• TomCorby

Part 1: Earth imaginaries and critical data

Updated: Apr 20


Climate data oxygen watercolour (Corby/Baily 2009)


We do not possess an imaginary of climate change that is capable of accounting for what the science has shown us of how the planet and its climate functions, i.e. a complex of atmospheres, oceans, landmasses and energy exchanges within which we are implicated. We do not possess visual, temporal, critical and spatial languages or models of practice that can articulate these processes. We have barely begun to sketch out the subjects of this new reality and how it links to and impacts on our bodies, indigenous knowledge, decolonisation processes and wider politics in what researchers in geography call coupled natural–human systems.


As a project that engages data as a critical and representational tool towards engaging what I describe as ‘climate change in our heads’. This post is the first of two or possibly three, that attempt to draw together a number of issues related to data and its epistemologies that will be speculative, but what I hope to do is move towards a series of clarifications on how artists can employ climate data to articulate how the Earth is changing and what the issues are in respect of such an approach. I’m going to be drawing upon a range of disciplinary sources, but please don’t expect a neat academic exposition of the issues at stake, I will be jumping between subjects, cultures, epistemic traditions and topics. The scope and scale of climate change seems to demand a certain fragmentation of approach and agility to face its complexity and scales.


On data

It goes without saying that in public imagination data is inextricably linked to the digital, i.e. understood as collections of strings of alphanumeric characters; symbols; electrical signals; binary switches etc. stored and distributed across a number of different digital platforms. These components, are then subject to algorithmic and other processes which organise them into informational forms, e.g. databases or ‘digital media’ and not unproblematically used to train AI systems. In broader research contexts outside of digital discourse data refers to evidencing procedures in the sciences and social sciences, and in such terms has an epistemic function supporting hypothesis setting, knowledge production, dissemination and so forth.


From a historical perspective, Daniel Rosenberg argues an etymology of ‘data’ as derived from a theological term from the 17th Century referring to incontrovertible scriptural truths. Around the same time scientists began to use data to refer to empirical evidences gathered to test scientific hypothesis. This understanding of the term has persisted with two of the most commonly understood formulations of term being a given entity or integer in a mathematical context, or as empirical evidence (‘facts’) gathered to inform a legal process or scientific enquiry. Therefore, from an early age, ‘data’ was connected to a sense of unassailable facts framed by Enlightenment concepts of universal truth and wisdom.


The connection between data, information and knowledge is often blurred and Luciano Floridi has written extensively on this topic (not unproblematically) so I’m going to channel him as a means to unpicking a term which to use his phrase ‘enjoys considerable latitude’. He gives the example of ‘census data’ which establish facts about populations through organisation of raw data into information sets. For the sake of argument then we might say that data pre-exist information which cannot exist without it (although there is some lively debate on this matter in philosophical circles). For Floridi:


1 – Information consists of n data, for n ≥ = 1

2 – The data are well formed syntactically

3 – The well-formed data are meaningful


The relationship of data to the thing it measures is elaborated by Floridi using the concept Dedomena or ‘data in the wild’ which he describes as phenomena that exist prior to interpretation (“proto epistemic”) which are inaccessible without application of methods of abstraction (measurement, observation, formatting). Dedomena are the world in its material, social and ecological entirety; potential data whose presence is empirically observed as a difference between physical states . As ‘external anchors for information’ the measurable difference of Dedomena are capable of expression through higher levels of abstraction, (e.g. numeric and other language symbols) which reconstruct them in forms that enable analysis and comprehension (i.e. 2 and 3 above). He elaborates this by suggesting that data be understood as a lack of uniformity (for n ≥ =1) ‘in the world’ described as diaphora from the Greek meaning difference. We might think of the difference in degrees Celsius, or the plus or minus parts per million (ppm) of atmospheric carbon dioxide concentrations. Floridi’s description is essentially a classical view of data as an observer-independent phenomenon waiting to be discovered but essentially neutral.


