10.6092/issn.2038-3460/17343
In citizen-sensing projects, more extensively and democratically gathered data are typically presented as “the reasons for measuring air pollution”, since it is through collecting data that everything from enhanced participation in environmental issues to changes in policy are hoped to be achieved. The impetus to monitor and gather data is bound up with established (and emerging) processes of understanding environments as information-based problems. Within citizen-sensing projects, data are intended to be collected in ways that complement, reroute or even circumvent and challenge the usual institutions and practices that monitor environments and manage environmental data. Data are seen to enable modes of action that are meant to offer effective ways to respond to those problems. With more data, potentially more accurate data, and more extensively distributed data, environmental problems such as air pollution are anticipated to be more readily and effectively addressed. Data are intertwined with practices, responses to perceived problems, modes of materializing and evidencing problems, and proposals for political engagement. But how are air-quality data constituted, whether through expert or citizen practices? How do differing practices of environmental monitoring inform the character and quality of data gathered, as well as the possible trajectories and effects of those data? What are the instruments, relations, and experiences of air-quality data generated through these distinctive engagements with environments and technology? And in what ways do environments become computational through the use of low-cost air-pollution monitoring technologies? I consider how citizen-sensing practices that monitor air pollution experiment with the tactics and arrangements of environmental data.
application/pdf
2038-3460
17343
1
en
Jennifer Gabrys
https://creativecommons.org/licenses/by-nc-sa/2.5/
Tecnoscienza – Italian Journal of Science & Technology Studies
creaturing
The Becoming Environmental of Computation. From Citizen Sensing to Planetary Computerization
Text.Serial.Journal
https://tecnoscienza.unibo.it/
8
Lectures
2017-07-20
2023-06-22
2017-07-20
2023-08-21
5-21
TS
Jennifer Gabrys
2017/07/20
10.6092/issn.2038-3460/17343
5
Goldsmiths University of London
2038-3460
1
creaturing
en
21
The Becoming Environmental of Computation. From Citizen Sensing to Planetary Computerization
https://tecnoscienza.unibo.it/article/download/17343/16192
8
                                                                                      Lecture

The Becoming Environmental of
Computation
From Citizen Sensing to Planetary Computerization
Jennifer Gabrys
Goldsmiths University of London (UK)



    Abstract: In citizen-sensing projects, more extensively and democratically
    gathered data are typically presented as “the reasons for measuring air pollu-
    tion”, since it is through collecting data that everything from enhanced par-
    ticipation in environmental issues to changes in policy are hoped to be
    achieved. The impetus to monitor and gather data is bound up with estab-
    lished (and emerging) processes of understanding environments as infor-
    mation-based problems. Within citizen-sensing projects, data are intended to
    be collected in ways that complement, reroute or even circumvent and chal-
    lenge the usual institutions and practices that monitor environments and
    manage environmental data. Data are seen to enable modes of action that
    are meant to offer effective ways to respond to those problems. With more
    data, potentially more accurate data, and more extensively distributed data,
    environmental problems such as air pollution are anticipated to be more
    readily and effectively addressed. Data are intertwined with practices, re-
    sponses to perceived problems, modes of materializing and evidencing prob-
    lems, and proposals for political engagement. But how are air-quality data
    constituted, whether through expert or citizen practices? How do differing
    practices of environmental monitoring inform the character and quality of
    data gathered, as well as the possible trajectories and effects of those data?
    What are the instruments, relations, and experiences of air-quality data gen-
    erated through these distinctive engagements with environments and tech-
    nology? And in what ways do environments become computational through
    the use of low-cost air-pollution monitoring technologies? I consider how
    citizen-sensing practices that monitor air pollution experiment with the tac-
    tics and arrangements of environmental data.

    Keywords: Citizen sensing;                    air   pollution;   environmental   sensors;
    environmental data; creaturing.

