6

Sensing Air and 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 monitoring 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. 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 station generates data that indicate whether the UK is meeting EU air quality objectives for both short- and long-term emissions of pollutants.1 The 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.2

Passersby may experience, in a potentially fleeting way, the connection 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 encounter with this station, but instead are located in more distant spaces of laboratories and servers, where data are gathered and processed to influence 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 pollution 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 city.3 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 consequences for urban dwellers in these areas.

Inevitably, the question arises as to how individuals may map 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 agencies to a practice in which DIY groups and citizen sensors are now engaged. One attempt to sense air quality beyond fixed and official monitoring sites has included community deployments of diffusion tubes, a low-cost analogue method for gauging air pollution but which requires weeks-long deployments of tubes that are then sent off to labs for analysis and data production. Here, the process of gathering air pollution data may be democratized, but the generation and analysis of meaningful data take place in remote laboratory settings.

More 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 connected 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, including Preemptive Media’s “Area’s Immediate Reading” (or AIR), which consists of a mobile and individual air monitoring device for gauging individual exposure to air pollutants;4 other projects, including Safecast, suggest in relation to environmental disturbances such as the Fukushima nuclear fallout 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, such as radiation levels.5

Whether displaying pollution levels or developing platforms to make pollution information more readily available, many citizen-sensing pollution 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 Common Sense’s work with fitting air quality sensors to street sweepers in the Bay Area, to any number of citizen-sensing kits and devices that use low-cost electronics, including Speck (for PM 2.5 sensing) and AirCasting (for NOx sensing).6 Citizen sensing is a strategy that often attempts to translate practices of monitoring pollution from the spaces of “expert” scientific and government oversight into practices and technologies that are available to a wider 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 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 EPA report notes, “are now making it possible for anyone in the general public to measure air pollution and are expanding the reasons for measuring air pollution.”7 With these citizen-sensing practices, data shift from having to meet a regulatory standard to ensure policy compliance to indicating change, and in the process instigate different citizen-led actions.

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 intended to be more readily and effectively addressed. Data are intertwined with practices, responses to perceived problems, modes of materializing and evidencing problems, and anticipations of political engagement. 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 pollution monitoring technologies?

In this chapter, I consider how citizen-sensing practices that monitor air pollution 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 augment scientific studies or to act on their environments. Rather, as I suggest throughout Program Earth, computational-sensing technologies are bound up with the generation of new milieus, relations, entities, occasions, 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 chapter 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 “process is the becoming of actual entities. Thus actual entities are creatures; they are also termed ‘actual occasions.’”8 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 entities 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 together are creations that materialize through distinct ways of perceiving and participating in environments. These creatures may have scientific legitimacy. 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 attention to the concrete actual entities of data—even the “accidents” of data, as Whitehead would have it—and to take into account the “conditions” that give rise to and sustain these creatures of environmental data.9 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. By turning to the creaturing of data, I consider in the projects that follow how data mobilize or underwrite environmental practices. At the same time, data might fail to materialize as anticipated, and through this process activate participatory arrangements that might be quite different from those intended. The failure of environmental sense data to translate into an easy spur to environmental action can even be an important way in which the creaturely aspects of data concresce. Data unfold not simply through instrumental or even epistemic registers but also as attractors and attachments. It is through these attractors and attachments that experiments with environmental citizenship—and not just sensor technologies—also develop.

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 environmental concerns. These projects test, experiment with, and mobilize alternative modes of environmental citizenship. Yet in what ways do practices 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, engagement? How do the creatures of environmental data become points of attachment for influencing and in-forming environmental concern and politics?

Through this discussion of citizen-sensing projects that develop experimental and creative approaches to monitoring air quality and generating environmental data, including Feral Robotic Dogs, the Pigeon Blog, and Air Quality Egg, I further consider how these technological modes of sensing generate distinct practices of environmental citizenship in and through engagements with data. The projects I discuss below involve the creaturing of data in a double sense, since they also deploy more-than-human participants, including robotic dogs, homing pigeons, and plastic eggs as concrete entities for drawing together citizen-sensing practices. While these environmental sensing projects are, on one level, focused on creating opportunities for citizen sensors (of sorts) to generate their own data, on another level these projects also create additional data in and around the practices they set in motion. This is not just the data of environmental phenomena observed and monitored but also the data of not obtaining what was expected, of shadowing events in different ways than a run of quantitative data might evidence, of generating residual and qualitative data from the eventfulness of environmental monitoring, of creating different patterns of data rather than adhering to accuracy as the sole criterion for data legitimacy, and of mobilizing alternative creatures of data, such as dogs, pigeons, and eggs (and their extended milieus), within the distributed digital infrastructures of environmental monitoring.

