Page 99 - Carbon Capitalism and Communication Confronting Climate Crisis

7 BIG DATA, OPEN DATA AND THE CLIMATE RISK MARKET 85

BIG DATA AND INFORMATIONAL POWER
Scientific knowledge about phenomena, such as climate change, is highly
data dependent. Without the appropriate data it would not be possible to
identify the extent to which the global climate has altered over the years or
analyse the potential causes. Without the ability to analyse vast amounts of
weather observation data, society would only experience the consequences
of climate change: extreme weather, rising sea levels, crop failures and so
on.
The meteorological and climate sciences have long been data-driven
disciplines (Edwards 2013). The reason we know that the climate is
changing, why it is changing, and how we should respond, is the result of
decades of complex processes of data collection, cleaning, analysis and
modelling by climate scientists. Meteorological organisations around the
world hold vast archives of weather observations that can be analysed to
predict the weather and understand average weather conditions—the cli-
mate—over time. Scientists are also exploring innovate ways to fill in the
gaps in their datasets in order to increase their understanding. For example,
citizen science projects such as Old Weather (https://www.oldweather.
org/) that use the labour of volunteer ‘citizen scientists’ to transcribe
historical shipping records, so that the digitised data can be fed into
weather observation databases and climate models.
However, it is not only scientists that are interested in using data in
order to understand and respond to changes in the climate. As meteoro-
logical data becomes more abundant and fine-grained, it—like many other
forms of data—is being increasingly exploited by those who want to use
high level data analytics in order to extract profits. This, according to
Mayer-Schönberger and Cukier (2013), is the era of “datafication” in
which more and more aspects of human existence are being quantified and
turned into computerised data. Over the last decade it has become almost
cliché to claim that “data is the new oil”,or—as the former European
Commissioner for Digital Agenda Neelie Kroes’ (2011) claimed—“the
new gold”. Exponential increases in data and computing power, the World
Economic Forum argue, are fuelling a “Fourth Industrial Revolution”
(Schwab 2016). While such claims are open to critique, for example, we
may draw on Webster’s (2006) analysis of earlier claims about the revo-
lutionary nature of informationalisation that question the notion of revo-
lutions within a capitalist political economy, it is still vital to recognise the
deepening dependence of the capitalist mode of production on data.