    Corresponding author: Jennifer Gabrys, Department of Sociology,
    Goldsmiths University of London, New Cross, London SE14 6NW, United
    Kingdom – Email: j.gabrys@gold.ac.uk




TECNOSCIENZA
Italian Journal of Science & Technology Studies
8 (1) pp. 5-21- ISSN 2038-3460
www.tecnoscienza.net                                    2017
6                                                            Tecnoscienza – 8 (1)

1. Introduction

    In addressing the STS Italia conference theme of “sociotechnical envi-
ronments”, I am drawing in part on my research into environments, envi-
ronmental sensors and the increasing instrumentation of the planet1. I
take up this topic in my book, Program Earth (2016), which addresses the
programmability of the planet by focusing on the becoming environmen-
tal of computation. I understand computation to include computationally
enabled sensors that are distinct and yet shifting media formations that
traverse hardware and software, silicon and glass, minerals and plastic,
server farms and landfills, as well as the environments and entities that
would be sensed. In other words, I am attending to the extended scope of
computation that includes its environmental processes, materialities, and
effects.
    Through discussing specific instances where sensors are deployed for
environmental study, citizen engagement, and urban sustainability across
three areas of environmental sensing, from wild sensing to pollution sens-
ing and urban sensing, I ask how sensor technologies are generating dis-
tinct ways of programming and concretizing environments and environ-
mental relations. I further consider how sensors inform our engagements
with environmental processes and politics, and in what ways we might
engage with the “technicity” of environmental sensors to consider the
possibility for other types of relations with these technologies2.
    Environments, as I develop the concept in Program Earth, are conju-
gations of subjects and superjects, following Whitehead, entities can be
approached not as detached objects for our subjective sensing and con-
templation, but rather as processes in and through which experience, en-
vironments, and subjects individuate, relate, and gain consistency (1929,
15 and 41; 1938, 94 and 112). “Environment” as a term has multiple res-
onances and genealogies. Within this space of examining ubiquitous
computing and sensor networks, I consider specifically how environments
inform the development of sensor technologies and how these technolo-
gies also contribute to new environmental conditions. Not only do com-
putational technologies become environmental in distinct ways, the envi-
ronments they populate are also in process.
    Environment is not the ground or fundamental condition against
which sensor technologies form, but rather develops with and through
sensor technologies as they take hold and concresce in these contexts.
Distinct environmental conditions settle and sediment along with these
technologies as they gain a foothold. These processes involve not just the


   1
     See Gabrys (2016). This text includes portions of an abbreviated reprint
from Program Earth, courtesy of the University of Minnesota Press.
   2
     For a more extensive discussion on technicity, see Simondon (1958, 152);
Combes (2013, 60); Lamarre (2013, 92).
Gabrys                                                                     7
creation of the entities and environments that are mutually informed but
also the generation of the relations that join up entities and environments.




                Fig. 1 – Program Earth, Jennifer Gabrys, 2016.


    On one level, environmental sensors are input devices that facilitate
monitoring, measuring, and computing. Yet on another level, environ-
mental sensors can be described as engaged in processes of individuating
by creating resonances within a milieu, where individual units or variables
of temperature and light levels, for instance, are also operationalizing en-
vironments in order to become computable. Working across my Program
Earth text and signaling toward the Citizen Sense research group’s prac-
tice-based work on pollution sensing3, in this article I specifically look at
technological milieus and the creaturing of data in relation to air pollu-
tion sensing.




   3
     For more information on the Citizen Sense research project, see citi-
zensense.net.
8                                                              Tecnoscienza – 8 (1)


2. Sensing Air, Creaturing Data

    If you should find yourself standing outside the Hobgoblin Pub on
New Cross Road in the Borough of Lewisham, London, you might notice
a grayish-white box approximately two-and-a-half meters high scrawled
with a faded and cascading line of graffiti. Wedged in the space between
buildings and facing outward toward the road, the air vent and monitor-
ing equipment at the top may be one of the few details that betray the
purpose of this structure, which is to measure air quality at this fixed spot
in London.




     Fig. 2 – The New Cross Gate Air Quality station (Citizen Sense, 2013).


