10.6092/issn.2038-3460/17378
In this article, we examine the role of environmental big data in the installation of an environmental sensor in a UK city. Taking the installation of the Elm sensor as an empirical case study, we understand the installation as incurring an instance of natural breakdown which reveals the contingent workings of the device, and places it in the context of the practices of normalisation and stabilisation of the device. We use this to ask questions about the taken for granted smoothing of outputs and the continual elaboration of use and design, alongside the constructive potential for disruptive digital literacies as a site of intervention. By following, empirically, the installation of the technology, we are led to combine, and re-examine, theoretical lines of reasoning about data competences and relationships, and in turn advocate a form of “material politics”.
application/pdf
2038-3460
17378
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en
Darren J. Reed
https://creativecommons.org/licenses/by-nc-sa/2.5/
Tecnoscienza – Italian Journal of Science & Technology Studies
environmental sensors
Discovering the Data-driven City. Breakdown and Literacy in the Installation of the Elm Sensor Network
Text.Serial.Journal
https://tecnoscienza.unibo.it/
8
Essays
2018-01-29
2023-06-25
2018-01-29
2023-08-24
81-104
TS
Darren J. Reed
2017
10.6092/issn.2038-3460/17378
81
University of York
2038-3460
2
environmental sensors
en
104
Discovering the Data-driven City. Breakdown and Literacy in the Installation of the Elm Sensor Network
https://tecnoscienza.unibo.it/article/download/17378/16235
8
                                                                                   Essay

Discovering the Data-driven City
Breakdown and Literacy in the Installation of
the Elm Sensor Network
Darren J. Reed
University of York (UK)


    Abstract: In this article, we examine the role of environmental big data in
    the installation of an environmental sensor in a UK city. Taking the installation
    of the Elm sensor as an empirical case study, we understand the installation as
    incurring an instance of natural breakdown which reveals the contingent work-
    ings of the device, and places it in the context of the practices of normalisation
    and stabilisation of the device. We use this to ask questions about the taken
    for granted smoothing of outputs and the continual elaboration of use and
    design, alongside the constructive potential for disruptive digital literacies as a
    site of intervention. By following, empirically, the installation of the technology,
    we are led to combine, and re-examine, theoretical lines of reasoning about
    data competences and relationships, and in turn advocate a form of ‘material
    politics’.

    Keywords: environment; big data; digital literacy; material politics;
    environmental sensors.

    Submitted: October 15, 2016 – Accepted: November 15, 2017

    Corresponding author: Darren J. Reed, Department of Sociology,
    University of York, Wentworth College, W/241, Heslington, YO10 5DD,
    United Kingdom. Email: darren.reed@york.ac.uk



1. Introduction

    This article follows the problems encountered in the installation of a
new environmental sensor, and reveals the potential for new relationships
between members of the public and environmental monitoring sensors
data, as a site “of intervention where new data actions and relations might
converge” (Gabrys 2016, 4). It is premised upon an empirically inspired,
theoretical examination of the installation and configuration of a commer-
cial product, the Elm sensor, and uses this work to open up and reveal the


 TECNOSCIENZA
 Italian Journal of Science & Technology Studies
 8 (2) pp. 81-104 – ISSN 2038-3460
 www.tecnoscienza.net                              2017
82                                                           Tecnoscienza – 8 (2)

