concerns computer programming, for instance, Galloway states that “software
is not primarily a verbal narrative or a visual image, even if certainly these latter forms can
be remediated in software” which underlines the primarily functional character of software
instruments (while not denying obfuscation as a technical requirement for successful
execution). The topic of narrative leads to discussions on interface and interactivity since
in recent years “interaction with information devices became a designed experience”
(Manovich, “Information as an Aesthetic Event” 5) so the interface possesses, by default, an
in-built narrative.
Chun is one of the authors who explore the notion of interfaces as “functional analogs to
ideology and its critique” (Chun, Programmed Visions: Software and Memory 59)
emphasizing emotional and cognitive values through the illusion of direct manipulation,
feeling of amplification and engagement provided to the user.
The aspects related to critique as raised by the author are particularly interesting in this data
context as she states “software enables this critique by representing it [the relations between
the action of individual actors and the system as a whole] at a scale—in a microworld—that
we can make sense of” (Chun, “On Software, or the Persistence of Visual Knowledge” 42).
[11] This judgment can be circumscribed under the historical tradition which considers that “machine
processing endows results with a higher epistemological status” (Rieder, Rohle 70).
[12] In terms of complexity, Manovich establishes an inversely proportion relation between databases
and algorithms claiming that “the more complex the data structure of a computer program, the
simpler the algorithm needs to be, and vice versa” (Manovich, “Database as a Symbolic Form” 5).
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However, taking into account that data art projects do not necessarily entail digital interfaces
for the end user in all occasions, these aspects related to interaction and interfaces will not be
developed in depth in this particular essay.
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3. From Databases to Information
Databases position themselves as the intermediate structure between data and
information [13] and the genealogy of the latter concept can be circumscribed to cybernetics
and information theory – in both cases with an early emphasis on the material aspect of the
notion.
In cybernetics (a discipline related to the military arena in its inception), information played
a central role in feedback systems aimed at control through the means of prediction [14].
In information theory (more closely connected to telecommunications engineering),
information became the accurately reproduced signal which stood out from the noise [15].
However, even within those two approaches, information possessed also an abstract nature
and, for that reason, displays what Galloway labeled as “an ambivalent relation to the
material world” (Galloway, Thacker 20) [16].
Some authors claim that such immateriality has actually been amplified by contemporary
technological developments [17] which may sound somehow paradoxical taking into
consideration the origins just described.
Within this abstract domain, a property which is important to refer is the one of meaning as
an element which attributes logic and contextualizes information within a larger intellectual
sphere.
Authors such as Crasson [18] and Baudrillard establish an interesting relationship between
[13] Whitelaw refers to data and information as being “converse, two sides of the same thing: data is the
raw material of information, its substrate; information is the meaning derived from data in a
particular context” (Whitelaw).
[14] The ambition for the devices built initially within the cybernetics field was to “predict the future
actions of an organism not by studying the structure of the organism but by studying the past behavior
of the organism” (Galison, 243).
[15] As stated by Terranova: “(…) in the first half of the twentieth century, information theory is
fundamentally concerned the accurate reproduction of an encoded signal” (Terranova, Network
Culture: Politics for the Information Age 10).
[16] When referring to information, Galloway and Thacker define it as being “both immaterial and
materializing, abstract and concrete, an act and a thing” (Galloway, Thacker 20).
[17] Terranova, for instance, claims that the “immateriality of information has been further amplified
by technical developments that have made possible the instant transmittal and multiple distribution
of any type of information at all” (Terranova, Network Culture: Politics for the Information Age 6).
[18] Crasson defines meaning as “what makes sense, produces no surprises, requires a minimal amount
of information to define its shape” (Terranova, Network Culture: Politics for the Information Age 14).
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the two entities advocating that “information and meaning might be reversely proportional:
the more information the less meaning” (Terranova, Network Culture: Politics for the
Information Age 14) which may then suggest that the current informational society is going
through a crisis of meaning [19].
Such situation potentially undermines the acquisition of knowledge as the accumulation of
relational meaning over time. On this matter, it is interesting to note that some authors
establish a continuum from data to knowledge, including information in between [20], but
without contemplating meaning which might indicate the secondarization of such notion.
On a micro level perspective, the overwhelming amount of information made available via a
multitude of technological platforms can impact the individual on two levels: a sub-
conscious level since, as defended by McLuhan regarding technology, “the effects (…) do not
occur at the level of opinions or concepts, but alter sense ratios or patterns of perception
steadily and without any resistance” (McLuhan 207), and a conscious level as the individual
is forced to distribute his time and select what to focus on giving rise to, what Terranova
denominates, “the attention economy” where attention becomes not only a commodity, but
also a type of capital (Terranova, “Attention, Economy and the Brain” 2).
Does this fact reinforce the crisis of meaning aforementioned or does it merely suggest a
mutation in its character as it happened in previous historical moments [21]?
If meaning is intersubjective, in opposition to information which is objective, as some
authors claim [22], then it is only natural that it will mutate over time and acquire contours
affecting consequently the creation and maintenance of knowledge.
Having briefly described the notions of data, databases, information, meaning and
knowledge, and some of the theories surrounding the same as a required prelude to a data
art discussion, it is now the moment to move forward to considerations regarding aesthetic
aspects.