    One of the stations in the London Air Quality Network (LAQN) that
covers thirty-three boroughs, this monitoring station contributes to the
hourly indexes of air quality and news of pollution “episodes” in London.
Detecting sulfur dioxide (SO2), particulate matter 10 and 2.5 (PM 10, PM
2.5), as well as nitrogen oxide (NO) and nitrogen dioxide (NO2), the sta-
tion generates data that indicate whether the UK is meeting EU air quali-
ty objectives for both short- and long-term emissions of pollutants4. The

    4
      While all of these pollutants affect cardiovascular and pulmonary health,
particulate matter (PM) is of particular concern. As the World Health Organiza-
tion (WHO, 2014) notes in a fact sheet on air quality, “PM affects more people
than any other pollutant. The major components of PM are sulfate, nitrates, am-
Gabrys                                                                            9
data also contribute to environmental science research and are managed
and made available by the Environmental Research Group (ERG) at
King’s College London, where this network is managed and run.
    Passersby may experience, in a potentially fleeting way, the connec-
tion between this station, the local air quality, and the data it generates,
which typically circulate in spaces of environmental science and policy.
The air quality data that are generated at this fixed site are black-boxed
and located in spaces somewhat remote from experiences of air quality on
the street. Air quality data are not typically present at the point of en-
counter with this station, but instead are located in more distant spaces of
laboratories and servers, where data are gathered and processed to influ-
ence the management of environments and air quality.
    In order to make air pollution data gathered by this station and the
approximately one hundred other stations in the LAQN more accessible,
King’s ERG has designed a London Air app to allow people to observe
emissions levels at key monitoring sites and to make inferences about
their own personal exposure when passing through these sites. While this
strategy moves toward making the data of fixed sites more accessible
through an air quality app, the pollution that individuals experience in
their everyday trajectories may be quite different than the types of pollu-
tion that are captured through fixed monitoring sites generating data that
are averaged over set monitoring periods. The New Cross Road station,
for instance, typically records an annual exceedance of NO2 at this fixed
point – a pollutant formed through combustion of fuel that is largely the
result of high levels of automobile use in the city5. Yet all along New
Cross Road individual moments and locations of exposure may give rise
to a far different set of pollution “episodes”, with much different conse-
quences for urban dwellers in these areas.
    Inevitably, the question arises as to how individuals may generate data
about their own mobile exposure to air pollution, which is likely to differ
from the fixed sites of the official monitoring stations. As discussed
throughout this study, environmental monitoring is proliferating from a
project undertaken by environmental scientists and governmental agen-
cies to a practice in which DIY groups and citizen sensors are now en-


monia, sodium chloride, carbon, mineral dust and water. It consists of a complex
mixture of solid and liquid particles of organic and inorganic substances suspend-
ed in the air. The particles are identified according to their aerodynamic diameter,
as either PM (particles with an aerodynamic diameter smaller than 10 μm) or PM
(aerodynamic diameter smaller than 2.5 μm). The latter are more dangerous since,
when inhaled, they may reach the peripheral regions of the bronchioles, and inter-
fere with gas exchange inside the lungs.” See WHO, “Air Quality and Health.”
    5
      The EU air quality objective (2008) indicates that there should be no more
than 40 µm/m3 of NO2 per year. The New Cross Road station (in the borough of
Lewisham) recorded 51 µm/m3 of NO2 in 2013. Also see the London Air Quality
Network (LAQN) and the European Commission “Air Quality Standards”.
10                                                              Tecnoscienza – 8 (1)

gaged. Many recent citizen-sensing projects that deploy lower-cost digital
sensors and smartphones have focused on monitoring air quality levels in
ways that attempt to make environmental data more immediate and con-
nected to experienced conditions. One of the primary ways in which such
citizen-sensing projects have sprung up is through direct engagement
with monitoring environmental pollution. While some citizen-sensing
projects use the itinerant aspects of individual exposure to environmental
pollution as a way to experiment with mobile-monitoring practices with
which fixed sites of detection cannot compare, other projects, suggest
that official or government data may not always be available or trusted, so
that alternative data sources may be necessary in order to gauge exposure
to pollutants of immediate concern.




           Fig. 3 – DIY air pollution sensing (Citizen Sense, 2014).