strategies of data manipulation of the device installers and the existing in-
frastructures of the city. In response, it extends the arguments of Noortje
Marres (2012), and her reasoning about the potential for political action in
the real-world situation of engagement with environmental data, by advo-
cating the nurturing of “new data literacies”, particularly those deemed
“disruptive”, as a form of intervention based upon the creative engagement
with the rich complexities of environmental data. The article rests on the
history of work in Science and Technology Studies (STS), and the per-
formativity of technology to effect new social relationships (Law and Sin-
gleton 2000; see also Barry 2001). Rather than starting with an ideal partic-
ipant, it follows the technology and the way the script (Akrich 1993, 206)
of the competences and “geographies of responsibilities” are elaborated,
to inform the potential for new forms of civic participation. There is a
growing interest in smart cities in the social sciences (Kitchin 2014) and
spatial data (Leszczynski and Crampton 2016). These are related to an
emerging focus on environmental big data (Gabrys 2016; see the special
issue of Big Data & Society, 2016) and the way they allow for an engage-
ment with “practices, materialisations and contestations” within deploy-
ment processes (Akrich 1993, 3). Such moves complement those that seek
to engage big data as they are made meaningful in everyday life (Wilmot
2016; Pink et al. 2016).
    The Elm sensor is a modular device developed by the American com-
pany Perkin Elmer. At the time of writing, Perkins Elmer has handed over
rights to the development of the device to the University of York, but its
origins lie in an idealised notion of the potential for new environmental
sensors and public participation. Jon DiVincenzo, President, Environmen-
tal Health at Perkin Elmer had this to say about the sensor at its launch,
“the Elm network is designed to create better awareness, empowering all
of us to connect our understanding about the quality of our environment
with its long-term impact on our health - helping cities and their popula-
tions make smarter, more informed decisions” (http://ir.perkinel-
mer.com/).
    The position espoused in the above quotation is one based on a tech-
nological deterministic line; the technology is characterised as effecting
these positive outcomes without recourse to the social context of their in-
stallation and use. The sociological approach to critical data studies (Iladis
and Russo 2016), and in particular environmental devices and data, take a
critically reflective stance to this position. As Kitchin (2014, 8) points out
such technologies and the data they produce are inherently political and
are not neutral, “[d]ata do not exist independently of the ideas, techniques,
technologies, people and contexts that conceive, produce, process, man-
age, analyze and store them”. And further, “data are inflected by social
privilege and social values” (ibid).
    A so-called “technocratic view” presents the idea that data is benign
and the more we have, the more likely we will be able to make good deci-
sions. Yet as Kitchin points out, such a viewpoint ignores the contextual,
Reed                                                                      83
contingent, and relational nature of such data, in its production, use, and
effects. In Kitchin’s terms “[i]t is less well suited to contextualising such
data or revealing the complex contingent and relational inner lifeworld of
people and places” (2014, 9). In this article, we argue for an approach
based on “new data literacies” as critical intervention, a deliberate re-fo-
cussing on the potential for encouraging and supporting the meaningful
agency of people in their relationship with environmental sensors and the
data they produce by resisting efforts to ‘smooth’ the data before presen-
tation. We mean this as a critical intervention. That is, we are not advocat-
ing a return to an individual competence model or requirement for device
functioning, but a ‘de-stabilising’, premised upon the possibilities for the
redistribution of agency and formation of new actor-networks.
    The University of York, became involved with the Elm sensors when it
placed it at the centre of a research project called YorkSense. Subse-
quently, the sensors have become central to two other research initiatives
at York, the CAPACITIE project − an EU Initial Training Network for
new Environmental Scientists, and the York City Environment Observa-
tory (YCEO) − a pilot exercise to develop the city of York into a base for
environmental sensing and stakeholder engagement (for more details see
https://www.york.ac.uk/yesi/projects/yceo/). Both YorkSense and YCEO
espouse a particular model of the data-driven city premised upon open
data seen in the central involvement and use of the York Open Data plat-
form (www.yorkopendata.org). These initiatives combine to form a con-
certed effort to establish York as a “data-driven city”, premised upon citi-
zen access and active engagement.
    The YorkSense project had the simple aim of installing 100 Elm sensors
in York as a test bed for their use and development in other urban settings.
The author was attached to this project as a sociologist concerned with
stakeholder relations alongside positional deployment choices (new to
schools etc. − see below).
    The deployment in York suffered several delays in relation to the tech-
nical configuration of the devices. These included unforeseen problems
with finding an appropriate power supply and negotiating with the local
council for the use of existing lamp posts for this purpose. In addition, it
was found that the sensors did not give constant readings, neither between
devices, nor when compared with other, more expensive, monitoring sys-
tems. Rather than view these delays as faults in the system of installation,
this article takes these delays as instances of the real-world configuration
and (re)stabilisation of the devices as a working system – that is in a soci-
otechnical sense, which interweaves technical functionality with appropri-
ate social functioning (Bijker et al 1987; Mackenzie and Wajcman 1985).
As such the social and interactional qualities and practices of installation
and deployment are viewed as ethnographic research data, and a “probe”
(Gaver et al. 2004), or prompt, for sociological analysis. It should be em-
phasized therefore that this was a partial ethnography, and we would fore-
ground the limitations of such an approach. The details conveyed below
84                                                           Tecnoscienza – 8 (2)

are perspectival, premised − as they are − on the experiences of the instal-
lation efforts by the researcher as part of the team. The provision of limited
ethnographic ‘snapshots’ are a consequence of this participatory position.
It is true that such a position runs the risk of undermining the agency of
the research (as independent actor). At the same time, the features included
were central concerns for the installation stakeholders; they key off the
“sense-making practices” (Garfinkel 1967) within the installation process
and are therefore true to the members’ sense-making practices, perspective
and proximity to the process.
     We first outline the key issues encountered by the installers, and then
introduce sociological theory to help open up the process as a case study,
drawing on foundational literature in Science and Technology Studies, spe-
cifically the work of Akrich (1992, 205) and the “(de)scription of technical
objects”.
     We extend this idea by noting the ‘de-scription’ of the algorithm possi-
ble through the ethnographic work, that is the unpacking of the manner of
algorithm formation, and adaptation to an imagined (confused) user. Once
understood in sociological terms, the issue of the materiality of these ob-
jects as enacting and configuring new forms of political participation is de-
tailed through the work of Marres (2012). This line of reasoning, led us to
consider what we call “new digital literacies” based on work of Lankshear
and Knobel (2008). We extend this line of reasoning with what Couldry et
al. (2016, 118) call “real social analytics”. While these authors come from
different scholarly traditions and represent different conceptual view-
points, we rationalise their combination through the concerns of the de-
signers and academics with “literacy and agency”. That is their coherence
comes from a sensitivity to the research domain, rather than adherence to
a particular position. The agency and experiences of the user as a social
actor re-emergences as a central concern. From here, we speak to the po-
tential for new ‘disruptive’ literacies and their place within a form of en-
gaged citizenship based on critical and creative engagement with data.