[19] The increasing loss of meaning is one of the features attributed to, what Dean refers as,
“communicative capitalism” as described in Blog Theory: Feedback and Capture in the Circuits of
Drive.
[20] As a reference, consult the 2007 article by Zins on “Conceptual approaches for defining data,
information, and knowledge”, and the 2009 paper from Chen et al. on “Data, Information, and
Knowledge in Visualization.”
[21] As an example of previous historical moments when a modification of meaning occurred, Dean
refers the example of avant-garde art from the late nineteenth and early twentieth century (Dean 90).
[22] On this matter, see the 1995 article “Information and meaning: foundations for an intersubjective
account” by Mingers.
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4. Data Aesthetics and Conceptualism
The necessity of extracting meaning out of a vast amount of data is, in most cases, fulfilled
not through purely textual methods but via graphical visualizations [23]. This is by no means a
contemporary and innovative solution as using illustrations to portray a relatively high
volume of information in a simplified manner is a technique with some centuries [24]. In any
case, the goal has remained fundamentally the same throughout time. As stated by Tufte, a
north-American professor and author considered to be a pioneer in the field of data
visualization, “what is to be sought in designs for the display of information is the clear
portrayal of complexity” (Tufte, The Visual Display of Quantitative Information 191).
What differ at this moment in time are the volume and the (potentially) democratic
accessibility to data and tools enabling the production of such visualizations. The minimal
requirements for information visualization to be labeled as such, have been established
by some authors as including the following features: 1) the visualization is based on (non-
visual) data; 2) it produces an image; 3) the result is readable and recognizable (Kosara, 2)
[25].
However, not all of these graphical representations fall under the same category. Some
authors differentiate between infographics and information visualization stating that they
“exist on a continuum” (Cairo) with presentation and exploration in each end respectively. If
a graphical representation allows for low degree of exploration then it would be more
accurately denominated as infographic and vice-versa: if the graphical representation would
demand more involvement from the recipient’s part, then it should be labeled as information
visualization.
[23] On a parallel note, it may be interesting the read Flusser’s view on the invention of, what he labels
as, “technical images” (any image produced by an apparatus) as the answer to the crisis of text and
history in Towards a Philosophy of Photography.
[24] Currently, there is an increased interest in establishing a history of infographics and information
visualization as evidenced by the number of publications and even exhibitions on the matter. As a
reference for the first see Mapping the Nation: History and Cartography in Nineteenth-Century
America by Susan Schulten and Cartographies of Time: A History of the Timeline by Anthony
Grafton and Daniel Rosenberg; and for the latter “About the history of infographic - An Exhibition of
rare information graphics collectibles” by the Academy of Journalism and Medias (AJM) from
Université de Neuchâtel held between 12 - 16 December 2011.
[25] Tufte proposes more detailed criteria for graphical excellence in the first chapter of The Visual
Display of Quantitative Information but, since the present focus moves beyond the pure realm of
information visualization, those requirements will not be discussed here.
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In a number of fields (such as science, engineering or even journalism), these visualizations
are assessed according to their efficiency: the more information and clearer meaning they are
able to convey to any recipient in a short period of time, the more successful they would be
from a purely utilitarian point of view. In these cases, information visualization complies
with concepts and criteria originated in the intersection between design, statistics and
computer science. As observed by Tufte “To envision information (...) is to work at the
intersection of image, word, number, art.” (Tufte, Envisioning Information 9).
What kinds of shift do these features related to functionality and efficiency suffer when data
– both as subject and as material [26] - moves into the art world?
Some authors state that the understanding of this type of projects within the artistic sphere
is reached through the question of why the textual and numerical should be mapped into the
visual in opposition to how (Sack 1) which can then lead to a discussion on aesthetics. This
approach highlights the function of the senses taking aesthetics as “a field of inquiry, [which]
examines issues of sensation and perception and seeks to understand why something is (…)
emotionally, sensually moving” (Sack 1).
On the crossroads between information and aesthetics, Manovich relies on the specific term
“info-aesthetics” to refer to “various new contemporary cultural practices which can be best
understand as responses to the new priorities of information society: making sense of
information, working with information, producing knowledge from information” (Manovich,
“The Shape of Information” 2).
The author proceeds to question the form that information takes currently, arguing that the
artistic projects dealing with the representation of data and information cannot be
circumscribed under the label of classical art (concerned with human form) or modern art
(concerned with abstract form).
Would these projects be more accurately classified under a new label such as
informationalism (as defined by Castells) [27]? If this would be the case, then what would be
the material form of a movement which deals with highly dynamic and endless immaterial
[26] As noted by Whitelaw: “new media art has in recent years turned towards data as both subject and
material.”
[27] Castells defines informationalism as a “technological paradigm based on the augmentation of the
human capacity of information processing and communication made possible by the revolutions in
microelectronics, software, and genetic engineering” (Castells, 11).
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flows [28]? And how stable could this form be [29]?
Some authors consider “data art” within the conceptual art frame (Sack 4). Emerging in
the late 1960s, the conceptualist movement is based on four basic premises [30]: 1) the art
work is mainly focused on an idea or a concept (rather than a material object), 2) the
distinction between art and language becomes blurred, 3) it entails a critique to the
commercialization of art, 4) it disrupts ownership processes translated into social status and
cultural authority.