    Whether displaying pollution levels or developing platforms to make
pollution information more readily available, many citizen-sensing pollu-
tion projects attempt to make the details of environmental pollution more
instantaneous and actionable. An even more extensive range of pollution-
sensing projects have turned up in this area, from devices that use low-
cost electronics, including Speck (for PM 2.5 sensing) and AirBeam (for
NOx sensing), as well as Citizen Sense kit using Shinyei PM 2.5 sensors.
Citizen sensing is a strategy that often attempts to translate practices of
monitoring pollution from the spaces of “expert” scientific and govern-
ment oversight into practices and technologies that are available to a wid-
er array of participants. As the EPA has noted in its work on surveying
and assessing the rise in citizen-sensing practices and low-cost monitoring
Gabrys                                                                 11
equipment, air pollution monitoring is no longer confined just to official
networks and the professional practices of scientists and technicians, but
is proliferating into new types of uses that might, they anticipate, even
begin to “supplement” regulatory approaches to air pollution. “New
breakthroughs in sensor technology and inexpensive, portable methods”,
one U.S. EPA (2013, 2) report notes, “are now making it possible for an-
yone in the general public to measure air pollution and are expanding the
reasons for measuring air pollution”6. With these citizen-sensing practic-
es, data shift from having to meet a regulatory standard to ensure policy
compliance to proliferating and indicating change, hence perhaps insti-
gating different citizen-led actions.




                   Fig. 4 – The PM 2.5 sensor (Citizen Sense, 2014).


    In citizen-sensing projects, more extensively and democratically gath-
ered data are typically presented as “the reasons for measuring air pollu-
tion”, since it is through collecting data that everything from enhanced
participation in environmental issues to changes in policy are hoped to be
achieved. The impetus to monitor and gather data is bound up with es-
tablished (and emerging) processes of understanding environments as in-
formation-based problems. Within citizen-sensing projects, data are in-
tended to be collected in ways that complement, reroute, or even circum-
vent and challenge the usual institutions and practices that monitor envi-


    6
        See also Snyder et al. (2013).
12                                                          Tecnoscienza – 8 (1)

ronments and manage environmental data. Data are seen to enable modes
of action that are meant to offer effective ways to respond to those prob-
lems. With more data, potentially more accurate data, and more exten-
sively distributed data, environmental problems such as air pollution are
intended to be more readily and effectively addressed. Data are inter-
twined with practices, responses to perceived problems, modes of materi-
alizing and evidencing problems, and anticipations of political engage-
ment. But how are air quality data constituted, through expert or citizen
practices? How do differing practices of environmental monitoring in-
form the character and quality of data gathered, as well as the possible
trajectories and effects of those data? What are the instruments, relations,
and experiences of air quality data generated through these distinctive
engagements with environments and technology? And in what ways do
environments become computational through the use of low-cost air pol-
lution monitoring technologies?
    In the process of monitoring air pollution, citizen-sensing practices
experiment with the tactics and arrangements of environmental data.
These monitoring experiments, however, are not just a matter of enabling
“citizens” to use technology to collect data that might allow them to aug-
ment scientific studies or to act on their environments. Rather, as I sug-
gest throughout Program Earth, computational-sensing technologies are
bound up with the generation of new milieus, relations, entities, occa-
sions, and interpretive registers of sensing. The becoming environmental
of computation describes this process. Sensor-based engagements with
environments do not simply detect external phenomena to be reported;
rather, they bring together and give rise to experiencing entities and
thereby actualize new arrangements of environmental sensing and data.
The production of air quality data through environmental monitoring
generates distinct subject-superject entities and occasions for generating
and making sense of that data – as scientific facts, matters of concern, or
even as inchoate patterns produced through unstable technologies or
sporadic monitoring practices.
    As a central point of focus, this lecture then crucially asks in what
ways environmental sense data emerge not through universal categories
or forms but as concrete entities – or creatures – that concresce through
processes of subjects participating in environments and environmental
events. “The actual world is a process”, Whitehead writes, and this “pro-
cess is the becoming of actual entities. Thus actual entities are creatures;
they are also termed ‘actual occasions’” (1929, 22). Actual entities are
creatures, or lively meetings of entities that form routes of experience. In
this sense, the process of gathering air pollution data might be identified
as more than documenting static facts of air quality at any given time or
place and instead be approached as a practice that gives rise to entities
and modes of participation that transmit data in particular ways and
along distinct vectors of environmental participation.
    Working with this Whitehead-inspired analysis of how concrete enti-
Gabrys                                                                  13
ties of environmental data materialize through pollution sensing, I then
consider how environmental-sensing projects are processes of what I call
creaturing data, where the actual environmental entities that come to-
gether are creations that materialize through distinct ways of perceiving
and participating in environments. These creatures may have scientific le-
gitimacy. Or they may form as alternative modes of evidence presented in
contestation of scientific fact. But in either or both capacities, they are
creaturely rather than universal arrangements of data.
    The point of attending to the creaturing of data is to at once draw at-
tention to the concrete actual entities of data – even the “accidents” of
data, as Whitehead would have it – and to take into account the “condi-
tions” that give rise to and sustain these creatures of environmental data.
Creatured data are not an abstract store of information or something to
be coherently visualized, but rather are actual entities involved in the
making of actual occasions and material processes. Data may typically
appear to be the primary objective of environmental sensing projects,
which focus on obtaining data to influence environmental policy and
practices, but along the way the relations and material arrangements that
data gathering sets in place begin to creature new entities that concresce
through monitoring practices.