2. The Case Study: The Deployment of the Elm Sensors

    The Elm sensor was developed by Perkin Elmer, a large US company.
The company partnered the University of York on a locally funded project
in the Environment department called YorkSense, which had the explicit
aim of installing 100 sensors in the city of York UK, between July and De-
cember of 2015.
    The Elm device is a multi-sensor air quality monitoring device that
measures particulate matter (PM), total volatile organic compotes (VOCs),
nitrogen dioxide (No2), as well other atmospheric components. It is a mod-
ular system; such that new individual sensor components can be added
over time. Data is collected and then transmitted over GSM to a central
Reed                                                                      85
cloud storage. The results of which are then presented on the Elm websites1
(Williams et al. 2015).
    The research team was comprised of academics from the departments
of Environment, Chemistry, Computer Science, and Sociology at York
University. In addition, technical support was supplied by members of the
Electronics department. On the York Council side, various departments
partnered the research, including those concerned with transport manage-
ment, asset management (street lamps etc.) and the Business Innovation
unit.
    The author was attached to YorkSense as an ethnographer, which en-
tailed following the installation process, and advising on the deployment
locations, and researching the relationships between stakeholders. In good
part, this entailed an appreciation of the likely users of the eventual net-
work of devices, as well as giving advice on how the interface to the output
data might be developed and refined (the author’s history in Human-Com-
puter Interaction, and interaction design providing a foundation for such
recommendations). The author attended planning meetings, viewed the
sensors in place, and interviewed various stakeholders (members of the
council, colleagues in the environment department) involved in the project.
Central to these efforts, and the account given here, was a slow revealing
of the underlying issues based upon unanticipated issues and problems.
The article takes (theoretical) issue with the (empirical) decisions and dis-
cussion of the installation process. The script – as such – emerged from
these decisions and practices, and could be said to be unfinished from a
design point of view (as the sensors are not yet deployed). The materials
contained in this article come from notes taken in meetings, and informal
discussions (with the researcher being part of the installation team). The
quoted materials (graphs etc.) come from project presentations and emails
discussions.
    Key to the story is the unanticipated delays encountered in the simple
technical functioning of the devices. Rather than being deployable ‘as is’,
it was realised early in the process that the device was not ‘field ready’.
Alongside other practical matters – such as finding a power supply for each
unit, and accounting for and adapting to data transmission drop out (more
below) – it was quickly realised that the readings from each unit were not
only divergent (in that they gave different readings to one another) but,
more importantly for our purposes here, some of the readings were judged
to be inappropriate for a number of reasons. These are instances of “prac-
tical meaning-making” in that the project partners anticipated that the us-
ers of the system would read the outputs in negative ways. This implies a
concern within the design and subsequent script of competence and liter-
acy (or lack) of the user.



   1
       https://elm.perkinelmer.com.
86                                                              Tecnoscienza – 8 (2)

    In what follows we will address three aspects of the Elm sensor deploy-
ment that progressively emerged from the ethnographic fieldwork: data ve-
racity and completeness; physical installation of the sensors; and usability,
and anticipated response to the sensor readings. In detailing these three
elements, we aim to move from a purely technical position, through a con-
cern with the spatial aspects, to an appreciation of the social contexts of
the sensor deployment exercise. We also reveal a “discovery narrative”,
borne of following the actors (academic staff, installation staff, and council
staff) and those actors reflecting on the process of technology configuration
and deployment.

2.1 Technical Aspects: Data Veracity and Completeness

    While the operating manual of the Elm sensor implies that there should
be no data loss, because the sensor stores any information and transmits it
when there is an adequate GSM connection (Williams et al. 2015), it was
found in the testing of the sensors that data dropout was a common occur-
rence. The issue of data loss became relevant when calculating the average
readings from each sensor.
    The following diagram shows the connectivity of 19 sensors over a 44-
day period. It should be noted that the sensors were not installed in the city
at this point, but were installed together on the roof of one of the university
buildings. Put another way, the potential variability in signal strength and
connectivity due to variation in GSM coverage and interference due to
changing physical conditions (such as traffic density) was not seen in this
early stage of the installation process.




     Figure 1 – Data transmission of the Elm Sensor array. Source: staff member.
Reed                                                                            87
    In the above figure (Fig. 1) the black sections indicate hour-long peri-
ods in which no data was transmitted. While certain periods, notably from
the 2nd to the 13th of August, saw relatively uninterrupted connectivity
(aside from one sensor − 1363 − that appeared to be offline) the period
from the 13th August to the 6th of September saw a great deal of connec-
tion loss.
    The sensors collect (and transmit) information every 20 seconds, so this
means that in those periods coloured black, none of the three transmission
points were successful. In the following figure (Fig. 2), we can see readings
represented in units of six hours:




       Figure 2 – Data transmission of the Elm Sensor array. Source: staff member.


   The section between 30th of August, 1200 to 1800 hours has only two
out of the 19 sensors transmitting continuous information. Such issues
were dealt with pragmatically by the installers of the system. It was sug-
gested that those periods in which there was data dropout would simply
not be reported. Whether this would be indicated in the interface to the
data was unclear (indeed, at this point the issue of data presentation took
second place to data use, and calculation of an average figure).

2.2 Spatial Aspects: Location of Sensors

    During the above-mentioned exercise in which the sensors were in-
stalled on a university roof top, planning for where the sensors would be
installed in the city was underway. The requirement for a power supply led
to a strategy of attaching Elm sensors to lamp posts. The existing position-
ing of lamp posts became a foundation for the choices made in relation to
situating the sensors. A Research Fellow on the programme undertook a
88                                                               Tecnoscienza – 8 (2)

review of the city that combined lamp post positioning with the location of
schools, care homes and businesses to figure through an optimum position-
ing of sensors based on positioning them near vulnerable individuals and
businesses.
    The following diagram (Fig. 3) shows the results of two of the mapping
exercises.




      Figure 3 – Location suggestions for the Elm Sensors. Source: staff member.


   In figure 3, the lamp post suggested relates to the physical location of
businesses, care homes and schools. In the following diagram (Fig. 4) the
positioning of lampposts was set against “vulnerable subpopulations”. This
was based on census data.