The central and predominant role of a concept or idea within the contemporary art scene
appears to be a more general trend as noted by Manovich: “a typical contemporary artist who
was educated in the last two decades is no longer making paintings, or photographs, or video
– instead, s/he is making ‘projects.’ This term appropriately emphasizes that artistic practice
has become about organizing agents and forces around a particular idea, goal, or procedure.
It is no longer about a single person crafting unique objects in a particular media.”
(Manovich, “Don’t Call It Art” 6).
Another discussion on data art initiated by Manovich is the one which explores its
relationship with the sublime. In his 2002 article The Anti-Sublime Ideal in Data Art, the
author claims that data art seems to fail on the representation of a “personal subjective
experience of a person living in a data society” (Manovich, “The Anti-Sublime Ideal in Data
Art” 15) displaying choices which often appear as arbitrary and being partially affiliated with
modern science (in its desire to map the macro and the micro, the infinite and the endless
into manageable visual objects).
Sack, in his article on Aesthetics of Information Visualization, is one of the authors refuting
this idea which subscribes anti-sublime projects mainly to the scientific arena and moves
[28] In an article on “Information and Form”, Manovich defends that information can be translated
into form (albeit a different form than the one assumed in previous artistic movements), but what may
be challenging is how to present the same in the institutionalized art venues such as museums and
galleries without nullifying or restricting its core properties.
[29] On this matter, Sack writes that these visualizations attempt to portray bodies which are at
“constantly at risk due to disk crashes, miniaturization, noisy networks, and, in general,
disappearance. These bodies are under threat of destabilization, dematerialization, and
disembodiment” (Sack 13) which is in tune with Chun’s idea that “the digital, if it is anything, is the
enduring ephemeral” (Chun 95).
[30] As defined in …Isms – Understanding Art by Stephen Little.
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forward to associate some data art projects with the notion of sublime as defined by Kant [31].
In a more practical approach, Kosara establishes the utilitarian and the sublime as the
extremes of a continuum where the pragmatic visualizations would be placed under the first
and artistic visualizations under the latter (Kosara 3). The same author highlights the need to
establish “visualization criticism” as a means to develop the theory and the language which
are largely missing in this specific field (Kosara 4).
On a broader level, one possible methodology proposed to distinguish art from non-art relies
on attention as “attention alters what is attended” (Kaprow 236) as exposed by Fuller in “Art
Methodologies in Media Ecology”. The environment in which projects are contextualized
assumes then a crucial part in, what Fuller labels as, an “attempt to forestall “humans'
propensity to 'inattentional blindness'” (Mack and Rock, 2000) (Fuller, “Art Methodologies
in Media Ecology” 53).
This idea is somehow reminiscent of the concepts of distraction and concentration in relation
to a work of art as formulated by Benjamin. According to the author, these are antagonistic
aspects as “A person who concentrates before a work of art is absorbed by it; he enters into
the work (...). By contrast, the distracted masses absorb the work of art into themselves”
(Benjamin, 40). Such notions stress the role of the environment and the perceptual attitude
towards art in the definition of art itself.
Some of the theories and approaches described above may shed some light into a provisory
set of criteria enabling the identification of data art projects (in opposition to information
visualization works). These requirements for defining a data art project can be summed up as
follows: the primary goal should be to communicate a concept or idea [32] (beyond the
functional visualization of a phenomenon), it should require the engagement of the recipient
[31] In Observations on the Feeling of the Beautiful and Sublime, Kant distinguishes sublime from
beautiful in the following manner: “the sublime must always be great; the beautiful can also be small.
The sublime must be simple; the beautiful can be adorned and ornamented” (Kant 48). The
philosopher further defines three types of sublime: the terrifying, the noble and the splendid sublime.
In his work, Kant critiqued some of Burke’s more radical theories included in A Philosophical Enquiry
into the Origin of Our Ideas of the Sublime and Beautiful published eight years before which defined
the sublime as the strongest emotions a human being could feel, but usually associated with more
negative aspects such as pain and horror (Burke 47).
[32] On this matter, Manovich asserted that “if brilliant computer images are not supported by equally
brilliant cultural ideas, their life span is very limited” (Manovich, “Don’t Call It Art” 10).
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in a non-immediate manner [33] for the concept to be explored and, at least partially,
understood, it should provoke some reaction from the recipient which goes beyond
contemplation [34] (as the visualization does not necessarily need to be visually pleasing as
referred previously when discussing the relationship between data art and the sublime).
[33] This lack of immediacy can be illustrated by Adorno’s saying: “It is self-evident that nothing
concerning art is self-evident.” (Adorno 1).
[34] As Fuller puts it: “Art provides a lightning rod to sensations, a discipline for finding the means to
allow sensation to couple itself with a multiple form of materiality” (Fuller, “Art Methodologies in
Media Ecology” 48).
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5. Analyzing Data Art
In "Art Against Information: Case Studies in Data Practice", Whitelaw analyses several data
art projects and classifies them according non-exclusive categories as discursive devices to
describe their properties and potential goals.
The selected projects were sorted according to their connection to reality: 1) as indexical or
non-indexical and 2) as consonant or dissonant; and their relation to information 3) as
informational, un-informational (holding a neutral, and perhaps uninterested, stance to the
extraction of information) and anti-informational, and either 4) focusing mainly on data or
on information – a set of criteria which originates a myriad of combinations.