                    Fig. 5 – Air quality sensor prototype.
14                                                              Tecnoscienza – 8 (1)

    The general ethos of many DIY- and citizen-sensing projects has been
that by enabling and democratizing the monitoring of local environments,
it may also be possible to achieve increased engagement with environ-
mental concerns. These projects test, experiment with, and mobilize al-
ternative modes of environmental citizenship. Yet in what ways do prac-
tices of environmental monitoring with sensing devices give rise not just
to experimental modes of participation and civic engagement but also to
different modalities for experiencing environmental pollution through
monitoring practices that generate air quality data? Within these projects,
how does the experience and experiment of air pollution and air quality
data become a site of political, as well as potentially affective, engage-
ment? How do the creatures of environmental data become points of at-
tachment for influencing and in-forming environmental concern and poli-
tics?


3. Citizen Data and Environments of Relevance

    While in Program Earth I discuss a range of citizen sensing projects as
a way to engage with these questions, I also take up these questions spe-
cifically discussing the creatures of data that could be seen to emerge
within Citizen Sense research. Within this abbreviated discussion of the
“pollution sensing” aspects of the Citizen Sense research project, I con-
sider how the generation of citizen data became entangled with the crea-
tion of environments of relevance, which were required in order for citi-
zen data to take hold and have effect. I take up a more extensive discus-
sion of these aspects of the Citizen Sense research in collaboratively writ-
ten project articles on citizen and collective forms of monitoring, and in
an investigation of the “just good enough data” that citizen monitoring
mobilized in order to make claims to policymakers and regulators7. But to
briefly mention this Citizen Sense research work here, I would note that
the processes of citizens gathering data through kit that we collaboratively
developed did not only involve working with sensors to tune in to air and
emissions. These processes also involved arranging data as evidence, put-
ting together data stories that were ways of “figuring” the problems of air
pollution and the worlds that might come together in order for this air
pollution to register, and of forming extended social environments in and
through which citizen data could gain a foothold and become relevant for
addressing problems of air pollution.
    As citizen sensing and citizen data collection practices demonstrate,
defining what counts as air pollution is not always a straightforward mat-
ter. This is particular the case when attempting to establish evidence of