     Figure 4 – Location suggestions for the Elm Sensors. Source: staff member.
Reed                                                                          89
    It should be stressed that this exercise was a provisional preparatory
exercise, and in the actual deployment seen since the preparatory work the
sensors have been installed on a piecemeal basis, related to targeting areas
with a range of interesting features, such as a mixture of housing stock, in
combination with a school and park areas. This research based reasoning
foregrounded the need to show that the sensors worked within a pre-
scribed physical ecology. It also addressed a broader issue of availability of
sensor units. The large-scale strategy imagined that one hundred sensors
would be available at the same time. Given the variance in readings across
the units, it became clear that this availability would be at least curtailed,
and potentially undermined, by faulty (or at least variably reporting) units.
    The Elm sensor did not have a location in its initial design. As a unitary
device that functions within a network of devices, the Elm sensor's design
was concerned rather with its laboratory functioning, rather than its real-
world functioning. This is often the case in technology design. A device
developed in the R&D department of a company, rarely undergoes usabil-
ity testing, except in terms of its simple interface functionality. It is not, in
this sense, field tested or put into use in everyday settings; until, that is, it
is released for sale. Recent instances of battery fires in the Samsung Note 7
(http://www.bbc.co.uk/news/business-37253742 – retrieved September 1,
2017), for example, stand as examples of this failure to consider the social
context of use. Elm functioned appropriately under the ‘perfect condi-
tions’ of the laboratory, but as we know such contexts are without extra-
neous factors such as environmental conditions, imperfect GSM signal, or
variable power supply.
    As mentioned previously a key aspect of the first design of the sensors is
that they were not independently powered (either through a battery, or solar
power cells). Therefore, deployment was strictly limited to places where
power-supply was already present. In the case of the test rig on the university
campus this could be organised by extending a building’s power supply to
the roof. However, ‘on the street’ the logical answer was to position the sen-
sors on lamp posts. Further delays were encountered in negotiating with
those in charge of lamp post installation and maintenance for various rea-
sons. First, there was the issue of who would pay for the changes, second the
likely effects on the structural integrity of each lamp post needed to be inde-
pendently established, and finally a means needed to be found to account
(and potentially pay) for the power used. In relation to what became known
as the “seven up, ten down solution” − where a power line would be run up
the outside of the lamp post to the lamp at the top and then fed down the
centre of the post to the power supply at the bottom, rather than drilling into
each lamp post at the point at which the sensor was attached − the issue of
sensor height became important. This, as it turns out, is a non-trivial issue for
the readings gathered. Lamp posts are typically positioned on roads, and the
traffic on roads varies dramatically, not only by location, but also by time of
day. In addition, the likelihood of standing traffic would need to be taken
into account. The lower the sensor is to the ground, the more likely that
90                                                            Tecnoscienza – 8 (2)

higher readings would occur. However, taken too high and the comparabil-
ity to pollution inhalation by a walking person would be obscured. It was
decided that the seven up, ten down option (which assumed a position three
metres above the ground) was inappropriate due to potential vandalism, and
hence an independent structural analysis was undertaken. So here we can see
a range of technical and social issues that intertwine and potentially impact
each other. These are, therefore, socio-technical issues, neither merely social
nor merely technical, but a combination of both.
    Here then we have one key issue of social spatial and material configura-
tion – the marrying of sensor position to the positioning of human pollution
receptors. The original script of “awareness”, “empowerment” and “in-
formed decision” of the sensors (seen in the quotation above) was premised
on the idea that they measured the pollutant levels experienced by a typical
human − or at least within reasonable tolerances, but the material and prac-
tical instantiation of the positioning threatened to undermine any such a
script.
    We can see then that such issues as power supply and height position-
ing, while premised upon technical issues quickly became spatial and ma-
terial concerns. Such elements of the installation were not part of the orig-
inal design, and hence in a sense the devices were unprepared for real
world deployment. What ensued in the case study was far from a simple
matter of technical problem solving, instead it entailed contending with
institutional and organisational factors, such as the rule and regulations
governing lamp post maintenance, power supply payments, and ownership
of the host systems. At one point, it seemed that the “lamp post depart-
ment” (we never found out the correct name for whichever department
was responsible) would veto our attempts to have the sensors installed.
This reminds us that any technology is reliant upon the social and technical
infrastructures already in place (Bowker et al. 2010; Dourish and Bell
2007).

2.3 Data Readings and Social Acceptance

    Another apparently purely technical aspect of the Elm deployment was
a comparison between the separate units. However, this quickly became a
social issue, as the nature of the data variance was deemed to be giving an
impression of dangerously high concentrations of pollutants. This is again
an instance of projected sense-making, in that the project partners assumed
they could put themselves in the place of the typical user, and anticipate
their experiences and thoughts. As can be seen from the previous section
on data dropout, each of the sensors transmits information separately. As
part of the initial work done on the deployment, the sensors were located
together to compare the reading that each was making against one another.
    This can be best seen through the following graph (Fig. 5), which shows
readings from three Elm devices set against an expensive city-based gov-
ernment monitoring station.
Reed                                                                       91




        Figure 5 – Comparative readings from AURNAQM and 3 Elm sensors.
                               Source: staff member.

    The lower thick black line shows the readings of NO2 from the Auto-
matic Urban and Rural Network (AURN) Air Quality Monitoring (AQM)
station run by DEFRA (The UK Department for Environment Food and
Rural Affairs). The lighter red, blue and green lines are taken from three
co-located Elm sensors. Not only do these sensors’ readings show variance
(although it should be noted they generally follow the same pattern of
peaks and troughs), they also show readings that are a multiple of ten of
those from the AURN station.
    To put this in context, the hourly limits for NO2 are 200 µg/m3 (200
micrograms per metre cubed) according to EU and UK law, which relates
to 106 ppb (parts per billion2). What this means is that the reading of 300
ppb given for some Elm sensors was nearly three times the requisite level.
    Upon enquiry, the reasons for this variance spanned three different
logics: 1. device function (quality of device; difficulty in air sampling); 2.
location and context (contingent features of location of device); 3. atmos-
pheric variability.
    In the discussions that ensued between the partners of the project, it
was decided that such figures would upset users and give a poor impression
of the efforts to reduce air pollution in the area (the local council, with
whom the YorkSense were partnered, anticipated hosting the sensor infor-
mation on their open data platform − www.yorkopendata.org (retrieved
September 1, 2017).
    The net result of this observed variance was an effort to normalise the
readings and calibrate the device:

   2
       1 part per billion equates to 1.88 µg/m3 at 25.
92                                                               Tecnoscienza – 8 (2)


Normalisation involves transforming the data so that it is on a common scale. For
example, if you have Elm and a reference unit data, you might transform both sets
of data so they cover the scale 0 - 1. Calibration involves comparison of the Elm
data with a reference instrument. Using the relationship obtained, you can add a
correction to the Elm readings so that they give a sensible reading (personal email
correspondence with project lead).