Data in this reading are direct descriptions of a priori conditions. However, once ‘collected’ or ‘found’, data in Floridi’s terms must be ‘well formed’ or in effect represented, embodied and contextualised in some form. This does tend to undermine the premise of neutrality as it will obviously involve translation which impacts on the reception of the data.


On situating knowledge

This view of data as ‘given’ or discrete, has been the focus of much of critical data studies of recent years and has been problematised by Joanna Drucker amongst others who has cogently argued that presenting data as something ‘neutral’ elides human relational, processes of intervention. She is particularly critical of the importation of data visualisations into humanities disciplines in ways that inherit assumptions that such tools are inoculated from subjective interpretations:

Rendering observation (the act of creating a statistical, empirical, or subjective account or image) as if it were the same as the phenomena observed collapses the critical distance between the phenomenal world and its interpretation, undoing the basis of interpretation on which humanistic knowledge production is based (Drucker, 2011).

Drucker goes on to formulate an alternative to the term data, ‘capta’ which brings to the fore the act of subjective interpretation as central, to any encounter or construction of a data visualisation (or other form of data representation). Capta shifts understanding of what data is and its relationship to phenomena it measures as it emphasises data as something ‘taken’ as an activity, rather than something ‘given’ which is passively recorded. Data, in this sense is recognised as something, situated and relational, bound up with other bodies of knowing, materials, situations and sensations.


The relational and situated properties of data have also been the focus of ‘critical data’ studies (Gitelman, 2013, amongst others) who question widely-held beliefs of it as a purely objective form. Rob Kitchen, (2014) argues for a conception of data as an assemblage that is inherently bound to the social and interpretive, framed by questions of ethics and politics, and messily bound to technologies of production and production. In such terms, critical data studies aligns itself with traditions in social science that have scrutinised how science produces its knowledge, exemplified by Bruno Latour’s (in)famous We Have Never Been Modern (1992), in which he critiques the modernity on which science sits as a flawed ontology that forces a separation between human and political culture, science and nature.


Latour’s project is important as like critical data studies, it bought to the fore an understanding of science, it’s data and knowledge production, not as a unsullied process productive of incontestable ‘truth’ but as a human endeavour that is an congregation of institutions, social practices and methods geared to a common goal of knowledge and insights. We Have Never Been Modern has been seen as one of the key texts in what came to be known as the ‘science wars’, but his later writings in particular Why Has Critique Run out of Steam? From Matters of Fact to Matters of Concern (2003) have offered a mea culpa as a horrified reaction to how his arguments have been used amongst other things to deny the possibility of reality as something that can be measured and understood. Latour has stressed that his concern was not to attack science but to merely make visible the ways in which its knowledge is produced. He argues correctly that the idea of science that is active in the public imagination as something that is productive of irrefutable ‘truth’ has made it vulnerable to bad actors, as it sets an impossibly high evidential bar that is impossible to reach for the scientific community.


Climate science in particular is vulnerable as it presents degrees of likelihood and future scenarios derived from climate models that theorise and simulate the interactions of an incredibly complex range of temporal, chemical, physical, material and atmospheric processes (Edwards, 2010). The use of direct experimental methods that are capable of offering 100% verification are not practical in climate science, as we only have one planet on which to test how quickly warming is happening, climate models therefore give us a way of exploring and predicting future scenarios and past climates and have been effective in doing so.


Nevertheless, methods in climate science span processes of global temperature collection, historical records, satellite observation, proxy data (ice cores and tree rings) and outputs from complex climate modelling processes. These abstractions and the commensurate impacts on the material world represent a complex space within which climate change deniers have operated, using bad faith arguments based on expectations of ‘certainty’ and critiques of ‘theory-based’ modelling detached from reality that are difficult for science to counter in a public realm conditioned to understand scientific process as something that produces unassailable truth (Oreskes and Conway, 2010).