How might we describe the processual and creaturely entities that concresce through different practices of monitoring the air? What does the air (and “the environment”) become through monitoring devices, and what are the ways in which it concresces and becomes involved with experience, particularly if we consider experience as “constructive functioning”?10 What are the relationships, political engagements, and ways of mobilizing data that make for the most a/effective environmental practices? And if monitoring and citizen sensing are emerging as new modes of environmental participation, in what ways do these experiments further enable practices for engaging with and addressing air pollution, and for speculating with environmental politics? These are some of the questions that arise when considering how a creaturely approach might shift the ways in which data are seen to materialize and gain perceptive power.

Creaturing Data I: Monitoring and Materializing Air

Breath is an example of the difficulty involved in delineating where the body ends and the world begins, as captured Whitehead.11 It may be somewhat commonplace to note that breathing is a process in which we are all involved, necessarily, to sustain our bodies. Whitehead’s articulation of the ways in which—through breathing—bodies cannot be conceived of as discrete from environments and other entities on which they rely further indicates the ways in which this process concresces into environmental, political, social, and more-than-human occasions. Breathing articulates distinct subject-superject relationships, since it involves more than the simple fact of needing to breathe and extends to the sites, entities, and conditions involved in exchanging air, which can be polluted and irritating to specific organisms, as well as given to remaking the bodily capacities of organisms as they live and endure within particular ecologies of air.

The ways in which bodies, environments, and the multiple substances that percolate and stir through any given patch of air come together can be distinctly influenced by what is actually in the air. Beyond the usual list of atmospheric gases, including nitrogen (78 percent), oxygen (21 percent), argon (1 percent), and various trace minerals, pollutants may be present in quantities that register as parts per million (ppm) or parts per billion (ppb) molecules of air. CO₂, as discussed in chapter 4, has been measured at Mauna Loa, Hawaii, to now be measurable at 400 ppm and rising.12 Pollutants, in other words, are often present in seemingly miniscule quantities and yet are able to disrupt and remake environments, bodies, and ecological processes on local and global scales. Beyond trace gases, however, a whole range of coarse to ultrafine particles also chuck through the air, from dust and skin flakes to diesel particles, to the airborne residue of grilled hamburgers and more. The air further exchanges materials with the soil and oceans in a complex cycling that influences weather and climate. Airborne specks and remainders simultaneously issue from and are exchanged to reshape the bodily and atmospheric inhabitations underway in any given environment.

Gases and particles that are actually monitored in relation to managing air quality then constitute a select portion of all the substances mixing within the air. While there is a wide range of pollutants circulating through the air, the EPA has designated common or criteria pollutants that are regularly monitored and are notable for their effects on human and environmental health. These pollutants include CO, nitrogen oxides (NOx), SO₂, PM 10 and PM 2.5, lead (Pb), and ozone (O₃).13

Smokestacks and chimneys have served as the industrial icons of air pollution, and sulfur-saturated skies were the historic events that led to the formation of clean air legislation in many Western countries, from the Clean Air Act in the UK (1956) to the Clean Air Act in the United States (1963), as well as evolving air quality objectives in the EU (2008).14 Inevitably, the “cleaning up” of Western skies often raises questions about how coal-fired manufacturing may have been displaced rather than remedied, as the exceedingly high levels of pollution in China and other Asian manufacturing hubs demonstrate.15 Beyond coal use, pollution now emanates from a range of sources and is not always present primarily as SO₂ that forms from the burning of coal. Instead, NOx and PM are the relatively colorless and odorless pollutants of increasing concern and that are primarily generated in urban areas from automobile traffic as well as the heating of buildings. Unlike SO₂, which is a far more visible and palpable pollutant both in its immediate presence and eventual effects in the form of acid rain, defoliation, and more, NOx and PM tend to be less immediately evident as key pollutants, but they have considerable effects on human and environmental health.

Defining what counts as air pollution is far from a straightforward matter when the evidence of harm potentially becomes more difficult to establish.16 Institutional and governmental monitoring networks typically identify pollutants of concern in response to health research that provides evidence for levels of harm caused by particular pollutants. 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 pollutants.17 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 monitoring and enforcing these standards can miss the localized pollution experienced by individuals. Environmental and individual health are bound up with articulations of what does and does not count as a pollution episode 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 disturbances 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.18 Emissions and exposure mitigation have then been identified as two different ways in which to monitor and manage air quality: one addresses fixed sites and reductions of air pollutants; the other attends to how individuals may manage their individual experience to lessen air pollution exposure, such as monitoring and taking alternative routes through cities, although not necessarily attending to overall reductions of air pollutants.