These are undoubtedly useful categories to examine different types of projects and provide a
glimpse into their diversified properties, but other typologies of classification are equally
possible and valid depending on the focus at stake. On a more functional approach it would
be possible to classify the projects according to the materiality of the input and the output as
digital or physical or a combination of both. It would be possible to distinguish the projects
according to the data source as the internet or the “outer-internet” (even if many projects
deal with data originated in the web and increasingly in social media platforms).
What follows is a presentation of specific data art projects according to some of the criteria
exposed above to highlight the aspects which appear to be more fruitful for a discussion on
the matter.
5.1 - Beyond Digital: Embracing the Physicality
As described previously, data art projects do not necessarily have a digital output and require
computational interfaces.
In 2011 the Dutch artist Erik Kessels produced an installation with one million printed
photos posted on Flickr during a 24-hour period and dumped through several rooms of the
exhibition space (Foam, Amsterdam). The artist envisioned the feeling of “drowning in
pictures of the experiences of others” [35] and the most visitors felt compelled to randomly
select some photos from the several piles distributed through the space or simply dive into
the pools of imagery extracted from the web platform.
The printed photos had no underlying narrative except for the fact that they had been
uploaded to Flickr during a set period of 24 hours, therefore each photo was no more than a
[35] As described in Foam’s press release: <http://foam.org/press/2011/whatsnext>.
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decontextualized digital residue of someone else’s life. The visitor could then just pass by and
engage with the installation at a macro-level by merely contemplating the physical
dimension of a glimpse of digital activity or he/she could interact with it at a micro-level and
attach an imagined narrative to arbitrary images picked up and thrown to the piles of photos.
However, the sheer amount of images available seriously hampers the propensity for genuine
engagement with individual items since the visitor ends up extracting “sameness even from
what is unique” as described by Benjamin in his writings on the technological reproducibility
of art works.
The goal of the installation seems to be dual: on one hand the physical illustration of the
notion of informational space as an immersive area, a “field of displacements, mutations and
movements that do not support the actions of a subject, but decompose it, recompose it and
carry it along” (Terranova, Network Culture: Politics for the Information Age 37); and on
the other hand the representation of the progressive erosion of the boundaries between
private and public information [36] – in this case in the shape of memories [37].
Another project translating data into a physical output is Invisible Airs (2011) by Ioha
described as “an investigation of Power, Governance and Data informed by the expenditure
database of Bristol City Council” [38]. Exploring several aspects of political and social nature,
the project included the creation and public presentation of five pneumatic contraptions
(which Graham Harwood defines as “where the technical and the imaginary overlap”) : the
older people pneumatic floor polisher , the public expenditure riding machine, the open data
book stabber, the expenditure Filled Potato Cannon and the expenditure Filled Spud Gun.
The title of the project illustrates the analogy between air and data as two ubiquitous entities
crucial in life maintenance and yet invisible to all. By materializing data in an uncommon
manner – in this case, converting the City Council’s expenditure into proportional air
pressure feeding each one of the contraptions in a specific manner - the artists hoped to
engage people with data in ways they would not normally understand.
In an attempt to increase political transparency, several governmental institutions in the UK
made their data publicly available. What the artists discovered while preparing the material
for their project, was that open data was not synonym to providing access to all data
[36] This idea is illustrated by the following Dean’s statement: “our participation in social networks
relies on the supposition that we expose but are not exposed, that we are unique but ultimately
indistinguishable” (Dean 66).
[37] See the BBC article “Artist Erik Kessels unveils 24 hour photo installation”
<http://www.bbc.co.uk/news/entertainment-arts-15756616>.
[38] As described in <http://yoha.co.uk/invisible>.
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available [39] which undermines the concept and the goal of open data from the start.
However, executing “dataset forensics” (examining which data are missing from the publicly
available database and uncover connections between different sets) requires an investment
in terms of time and energy that most citizens are not willing to make. If increasingly more
institutions make their data public, could this trend eventually lead to diminished public
vigilance as citizens become overwhelmed by the volume of data while simultaneously being
devoid of means to extract meaningful information out of it?
As advocated by Dean: “All the data in the world – as if such a fantasy of static completion
were even possible – are useless without a question to cut through and organize them” (Dean
94).
When staging the contraptions and inviting the public to experience the actions produced by
them (as a result of expenditure data feeding), the artists concluded that the most impactful
interventions were the ones where the public could physically feel, in their bodies, the effects
of data [40] which stresses the importance of data art as moving “towards immersion and
sensation; it emphasizes openness and intuition, rather than the extraction of value or
meaning” (Whitelaw).
5.2 - The I, the You and the Us in Web Data
One of the properties of data art is its ability to map macro and micro phenomena and
respective connections and reflect the same into a scale that human perception and cognition
are able to grasp (Manovich, “The Anti-Sublime Ideal in Data Art” 11).
Our participation on social media platforms and use of web services enables the collection of
personal information beyond the realm of standard demographics to an extent that “it is as if
the inner workings of private worlds have been pried open because their inputs and outputs
have become thoroughly traceable” (Latour 2).