   The following diagram (Fig. 6) shows the readings before and after the
normalisation process occurred.




       Figure 6 – Before and after normalisation of data. Source: staff member.


    So, the sensor readings from the Elm sensors were manipulated so as to
give more acceptable information. This is very common practice when
shaping data such as this for public consumption. The idea that such read-
ings might have been due to the functioning of the equipment, the location
of the device, and atmospheric variance was not considered as an appro-
priate line of information and engagement with the public. This, it was an-
ticipated, would complicate matters, and would lead to disinformation and
confusion.
    We would like to take these three elements and consider them through
contemporary social theory and the conceptual work within science and
technology studies.


3. Theoretical Discussion

     In a foundation article in STS, Madelaine Akrich (1992, 206) takes up
Reed                                                                      93
and elaborates a position in relation to social change afforded by technol-
ogy – or what she calls the “partial reconstruction” of society and our
knowledge of society − that takes neither a technologically deterministic
nor social constructivist line. Instead it recognises that “technical objects
participate in building heterogeneous networks that bring together actants
of all types and sizes, whether human or nonhuman” by “mov[ing] con-
stantly between the technical and the social” (ibid).
    This is not easy to do, especially as such objects are commonplace and
their workings are often hidden from view. She suggests the researcher
should contend with a methodological problem, “if we want to describe
the elementary mechanisms of adjustment, we have to find circumstances
in which the inside and the outside of objects are not well matched. We
need to find disagreement, negotiation, and the potential for breakdown”
(1992, 207).
    The Heideggerian notion of breakdown in phenomenology and hu-
man-computer interaction (Koschmann et al. 1998) is instantiated when a
technology does not perform the way expected, or anticipated. In ethno-
methodology instances of breakdown become a “perspicuous setting”
(Garfinkel 2002, 186) for understanding naturally occurring breaches in
practices (Garfinkel 1967), which reveal their workings and the efforts by
users to re-establish a sensible scenario. In the case of the Elm sensor this
occurred as the sensor moved from one social context − and concomitant
network of actants of designers, commercial interests, and environmental
scientists − to another, involving the imagined users, consumers and pub-
lics; and specifically, in the way the readings of the sensor were deemed
‘incorrect’ (the scare quotes are meant to convey the ambiguous nature of
such a positioning) and inappropriate. This was during the deployment of
the sensors. We treat this period as a naturalistic period of breakdown, and
hence a methodological tool for revealing the workings of the device inter-
woven with the understandings of the device by relevant actors.
    While the Elm sensor is itself made up of component parts, each of
which has previously been calibrated and tested, it was received by the
University as a stabilised technology. Preparation for its deployment in a
real-world setting, however, “de-stablised” the technology by introducing
alternative relevant social groups, and foregrounding its “interpretive flex-
ibility” (Bijker et al. 1987, xlii; Pinch and Bijker 1984).

3.1 Inscribing Design through Scripts

   Technology design is not a simple matter of incorporating functional
elements in an artefact. It also involves building in various assumptions
about who is going to use the device, and how it will be used. Akrich (1992,
206-7) asserted that, “when technologists define the characteristics of their
objects, they necessarily make hypotheses about the entities that make up
the world into which the object is to be inserted”. This script is then de-
94                                                           Tecnoscienza – 8 (2)