    7
      For a more extensive discussion of these aspects of Citizen Sense research,
see Pritchard and Gabrys (2016) and Gabrys, Pritchard and Barratt (2016).
Gabrys                                                                           15
harm or possible harm . Institutional and governmental monitoring net-
                          8

works typically identify pollutants of concern in response to health re-
search that provides evidence for levels of harm caused by particular pol-
lutants. As part of the Global Burden of Disease 2010 study, outdoor air
pollution was identified as a leading cause of death, contributing to heart,
lung, and cardiopulmonary disease, which are now particularly linked to
PM 2.5 exposure, which are also less evident as pollutants9. In many
ways, health research influences environmental policy, which sets targets
in relation to which monitoring networks set criteria for monitoring, as
well as providing air quality forecasts, management, and mitigation.
    While the impacts of air pollution on human health are one of the key
motivators for establishing air quality standards, often the means of moni-
toring and enforcing these standards can miss the localized pollution ex-
perienced by individuals. Environmental and individual health are bound
up with articulations of what does and does not count as a pollution epi-
sode and what may constitute an excessive level of pollutant exposure.
Emissions of a certain pollutant at a given site in a city may be within an
acceptable range, but individual exposure may vary considerably. Air,
noise, and water pollution are local if distributed environmental disturb-
ances that many urban dwellers experience on a regular basis, although
for some more than others since sites of pollution are often concentrated
in lower-income urban areas. Emissions and exposure mitigation have
then been identified as two different ways in which to monitor and man-
age air quality: one addresses fixed sites and reductions of air pollutants;
the other attends to how individuals may manage their individual experi-
ence to lessen air pollution exposure, such as monitoring and taking al-
ternative routes through cities, although not necessarily attending to
overall reductions of air pollutants.
    Articulations of personal, urban, and environmental health shift across
these different strategies for addressing air pollution. Practices of moni-
toring pollution at the citizen or individual level is a way to counter or re-

    8
       For established limits for common pollutants, see the U.S. EPA National
Ambient Air Quality Standards (NAAQS) Table (https://www.epa.gov/criteria-
air-pollutants/naaqs-table) and the European Commission “Air Quality Stand-
ards”. For a discussion of the ways in which legal disputes become entangled in
establishing both the matters of fact and concern of air pollution, see Jasanoff
(2010). For a discussion on how exposure and harm become increasingly difficult
to link within newer regimes of chemical living, particularly in relation to indoor
air quality, see Murphy (2006). For a forthcoming discussion on evidencing harm
through citizen-sensing practices, see Gabrys (2017).
     9
       Ambient PM pollution contributes to 3.2 million deaths annually, and there
are increasing levels of heart disease, lung cancer, and cardiopulmonary disease in
association with PM 2.5 exposure. See Lim et al. (2012). The WHO (2014) sug-
gests that “exposure to air pollutants is largely beyond the control of individuals
and requires action by public authorities at the national, regional, and even inter-
national levels.”
16                                                            Tecnoscienza – 8 (1)

dress the possible gaps in data, but there is more to these projects than
this, since in mobilizing sensors to bring environmental monitoring into a
more democratic, if often individual, set of engagements, new material-
political actors, engagements, and experiments concresce – along with
new political (im)possibilities. The question arises as to how data become
relevant. Air pollution data might become relevant through health re-
search that establishes high levels of morbidity due to particular air pollu-
tants, or through scientific monitoring networks that identify pollutants
exceeding accountable limits, or through concerns for certain environ-
mental effects, from acid rain to eutrophication, which unfold with exces-
sive levels of pollutants.
    Relevance is a term that Whitehead uses to address the ways in which
facts have purchase, and the “social environments” that are set in place in
order for facts to mobilize distinct effects (1929, 203; cfr. Stengers 2011,
259). Relevance is a critical part of the process of creaturing, since crea-
turing involves the ways in which creativity is conditioned or brought into
specific events and entities. The ways in which creatures gain a foothold,
in other words, is an expression of relevance. Social environments are in-
tegral to the immanent processes that condition and give rise to creatures
– they do not exist without the formation of creatures, and they continue
to co-evolve as the situations in which creatures make “sense” and have
effect.
    Environments, as understood within Citizen Sense research and
throughout Program Earth, are then at once an “object” of study as well
as a mutually in-formed and coproduced relation through which monitor-
ing practices and gathered data take hold and gain relevance. The rele-
vance of air quality data is not determined through absolute criteria, since
these criteria shift depending upon modes of governance, location, and
more. If data are understood instead as perceptive entities, it then be-
comes possible to attend to how data are differently mobilized and con-
cresce within and through practices.
    Data in one context might have the status of facts, and in another con-
text might galvanize a much different set of a/effects. As the U.S. EPA
has expressed in its analysis of new modes of environmental monitoring,
“types of data” and “types of uses” are interlinked (2013, 2-5). Data typi-
cally only become admissible for legal claims when gathered through
specified scientific procedures and with quite precise (as well as expen-
sive) instrumentation. There may also be situations in which data are “just
good enough” for establishing that a pollution event is happening, for in-
stance.10 Yet it remains a relatively open question as to what the uses and
effects of data gathered through citizen-sensing technologies might be,
since these creatures have arguably not yet settled into entities for which
relevance is expressible. In other words, how do citizen sensors undertake