In the interactive installation I Want You To Want Me by Jonathan Harris and Sep Kamvar
commissioned by the Museum of Modern Art for their "Design and the Elastic Mind" 2008
exhibition [41], the artists worked with real-time data captured from dating sites focusing on
textual elements which provided information on who is the user is and what is he/she
looking for.
The project has an indexical nature and “aims to be a mirror, in which people see reflections
[39] See <http://yoha.co.uk/expenditure>.
[40] See <http://yoha.co.uk/ia_documentary>.
[41] See <http://www.iwantyoutowantme.org/>.
16
of themselves as they glimpse the lives of others” (Harris, Kamvar, 2008).
In this particular case, the “database became the site to derive the other” (Rogers 32) on the
most personal level. As the artists describe it, the personal profiles work as “modern
messages in a bottle” as it remains unclear if someone will read a profile and, if so, when and
who will that person be.
Databases and digital interfaces offer contemporary functionalities to improve the classical
role of the ocean as a metaphorical carrier of the message and fine-tune the delivery to
adequate recipients, but the mystic associated to the imagery of a message in a bottle might
have trouble finding an equivalent in a multitude of ever-changing database entries. Yet, the
theoretical exhaustiveness and potential relationality of databases holds the promise that
what we are looking for is always within reach via technological means.
Once again, the simultaneous exploration of the micro and macro is allowed as the visitor
can focus on an individual profile or examine general trends regarding most popular first
dates, turn-ons, desires, self-descriptions and interests through the five formal movements
offered in the interactive interface: Who I Am, What I Want, Snippets, Matchmaker, and
Breakdowns.
Through the individual snippets and the collective relational movements, the project
explores the search for love, but also the search for self as the artists consider the
information contained in dating sites as a “fertile ground to build a mosaic of humanity” [42].
5.3 - Data as a Labor Icon
The Sheep Market [43], a 2006 thesis project by Aaron Koblin, takes interaction to a
collaborative level and, inspired by the concept and process of Amazon’s Mechanical Turk
[44], requested users to perform a predetermined task in exchange for a small amount of
money ($USD 0.02). In this particular case, the task consisted in drawing one sheep and the
requested task was not, by any means, random as the selected animal aimed at reflecting
crucial social, cultural and economic moments in human history using sheep as a symbol [45].
The artist gathered 10.000 submissions forming a massive database of human drawings
[42] See <http://www.youtube.com/watch?v=GZUaXDm4qik>.
[43] The official website of the project is <http://www.thesheepmarket.com/>.
[44] For additional information on Amazon’s Mechanical Turk, visit
<https://www.mturk.com/mturk/welcome>.
[45] The contextualization of the sheep choice is provided at length in Section 2.1 – Elements of
sheepology, see: <http://www.aaronkoblin.com/work/thesheepmarket/thesheepmarket.doc>.
17
which were presented both offline (in five different exhibitions) and online (in the official
website).
Behind an apparent simplicity, the project ponders over the notion of post-industrialized
labor in a globalized digital economy and refers to aspects such as exploitation and creativity.
As stated by the artist, the objective was to “cast a light on the human role of creativity
expressed by workers in the system, while explicitly calling attention to the massive and
insignificant role each plays as part of a whole” (Koblin 8).
Some of the ideas explored seem to resonate with Terranova’s theories of free labor in the
context of this new economy and the voluntary channeling of collective cultural labor into
capitalist practices (Terranova, Network Culture: Politics for the Information Age 80), but
in this experiment the artist seems to move one step further. While in free labor practices the
activities undertaken are in many cases not faced as work [46] and not remunerated in the
standardized manner (through an agreed payment), in The Sheep Market the users provided
their contribution as acknowledged remunerated labor and did not necessarily derive any
pleasure or meaning from it. If concerning free labor, the author stresses “voluntary
channeling” over “exploitation”, in this particular experiment it is difficult to circumvent that
notion from the starting point. Interestingly, the feeling of exploitation seems to only reach
the participants when the artist decides to publicly sell the fruit of their labor which indicates
that most individuals are not averse to this type of alienation processes as long as they feel
they receive “their fair share”.
In this particular case, the database became a symbol of human labor exploitation in a digital
economy and its updated capitalist modes of production.
[46] As a consequence of the “blurred territory between production and consumption, work and
cultural expression” (Terranova, Network Culture: Politics for the Information Age 75).
18
6. Data Art as Info-Critique
In a period of data ubiquity, information visualization seeks to illustrate selected sets of data
and particular connections between them in order to produce useful and graspable
information (either in a ready-made format or requiring partial processing from the
recipient’s part). Through means of software, “the invisible whole emerges as a thing, as
something in its own right, and users emerge as mapping subjects” (Chun Programmed
Visions: Software and Memory 71).
While reflecting a “contemporary worldview informed by data excess; ungraspable quantity,
wide distribution, mobility, heterogeneity, flux” (Whitelaw 12), data art moves beyond the
functional role of illustration and, in opposition to data visualization, does not have as an
ultimate goal the creation of information. In fact, most projects in this area could be
classified under an info-critique label [47] as they deal with data and databases – both as
material and object – to expose previously unexplored properties of the same in connection
with social, cultural, financial or political aspects without aiming at the standard notion of
information [48].
In this sense, data art ruptures what is the apparent linear linkage between data and
information and populates the resulting fissures exploring omissions and proposing new
relationships and perspectives which, in many cases, originate parallel versions of alternative
meaning [49].
