Search

OurCity is a site-specific digital artwork designed to solicit, aggregate and visualize citizens’ views on the cities in which they live. It aims to allow people to have their voice heard in a way which is fun and engaging and reduces the gap between citizens and policymakers. OurCity builds on our previous work, VoiceYourView (Whittle et al 2010) which used similar data aggregation techniques but a completely different visualization of user-generated data. This paper revisits the key results from VoiceYourView and hence uses OurCity as an additional validation exercise to assess whether VoiceYourView results are generalizable.

Lagos, Nigeria, is rapidly urbanizing and is one of the fastest-growing cities in the world, with a population that is increasing at almost 500 000 people per year. Yet the impacts on Lagos’s local climate via its urban heat island (UHI) have not been well explored. Considering that the tropics already have year-round high temperatures and humidity, small changes are very likely to tip these regions over heat-health thresholds. Using a well-established model, but with an extended investigation of uncertainty, we explore the impact of Lagos’s recent urbanization on its UHI. Following a multiphysics evaluation, our simulations, against the background of an unusually warm period in February 2016 (during which temperatures regularly exceeded 36°C), show a 0.44°C ensemble-time-mean increase in nighttime UHI intensity between 1984 and 2016. The true scale of the impact is seen spatially as the area over which ensemble-time-mean UHIs exceed 1°C was found to increase steeply from 254 km2 in 1984 to 1572 km2 in 2016. The rate of warming within Lagos will undoubtedly have a high impact because of the size of the population (12+ million) already at risk from excess heat. Significant warming and modifications to atmospheric boundary layer heights are also found in rural areas downwind, directly caused by the city. However, there is limited long-term climate monitoring in Lagos or many similarly expanding cities, particularly in the tropics. As such, our modeling can only be an indication of this impact of urbanization, and we highlight the urgent need to deploy instrumentation.

It is increasingly recognized that a whole-system approach is needed to address many challenging environmental research questions. While the whole-system approach is increasingly adopted by integrating data and models from various sub-systems, the ambition to apply this approach more widely across the environmental sciences requires infrastructure, methodologies, and a culture shift in order to facilitate seamless collaboration and re-deployment of workflows. We report our recent progress in addressing some of these issues. We focus our examples here on work related to the UK Environmental Change Network (ECN, an eLTER member network). A transdisciplinary project team comprised of environmental scientists, statisticians, and computer scientists collaborated through the medium of a virtual research platform (DataLabs). Within the DataLabs platform, all data and analysis code are centrally stored via a cloud service and easily accessible via an internet browser from any operating system. Access to cloud computing resources for analyses are also available. More importantly, all users have access to the same versions of the data and software running on the same hardware throughout the collaboration process.Such close collaboration allows us to co-develop statistical/data science algorithms that are suitable for a wide range of environmental data. These algorithms are not domain-specific and are generic enough to be used on any environmental datasets. Here we demonstrate how they are used to highlight periods of data with significant change. The first example is a "state tagging" algorithm, where each point in time of a dataset is classified as belonging to an arbitrary state based on clustering of covariates. Subsequently, confidence intervals, based on the statistics of each state, are computed and any data points that lie outside the confidence intervals are flagged for further investigation. A second example is the development of an algorithm for the identification of changepoints across multiple time series comprising different sampling frequencies or misaligned sampling times. Existing multivariate changepoint algorithms assume that each time series is sampled at the same time (a situation not commonly applicable to environmental data). Our method removes this assumption, and emerged after consultation and collaboration with domain scientists. It has many potential applications, such as confirming whether changepoints occur across sites or across multiple variables within sites, or combinations thereof. In the final example, we show how DataLabs can facilitate the acquisition and application of third-party data to improve understanding of ECN atmospheric deposition chemistry data. Specifically, it allows users to take advantage of cloud computing and storage and collaborate seamlessly; where each collaborator is not required to have independent versions of software and data, saving time and effort. The developments reported herein highlight the benefits of collaborative research using DataLabs to advance the integration of data, models, and methods across the environmental sciences. It provides the infrastructure, data, and culture to allow scientists to work more closely together. This in turn allows rapid incorporation of novel data science methods. It also allows the data integration workflows developed to be more readily applied elsewhere, while stakeholders can view and manipulate resultant data products.