There is an extensive literature that discusses citizen engagement in moni-toring air pollution, although often at the level of how citizens respond to or aid scientific findings, or how they collect evidence themselves in order to contest or augment official air quality readings.19 In this second approach, analyses of participatory- and environmental-justice-focused engagements with air pollution have discussed the many and even noncomputational ways in which air samples may be collected in order to influence environmental science and politics. Global Community Monitor, for instance, is an environmental activism group engaged in a DIY-bucket collection method to monitor air quality in places such as neighborhoods adjacent to oil and gas refineries located in regions known as “Cancer Alley.”20 While the bucket becomes a device for collecting air samples in a more democratic and local way, the analysis of the air samples must still take place in laboratories (similar to the diffusion-tube air analysis) that are not sites of citizen engagement. Such projects present a low-tech way of conducting a version of citizen science, which are largely focused on environmental activism and justice, but they also raise questions about how air quality data might be experienced in more real-time situations and how data might become admissible as evidence for making environmental claims. This is where many citizen-sensing initiatives attempt to make a contribution by providing more immediate and accessible access to air quality data. But this approach is also not without its problems, as will be discussed below.

Data Becoming Relevant

Articulations of personal, urban, and environmental health shift across these different strategies for addressing air pollution. Practices of monitoring pollution at the citizen or individual level provide a way to counter or redress 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. With many of these projects, the question arises as to how data become relevant. Air pollution data might become relevant through health research that establishes high levels of morbidity due to particular air pollutants, or through scientific monitoring networks that identify pollutants exceeding accountable limits, or through concerns for certain environmental effects, from acid rain to eutrophication, which unfold with excessive levels of pollutants.21

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.22 Relevance is a critical part of the process of creaturing, since creaturing 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, are expressions of relevance. Social environments are integral 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 here and throughout this study, are then at once an “object” of study as well as a mutually in-formed and coproduced relation through which monitoring practices and gathered data take hold and gain relevance. The relevance 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 becomes possible to attend to how data are differently mobilized and concresce within and through practices. Data in one context might have the status of facts, and in another context might galvanize a much different set of a/effects. As the EPA has expressed in its analysis of new modes of environmental monitoring, “types of data” and “types of uses” are interlinked.23 Data typically only become admissible for legal claims when gathered through specified scientific procedures and with quite precise (as well as expensive) instrumentation. There may also be situations in which data are “just good enough” for establishing that a pollution event is happening, for instance.24 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 actions with and through air pollution sensing practices and data? Could it be that the environments of relevance for this data are still in formation?

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 constructivism not as a process of making fictions, but rather of making realities concresce and take hold—or gain a “foothold,” as Stengers has discussed elsewhere.25 As discussed in chapter 1 of this study, sensors are part of generative processes for making interpretative acts of sensation possible and for attending to environmental matters of concern. 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 differently constituted air pollution data and data-gathering practices might have relevance and be able 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.26 As Whitehead notes, every fact must “propose the general character of the universe required for that fact.”27 Here is another aspect of tuning, which is not just a process of making particular modalities of sensing possible across subjects, environments, and experiences, but also 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,28 this does not make them illusory. Rather, it draws attention to the conditions needed for facts to have effect. In this way, facts are creatures, since, as Whitehead elaborates:

The creatures of facts—and data—constitute entities that bring worlds into being. Sense data are productive of new environments, entities, and occasions that make particular modalities of sensibility possible. A social environment then plays a formative part in conditioning and supporting creatures of fact and creatures of data.30 These are creatures of data because they are involved in creative processes that bring sensing to possibility and that in-form the environments where these modes of sensing have relevance.

It might be useful at this point to step back, briefly, to explain how creativity unfolds within Whitehead’s cosmology. “Creativity” is another word for the creative advance, or process, of entities, which explains how entities may be understood both as being and becoming. Creativity is “ultimate” within Whitehead’s speculative philosophy, and this approach enables an engagement with entities that moves beyond a fixed subject-object relation to attend to processual and immanent conditions of the formation of entities. In this way, the entities that concresce through a creative advance are “creatures.”31 Creatures are subject-superjects, they are the “conditions” that creativity settles into, since creativity can only be known through its conditions. It should also be noted that creativity is not inherently good. Whitehead expressly develops a “neutral” metaphysics that seeks to explain process, but he does not cast judgment on the ways in which a creative advance settles into creatures.32

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 this study, 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. Through this experiencing (and so processing and transforming) the datum, subject superjects are able to generate actual entities, or creatures. As he explains:

Whitehead uses Kant’s notion of experience as “constructive functioning,” but reverses the order of experience. Experience is not always “on its way to knowledge” in the form of “objective content,” but rather can be understood in the way that the datum is felt and processed to become superjectal. In this approach, Whitehead inverts the usual Kantian way of understanding experience (i.e., as a subject decoding universal objects) to suggest that objects find “satisfaction” in subject-superjects, which take account of the datum in particular ways.34