[47] Whitelaw advocates that data art resists information, but even when the artist makes the voluntary
and explicit effort to conceal or annihilate information, this always leaks through data so the artist’s
role would be to acknowledge this “impurity” of the material.
[48] Some projects display a more immediate and direct stance on their critique to the overwhelming
number of information visualization projects which widely circulate in a variety of areas on the most
diverse topics by completely disrupting the connection between data, information and graphics. These
are two examples of pieces which could be classified under the info-critique label: Nonsensical
Infographics (2009) by Chad Hagen – see <http://www.chadhagen.com/Nonsensical-Infographics>
and read <http://www.20x200.com/email/edition-announcement-196-chad-hagen.html>; and
Getting Lost (2012) by Marco Bagni – see <https://vimeo.com/37031074> and read
<http://www.thefunctionalart.com/2012/10/the-dysfunctional-art.html>.
[49] This idea of exploring the data’s vast potential can be partially reminiscent of Everett’s notion of
multiverse as composed of a quantum superposition of very many, possibly even non-innumerably
infinitely many, increasingly divergent, non-communicating parallel universes or quantum worlds.
19
Data art does not demonize disorder [50], but does not necessarily glorify it either – the focus
is on repurposing data to emphasize narratives invisible through the classical informational
patterns regardless of their format.
Possibly the most fundamental role of data art is to question information indexicality as we
currently know it and the cognitive structures it demands. As Chun puts it: “could it be that
rather than resort to maps, we need to immerse ourselves in networked flows - time-based
movements that both underlie and frustrate maps?” (Chun, Programmed Visions: Software
and Memory 75).
However, Chun’s suggestion entails a somehow radical approach and an intermediate
standpoint might prove to be more reasonable and, eventually, more fruitful. If one can only
derive meaning from what is partially new and partially familiar (Terranova, Network
Culture: Politics for the Information Age 14) and data art is not averse to meaning (as an
distinct entity from information), then a certain degree of indexicality (regardless of how
minimal) which enables a direct correspondence to reality in a standard manner might be
required in data art projects in order not to alienate the public, but instead truly engage them
in the exploration of alternative meanings deriving from data [51]. While not being totally
disruptive towards the mapping process and respective indexicality, such an approach does
not undermine the role of data art as art either as it leaves plenty of space for exploration
towards different directions having data as a vehicle.
If information visualization aims at enriching the density of data displays and escaping the
flatlands of the two-dimensional paper and computer screen (Tufte, Envisioning
Information 33), then data art should perhaps focus on deflating datasets and creating
alternative landscapes.
[50] As it was the case with cybernetics which “made an angel of control and a devil of disorder”
(Galison 40).
[51] In one of the data art projects referred in section 5.1 (Invisible Airs), the artists concluded that the
public was not able to engage with the most conceptual contraptions which might reinforce this idea
that a certain degree of indexicality through the means of the traditional mapping process is still a
requirement for the extraction of meaning from data art projects.
20
Bibliography
Adorno, Theodor. Aesthetic Theory. Continuum International Publishing Group, 2004. 25
December 2012. <http://books.google.nl/books?id=NGxSnig-u3wC>.
AJM. “Exhibition: About the History of Infographics.” Academy of Journalism and Medias
(AJM) from Université de Neuchâtel (exhibition held between 12 - 16 December
2011). 2012. 19 December 2012. <https://vimeo.com/35835303>.
Anderson, Chris. “The End of Theory: The Data Deluge Makes the Scientific Method
Obsolete.” Wired. 23 June 2008. Condé Nast. 9 December 2012.
<http://www.wired.com/science/discoveries/magazine/16-07/pb_theory>.
Bagni, Marco. Getting Lost. 2012. 20 December 2012 <https://vimeo.com/37031074>.
BBC. “Artist Erik Kessels unveils 24 hour photo installation.” 16 November 2011. British
Broadcasting Company. 25 December 2012.
<http://www.bbc.co.uk/news/entertainment-arts-15756616>.
Benjamin, Walter. “The Work of Art in the Age of Its Technological Reproducibility” [1935].
The Work of Art in the Age of Its Technological Reproducibility and Other Writings
on Media. Eds. Michael W. Jennings, Brigid Doherty and Thomas Y. Levin.
Cambridge, MA: The Belknap Press, 2008. 19-55.
Bowker, Geoffrey. Memory Practices in the Sciences (Inside Technology). Cambridge,
Massachusetts: The MIT Press, February 2008.
Boyd, Danah, and Kate Crawford. “Critical Questions for Big Data: Provocations for a
Cultural, Technological, and Scholarly Phenomenon.” Information, Communication,
& Society 15. 5 (May 2012): 662-679.
Burke, Edmund. A Philosophical Enquiry into the Origin of Our Ideas of the Sublime and
Beautiful. Basil, 1792. 23 December 2012.
<http://books.google.nl/books?id=UroAAAAAcAAJ>.
21
Cairo, Alberto. “The dysfunctional art: Marco Bagni's "Getting Lost" video.” 30 October
2012. The Functional Art – A Book by Alberto Cairo. 22 December 2012.
<http://www.thefunctionalart.com/2012/10/the-dysfunctional-art.html>.