   10
      For a more extensive discussion of the concept and practice of “just good
enough data”, see Gabrys, Pritchard and Barratt (2016).
Gabrys                                                                             17
actions with and through air pollution sensing practices and data? Could
it be that the environments of relevance for this data are still in for-
mation? This is something that the Citizen Sense Data Stories attempt to
work with and through, in order to understand not just environments of
relevance on a descriptive level, but also to contribute to practice-based
formations of such environments through citizen sensing engagements.


4. Conclusion

    At this point, it might be easy enough to make a statement about the
ways in which environmental monitoring technologies “construct” the air
and the problem of air quality. While this inquiry works in a way parallel
to constructivism, it also attempts, following Stengers, to think of con-
structivism not as a process of making fictions, but rather of making reali-
ties concresce and take hold – or gain a “foothold”, (2011, 163-164, 518).
Sensors are part of generative processes for making interpretative acts of
sensation possible and for attending to environmental matters of concern
in particular ways. The environments, arrangements, and practices that
are bound up with how facts take hold and even potentially circulate with
effect are then a critical part of any study into how expanded and differ-
ently constituted air pollution data and data-gathering practices might
have relevance and be able to make claims upon that data to effect
change.
    This approach to constructivism is different from a poststructuralist
rendering, since ideas and language do not mediate things, but rather
things concresce as propositional effects (Stengers 2011, 252). As White-
head notes, every fact must “propose the general character of the universe
required for that fact” (1929, 11). Here is another aspect of tuning, which
is not just a process of making particular modalities of sensing possible
across subjects, environments, and experiences (cfr. Gabrys 2012), but al-
so involves the tuning of facts and the conditions in which those facts
have relevance. If facts require particular social environments in order to
have relevance, this does not make them illusory (Whitehead 1929, 203;
Stengers 2011, 259). Rather, it draws attention to the conditions needed
for facts to have effect. In this way, facts are creatures, since, as White-
head (1929, 20) elaborates:

         “Each fact is more than its forms, and each form ‘participates’
    throughout the world of facts. The definiteness of fact is due to its forms;
    but the individual fact is a creature, and creativity is the ultimate behind
    all forms, inexplicable by forms, and conditioned by its creatures.”

   The creatures of facts – and data – constitute entities that bring
worlds into being – and also require worlds for these processes to unfold.
Sense data are productive of new environments, entities, and occasions
18                                                                  Tecnoscienza – 8 (1)

that make particular modalities of sensibility possible. A social environ-
ment then plays a formative part in conditioning and supporting creatures
of fact and creatures of data11. These are creatures of data because they
are involved in creative processes in bringing sensing to possibility and of
in-forming the environments where these modes of sensing have rele-
vance.
    A process of creaturing data then attends to the ways in which data
are not fixed objects gathered through universal criteria but instead are
entities through which forms and practices emerge as creatures, and
through creaturely processes. As discussed throughout Program Earth,
perceiving subject-superjects combine as feeling entities through actual
occasions. These entities might otherwise be termed creatures, since they
are formations of conditioned creativity. Furthermore, the “datum”, as
Whitehead discusses it, is not simply an external array of objects awaiting
conceptual classification by a human subject. Instead, the datum is that
which subject-superjects feel, and through this experiencing (and so pro-
cessing and transforming) the datum, generate actual entities, or creatures.
    Data are always felt and experienced by and as creatures, which
through feeling further give rise to distinct forms of data. A process of
transforming the datum into felt experience is a process of creaturing da-
ta because what issues through this process are subjects-superjects in-
volved in processes of being and becoming creatures. Perhaps in the most
concisely stated version of this insight, Whitehead writes, “An actual enti-
ty is an act of experience” (1929, 68). Feeling the datum is a process of
transforming the datum into experience, which concresces as an actual
entity or creature. Creaturing is then the description of this process of
feeling the datum, where creatures are the actual entities formed through
creaturing the datum.
    If we consider the “data” that digital sensors generate, then these de-
vices might be understood less as technologies for gathering (particularly
quantitative) data and more as technologies for processing, transforming,
and creaturing data – as a felt form of the datum. While it may be easy
enough to query the assertion that more data and more democratically
gathered data might lead to action and engagement, an approach to crea-
turing data suggests that it might be relevant to attend to the ways in
which data are taken up, felt, experienced, taken into account, gain rele-
vance, and attain “power” as the process whereby particular perceptions

