Doing place through data: Proliferation,profiling and the perils of portrayal in local climate action

Abstract

Building on work which has shown the role of digital technologies in reframing environmental relations, this paper explores ethnographically how environmental data is reconfiguring the concept of place. The paper takes as its focus an action-research project within a UK based, citizen-oriented initiative called Newtown Energy Futures, in which we sought to enfold climate and energy data into a social-justice informed attempt at climate action. By exploring how the project used data as an invitation for citizens to engage with and participate in local infrastructural and environmental dynamics, the paper sheds light on how environmental data came to participate in the making of place and in doing so raised questions about how to rebuild the socio-material relations through which ‘a sense of place’ might be reproduced. As climate and energy data increasingly demand that places become enrolled into environmental projects our findings suggest that data enables place to emerge as a ‘socio-technical potentiality’ an observation that has implications both for both engagement with, and the study of data and place. In practical terms, we suggest that this refiguration of place has the effect of creating hopeful trajectories for change, whilst also posing difficult questions about the limits of participation in a data-infused form of place-based politics.

In recent years there has been a flurry of social and political studies that have begun to look at the interplay between digital technologies and environmental processes (Dalsgaard et al., 2021; Goldstein and Nost, 2022; Lippert, 2015; Mah, 2016; Nost and Goldstein, 2021; Walford, 2018). Prompted in part by the appearance of large-scale projects of environmental data sensing and analysis, often led by global consortia of NGOs, governments and corporations, analyses of such projects have highlighted a range of social dynamics, from extractive logics to the infrastructural politics and governance imaginaries that are at play in these new environmental data systems.

One of the most compelling insights from this work has been the observation that data systems not only reveal environmental problems, but in the technical act of revealing they reconstitute environmental and social objects (Gabrys, 2016; Garnett, 2016; Heatherington, Forthcoming 2024; Houser, 2020; Omer, 2021). Forests mapped by Lidar-enabled mapping systems in Indonesia, for example, have been shown to be transformed into novel objects of governance for the Indonesian state (Lin, 2022). Similarly, the appearance of citizen sensing technologies has been shown to rework the notion of the citizen in the face of environmental change, raising novel questions about who or what environmental citizens are and how they are constituted in monitored and datafied environments (Gabrys, 2016, 2022). Rather than taking a simply critical stance towards data practices, these approaches demonstrate how sensory and environmental data shift social relations and configure environmental imaginaries through what Tahani Nadim terms ‘data formations’ (Nadim, 2021). This comparative work across a wide range of sites, demonstrates how novel forms of data upend existing forms of expertise, re-make approaches to environmental action, re-figure understandings of agency and governmentality, and re-work the objects and subjects of environmental politics (Gabrys, 2014; Gabrys et al., 2016; Fortun et al., 2016).

In this paper I build on this work to explore the way environmental data are involved in the material-semiotic (Law, 2009) ‘formation’ of place. Place often appears in literature on environmental data as an important contextual consideration – something that we might lament being erased by the abstractions of data analytics, or that needs to be re-inserted through citizen-data practices (Luque-Ayala and Marvin, 2020; Luque-Ayala and Neves Maia, 2018; Mattern, 2021). Such calls to reinsert place often speak to the unequal distribution of big data that privileges some locations whilst marginalising others in what some have termed the ‘data divide’ (Dalton et al., 2016; Thatcher et al., 2021). However, whilst there has been concern about the erasure or marginalisation of place(s) in discussions of data geographies, there is less work that critically engages with what is actually understood by place in these critiques. Conversely this paper explores the role of data not only in producing spatial effects, but in reframing understandings of what place is and what it might become in the face of global environmental change. ¹

The impetus for this analysis of place emerges from a concern with the way data has become implicated in framing the environmental challenges of climate change as a spatial problem. As ground-breaking studies like Paul Edwards’ A Vast Machine have shown, the work of data collection, statistical analysis and computer modelling are key to framing climate change as a uniquely global challenge, with profound local implications (Edwards, 2010) (see also Knox, 2020). Several scholars have fleshed out the globality of data practices – showing how distributed sensor networks and the big data systems of corporate technology companies, have contributed to establishing climate change as a ‘data arena’ (Ślosarski, 2023) with planetary dimensions (Gabrys, 2020; Wickberg et al., 2024). Sheila Jasanoff has written of such productions of the global as a ‘socio-technical imaginary’, whose power lies in a concatenation of ideas and technical systems that frames and directs approaches to environmental protection and conservation (Jasanoff et al., 2015; see also Jasanoff and Martello, 2004).

Yet for all the focus on how environmental data stabilises climate as a global problem, there has been much less attention on how climate data participates in creating other scales, not least the local, and spatial, category of place. As I have shown in my own previous work on climate models and the city, climate models produce a substantive understanding of carbon emissions concentrations that in turn demand that the global problem of climate change is apportioned to local sites where action on climate change can tangibly happen (Knox, 2020). One of the core challenges of climate change is how to turn the global messages generated by climate modelling into action in place. As a scalar move this requirement seems at first sight self-evident (Wastell, 2001). Having done the hard socio-technical work of stabilising a global environmental imaginary (Jasanoff et al., 2015), the subsequent question of how to reformulate activities in place should be relatively straightforward, except, it is not. One reason for this, I suggest, is the nature of what it means to work with and for place once it has been reframed by data.