Cairo, Alberto. The Functional Art: An introduction to information graphics and
visualization. Berkeley: New Riders, 2012. 1 December 2012.
<http://books.google.nl/books?id=xwjhh6Wu-VUC>.
Castells, Manuel. “Informationalism, Networks, and the Network Society: A Theoretical
Blueprint.” The Network Society: A Cross-Cultural Perspective. Northampton, MA:
Edward Elgar, 2004. 23 December 2012.
<http://annenberg.usc.edu/Faculty/Communication/~/media/Faculty/Facpdfs/Info
rmationalism%20pdf.ashx>.
Chen, Min et al. “Data, Information, and Knowledge in Visualization.” Computer Graphics
and Applications 29. 1 (2009): 12-19. 10 December 2012.
<http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=4736452>.
Chun, Wendy Hui Kyong. “On Software, or the Persistence of Visual Knowledge.” Grey
Room. 18 (2004): 26-51.
Chun, Wendy Hui Kyong. Programmed Visions: Software and Memory. Cambridge: The
MIT Press, 2011. 25 December 2012. <http://books.google.nl/books?id=n15KIako-
s4C&dq>.
Cohen, Patricia. “Digital Keys for Unlocking the Humanities’ Riches.” The New York Times.
16 November 2010. The New York Times Company. 9 December 2012.
<http://www.nytimes.com/2010/11/17/arts/17digital.html>.
Dean, Jodi. Blog Theory: Feedback and Capture in the Circuits of Drive. London: Polity
Press, 2010.
Deleuze, Gilles. “Postscript on Societies of Control.” The MIT Press 59. (Winter 1992): 3-7.
22
FastCompany. “Chad Hagen's Nonsensical Infographics: BYO Data.” 15 September 2009.
Mansueto Ventures LLC. 24 December 2012.
<http://www.fastcompany.com/1358723/chad-hagens-nonsensical-infographics-
byo-data>.
Flusser, Vilém. Towards a Philosophy of Photography. London: Reaktion Books, 2000.
Foam. “The Future of the Photography Museum - Press Release.” 17 October 2011. Foam. 25
December 2012. <http://foam.org/press/2011/whatsnext>.
Fuller, Matthew. “Art Methodologies in Media Ecology.” Deleuze, Guattari, and the
Production of the New. Eds. Simon O'Sullivan and Stephen Zepk. London:
Continuum, 2008. 45-55.
Fuller, Matthew, and Andrew Goffey. “Toward an Evil Media Studies.” The Spam Book: On
Viruses, Porn and Other Anomalies From the Dark Side of Digital Culture. Eds.
Jussi Parikka and Tony D. Sampson. New York: Hampton Press, 2009. 141-159.
Galison, Peter. “The Ontology of the Enemy: Norbert Wiener and the Cybernetic Vision.”
Critical Inquiry 21. 1 (1994): 228-266.
Galloway, Alexander. “Language Wants to be Overlooked: On Software and Ideology.”
Journal of Visual Culture 5. 3 (2006): 315–331.
Galloway, Alexander, and Eugene Thacker. “Protocol, Control and Networks.” Grey Room 17
(2004): 6-29.
Galloway, Alexander, and Geert Lovink and Eugene. Thacker. “Dialogues Carried Out in
Silence: An Email Exchange.” Grey Room. 33 (November 2008): 96-112.
Gillespie, Tarleton. "Can an Algorithm be Wrong?" Limn. 2 (2012). 12 December 2012.
<http://limn.it/can-an-algorithm-be-wrong/>.
Grafton, Anthony and Daniel Rosenberg. Cartographies of Time: A History of the Timeline.
New York: Princeton Architectural Press, 2010. 23 December 2010.
<http://books.google.nl/books?id=SBzI64enXZwC>.
23
Hagen, Chad. Non-sensical infographics. 2009. 20 December 2012.
<http://www.chadhagen.com/Nonsensical-Infographics>.
Harris, Jonathan, and Sep Kamvar. I Want You to Want Me. 2008. 15 December 2012.
<http://www.iwantyoutowantme.org/>.
Harris, Jonathan, and Sep Kamvar. I Want You to Want Me [Video]. 2008. 15 December
2012. <http://www.youtube.com/watch?v=GZUaXDm4qik>.
Jennings, Michael. “The Production, Reproduction and Reception of the Work of Art.” The
Work of Art in the Age of Its Technological Reproducibility and Other Writings on
Media. Eds. Michael W. Jennings, Brigid Doherty and Thomas Y. Levin. Cambridge,
MA: The Belknap Press, 2008. 9-18.
Kant, Immanuel. Observations on the Feeling of the Beautiful and Sublime. Berkeley:
University of California Press, 1960. <http://books.google.nl/books?id=K-
9G31HUQEwC>.
Kaprow, Allan. Essays on the Blurring of Art and Life. Berkeley: University of California
Press, 1993. 23 December 2012. <http://www.amazon.com/Essays-Blurring-Art-
Life-Expanded/dp/0935721355>.
Koblin, Aaron. The Sheep Market. 2006. 20 December 2012.
<http://www.thesheepmarket.com/>.
Koblin, Aaron. The Sheep Market: Two Cents Worth. 2006. Design - Media Arts, UCLA,
Thesis Document. 20 December 2012.
<http://www.aaronkoblin.com/work/thesheepmarket/TheSheepMarket.doc>.