    11
       As Whitehead notes: “The data upon which the subject passes judgment are
themselves components conditioning the character of the judging subject. It fol-
lows that any presupposition as to the character of the experiencing subject also
implies a general presupposition as to the social environment providing the dis-
play for that subject. In other words, a species of subject requires a species of data
as its preliminary phase of concrescence... The species of data requisite for the
presumed judging subject presupposes an environment of a certain social charac-
ter” (1929, 203).
Gabrys                                                                            19
or modes of prehension involve or prevail over others (Whitehead 1929,
219). These processes require the formation of social environments in or-
der for data to have effect.
    Why is this important? Because on a concrete level in order for citi-
zen-generated data to be taken seriously and to inform environmental
policy and politics, it is necessary to consider the infrastructures, envi-
ronments and practices that are bound up with the creaturing of data in
order to understand how to make citizen-generated data (among other
forms of data) relevant in ways that can effect change. In other words,
this requires tuning our attention to which modes of experience count,
and for which purposes. Citizen-sensing practices are in-formation as ex-
perimental practices that test not just how environmental monitoring data
might be differently gathered but also how such data might be mobilized
within distinct environments of relevance, and to what (political) a/effect.
Within this space, the modes and practices of data – the creaturely enti-
ties in and through which data manifest and give rise to worlds – are ar-
guably an area yet to be fully explored, since data are so frequently pre-
sented as the abstract and dematerialized evidence of environmental fact.
    In this context, what does it mean to “sense” or experience air pollu-
tion with computational sensors? Monitoring air pollution with digital
sensors is not just a way of obtaining a “result” or fact about a particular
environment but is also about the ways in which data are creatured and
mobilized, the social environments that concretize and allow those facts
to have relevance, and the additional attendant data practices that might
come together to generate a/effects. Creaturing data is an approach that
asks how we might consider much more than the “facts” gathered, since
the extended social environments, practices, and speculative relations re-
quired to bring facts into a space of relevance are crucial to the creatures
of data that materialize. Creaturing data is a way of attending to the pro-
cessing and transforming of environmental data. This is not simply a mat-
ter of attending to the extended capacities of generating data but instead
involves considering the creatures of data, the entities and situations that
form and take hold, whether to solidify, experiment with, or change envi-
ronmental practices and politics. As Whitehead (1929, 50) writes:

        “We find ourselves in a buzzing world, amid a democracy of fellow
    creatures; whereas, under some disguise or other, orthodox philosophy
    can only introduce us to solitary substances, each enjoying an illusory ex-
    perience”.

   These creatures, as Whitehead (following James) has reminded us,
then settle into “a democracy of fellow creatures,” where the shared ex-
periences of air, pollution, and possibilities for engagement might even
bring us into inventive modes of solidarity.
20                                                             Tecnoscienza – 8 (1)

Acknowledgments
The research leading to these results has received funding from the European Re-
search Council under the European Union's Seventh Framework Programme
(FP/2007-2013) / ERC Grant Agreement n. 313347, “Citizen Sensing and Envi-
ronmental Practice: Assessing Participatory Engagements with Environments
through Sensor Technologies.”



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