In turning my attention to the question of place, and the way it is materialised in relation to environmental data, I thus seek to de-naturalise the idea of place in environmental politics. To do so I build on the work of Keith Basso and his observation that place is not something that is, but is something that people do (Basso, 1996). Basso's careful ethnography of the doing of place among the Western Apache demonstrates that what he terms ‘a sense of place’, is culturally embedded and emerges from an interplay between different tools of engagement. In the case of the Western Apache, place – as simultaneously a concept, an experience and a location – is made out of language, territory, myth, memory and social relations with ancestors and contemporaries. Place emerges in his arresting description of naming and storytelling, not just as a proximate context for Apache social life, but as a social preoccupation that is entangled with broader questions of social reproduction and moral conduct. By attending to how place is done, Basso shows us that place is something we should pay attention to, not assuming it as merely a backdrop to activity or a self-evident matter of scale but rethinking it as an active accomplishment which is framed by, and frames, other dimensions of social life.

In what follows, I explore the doing of place with data in the context of climate change, through a description of an action-research project that I was involved in, in which we set out to explore how data on climate and energy might be used to situate the challenge of global climate change in relation to two neighbourhoods in a town in the north of England which I term, pseudonymously, Newtown. ² The account provided is not an ethnography of how environmental data abstracts from or confronts a more real or authentic local understanding of place but is rather concerned with what happens to a sense of place when data is deployed as a tool to facilitate institutional and civic approaches to climate action.

Focusing on the experiences of this project, I draw out three key dynamics that the demand to engage with place through data came to reveal. The first of these was the experience of data proliferation or what Heather Houser (2020) has termed ‘infowhelm’ wherein an attention to data on place had the effect of enacting place as an unfolding multiplicity of objects and subjects that could potentially be or become relevant. The second dynamic was a practice of assembly whereby objects and entities were de-coupled from settled, linear, historicised and categorical designations, and freed up to build a sense of place in more iterative and destabilised ways. This work served to undercut certain discursive tropes about place, setting in train possibilities and imaginaries that had not been available before. Finally, the third dynamic of data revealed the dangers of these novel forms of description. I term these three effects of data proliferation, profiling and the perils of portrayal.

Through an analysis of these dynamics, I suggest the challenge laid down by data in relation to place is less a problem of communication, truth, or expertise, than one of potentiality. This resonates with similar findings in the work of Yanni Loukissas who showed how the use of data at the Arnold Arboretum also served to remake place (Loukissas et al., 2019). As for Loukissas, data deployed to the ends of climate action in Newtown, emerged less as a picture to be defined, and more as an invitation to find new relationships, discover alliances, strengthen existing ties and circumvent others. Whilst it is already recognised that data gains power not only by being truthful but also by being actionable (Jasanoff, 2017), our findings go one step further to show how the very grounds of action-ability are framed by an emergent understanding of place that is itself reconfigured by data. Overall, attention to data in the Newtown project revealed a particular version of place that was characterised not as a concretisation of the past, nor a singular present, but rather, paraphrasing Jasanoff, as a ‘socio-technical potentiality’.

The research approach

This paper draws on action-research conducted over a 15-month period between 2021 and 2022 within a project pseudonymously called Newtown Energy Futures (NEF). NEF was funded as a practical exploration of the role that climate and energy data might play in engaging communities in conversations about how to achieve reductions in carbon emissions. I participated in the project as a researcher with the role of raising questions, collating insights from the project and feeding back reflections during and after project activities. Although not framed explicitly in the terms of action-research, the project and my research, shared many of the features of action-research methodology, in that we sought to learn about the possibilities and pitfalls of using data to engage communities through a practical process of intervention (Hemment, 2007). Writing about these activities I relate them as a form of research in their own right, through which understanding about data and its relationship to place were derived. The project was thus not so much a conventional ethnographic fieldsite as a collective practice of investigation and reflection, from which the findings presented here were collaboratively arrived at.

At the same time, the research I conducted was ethnographic in nature in that it involved close and ongoing participation in the project from before its inception until after its completion. I interviewed staff on the project as well as other institutional participants about their motivations and reflections on the activities, led ‘reflection sessions’ where members of the project discussed what they thought went well or was problematic about what we were doing, and contributed to the development of a ‘toolkit’ for others who might be interested in running in a similar project in other places. I also had access to and analysed, a large repository of materials generated by those working on the project, including photographs, transcripts and notes on meetings and workshops, planning documents, recordings of zoom calls and the production and analysis of novel forms of data, which I discuss in more detail below. Due to my active involvement in the project and the shared nature of our ambition to explore and understand how data did and did not facilitate knowledge on how to act on climate change, the research might best be understood as a form of collective auto-ethnography, in which the analytical gap required for ethnographic analysis lay between a pre-project and post-project state of understanding rather than between myself as anthropologist, and project members as ‘informants’ (Strathern, 1987).