I suggest we understand Whitehead’s Kantian inversion as a process of creaturing data, since it draws attention to the ways in which 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 data because what issues through this process are subject-superjects involved in processes of being and becoming creatures. Perhaps in the most concisely stated version of this insight, Whitehead writes, “An actual entity is an act of experience.”35 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 devices might be understood less as technologies for gathering 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 creaturing data suggests that it might be relevant to attend to the ways in which data are taken up, felt, experienced, taken into account, gain relevance, and attain “power” as the process whereby particular perceptions or modes of prehension involve or prevail over others.36

Practices of processing environmental data are the routes whereby data achieve “subjective satisfaction” and become relevant to the persistence and further formation of that data. Furthermore, subjects that process and transform environmental data are human and more-than-human creatures. This is to say that subjects include a vast array of entities, from pavements to trees to sensors—that form and are formed by creative processes of taking up and transforming data. Environmental data are not simply gathered from environments, as though this process only requires that human subjects discover objective universal data to be communicated. Instead, subjects constitutively enable the becoming and being (which is to say, settlement and endurance) of particular forms of data through the ways in which they experience the datum. The creatures that concresce draw from and express worlds in which those data have relevance. The formation of environments as monitor-able then comprises a key part of how data and facts take hold, since environments are co-created along with the processes of subjects parsing and creaturing data.

Creaturing Data II: Dogs, Pigeons, and Eggs

Sensing technologies are then entangled with and mobilize new environmental monitoring practices and new ways of gathering data. The modes of engagement and spaces through which data are gathered, analyzed, and communicated are central to the emergence of these environmental modes of practice. Citizen-sensing projects are frequently described as data campaigns or as identifying an issue about which more data may be needed in order to effect policy changes. As numerous studies of science and technology have noted, however, data are always embedded within political practices, structures, and institutions that in-form everything from how data are delineated and collected to how they are joined up, communicated, and acted upon.37

For the remainder of this chapter, I focus on these aspects of environmental data as forming creatures of data. By looking specifically at three projects that engage with computational modes of sensing environments, I consider the relations, practices, and political possibilities that concresce to form these distinct creatures of environmental data. Feral Robotic Dogs, Pigeon Blog, and Air Quality Egg are citizen-sensing projects that largely focus on doing science and environmental monitoring differently through the actors, arrangements, tools and spaces where monitoring is undertaken. At the same time, in pollution-monitoring projects, the gathering of sense data is often closely tied to a/effecting political action and environmental change by addressing how data are generated, collected, and acted upon—as well as creatured through processes of subject-superjects feeling the datum.

Dogs

One of the earliest creative-practice projects to engage with environmental sensing, Feral Robotic Dogs was originally developed by Natalie Jeremijenko in 2002 through the Bureau of Inverse Technology (or BIT) and developed in additional versions and deployments through 2006. The project adapted existing Sony Aibo toy dogs by “upgrading” them with all-terrain bodies and environmental-sensing brains and noses. Ready-made robotic toy dogs with preprogrammed tasks were identified as having more interesting potential uses: these were creatures “awaiting further instructions.” The first generation “gamma dog” was proposed to store and transmit environmental data from “any radioactive source” that exceeds EPA thresholds, where the deployment of these dogs in multiples would “provide informational spectacle and conclusive on-data convergence in a given local area.”38 In their development, the semiautonomous gadgets were rerouted to “sniffer” dog mode and fitted with environmental sensors capable of detecting environmental pollutants including volatile organic compounds (VOCs), CO, and methane (CH₄), while providing general indications of air quality.

A number of deployments of the dogs were then developed for sites of likely pollution, including a Former Gas Plant at East 173rd Street Works at the Bronx River in New York, where dogs scouted for volatile organic solvents and polycyclic aromatic hydrocarbons; and at Baldwin Park, Orlando, Florida, where robots were deployed to search for VOCs at “sites of community interest,” including a former landfill site that was a proposed site for a middle school. This Florida deployment sought to provide an opportunity for an evidence-driven discussion of the environmental issues facing the community and the opportunity to coordinate diverse opinions and interpretations of the phenomena at hand. As the project description notes:

Environmental data were to become evident through the movements of dogs that sniff out and map pollutants. This was seen as a way to render environmental data more perceptible and more spectacular, while also changing the possibilities for who can generate and access data and so have the means for contributing to environmental and political debates. Inevitably, processes of monitoring pollutants here and in the projects discussed below are bound up with available sensors that are able to measure specific gases and which creature particular types of evidence. Such versions of data-led environmental citizenship become further in-formed by the prior investment in sensors developed with specialized technical capacities, often for military, industrial, or scientific uses.