ployed and becomes a pre-scription for the technology’s use. “The tech-
nical realization of the innovator’s beliefs about the relationships between
an object and its surrounding actors is thus an attempt to predetermine the
settings that users are asked to imagine for a particular piece of technology
and the pre-scriptions (notices, contracts, advice, etc.) that accompany it”
(1992, 208, emphasis added).
    Key to Akrich’s formulation of scripts, however, is the potential for an
ongoing and continual process of ascription. This is what sets it aside from
classical conceptions of designed-in purposes, in that there is not an end to
the characterisation of uses for a device or system. In this case, ongoing
processes include not only the subsequent de-black-boxing (Latour 2005)
that occurred during deployment (initiated by the researchers), but also
the effects of the networks of heterogeneous actants, including people
(from the council, technical installers, and academic researchers) and arte-
facts (lampposts, power supplies) and materialities (streets, the city, and
varying pollutants) detailed in section 2. This is what Woodhouse and Pat-
ton (2004) call “design by society”.
    Returning to Akrich (1992, 206), the script of a device not only delimits
use, it also implicates responsibilities: “If most of the choices made by de-
signers take the form of decisions about what should be delegated to whom
or what, this means that technical objects contain and produce a specific
geography of responsibilities, or more generally, of causes”.
    Extending Akrich’s general point about design to this process of recon-
figuration, we are interested in the shifting “geography of responsibilities”
afforded by the configurational changes, particularly − as we will see − in
relation to the competences (or lack of them) ascribed to imagined users of
the informational outcomes.
    This fits well with the notion of material participation of Marres (2012),
especially as it relates to the political objective of civic engagement of the
Elm sensor. In talking about the way environmental devices are explicitly
implicated in forms of politics, Marres (2012, xii) comments, “material
things are today deployed to enact a distinctive public form of engagement.
In these cases, material objects, devices and setting are explicitly ascribed
the capacity to enable political participation” they “wear their politics on
their sleeve”.
    In terms of Elm, its imagined user base and use context implicates a set
of political arrangements, in which − as we saw from the quote from Perkin
Elmer above − the device enables, but also requires, the participation of
members of the public. Key is the ascription of competence (or lack of)
and hence literacy. Elm certainly wears its politics on its sleeve. While
shaped in terms of creating awareness, empowering, understanding, help-
ing, make smarter, and informed decisions, it is not difficult to hear the
responsibility placed on users to be aware, form an understanding, and
make smarter decisions − in short be competent and skilled users. The pre-
scripted “user” is clear.
    It is often the case within a technological deterministic argument that
Reed                                                                         95
devices such as Elm are presented as bringing about change without the
need to consider social arrangements. Such language obscures not only the
social context, but also the requisite competences and responsibilities that
such devices implicate. As Barry (2001, 127) points out “active, responsible
and informed citizens have to be made”. Grint and Woolgar (1997) talks
about the “configuration of the user” through such processes. Configura-
tion in this instance would seem to be oriented to an “informational citi-
zen”, who is aware, informed, and willing to make decisions. This in turn
implicates a set of motivations, competencies, and behaviours. This fact
leads us to consider issues of literacy.
    Marres (2012) presents the history of efforts to engage the public in
environmental concern, by first noting that it is apparent that the “infor-
mational citizenry”, implicated in efforts to improve literacy, have largely
failed to result in the recruitment of the requisite numbers of people. In-
formational literacy campaigns do not address the complexities and con-
textual aspects of social factors. Not only does informational literacy forget
the contexts of technology installation and use, it also could be said that it
is based on a “deficit model” of competence, in that it positions typical
members of the public and lacking the requisite skills. The implication be-
ing that to become an engaged citizen requires a re-education of members
of the public (or in this case a ‘dumbing down’ of the information). We
want to argue that this position is too one-sided. It is the case that there are
various competences required, but it is also the case that there are existing
competences that such perspectives forget. These play into potentials for
heterogeneous and alternate actor networks.
    Rather than rejecting this history outright, Marres (2012, 5-6) goes on
to say that “material participation does not involve stripping participation
of its foundational, linguistic or discursive components”, Instead, we
would argue, literacy (and other discursive components) are interwoven
with forms of action; a far more complicated scenario ensues in which read-
ing information is mutually elaborative with design. Technologies simulta-
neously perform a particular user, and are performed by those users. So, in
the case of Elm, participation is reconfigured by “turning everyday material
action into an index of public participation” (2012, 3).
    Marres takes these ideas a step further by being critical of contemporary
moves within environmental monitoring, which are oriented to recruiting
participants through the allure of simple interfaces and easily consumable
information. Behavioural change through design initiatives are oriented to
“involvement-made-easy” and “small changes” (2012, xiv). These function
“without any significant appeal to their [the actors’] consciousness being
necessary” and hence risk “removing initiative”. Marres takes issues with
such approaches, and advocates seeing the introduction of devices such as
Elm as “experimental sites of material politics, a site where the political
capacities of objects and environments are being actively configured”
(2012, xv).
96                                                               Tecnoscienza – 8 (2)

     Marres champions material participation as an undervalued oppor-
tunity for new forms of public engagement. In relation to sensors this re-
lates to not only the material agency of the particulates being measured,
but also the material interaction with devices and systems by people them-
selves. There is, of course, an additional material element, which completes
this pairing, that is the materiality of the physical environment. Person-de-
vice-environment form a triangle of relationships that in turn implicate a
materially grounded and located set of activities. As Marres puts it an “in-
terest in the role of material entities in the organization of citizenship” itself
offers a renewed “sense of public engagement as an embodied activity that
takes place in certain locations and involves the use of specific objects,
technologies and materials” (2012, 7).
     However, we would like to contend that such opportunities are poten-
tially undermined if the operations of those materially-oriented technolo-
gies are obscured and obfuscated. We argue therefore that if the contextual
details of the sensors’ deployment (the necessity to choose installation
points with lamp posts, the sensitivities of placement of the devices at cer-
tain height, and proximity to traffic) and the adaptations and manipula-
tions of the generated data (through calibration and normalisation) are ex-
cluded.
     In relation to Elm, we might say that Marres would be critical of efforts
to remove the contingencies of their placement and the smoothing of read-
ings through various data manipulations. Rather, we should see Elm as an
opportunity to engender an “experimental site of material politics” (2012,
106) by allowing for questioning, knowledge development, and criticism of
the devices and its outputs.
     Building on the point of the mutual elaboration of technology and use,
we turn to the educational literature of literacies to draw out, and critically
engage with, the history of work on digital literacy. The plural form conveys
the central theme of the perspective which dissuades us of a single under-
standing of literacy and advocates a multiplicity of distinct but interrelated
forms. Again, we should emphasise that we are not claiming an individual
competence model. Rather this pluralisation opens up both the concept of
literacy, and problematizes its simple application to human-device rela-
tions. We agree with Marres’ criticism of the formation of the informational
citizen, but seek to extend her inclusion of the discursive and linguistic
readings in design and deployment.