The NEF project emerged as the result of a successful bid led by an organisation called the Carbon Coop, an energy cooperative based in Manchester, UK to a funding scheme run by ICLEI – an international consortium of cities for sustainability. The project proposal was a response to a call for projects that would experiment with using data to tackle climate change. The ICLEI call was a collaboration with Google.org, who had recently been promoting their climate action platform Google Environmental Insights Explorer and were supporting European-based projects that would ideally use Google's platform to extend local climate action initiatives in cities.

The NEF project proposal was put together by Carbon Coop in collaboration with four other partner organisations who were, for different but overlapping reasons, interested in the role of data in local climate action – an urban design consultancy cooperative, a local council, a local think tank, and my own university. The stated aim of the project was to ‘put [..] data into the hands of citizens, working with skilled experts and municipalities to take control of their own neighbourhoods to plan and implement socially just, citizen-owned municipal energy transition projects’. ³ For Carbon Coop this project built on a long running interest in using sensory and meter data to support practices of decarbonisation. They had previously used electricity, heat and temperature data from meters and sensors to support homeowners and communities in lowering their carbon emissions and ensuring their homes were comfortable. For members of the urban planning cooperative Urbed, this project was an extension of prior work that they had been conducting for many years, using maps and digital interfaces to engage communities in participatory planning processes. For Newtown council the driving interest was in bridging the gap between their carbon targets of achieving net zero carbon emissions by 2030, and the needs of local communities. For the think tank it was an opportunity to develop methods of community led energy planning. And for me, it built on a long running research interest in how climate change was action mediated through data (Knox, 2020, 2021). In the bid, these approaches were brought together in the question of whether, through engagements with data, new ways might be found to help people plan and transform their local energy infrastructure in ways that would contribute to climate change mitigation and build socially beneficial futures. The project sought to directly challenge the siloing of data as a tool of top-down governance or corporate engineering of the climate, seeking instead to draw on paradigms such as the idea of just-transitions, community wealth building, and social solidarity, exploring how data might become a medium in achieving these ends.

Beyond these specific institutional interests, another reason why data was seen as a promising tool for mediating discussions about decarbonisation was data's flattening effect. By this I mean there was a hope that data on material processes might be able to cut through an otherwise charged understanding of local politics and place, particularly when it came to discussions about climate change. The tenor of political debate on decarbonisation in the UK at the time was class-infused, politically divisive and characterised by fears of both entitlement and disenfranchisement. ⁴ Beyond this, there was awareness in the project that climate change was a distant problem for many of those that the project hoped to engage, but also that these same people were persistently left out of conversations about climate change and energy. The question of how people who were ‘not the usual suspects’ of action on climate change (i.e. not climate activists, not scientists, not academics and not policy advisors – that is, not the people running the NEF project), might be invited into such a conversation in a way that did not already fix the terms of what the problem was, or how they should respond, was central to the rationale for using data as a tool of engagement. Data was deployed then not as a global and stable context that demanded a local response, but rather as an ‘agonistic’ technique (Crooks and Currie, 2021) through which a space of debate about climate change and decarbonisation might be brought about.

As a simultaneously co-operative led, citizen focused and data-informed initiative, the project's approach resonated with other activities which have sought to use environmental data to engage communities in environmental issues (Crooks and Currie, 2021; Kimura and Kinchy, 2019). This includes projects that have mobilised the power of data to reveal chemical exposures such as air pollution, toxic waste spills and water contamination (Fortun et al., 2016, 2021; Pritchard et al., 2018). In the UK context our focus on data as a tool for political intervention built on an awareness of work on land ownership mapping, which had recently served to reveal hidden power dynamics that underlie land use for farming and housing development (Christophers, 2018; Shrubsole, 2019). The focus of the project on effecting an energy transition through data resonated with the preoccupations of a wider network of community activist organisations across Europe that had been seeking to capitalise on the possibilities of decentralised renewable power to build social and economic resilience against climate change and extractive capital through technical means (Hewitt et al., 2019). In the UK an important touchpoint was the work of the Centre for Sustainable Energy which was known for having developed community-based approaches to participatory energy planning. When I interviewed project members about resources or initiatives that had framed the project's approach, they also articulated it as emerging from an interest in political movement building, noting the influence on their thinking by grassroots movement-building organisations like NEON in the UK, and Momentum in the USA. A key ambition for all the project organisers was to run the project in a manner that was consistent with an intellectual and political philosophy that was committed to using data in a way that was democratic, empathetic, and which involved both storytelling and open-listening.

In the NEF project, we set out to achieve our ambitions of exploring how to engage communities through data, through four key activities which I explore in more detail below. The first was the building of a repository of data which could be used by communities to support their action on climate change and build local interventions into the broad field of ‘community energy’. The second was the organisation of a series of workshops with two communities in Newtown, in which we would both engage people in existing data, learn about their concerns and needs and generate local data that could inform an energy planning process. The third was to collectively build on this data to create a community led action plan for each of the communities. And the fourth aim was to develop a toolkit which would provide a guide outlining our methodology so that it could be used in other communities. The current paper was also listed as an additional output from the project. In what follows I explore the issues that emerged as we explored how data could be a medium for engaging people in the question of how to effect decarbonisation in place.

Data proliferation

With the core focus of the project being on data, the first question we confronted was what kinds of data should be incorporated into the work of engaging communities. Our starting point was a stipulation by the funder that we explore the value of using a proprietary platform developed by Google.org called Google Environmental Insights Explorer. As Google was one of the funders of the project, there was an expectation by the funding body that the platform should lie at the heart of our work, but very quickly difficulties with the kinds of data that this platform generated became clear.