The Weather Research and Forecasting (WRF) community model is widely used to explore cross‐scale atmospheric features. Although WRF uncertainty studies exist, these usually involve ensembles where different physics options are selected (e.g., the boundary layer scheme) or adjusting individual parameters. Uncertainty from perturbing initial conditions, which generates internal model variability (IMV), has rarely been considered. Moreover, many off‐line WRF research studies generate conclusions based on a single model run without addressing any form of uncertainty. To demonstrate the importance of IMV, or noise, we present a 4‐month case study of summer 2018 over London, UK, using a 244‐member initial condition ensemble. Simply by changing the model start time, a median 2‐m temperature range or IMV of 1.2 °C was found (occasionally exceeding 8 °C). During our analysis, episodes of high and low IMV were found for all variables explored, explained by a relationship with the boundary condition data. Periods of slower wind speed input contained increased IMV, and vice versa, which we hypothesis is related to how strongly the boundary conditions influence the nested region. We also show the importance of IMV effects for the uncertainty of derived variables like the urban heat island, whose median variation in magnitude is 1 °C. Finally, a realistic ensemble size to capture the majority of WRF IMV is also estimated, essential considering the high computational overheads (244 members equaled 140,000 CPU hours). We envisage that highlighting considerable IMV in this repeatable manner will help advance best practices for the WRF and wider regional climate modeling community.

International audience; There is growing interest in the application of the latest trends in computing and data science methods to improve environmental science. However we found the penetration of best practice from computing domains such as software engineering and cloud computing into supporting every day environmental science to be poor. We take from this work a real need to re-evaluate the complexity of software tools and bring these to the right level of abstraction for environmental scientists to be able to leverage the latest developments in computing. In the Models in the Cloud project, we look at the role of model driven engineering, software frameworks and cloud computing in achieving this abstraction. As a case study we deployed a complex weather model to the cloud and developed a collaborative notebook interface for orchestrating the deployment and analysis of results. We navigate relatively poor support for complex high performance computing in the cloud to develop abstractions from complexity in cloud deployment and model configuration. We found great potential in cloud computing to transform science by enabling models to leverage elastic, flexible computing infrastructure and support new ways to deliver collaborative and open science.

The concept ‘models of everywhere’ was first introduced in the mid 2000s as a means of reasoning about the\ud environmental science of a place, changing the nature of the underlying modelling process, from one in which\ud general model structures are used to one in which modelling becomes a learning process about specific places, in\ud particular capturing the idiosyncrasies of that place. At one level, this is a straightforward concept, but at another\ud it is a rich multi-dimensional conceptual framework involving the following key dimensions: models of everywhere,\ud models of everything and models at all times, being constantly re-evaluated against the most current\ud evidence. This is a compelling approach with the potential to deal with epistemic uncertainties and nonlinearities.\ud However, the approach has, as yet, not been fully utilised or explored. This paper examines the\ud concept of models of everywhere in the light of recent advances in technology. The paper argues that, when first\ud proposed, technology was a limiting factor but now, with advances in areas such as Internet of Things, cloud\ud computing and data analytics, many of the barriers have been alleviated. Consequently, it is timely to look again\ud at the concept of models of everywhere in practical conditions as part of a trans-disciplinary effort to tackle the\ud remaining research questions. The paper concludes by identifying the key elements of a research agenda that\ud should underpin such experimentation and deployment.