In discussing the Feral Robotic Dogs project, a group of artists and technologists who variously came to work on the project suggested that the meeting of robotics and environmental sensing and mapping could propel activism to new types of encounters, where creative explorations with data gathering and environmental monitoring might create renewed engagements with local environments.40 Here is a sensing project that speculates about the possibility for participatory and citizen-based data collection in order to create more direct and materialized connections between environmental information and the observers of that information.41 Through the collection of environmental data, it is imagined that a more immediate and accountable mode of environmental action might also be possible.

Yet this direct connection between data and action could be queried on many levels, since such a translation is not necessarily automatic and in many ways depends on an assumed efficacy that scientific data are assumed to have in the world. The ways in which climate change data, for instance, fail to have an immediate effect on political action may give rise to speculation about whether data necessarily constitute incontrovertible evidence with which to influence and change environmental politics. The failure of data to lead to environmental action might, on one level, stem from the assumed force of a scientifically evidenced and “rational” argument, where decisions made in relation to environmental matters of concern instead unfold through multiple and competing political interests. On another level, however, the ways in which data in and of themselves are meant to be—and may also fail to be—compelling may raise questions about the a/effective registers of data. Is a robotic dog a more a/effective data-creature than a spreadsheet, bar chart, or policy document? The point here is not to set up a false dichotomy between these data forms, but rather to ask about the ways in which the creaturing of data may be one way to experiment with the modes and practices of environmental citizenship. In these creaturely arrangements of dogs, pigeons, and eggs, new distributions of participation might even materialize. But the exact ways in which these forms of participation in-form environmental politics remain a point of speculation that continues to be explored and taken up in subsequent citizen-sensing projects.

Pigeons

If the Feral Robotic Dogs project deployed air-sensing technologies through a robotic toy to make new technical modalities of environmental monitoring more widely available, the Pigeon Blog project raises the question of how air quality sensing transforms even further when pigeons are the reporters and carriers of sensing equipment. Pigeon Blog, developed by Beatriz da Costa with Cina Hazegh and Kevin Ponto in 2006, was a project that used sensor backpacks fitted to homing pigeons to collect low-altitude air quality readings while the pigeons flew through the frequently polluted skies of Southern California. The sensor backpacks consisted of a combined GPS receiver that provided latitude, longitude, and altitude readings, a dual automotive CO and NO sensor, a temperature sensor, and a purpose-built mobile phone for transmitting text messages. The backpack kit was developed as a miniature unit small enough to be carried by the pigeons so that real-time air quality data could be transmitted and visualized as pollution levels on the Pigeon Blog and within a Google Map visualization.42

Situated within Southern California and initially developed in Los Angeles, the project addressed the ongoing problem of air pollution and environmental justice by developing an open-source sensing kit that could be used for “grassroots scientific data gathering.”43 The “Pigeon Blog” project was developed as a response to the limited number of fixed air-monitoring stations that are focused on generating longer-term average data about air quality and which may not necessarily be located in areas of the highest-pollution episodes. By providing the possibility for more local measurements and data about local exposures, the Pigeon Blog project sought to complement if not challenge existing data on air pollution to look at the distribution of pollution on a finer-grained level. This approach was shared with AIR, a 2006 Preemptive Media project (briefly mentioned at the introduction to this chapter), on which da Costa collaborated along with Brooke Singer and Jamie Schulte. Consisting of portable air monitors, AIR enabled urban dwellers to complement coarser and fixed air quality data by collecting local data through individual journeys.44 Equipped with GPS and coordinated with a database of known pollution sources, the air monitors sensed CO, NOx, and ground-level O₃ at distinct locations and provided real-time visualizations of air pollution levels in relation to an EPA air quality index. By making individual maps of urban air pollution exposure, the hope was that urban dwellers could become more aware and engaged in discussing environmental issues through everyday exposure, individual risk, and neighborhood-level mapping.

In both Pigeon Blog and AIR, citizen sensing is presented as an activist project of sorts. Yet Pigeon Blog in particular does not undertake a typical approach to environmental politics and urban air quality. By enrolling pigeons into the project of sensing air, the Pigeon Blog project questions how to develop a mode of “interspecies co-production in the pursuit of resistant action.”45 The pigeons were sent out as “reporters” to draw attention to the issue of air pollution while providing inventive and more accessible ways of gathering data in order to provoke new possibilities for political action. Pigeons participated in this project in multiple ways, since they are creatures with unique navigational abilities and often fly according to major landscape features, such as highways, and are also a pervasive (if often reviled) bird in urban areas. Pigeons often occupy polluted urban areas and may provide a specific view of low-altitude air pollution in areas of high traffic. Pigeons further act as biosensors, and make available distinct urban experiences through proxy modes of sensing.