The Google Environmental Insights Explorer platform is an example what we might call a corporate ‘data for good initiative’ (Espinoza and Aronczyk (2021). Like other such initiatives, where big technology companies mobilise events like hackathons and public data engagements to resolve large-scale environmental problems, the Google Environmental Internet Explorer platform was being promoted as a quasi-public tool to assist municipalities in their decarbonisation efforts. ⁵ Specifically, it promised to help local councils by displaying data on transport decarbonisation, tree planting and solar potential of rooftops. It did so in the form of a birds-eye view dashboard that combined a map, alongside various sliders to visualise the relationship between potential infrastructural interventions and their quantified contribution to meeting environmental targets.

The media scholar and anthropologist Shannon Mattern has written compellingly about the limitations and dangers of such dashboards. In describing the rapid rise of urban dashboards in the early 21st century, Mattern reminds us that the word ‘dashboard’ was originally a 19th century term, which referred to the ‘board or leather apron on the front of a vehicle that kept horse hooves and wheels from splashing mud into the interior’ (Mattern, 2015). Building on this analogy she points out that urban data dashboards are purposely designed to keep the mud and mess of social life at bay, in order to produce a clean vision of urban relations. This then has the effect of privileging certain kinds of action that are framed by the metrics that appear on the dashboard whilst ignoring other issues which remain outside the visual reference that dashboards establish.

Going beyond a critical view of dashboards, literary theorist Ursula Heise (2008) suggests that platforms like Google Earth don’t so much erase the local, as offer a novel response to the challenge of how to reconcile a relationship between the global and the local with which environmental movements have long struggled. Heise argues that digital environmental platforms that were emerging in the early 2000s when her book was written, served to introduce a novel reformulation of place, dependent on what Lev Manovich terms a ‘database aesthetic’ (Manovich, 2001) and characterised by the visual spectacle of seeming to be able to move seamlessly from the whole globe down to a specific place.

However, in the NEF project, it was clear early on that the Google Environmental insights Explorer platform was going to be problematic as a tool of engaging with place. Although it promised an apparently seamless link between global targets and local conditions, its depiction of what constituted environmental infrastructure was in the end both too narrow – focusing only on solar energy, tree planting and transport emissions; and too generic, providing only highly aggregated data on each of these categories. However, despite the limitations of this platform, we did not respond by discarding the idea of the dashboard entirely as a way of engaging place, but instead sought to explore how it might be possible to repurpose the idea of a data dashboard in a way that would lead to a more appropriate and engaging rendering of place for the purposes of tackling climate change. This was to require an approach that would, in Mattern's terms, let some of the ‘mud back in’.

The reason for sticking with the data dashboard was twofold. First it had been written into the project bid that a dashboard would be created as a way of bringing data to communities so there was an obligation to create a dashboard to fulfil the requirements of the funding. But perhaps more importantly there was also a genuine commitment to see just what kinds of data on climate change and energy could be collated, analysed, displayed and used in ways that would support and transform a community's ability to act in a climate-engaged way.

As we moved away from the constraints of the Google Environmental Insights Explorer platform, data in the project quickly began took on a more expansive form. First, John [please add a footnote here stating that all personal names in the document are pseudonyms.], a data analyst in the project who had a specialism in urban analytics, began to explore how he might bring together diverse data sets to shed new light on the urban area we were working in. His hope was that in doing so, new knowledge of the socio-material dynamics of place, and consequently new kinds of interventions might be possible. To conduct this work John built on a recent analysis he had conducted on housing retrofit in Manchester. Here he had found that by juxtaposing the demographic data on an area with the housing types in that area, it was possible to predict how likely residents were to sign up energy retrofit schemes. Building on this, in the NEF project he was interested to see whether the mass of environmental and demographic data now available about cities, could be deployed in a similar way to find novel insights that could shape intervention in energy systems transformation.

The NEF project was taking place in the wake of a long running interest in the UK in making civic data available for public use (Barns, 2020; Luque-Ayala and Marvin, 2020). John draws on an open-source mapping tool created for Greater Manchester called MappingGM, ⁶ as well as data from open street map and on other national open data repositories to begin to assemble data on diverse issues and layer them into a map interface. This would allow for a resonance to appear between forms of information that were not normally brought together.

John's work significantly extended the limitations of the Google Environmental Insights Explorer platform. It incorporated far more types of data that were relevant to the aims of the project to tackle climate change drawing attention to questions like why do people use cars, what kind of access to parks and green spaces do people have, how easy is it for them to use public transport, and what are their homes like? However, even this more expansive use of data had its own limitations.

First as data layers began to accumulate, the volume of data began to cause challenges with the mapping platform. The number of datasets being incorporated meant that the map was taking a long time to load, and John was reticent about simply adding more and more layers of data as he was worried that the system would not be able to cope. Moreover, he was losing sense of the value of the diverse datasets that project members were suggesting could be useful. The risk in climate and energy work was that there were so many kinds of data that could potentially be useful as a signal of, cause of, or potential solution to climate change. Whilst for John, his interest was in how specific forms of spatial data could be juxtaposed and cross referenced to produce new insights that might inform interventions, for other on the NEF project data offered a much more open set of possibilities.