On representation

So, where does this leave us, in respect of a project that engages climate change from a creative point of and critical point of view with climate data? There are known issues with public data representations of climate change. Predominant approaches employ visualizations and other screen-based images, however research from geography and science communication disciplines has shown that people respond poorly to these information-heavy diagrams, seeing little connection between the abstract data values they represent and the ‘natural values’ of the ‘subjective climate’ they experience (Westerberg,1994). This effect is amplified when data graphing, visualisations and other data translations of climate change enter the public sphere, where they are received as purely numeric descriptors of phenomena, free from the semiotic, cultural, semantic and other characteristics. This has had a number of unfortunate effects as noted by Heather Houser (2016) as these graphs in public understanding signify an incontestable scientific authority making them vulnerable to misuse as they circulate far beyond their original scientific and policy environments. For example, a significant component of the tactical arsenal of climate change deniers is the mis-use and distortion of the graph form or ‘cherry picking’ of imagery and data to distort the findings of science.


That being said, 2019 signified a huge shift in public consciousness in regard the climate crisis. Recent polling has shown high levels of agreement that climate change is caused by human activity and represents an immediate and present crisis (Eurobarometer: 93% of EU citizens; CBS: more than a three-quarters of Americans both September 2019). The increasing frequency of extreme weather patterns (as I write, large areas of the eastern coast of Australia burns), combined with breakthrough global activist movements (Extinction Rebellion) shows that climate change is now front and centre in public consciousness, if still being stymied by the laggardness of politicians in developing required and timely policy.


Within arts disciplines climate change is often framed as problem of communication that artists are well placed to solve (see for example, the Climart project in Trondheim and many others). While the ambition and focus of much of this work is laudable, personally I think we are beyond this now, climate change has been communicated within the public sphere; beyond these instrumentalising approaches, something subtler and more nuanced is required to engage with what I call the ‘climate change in our heads’ which represents the all-encompassing shifts in understanding of the world as a functioning space of eco-systems and our place in it. Or to put this another way, the role of the arts moves away from a problem of motivating behaviour or raising awareness, to one of articulation of the diffuse effects and changes that the reality of climate change is forcing in our lives and cultures. This requires languages.


Specifically, within the visual arts, we do not possess an imaginary of climate change that is capable of accounting for what the science has shown us of how the planet and its climate functions, i.e. a complex of atmospheres, oceans, landmasses and energy exchanges within which we are implicated. We do not possess visual, temporal, critical and spatial languages or models of practice that can articulate these processes and we have barely begun to sketch out the subjects of this new reality and how it links to and impacts on our bodies, indigenous knowledge, decolonisation processes and wider politics in what researchers in geography call coupled natural–human systems.


One possible route to these new critical imaginaries is through data which brings us back to our project which I will elaborate in pt. 2.


References


Drucker, J. (2011), ‘”Humanities approaches to graphic display”. In: Digital Humanities

Quarterly, 5(11), pp. 1-21


Edwards, M. (2010), A Vast Machine, MIT Press.


Floridi, L. ( 2008), ”Data”, pre-print article for the International Encyclopedia of the Social Sciences, 2nd edition, ed. W. A. Darity, Detroit: Macmillan.

</www.philosophyofinformation.net/publications/pdf/data.pdf> (accessed 15th May, 2014)


Gitelman, L. (2013), Raw Data is an Oxymoron, MIT Press.


Houser, H. (2014), “The aesthetics of environmental visualizations: More than

information ecstasy?”. In: Public Culture, 26(2), pp. 319-337.


Kitchin, R. (2014) Data revolutions, London: SAGE.


Latour, B (1992), We Have Never Been Modern, Harvard University Press.

Latour, B. (2003), “Why Has Critique Run out of Steam? From Matters of Fact to Matters of Concern “. In Critical Inquiry , Vol. 30, No. 2 (Winter 2004), pp. 225-248.


Oreskes M., and Conway, E.M. (2010), Merchants of Doubt, Bloomsbury Press.


Rosenberg, D. (2013), “Data before the Fact”. In: Raw Data is an Oxymoron, MIT Press.


Westerberg, U. (1994). “Climatic planning: Physics or symbolism?”. In: Architecture & Comportement/Architecture & Behaviour. 10. 49-71.



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