Pigeons are also key contributors to creaturing data and environmental participation in ways that move beyond the usual spaces of environmental activism. Da Costa makes the point that projects such as Pigeon Blog may create new capacities for engaging with environmental information and for mobilizing participation that are not exclusively focused on “how bad things are.”46 While the project set out to provide alternative datasets that might be widely gathered to contribute to more expert approaches to environmental monitoring, in many ways this objective was not achieved. Long-term or even complementary datasets were not generated from the project, and this anticipated outcome even became somewhat incompatible with the project’s attempt to experiment with new modes of environmental practice and participation. Instead, Pigeon Blog experimented with the urban, technological, and more-than-human entities that became part of the project of sensing, experiencing, and reporting on air quality. While this project failed to engage with air quality data in the ways initially anticipated it nevertheless arrived at an expanded approach to environmental practice that was less conventionally data driven and more attentive to the ecological modalities of citizenship that might materialize with such a distributed approach to sensing environments.47

Eggs

As earlier experiments into environmental sensing, Feral Robotic Dogs and Pigeon Blog tested the ways in which new and distributed modes of participation across human and more-than-human modalities might shift the possibilities for political engagement in air quality. These projects continue to influence citizen-sensing projects currently underway, which have proliferated not least through the increasing availability and affordability of sensor technologies. Air Quality Egg is one project in this area that has sought to connect up maker communities in developing digital devices to enable citizen sensing of air quality.48 Developed as a “community-led” project, where the community is largely comprised of creative technologists located in New York, London, and Amsterdam, the early prototype version of the egg project consisted of a Nanode sensing platform that detected CO and NO₂, which the project creators identified as key air pollutants. Housed in a rapid-prototyped egg-shaped shell, the air-sensing apparatus was initially developed at workshops in New York City and Amsterdam, further tested at the second Citizen Cyberscience Summit in London in 2012, and subsequently gained considerable backing on Kickstarter, which allowed the device to be manufactured for wider use.

As the eggs developed from prototypes to manufactured sensor kits, they could then be ordered from electronic hobby suppliers. Citizen-owned eggs were in turn mapped in an online platform and shown to be located in the United States, Europe, Australia, and Japan, and variously gathering measurements that were uploaded to a Xively data platform. While the Air Quality Egg project is ostensibly focused on air quality monitoring, it is more centrally located within technical communities that are driven to experiment with the technology of sensing devices. These communities typically engage in what has been referred to as “participatory-sensing” experiments by bringing the technical functionalities of sensors to more immediate points of encounter through setup, testing, modification, and online tutorials for upgrading devices.49 In the process, many questions have arisen regarding how these technologies actually work and the extent to which the data they generate are accurate. Comments on the community forum related to the Air Quality Egg raised a heated debate as to how viable it is to monitor air quality accurately with such a device, given the scale, lack of calibration, and coarse instrumentation of the metal oxide sensors it uses (which are typically used for automotive functions). To what extent are egg-gathered data useful and accurate? And what if the egg fails to function in the first place (as was the case in several of the prototyping workshops)?

In a project video, however, commentators on the project suggest that the accuracy of data is not a primary issue, since sense data might provoke environmental concerns that could be followed up with more thoroughly scientific study. Here, the focus is on a community of egg users and developers inclined toward testing devices, which might raise further calls to action, even if the trajectories from local, sporadic, and somewhat momentary datasets to the influencing of environmental science, policy, and behavior are not entirely clear.

At one point in the project video, which captures the testing of the egg during the London Cyberscience event in the spring of 2012, a participant remarks, “the chicken is not ready,” to refer to the back-and-forth attempts to have the egg setup, calibrated, and ready to gather measurements. In the context of creaturely data, this project seems to be an entity in-formation where sensor-led technical kit is the assumed impetus for galvanizing environmental issues and action. The environments that concresce here are highly in-formed by computational modes of sensing and acting. Data gathered through electronic sensing is seen to be the force that propels perceived possibilities for activism, but the force of data emerges less through the accuracy of data and more through the process of a technical community making a device that can draw attention to data practices as potentially political engagements. Data are creatured in the Air Quality Egg through a device ready to hatch and give rise to new modalities of data-driven activism. But the modes of participating in making devices and generating data may be much different entities and occasions, arguably, than the modes of participating in environmental activism, which may be a legitimating subtext for the egg but not the primary focus in this tech-led and maker-community approach to participation.50

Experimenting with Environmental Citizenship

The three projects discussed here share a similar approach to environmental sensing as a more democratic engagement with data gathering in order to influence environmental politics. Yet beyond these similarities, much different entities and modalities of citizenship come together in these projects. The Feral Robotic Dogs project tests deployments in landfills and the site of a proposed middle school, making the point that from these sites new communities of interest might emerge to influence environmental debate. Data are rendered as a more haptic and materialized experience, something demonstrated through a fleet of sniffing robotic dogs. The Pigeon Blog seeks to make urban air quality visible through a more-than-human engagement, which at once redistributes environmental participation while creating a more experimental approach to sensing urban environments. And the Air Quality Egg focuses on developing an Internet of Things approach to creating a worldwide sensor network, where new devices and the data they generate lead to new possibilities for participation and the formation of communities.