In conversations about potentially useful kinds of data, it became clear there was an understanding that data would produce change not by informing policy pathways, but rather by making visible environmental issues which had remained otherwise latent or out of sight. The expectation here was that by gathering and displaying data that was materially connected to local areas – whether paths, or waterways, or community centres, or local businesses, green spaces or roads or bus stops, data might operate as an elicitation device that would re-narrate the city in socio-environmental terms. It would create new senses of place and with it a novel understanding of what place-based interventions might be possible.

This expectation that data could operate as an elicitation device became particularly clear in conversations and discussions about which two neighbourhoods should become the focus for project work. The original bid had named Newtown council as a project partner, but Newtown is a large town made up of many smaller neighbourhoods which are quite different in terms of income, employment, proximity to energy sources, housing type and transport links. As the aim of the project was to bring data not to the municipality as a whole, but to two specific neighbourhoods, a key activity was to identify which neighbourhoods would be approached for inclusion in the work.

Like most of the other project members, I had never visited Newtown before the project began, and I recall, like others on the project, using a range of methods to sensitise myself to the area. We were still working in the shadow cast by months of COVID lockdown, and so ethnographic and face-to-face research remained difficult. Given this, I started with Google searches for literature on the area, joined some local Facebook groups about local history and local politics, watched some videos of walks through the town which had been uploaded onto YouTube and looked at various maps to get a sense of the topography and spatiality of the areas. Others in the project worked with other kinds of data to sensitise themselves to the geography and sociology of the area. This included drawing on the data that John had compiled, using other information from Mapping GM, looking at lists of local institutions and community groups, and organising online calls with community leaders and council officers.

This wide-ranging data-gathering work provided the grounds for collective discussions about which neighbourhoods to choose as the locations for the project. The aim of the project was to explore the prospect of local low carbon energy interventions in the two communities that the project would work with and so energy was a thread that wove this diversity of data together. Inner city areas, suffering from high levels of deprivation, but good transport links, were contrasted with more rural areas on the edge of the town where the prospects of renewable energy generation looked more likely. The socio-demographics of the areas were also considered as was data on housing ownership and community activities. A middle-class area already equipped with a community hydro project was dismissed as already too-far-on with community energy to be worthwhile engaging with in the terms of the project, which was seeking to engage new communities in the prospects of community energy. Another area in the city centre which had been at the centre of race riots a decade ago, and that seemed potentially appropriate as an area that might benefit from the opportunity to engage in a community energy initiative, was considered and then rejected based on the past experience one person had of trying to work with the community centre there, which had not worked out.

Data of different kinds worked here as an orientation tool that helped us learn about the social, material and political landscape that we were about to enter into. To hold stable a proliferating array of different kinds of data, many of the issues and themes discussed were pasted in a shared Miroboard. Here schematic maps of the possible neighbourhoods we might work with were presented as a series of anchors, around which conversations revolved, data energy infrastructure was added, and virtual sticky notes and text comments were placed. The conversations, in turn, were captured through more sticky notes that were added to the map. All this built up a view of Newtown's various neighbourhoods as more or less predisposed to community energy possibilities. As a result of this orientation process, two neighbourhoods were eventually identified that were invited to become partners in the project. People from each community eventually participated in eight workshops to explore climate action and energy possibilities in their area.

It was clear from this initial orientation work that being open to the multiplicity and ‘wildness’ (Lea, 2020) of data was key to the work of finding a site where climate conversations might be possible. A similar proliferation of data in the context of environmental governance has been noted by Hetherington (forthcoming 2024) who terms the experience of working with such data an experience of participating in ‘an infinity mirror’ where data is increasingly fetishized as the solution to environmental problems, but rarely subjected to effective critique (Heatherington, Forthcoming 2024). In our case, this ‘infinity mirror’ of data provided an answer to the question of how to situate the spatial ambitions of climate change mitigation (a net-zero borough by 2030) within a landscape unfamiliar to most project organisers. By bringing together data on infrastructure, environment and social concerns, place was made able to appear as amenable to the challenges of climate change and energy transitions. Although the neighbourhoods that were chosen did not already self-consciously understand themselves as actively engaged with climate change or energy challenges, they became constituted, due to data-work, as places potentially poised for such engagement. By confronting a dizzying array of diverse and proliferating data and parsing it through a process of assembly, ordering, shuffling, discussion, and evaluation a version of place that was relevant to climate and energy was able to appear. Data thus enabled a sense of place to emerge which was neither a ‘thin simplification’ of top down approaches (Scott, 1998), nor a dense web of embedded social relations (Geertz, 1973), nor indeed an enactment of Manovich's ‘database aesthetic’, but something altogether different – a version of place as socio-technical potentiality, that would come to frame the forms of engagement that subsequently ensued.