Kosara, Robert. Visualization Criticism – The Missing Link Between Information
Visualization and Art. Proceedings of the 11th International Conference on
Information Visualisation (IV), 2007. 631–636. 23 December 2012.
<http://viscenter.uncc.edu/sites/viscenter.uncc.edu/files/CVC-UNCC-07-07.pdf>.
Latour, Bruno. “Beware, your imagination leaves digital traces.” Times Higher Literary
Supplement. 6 April 2007. 26 December 2012. <http://www.bruno-
latour.fr/sites/default/files/P-129-THES-GB.pdf>.
24
Little, Stephen. …Isms – Understanding Art. New York: Universe Publishing, 2004.
Manovich, Lev. “Database as a Symbolic Form.” Articles. 1998. 20 December 2012.
<http://www.manovich.net/articles.php>.
Manovich, Lev. “Don’t Call it Art.” Articles. 2003. 20 December 2012.
<http://www.manovich.net/articles.php>.
Manovich, Lev. “Information and Form.” Articles. 2000. 20 December 2012.
<http://www.manovich.net/articles.php>.
Manovich, Lev. “Information as an Aesthetic Event.” Articles. 2007. 25 December 2012.
<http://www.manovich.net/articles.php>.
Manovich, Lev. “The Anti-Sublime Ideal in Data Art.” Articles. 2002. 22 December 2012.
<http://www.manovich.net/articles.php>.
Manovich, Lev. “The Shape of Information.” Articles. 2005. 20 December 2012.
<http://www.manovich.net/articles.php>.
Manovich, Lev. “Trending: The Promises and the Challenges of Big Social Data.” Articles.
2011. 22 December 2012. <http://www.manovich.net/articles.php>.
McLuhan, Marshall. “Two Selections - The Galaxy Reconfigured, The Medium Is the
Message.” The New Media Reader. Eds. Noah Wardrip-Fruin and Nick Monfort.
Cambridge, MA: MIT Press, 2003. 193-209.
Mingers. J. C. “Information and meaning: foundations for an intersubjective account.”
Information Systems Journal 5. 4 (October 1995): 285–306: 18 December 2012.
<http://onlinelibrary.wiley.com/doi/10.1111/j.1365-2575.1995.tb00100.x/abstract>.
Rieder, Bernhard, and Theo Röhle. "Digital Methods: Five Challenges." Understanding
Digital Humanities. Ed. David M. Berry. Basingstoke, UK: Palgrave Macmillan, 2012.
67-84.
25
Rogers, Richard. "Post-demographic Machines." Walled Garden. Eds. Annet Dekker and
Annette Wolfsberger. Amsterdam: Virtueel Platform, 2009. 29-39. 23 December
2012.
<http://www.govcom.org/publications/full_list/WalledGarden_ch04_RR.pdf>.
Sack, Warren. “Aesthetics of Information Visualization.” Context Providers: Conditions of
Meaning in Media Arts. Eds. Margot Lovejoy, Victoria Vesna, Christiane Paul.
Bristol: Intelect, 2011.
Schulten, Susan. Mapping the Nation: History and Cartography in Nineteenth-Century
America. Chicago: The University of Chicago Press, 2012. 19 December 2012.
<http://books.google.nl/books?id=nbdEEf91HPoC>.
Terranova, Tiziana “Attention, Economy and the Brain.” Culture Machine. 13 (2012). 20
December 2012.
<http://www.culturemachine.net/index.php/cm/article/view/465/484>.
Terranova, Tiziana. Network Culture: Politics for the Information Age. London: Pluto Press,
2004.
Terranova, Tiziana. “New Economy, Financialization and Social Production in Web 2.0.”
Crisis in the Global Economy: Financial Markets, Social Struggles and New
Political Scenarios. Eds. Andrea Fumagalli and Sandro Mezzadra. Los Angeles:
Semiotext(e), 2010. 153-170.
Tufte, Edward. Envisioning Information. Chesire, Connecticut: Graphics Press, 1990.
Tufte, Edward. The Visual Display of Quantitative Information. Chesire, Connecticut:
Graphics Press, 2001.
Whitelaw, Mitchell. "Art Against Information: Case Studies in Data Practice." The
Fibreculture Journal. 11: 2008. 1 December 2012.
<http://eleven.fibreculturejournal.org/fcj-067-art-against-information-case-studies-
in-data-practice/>.
Wikipedia. “Many-worlds interpretation.” 2012. Wikimedia Foundation. 26 December 2012.
<http://en.wikipedia.org/wiki/Many-worlds_interpretation>.
26
Yoha. Invisible Airs - Database, Expenditure & Power. 2011. 25 December 2012.
<http://yoha.co.uk/invisible>.
Yoha. Invisible Airs - Documentary. 2011. 25 December 2012.
<http://yoha.co.uk/ia_documentary>.
Yoha. Invisible Airs - Expenditure Data. 2011. 25 December 2012.
<http://yoha.co.uk/expenditure>.
Zins, Chaim. “Conceptual approaches for defining data, information, and knowledge.”
Journal of the American Society for Information Science and Technology 58. 4 (15
February 2007): 479-493. 10 December 2012.
<http://onlinelibrary.wiley.com/doi/10.1002/asi.20508/full>.