3.2 Digital Literacies

     In the field of education there is a history of work concerned with digital
literacy. This has, at different times, been referred to in different ways, in-
cluding information literacy, media literacy, and technology literacy (Martin
2008). While such terms have led to a recognition of the socially embedded
nature of such literacies, they are typically articulated such that a person’s
literacy can be measured, assessed and improved. That is there is a single
Reed                                                                        97
linear conception of the more-or-less literate person. Such approaches have
come under scrutiny through a concerted effort to engage with social con-
cepts, especially in relation to the notions of practice and context, “we per-
ceive literacy as a set of socially organised practices that make use of a sys-
tem of symbols and of a technology to produce and disseminate it. Literacy
is not simply knowing how to read and write a given text but rather the ap-
plication of this knowledge for specific purposes in specific contexts. The
nature of these practices including, of course, its technological aspects will
determine the types of abilities associated with literacy” (Scribner and Cole
1981, 236, as quoted in Illera 2010, 51).
    For Illera (2010, 50), practice and context implicate a processual ap-
proach, and simplistic notion of literate and illiterate are avoided: “The
idea of practice […] changes the focus of analysis: no longer solely con-
cerned with results, it highlights the relationship between the cultural (and
technological) context and the forms of specific use adopted by the sub-
jects. […] The gradual nature of literacy recognises that it is a continuum,
one of competence, in which there are many positions and not just two
categories (literate/illiterate)”.
    Yet for us, even these moves to situate practices of digital competencies
don’t go far enough. They still retain (as one might expect from an educa-
tional approach) a sense of (individual) measurement and deficit. One step
towards an alternative is seen in the advocacy of the plural form of literacies
(Lankshear and Knobel 2008; Illera 2010). The work on digital literacies
not only reaches for the “myriad social practices and conceptions of engag-
ing in meaning making […] that are produced, received, distributed, ex-
changes, etc., via digital codification” (Lankshear and Knobel 2008, 5), it
also reveals the potential for competing literacies and the denigration of
one type of literacy in the face of another. An example given by Lankshear
and Knobel (2008, 8) is video game literacy, and they draw this out to im-
plicate a far wider set of competing competences by speaking to the re-
search cliché of “young people trapped in a literary remediation in schools
whilst winning public esteem as fan fiction writers, AMV remixer, or suc-
cessful gamers online”. From here we might add digital literacies of online
shopping (Davies 2008), participating in social media communication
(Knobel and Lankshear 2008) and the ability to promote and market small
businesses (Efimova and Grudin 2008). Erstad (2008) points to music re-
mixing as a denigrated, or our terms disruptive, form of digital literacy (see
also Pegrum 2011).
    Once we move to remixing as a disruptive digital literacy, it is only a
small distance to other more questionable literacies such as hacking, glitch-
ing and modding. Our argument is that it is exactly these forms of behav-
iour - positioned as one more set of literacies – that are key to data engage-
ment and civic involvement (Townsend 2013). Indeed, understood as
forms of creative engagement, these literacies take on a positive character,
and one which has many benefits (not least that it encourages forms of
playful and non-trivial engagement). They also entail active networks of
98                                                             Tecnoscienza – 8 (2)

actants (humans, devices, and software) whose place within any script is
continual and challenging.


4. Experiencing Data

    Couldry et al. (2016) sets out a phenomenologically situated position in
relation to the agency of the algorithm and the human. He advocates a turn
to an understanding of social analytics, the study of the practices of sense-
making applied to contemporary forms of data analytics and presentation:
“A social analytics approach − more precisely, a sociological treatment of
how analytics get used by a range of social actors in order to meet their
social ends − aims to capture how particular actors reflect upon, and adjust,
their online presence and the actions that feed into it, through the use of
‘analytics’” (Couldry et al. 2016, 119).
    What we get from such discussions is a sense of the agency of persons,
and the crediting of them with a range of competences that could easily be
denied and avoided. In addition, the obfuscation of various elements can
lead to a one-sided visibility which blinkers the user and undermines her
viewpoint.
    As Couldry (2016, 120) points out, “while the mutual intertwining of
human and material agency is hardly a new insight (Pickering 1995, 15-20),
it acquires special bite when analytics’ operations are frequently opaque to
non-experts and hard for them to control, even if they do see them at work;
such tension is increased for those social actors who are orientated to goals
that are distinctively social, such as community organizations, charities, and
civil society actors”.
    Put another way, it is bad enough that various aspects of the Elm sen-
sors are opaque (let alone manipulated), but when there is a motivated
public, such as those concerned with air quality in a certain area, such opac-
ity is clearly a problem. While conceptually Marres, Knobel and Lank-
shear, and Couldry come from different positions, and hence engender dis-
tinctions and potential contradictions in relation to their world views, the
formulation presented here aims to navigate a path from material partici-
pation through the multiplication of competences as interwoven in the
emerging script of the device, to an advocacy of person-centred interven-
tion through creative agency. By favouring an ethnographic approach,
which follows the actors in the installation, testing and configuration of the
technologies, we are able to respond theoretically to the issues and con-
cerns encountered. Such sensitivities benefit constructively from moments
of breakdown and the subsequent activities to normalise the technology.
Yet, they also lead us to (re)consider digital literacy as implicated in the
construction of the scripted actor by relevant stakeholders. In turn, we con-
tinue a critical line in relation to such individualistic notions of literacy by
advocating a continuance of breakdown through the embracing instead of
Reed                                                                         99
apparently disruptive literacies. This is meant as a resistive political posi-
tion, as well as an optimistic directive for future technology developments.
Such combinations of method and theory, therefore, are necessary when re-
sponding to such complex, and embedded, contexts.
    And so, what we have is a situation in which a commercially developed
device, that has undergone testing in laboratory conditions, is deployed in
a real world setting. The device is judged to be unfit for deployment due
to inconsistent readings across individual units, and hence adjustments are
made to the readings to ‘normalise’ them. In addition, knowledge of the
real-world settings, which includes the placement of each device in a dif-
ferent, yet specific, location requires further adjustments in relation to ac-
counting for contextual features, such as the height off the ground, and the
likely architectural features of the city which might produce distinctive en-
vironmental conditions (such as the collection of particulates due to ‘ed-
dies’ caused by building positions and tunnel like features of houses and
shops).
    The question becomes whether changing the data in this way is a nec-
essary added step in the deployment of the sensors. On one side, we might
say that we have revealed the processes of data production, what Ribes and
Jackson (2013, 148) call a “complicated ontological choreography, as sci-
entists and technicians work to make data ‘the same’ in a changing ecology
of technologies, organisations, field sites, and institutional arrangement”.
At the same time, we have revealed the obfuscation of those very processes
in the attempt to produce a ‘perfect’ outcome based upon calibration and
normalisation.