Profiling places

With this orientation work completed, the question of how to use this data to engage the two communities became the focus of attention. First this involved a return to the idea of the data dashboard. With this mass of data now available its very existence seemed to demand that it be made useful and available for others. Those in charge of the data focus of the project, decided that the dashboard would take the form of a webpage for each community where detailed information on the neighbourhood could be saved and shared as the project evolved. The hope was that this data would prove useful for people's understanding of climate change and energy within their own neighbourhoods. As the dashboard was discussed, built, and tweaked, it moved further and further away from the kind of control-room live-feed version of the dashboard that Mattern describes. Instead, what was arrived at was a repository that acted more like a living archive of qualitative and qualitative data about the two areas. In recognition of this, the dashboard was first renamed the ‘community hub’. In subsequent conversations about a final toolkit being produced for the project, the community hub was once again renamed, taking on its final designation – the ‘neighbourhood profile’.

The re-naming of the dashboard as a neighbourhood profile brings me to a second dimension of place making that emerged through our use of data, namely the constitution of place through an active technique of ‘profiling’. It was not just in the context of the data dashboard that profiling emerged as a way of framing the use of data; it also characterised the way that data ended up being used in the project workshops.

One of the initial exercises that we ran with both community groups was a place mapping activity where people were asked to place pins on a map of the local area, indicating the institutions and locations that were important for them. This exercise was introduced to create an opportunity for workshop participants to share their own understanding of the significant locations in their local area, as well as using the map as a neutral mediating tool that would enable people who might find it hard to propose topics of conversation to engage in the discussion. It worked with an emergent orientation to objects and subjects, where issues and concerns were brought into view through techniques of data mapping and visual representation – in other words enacting place through a practice of data-informed profiling. This mapping exercise turned out to be highly generative, provoking debate and conversation about topics such as where different people thought the boundaries of the neighbourhood lay, what environmental issues they were concerned about in their local area, and the people or places who were already doing something about these challenges.

However, the language of profiling, particularly when associated with the use of digital data, has more commonly come to carry rather negative connotations. Other recent literature on digital systems has taken issue with the practice of data profiling, demonstrating how such profiling techniques have been used to pursue economic capture, enact state control and engender discriminatory forms of social classification (Eubanks, 2018; McElroy and Vergerio, 2022; Rizzini Ansari, 2022). Nick Seaver's (2018) work on music recommendation engines for example, shows how profiling activates people as digital prosumers. He describes how music platform listeners become profiled algorithmically through their listening habits, and how algorithmic techniques are developed to read these habits and build on them to capture the attention and the financial value of that attention for advertising revenue. Louise Amoore's (2006) work on biometric borders also shows how algorithmic profiling has been used security contexts to constitute people as ‘threats’. Here data profiling identifies individuals as security risks on the basis of an analysis of clusters of otherwise benign biographic data, turning people from passengers into security risks (see also Haggerty and Ericson, 2000). Others have shown how the datafication of the person biometric identity cards or DNA profiling also has the effect of reconstituting persons and their relations to others (Navne and Svendsen, 2022; Rao, 2018). As a person shifts from being a biographically constituted and agentive self to a series of points of data, possibilities for how they can act and relate, and to whom, are also altered.

Whilst this transformation in the person in the course of data profiling, from embodied self to object of governance and control has drawn much critical attention, it also demonstrates that data profiling has a concrete and transformative effect on conceptualisations of entities and an understanding of their capacity to act in particular ways. If profiling can transform people from listeners into prosumers, or kin into racial or class stereotypes, then what might environmentally oriented place-profiling do, in rendering ‘place’ more amenable to the challenges of climate change?

In Newtown it was in re-profiling places and relations that productive moves were made in reconceptualising social life in terms of its relationship to the global scale category of climate change. For example, one of the early activities run with one of the communities, involved reframing Newtown in light of global climate data. The well-known ‘hockey stick’ graph of rising concentrations of atmospheric CO₂, was displayed to the room and when people were asked whether they had seen it before, most shook their heads. This graph was then followed with information about the industrial past of Newtown, its history of coal mining and textile manufacture and its post-industrial decline into the town it is today. Prompted by this information, people at the workshop began to share reminiscences about the changes that the town had seen, from stories of how the ‘houses’ at school were named after the local Mills, to descriptions of the demolition of a local power station, to memories of ‘snow days’ when schools would be closed, and a sadness that those days did not seem to exist anymore. One of the young men in the workshop reflected that it seemed like Newtown was the Dubai of the 19th century, to which others became enthused about whether just maybe if change was coming, its fortunes could change again bringing new jobs and new opportunities into the town.

In the other community that we worked in, mapping the neighbourhood through data on green space and public footpaths, drew attention to forgotten or overlooked spaces. It prompted walks along rarely used paths and a re-familiarisation with a small nature reserve, a disused orchard, and far-reaching views across the hills. It drew attention to the litter discarded along the paths and the vandalism that the green spaces had suffered. It surfaced frustration at feelings of being cut off, of busy roads with no pavements, and of a dysfunctional bus service that didn’t go to where people wanted to go travel. On one of the walks around the neighbourhood where we were looking at solar panels and housing types in the area, one of the participants reflected ‘I don’t usually talk about climate change, but I think that maybe we should’.