Yet in each of these projects, the translation from environmental-sensing experiment to citizen-based engagement with environmental issues remains unclear. Such issues are not uncommon within more grassroots modes of citizen sensing and environmental monitoring. As the London Air Quality Network points out, monitoring air quality on a DIY-level may not be as easy as it first appears. This is due to the complexity (and expense) of working with precisely instrumented sensors and the questions of accuracy that pertain to sensing projects that use less refined sensing equipment or that are not set in up a systematic way to study environments over time. Yet the dogs, pigeons, and eggs of these projects are not gathering data at the level of scientific study but are making a case for the development of complementary data sets to inform what is monitored and how it is brought to attention in order to be acted upon.

At this level of action, additional questions arise as to how environmental sense data may influence environmental politics and actions. In an earlier human–computer interaction research project, Common Sense, which tested the deployment of sensors for measuring air quality on street sweepers, the project participants arrived at the observation that environmental community organization is actually the critical factor in order for data generated through sensor deployments to be relevant, meaningful, and actionable.51 In fact, community environmental organizations have in some cases been rather skeptical of the extent to which more data from computational sensors will necessarily facilitate more effective action. In this way, some researchers question the assumption that more localized and data-led processes of environmental observation and monitoring do actually enable greater environmental participation.

While the uses and effects of citizen-sensing data, particularly as gathered through digital technologies, are arguably still in formation, this situation raises challenging questions about the types of creatures that might concresce through citizen-sensing data. On the one hand, since the relevance of scientific datasets is something that citizen-sensing practices would ideally like to harness, there may be an overreliance on transferring scientific rationales to citizen-sensing datasets. On the other hand, the assumed effectivity of scientific datasets for mobilizing political action also remains unquestioned in this move, since more, or more accurate, scientific data does not always (if ever) incontrovertibly lead to political change, as the ongoing inertia around London’s air pollution and the exceedance of EU guidelines clearly indicates.52

The EPA’s report on new types of monitoring technologies and practices might be read even as more of a provocation for the types of data practices that are still in a generative or experimental phase and the ways in which the creatures of data are still in formation along with their environments of relevance. Citizen-sensing practices for monitoring pollution are experimental both in the technologies of environmental monitoring and data gathering and in the practices and social environments within which these data might have relevance and become creatures of data. In other words, citizen-sensing practices are in-formation as experimental 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.

Environmental sense data gathered without a clear link to community projects may not have the anticipated effects of facilitating greater participation in environmental matters of concern. Yet, to varying degrees, some of these projects do experiment with the methods, techniques, communities, modes of participation, sites of monitoring, and evidential modes of activism and politics that might materialize as new entities and processes for engaging with environments and environmental issues. These experiments with a/effectivity and practice bring openings—as well as further controversies—to approaches to environmental politics and participation that might be investigated further. Monitoring data—as typically conceived—might not be the critical unit for mobilizing environmental citizenship and action; and a gadget-led process for engaging with politics may not be the most definitive answer to developing new modes of environmental engagement. However, these citizen-sensing projects raise the question of what other experiments might emerge that open up the possibility for new types of environmental politics and new modes of collective participation.

Within this space, the modes and practices of data—the creaturely entities in and through which data manifest and give rise to worlds—are arguably an area yet to be fully explored, since data are so frequently presented as the abstract and dematerialized evidence of environmental facts. But the modalities, materialities, and creatures of environmental data may be one way of experimenting with monitoring practices as sites of environmental engagement, where affectivity and the relevance of social environments become critical to considering the effectivity of data.53 The creatures that concresce here are not only those of environmental sense data but also those of environmental citizenship. Distributed and more-than-human modes of participation contribute to air pollution and its monitoring. From computational sensors to moving air masses, manufacturing and transport, vegetation and animal bodies, temperature gradients and topography, and economic inequality and real estate, as well as policy and modeling, a number of entities converge in the project of experiencing, participating in, and experimenting with sensing air pollution.