4.1 Opening up Creative Practices

    The notion of error presupposes a perfect reading or outcome. As Lisa
Gitelman (2013) and other point out in “raw data” is an oxymoron, far
from there being a perfect objective outcome, objectivity is itself a product
of situated practices within applied scientific disciplines.
    In our case, the objectivity of the data is a key issue in relation to
dealing with the positioning of the sensors in particular locations. The
placing of the sensor on road side lamp posts introduced unwanted con-
textual factors. It turns out that the data was never objective and never raw.
    We can see that such instances open up possibilities for alternative en-
gagement with information, “Error, as errant heading, suggests ways in
which failure, glitch, and miscommunications provide creative openings
and lines of flight that allow for a reconceptualisation of what can (or cannot)
be realised within existing social and cultural practices” (Nunes 2012, 3-4).
    Error opens up the data as created and fallible. Such natural break-
downs implicate deliberate breaching and practices of creative engagement
with data. Contemporary conceptions of “hacking” and “glitching” are
turning to an appreciation of their creative qualities, and certain authors
100                                                           Tecnoscienza – 8 (2)

are advocating such notions as a means to characterise creative engage-
ment, and by extension forms of participation and political action.
    For example, Townsend (2013) combines big data with civic hackers
into a conception of smart cities. In a wide-ranging commentary on the
future of sensor enabled urbanscapes, he comments that “every civic labor-
atory needs a physical and social support system for hackers and entrepre-
neurs to experiment within” (2013, 301).
    We argue here that far from an errant feature of an unscripted set of
characteristics, the variance in readings that occurred with Elm could be a
means to enable an engaged public.
    First it can open up the functionality of the device. A realisation that
each device can give different readings in the same setting, opens up the
possibility of a series of artefacts that differ from one another. Far from a
replica of another, and far from the possibility of true replication of com-
ponents into a single possible outcome, the Elm sensor becomes a material
artefact that is realised in a particular context at a particular time. We are
not disturbed by such notions when we think of different individual humans
perceiving the world in different ways (such as subjective notions of the
weather being poor, or the temperature being too cold) so why should we
not credit measuring devices with such a multiple and perspectival quality.
    Second, such a perspectival quality opens up the notion of context.
Where a device is placed, how it came to be there, and the conditions in
which it finds itself are of course variable. Again, we have no problems in
understanding the varying contexts of the city; for example, that certain
streets will be more or less shielded from the effects of pollution, radiation,
and precipitation. So why would we imagine that it is obviously the correct
operational logic to remove such contextual aspects from the recording de-
vice? Do we imagine that the general public do not understand, or appre-
ciate, or indeed continuously work with and through such contextual fea-
tures?
    Third, by allowing for an appreciation of the perspectival and contex-
tual nature of the devices, we are further allowed to appreciate the func-
tionality of each device and its agentic qualities. Each device functions
within a context to produce a series of readings which are imperfect, but
meaningful. They are interpretations of the air quality (or should that be
qualities) in their immediate surroundings. The device becomes an inter-
preting machine and not a recording machine.
    Finally, a recognition of error, glitch, and breakdown license forms of
critical and creative engagement with information. This in turn might in-
form a type of open data that promotes discourse, questioning and debate.
Such openings up could encourage and require new understandings and
competences, new forms of (potentially disruptive) digital literacies. By ex-
pecting the typical user to content with the complexities of environment
data we might encourage the development of new skills in reading such data.
    Our argument is then that far from correcting the errors and normalis-
ing the readings for the physical contexts of deployment, such features
Reed                                                                          101
would enable a more creative and open engagement with the devices as
socially situated technologies. We should maintain the data frictions, to use
a term from Edwards et al. (2011) that recognises and embraces the ad hoc,
incomplete, loosely structured, and mutable nature of data.


5. Conclusion

    This article has used the case study an urban pollution sensor and its
real-world installation to address key issues in relation to the contingencies
of installation and the characterisation and taken for granted manipulation
of the resulting data. By following the installation process, contextual fea-
tures such as the requirement for infrastructural support for a power sup-
ply, and the resulting positioning of the sensors close to pollution produc-
ing vehicles, were used to describe the continuation of the design script of
the sensors and argue for its extension into the practices of installation.
Recognition of contingency by the installation team, and the variance in
readings obtained led the team to manipulate the data, through standardi-
sation, configuration and normalisation. Such processes were deemed nec-
essary and indeed a requirement for future installation periods. We took
an alternative view in relation to the experience of environmental data by
potential users. Rather than smooth the data, we advocated a perspective
premised upon opening up the physical, cultural and ecological context of
use, so as to engender the emergence of new digital literacies. This line of
reasoning recognises the changing nature of digital literacy, with the emer-
gence of new competences and skills, and argues that nurturing such liter-
acies could provide a means to engender a politically engaged participation
in environmental data, and in turn lend a complement to the notion of data-
driven cities − the creative engagement of data by citizens. In this way, we
hope the article contributes the debates and discussion of the relationships
between data and users in the city context.


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