Although the exercises might be read as a form of self-surveillance, the possibilities opened up through the data profiling of places were instead described by particular participants as intriguing, transformative and energising. The exercises were rooted in an understanding that bringing data to local actors had the ability to turn latent knowledge that people hold into more enhanced data, thus adding to an understanding (and reading) of the ‘place’ for all parties involved. Profiling drew attention to the sublimated, the overlooked, and the taken-for-granted dimensions dimension of place, wedding these with personal histories, collective tropes and contested narratives whilst simultaneously casting these existing senses of place in a new light. Mundane objects like paths and waste bins were brought from background to foreground, and as they were, possibilities opened up that had not been there before.

Data profiling in our project was not, then, a technique of closure or abstraction or control, but was instead experienced as one of generativity. It was a method that turned an initial proliferation of data into concrete possibilities, making place appear as full of potential. However, the form that this potential took was not always controllable or indeed desirable. In the next section, I move from a focus on how data profiling positioned places as sites of generative potential, to consider the overflows and side effects that constituting place as a socio-technical potentiality also produced.

The perils of portrayal

It is a warm July day and so we are outside in the garden of the community centre in Hilltop. Hilltop is a largely white, largely working-class area on the edge of Newtown and is one of the neighbourhoods that was chosen for the project. With far-reaching views across Greater Manchester, the neighbourhood is high up and exposed to the weather. Today the weather is unusual – Newtown itself is a couple of degrees colder than Manchester City centre, and Hilltop is colder than that. Usually, the wind whips up the hill and through the neighbourhood and though the sun is shining today, it is the wind that comes up most in conversations about renewable energy in the area.

The area was built as a housing estate in the 1960s. Half of it was demolished and rebuilt in the 1990s and new buildings continue to go up. There is high unemployment, meaning both poverty and fuel poverty are widespread, and we are told by those attending the workshop that the area has, for many years, been treated by some of those who live nearby, as a ‘no go’ area.

We have gathered in the community centre for the third energy workshop of the project. The members of the community present are those who are already part of the community centre's network – mainly retired people, with a couple of younger people who have joined because they have been encouraged to by family members. We are standing outside under a gazebo looking at the workshop exercise that participants are about to be asked to complete.

On the trestle tables in front of us, materials have been laid out: a list of energy performance ratings for each of the buildings in the neighbourhood, a map of the area, and coloured pens in green, yellow, orange and red. The exercise has just been explained to the participants – they need to look at a spreadsheet listing the Energy Performance Certificate (EPC) ratings for buildings along a specific road and colour the buildings in accordingly.

Energy Performance Certificate Ratings work on a colour-coded scheme where both appliances and buildings are classified on a scale of A–G to indicate their energy efficiency, with dark green being the most energy efficient and red being the least. The aim of the exercise is to generate a visual map of the energy efficiency ratings across the neighbourhood.

As participants began to colour code the buildings it quickly became clear that this activity offered a compelling mode of engagement with energy in the neighbourhood. As with other profiling work it cultivated an attention to both the social and material properties of the houses in the neighbourhood, causing people to raise questions and make interpretations of the data itself. However, whilst these questions were at times generative, different interpretations also drew out latent tensions and divisions that the data served to surface. When discussing the energy rating data listed for one particular road, participants began to unpack the meaning of these descriptions and their broader implications, wondering why some houses were more energy efficient than others, deciphering why that might be and wondering if the data was itself correct.

As we talked through the energy ratings of buildings, data opened up a space for discussion not just about the energetic properties of the buildings, but also about local politics and people's place within it. Alternating ratings suggested a housing landscape where some people were looked after, and others were not. Red draughty buildings hinted at abandonment, whilst anomalies in the data raised questions about the trustworthiness of the government bodies responsible for compiling the data in the first place. The affective qualities of a moralised visualisation of energy efficiency invited people to remember histories of failed urban development, the decentralisation of responsibility for housing infrastructure in the area, and a generalised sense of abandonment by local government bodies.

Data in the energy rating mapping workshop, offered a means then not just of profiling place as a site of possibility, but of informationally and emotionally concretising latent but viscerally felt politics that might be known idiosyncratically but which now seemed to being made visible in more concrete ways. Energy rating mapping created new insights, but it also invited interpretations which reinforced people's sense that they lived in an uneven economic geography and that their capacity to shape their own lived environment was very limited. These interpretations in turn had to be carefully managed. One concern we had was to ensure that this unevenness that was revealed did not stop at being just descriptive (as one of the workshop organisers put it, ‘we don’t want people going away thinking “we live in a shithole”’). ⁷ Instead, careful work needed to be done to help open up the possibility of using this newfound material concrescence in ways that would lead to constructive interventions and not to a continued politics of frustration, refusal, resignation or withdrawal.

A similar issue arose when the same community was shown the neighbourhood profile website before it went live. One of the pieces of data that was displayed on the website was a chart showing the neighbourhood's place on a national index of multiple deprivation. The index of multiple deprivation is a national measure that categorises places as to how affluent or deprived they are compared to other places. This was displayed on the data dashboard as a way of situating climate and energy concerns within a socio-demographic understanding of the community. Newtown is notorious for having achieved, in 2016, the lowest score on this index for the whole of the UK. Data on both neighbourhoods revealed them to still be low on this index at the time of our project. However, the appearance of this data was responded to very differently by the two different neighbourhood groups. Some of the residents of Hilltop saw this data as potentially further stigmatising the area, whereas the other community saw it as a useful identification of need which they felt might lead to resources flowing into the area.