Participation as Involvement

The engagements that are made possible through the expanded arrangements of environmental data could then be understood as modes of togetherness, or involvement, as Whitehead terms it, of environmental problems and events. This is a way of saying that environmental data are participatory, yet not simply as an articulation of humans using and connecting across gadgets or even of objects having agential force. Instead, data are participatory as technological concrescences that make distinct modes of engaging with environments take hold and persist while shaping the actuality and the possibility of environmental politics and imaginaries. The concrescences of environmental monitoring and environmental data encompass more than a concatenation of actors, since the participation of these multiple entities is also a mode of prehension that describes the ways in which “actual entities involve each other.”54

Involvement is a distinct and processual meeting of entities formed through encounters—as well as absences (hence, positive and negative prehensions). Involvement constitutes more than an assemblage, arguably, since the character and effect of relations are integral to the ways in which entities concresce to produce practices, facts, and subjects-superjects. Involvement is a process that further signals the concrete making of worlds (and environments)—the being and becoming of those worlds, as they endure and change. How then might environmental data be understood not simply as the end result of monitoring practices but as the ingression or mode of participation and even potential involvement, which mobilizes and concresces monitoring practices in particular ways?55

Some atmospheric scientists have suggested that low-cost digital sensors may, on the one hand, encourage more democratic engagement with environmental issues. But, on the other hand, these sensors might not produce data that are as “accurate” as higher-end instrumentation.56 While data are differently creatured across scientific and citizen-sensing practices, they are also productive in another way, since these realms and hoped-for uses are not mutually exclusive but begin to in-form each other as arrangements of environmental politics and practices of citizenship. While the “accuracy” of citizen-sensed data might not compare to the data gathered through scientific techniques, it might alternatively constitute different processes for creaturing data and for experimenting with environmental citizenship. Such an approach also raises the question of whether an exclusively scientific approach to environments and environmental data is the only way in which environmental politics might have legitimacy and effect. If we keep in mind Whitehead’s famous aphorism that science is necessary but not sufficient, then how might environmental citizenship unfold into a wider set of practices and approaches to creaturing data?57

This chapter has suggested that by attending to the particularities of how data are processed and transformed into experience—by attending to the creatures of data—it might be possible to open up new considerations for how environmental data become relevant, the environments that ensure this relevance, and what the a/effect of these data might be. If we return to the EPA report on the emergence of new monitoring practices and technologies, the point made about how new types of data might yield new types of data practices remains a salient point for this discussion. The report suggests that while legal and compliance-focused data may still largely be produced through scientific processes, new “personal” and “qualitative” uses of data might emerge through digital sensors and smartphones that have as-of-yet not fully determined functions or effects. If current air monitoring is largely focused on legal compliance and atmospheric science uses, then what environmental engagements might come together from different data practices and arrangements? What might citizen-sensing practices cause to “take hold” in relation to air pollution and air quality? And how do these practices exceed the instruments and devices of sensing to encompass a more creaturely distribution of experience?

As discussed through the three projects that mobilize dogs, pigeons, and eggs in a project of gathering environmental data along more citizenly engagements, environmental monitoring always involves more than its instruments, at that same time that data is never reducible to a universal category. The creatures of data that emerge in these projects are entities that concresce as distinct occasions of environmental engagement across experiencing subject-superjects. The “data” gathered here are not simply in service of visualizing environmental phenomena, whether through finer-grained or mobile modalities. Instead, these creatures are the “consequent reasons” for attending to, processing, and transforming data in these specific ways.58 While scientific datasets might be understood through particular consequent reasons that appeal to the objectivity of air pollution data, mobilizing these same reasons a priori for undertaking citizen-sensing projects may in fact restrict the possibilities that citizen-led monitoring might provide.

If data is de-creatured, as it were, how does this apparent universality of data obscure the arrangements that lend effectivity to data? At the same time, a case could be made here for reconsidering what counts as “raw data.” Rather than excising it entirely, raw data might also be considered to be a distinct effect and creature of data. As Whitehead has remarked in relation to Kant, “objective” conditions are simply a way of creaturing those data—as objective.59 Furthermore, the objectiveness or givenness of data is not an absolute substance or universal condition, but rather is an actual occasion or entity that has settled in this way to become a fact, but which may also change. If we reconsider raw data in this way, then data are less an absolute condition and more a way of creaturing data as a particular resource, where “rawness” sets particular practices and effects in motion. Within scientific practice rawness then is important as a condition of data upon which additional operations are made.60 But this creaturely inflection of data need not influence or speak for all other modalities for creaturing data nor the many practices that might be set in motion as ongoing inheritances of creaturely data.

In this context, what does it mean to “sense” or experience air pollution 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 required 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 processing and transforming of environmental data. This is not simply a matter 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 environmental practices and politics. These creatures, as Whitehead (following James) has reminded us in the epigraph to this chapter, settle into “a democracy of fellow creatures,” where the shared experiences of air, pollution, and possibilities for engagement might even bring us into inventive modes of solidarity.