Another source of data used in the project produced almost the exact reverse problem, creating anxiety not about the harm that data could do to a sense of place, but rather a misplaced hope that certain changes might be possible when actually they were not. This occurred when some project members had commissioned some mapping work to explore the viability of a community wind turbine in Hillside. The consultant who did the mapping work, used wind-flow analyses, land-ownership studies and contour mapping to illustrate that the community may be a viable location for a community-owned wind turbine. This suggestion and the data that supported it was enthusiastically received by many community participants. People started to imagine that instead of being a marginalised area their community might become home to an infrastructural spectacle with visitors coming specifically to see this future wind turbine. However, when some of the project members who had expertise in community energy heard about these discussions they were concerned. What had been a speculative discussion about tentative possibilities had quickly run away with itself, exceeding what was evident in the data in ways that risked creating hope that a local energy project might be possible when there were in fact significant physical and regulatory barriers that would likely make this impossible to achieve. The very openness of profiling created the hope that a different future might be possible, but the danger was that such hope was misplaced, and would in the end lead to disappointment and a replay of a persistent experience of abandonment and marginalisation that those living in this community had felt for many years.

Conclusion

In this paper I have sought to shed light on a specific manifestation of the ‘senses of place’ that I have argued are being reconfigured in the face of climate change. Building on approaches that emphasises place not as a taken-for-granted category where things happen, but as something that is actively done, I have sought to share what difference an attempt to use data as a tool of engagement made in the local framing of place in relation to the challenges of climate change. Taking climate change data to local places is often approached in the UK context as a process of ‘winning hearts and minds’. ⁸ In settings where there is an expectation that hearts and minds will be hard to win over, decarbonisation projects such as housing retrofit often have to be reframed as being about anything but climate change – instead highlighting issues such as fuel poverty, comfort and fairness over climate and energy data. Both these approaches rest on a reception-based understanding of place and community that sits uneasily in relation to expert, data-mediated, climate science. Here place is understood as already consolidated, maybe suspicious of initiatives coming from outside, and focused around the practice of everyday life (de Certeau, 1984) rather than a data-informed depiction of global existential survival.

In our project we took a different approach, using data as a way of mediating between climate and place. In doing so, I suggest the project came to reveal a substantially different understanding of place, with data serving to materialise place not as consolidated but instead as multi-layered, kaleidoscopic, sometimes overwhelming, and always open to change. Having started with the mapped data from Google Environmental Insights Explorer, by the end of the project we were collecting and sharing photographs, narratives, stories, assessments of wind possibilities, EPC ratings of buildings, thermographic images, archival documents and more.

In her 2008 book Sense of Place and Sense of Planet, Ursula Heise argues that American environmentalism has suffered from an uncritical romantic attachment to place, without sufficient interrogation of the conditions under which this sense of place emerged, or a consideration of the alternatives that might be necessary in the face of global environmental change (Heise, 2008). Heise's solution lies in attempts to foster what she terms eco-cosmopolitanism, whereby place is reconciled with global problems through a combination of a classic allegorical appeal to the large scale, wedded with a more hybrid, fragmented understanding of the local. Google Earth offers for Heise a thought-object that materialises a different way of positing placed-ness than a more conventional return to the local as site of authentic environmental relatedness.

Sixteen years on from the publication of Heise's book, the NEF project offers a different answer to this same question of how to reconcile global climate with local place in the context of environmental action. Rather than seeing the local as a fragment or shard of a larger mythical whole, in Newtown the work of doing place through data created a sense of place as something that could be made through an ongoing process of confrontation and cross-pollination between different orders of knowing. Data's invitation to always find new, alternative or other perspectives created a sense of place as a font of possibility. Moreover, the kinds of data that were collected – data on climate, on economy, on housing, on the sun, on transport and footpaths and on community – served to frame these possibilities as simultaneously environmental and social: new jobs, a more pleasant walk, a better-connected neighbourhood, or a way of getting more people involved in community activities. Instead of place being a data-unit in a global model, place was here conceived in more discursive terms, with data operating as an interactive proposition that entered into a dialogic field in which the future was being worked out collectively and in yet-to be determined ways.

A recognition of the part that data played here in reworking a sense of place, offers an opportunity to rethink the relationship between data and spatiality that goes well beyond existing analyses of data-divides. Although some have been critical of the proliferation of data, rightly questioning the way that data becomes inscribed within projects of power and control, including through distributional inequalities (Dalton et al., 2016), I have suggested that the capacity of data to refigure a sense of place in the context of climate action offers another view that points to its more generative possibilities. This is not to claim that data is transparent or a force for good in its own right, but to recognise that there are political possibilities in practices of profiling places through data, that extend and unsettle taken-for-granted understandings of place by refusing to treat its meaning as self-evident. This is not to be naively enthusiastic, or indeed overly optimistic about the power of data for bringing about change, for promises of socio-technical possibilities also open the door for such possibilities to be co-opted, not to be realised, for projects not to materialise, for funding not to appear, or relationships to fail. Nonetheless, recognising that data can enact place anew as a socio-technical possibility, opens the door to other ways of approaching climate action to those which have characterised place as a local site of history and continuity, and climate as an abstracted and external driver of social and environmental change.