Organizations increasingly rely on digital tools, such as social media, to harvest public opinion on a variety of issues ranging from brand reputations to political debates. One area in which digital tools have great potential is in consultation on design of public spaces. Public organizations are expected to consult with users of a public space before, during and after occupancy. Digital tools could increase the effectiveness of this consultation because: (i) they are available 24 h and do not rely on the presence of researchers and (ii) data are collected and analysed using automated methods, allowing faster decision-making. Despite these potential advantages, little is understood about how digital and non-digital consultations compare in practice. This paper reports on a live trial with a prototype digital consultation tool called VoiceYourView, which was co-designed with stakeholders and used to canvass opinion on the refurbishment of a major metropolitan library. Over 6 weeks, we used a variety of methods to collect comment from 600 users. VoiceYourView solicits opinion in unprompted form—it does not ask specific questions as in a survey—so users can say anything they like at any time. VoiceYourView carries out real-time analysis of data collected and uses public display screens to summarize comments-to-date in situ. Our research methods focused on observational studies conducted ‘in the wild’: this allowed us to capture user interactions with VoiceYourView in a realistic setting. Our findings indicate that VoiceYourView encouraged more positive feedback than non-digital methods. We also find that positive comments in general contain less actionable information than negative comments, and unprompted comments have similar actionable content to prompted comments. We suggest that this pattern in soliciting more (traditionally difficult to obtain) positive comments with VoiceYourView versus traditional survey methods implies that digital consultation tools of this type can complement existing channels.

Automated passive sensing applications and self-reported smart diaries seem to hold promise for the management of anxiety in autism and other mental health conditions. However, passive sensing often struggles with noisy data, ambiguous feedback and weak user agency over the device, whilst self-reporting relies on user-entered data which can be time consuming and cognitively demanding. To address these limitations, we explore a different approach, whereby individuals consciously actuate personal data capture and are in control of it at all times; yet, the interaction solely involves clicking a button, thus avoiding cognitive overload whilst supporting immediate reflection. We call this approach intentive computing. Through our initial investigations we found that conscious interactions cannot only provide real-time relief in anxiety management, but can also function as memory anchors irrespective of the content captured and even prior to data visualization.

Whether it is in the form of software, system architecture or interface design, anything digital is inevitably affected by values: the organizational values of the project sponsor, the values of the research partners, and the values of each developer and designer. Some values (e.g. commercial success, academic prestige) are easier to quantify than others (e.g. social justice, care for the environment) with the latter often dismissed in decision making processes as lacking of measurable 'evidence'. However, less easy to measure values are not less real: they are simply less visible. The aim of this one-day workshop is precisely to investigate mechanisms which give more exposure to those values in computing that are less frequently considered. We do so by bringing together practitioners from different computing backgrounds (e.g. software engineering, interaction design, information systems) who have first-hand experience of trying to represent on an equal footing all human values in computing.

The transformational potential of using social networking sites (SNS) for activism is a highly researched topic in various academic disciplines, but the topic of ‘success’ has been largely avoided by scholars, much to the detriment of activists themselves, for whom effective use of SNS has become action critical. In this paper, we triangulate findings (incorporating data from surveys, focus groups, and tweets from activists, and combining qualitative and quantitative methods of analysis, chiefly through corpus-based critical discourse analysis) to gain a better understanding of how activists perceive and construct activism on SNS, to describe some features of successful and unsuccessful activist tweets, and to provide some recommendations for heightened impact of activist activities on SNS. To this aim, we describe to what extent certain actions leverage the affordances of digital media and distinguish between categories of action along two dimensions: individualistic vs. collectivistic and persuasive vs. confrontational. We find that activists describe goals that involve individualized, persuasive (and therefore low-risk) activities to be most effectively achieved using Twitter, likely due to fear of police intervention. Activist tweets are found to be retweeted at a dramatically lower rate than a reference corpus of general tweets, and are characterized by lack of original content. We conclude by discussing the various ways in which activists could improve these circumstances and optimize their engagement with SNS by radically increasing their leveraging of the affordances of digital media.

Science-fiction prototyping is often used to explore the social implications of science and technology and to provide inspiration for innovation. The future that is being imagined however often exhibits a form of techno-optimism. This paper critiques that optimism by describing the #Patchworks project in which science fiction prototypes were used to explore the social implications of who does the imagining. Through our vignette we explore how the promissory nature of science fiction prototyping folds back into the present to change current understandings of real life situations. We suggest that the power to imagine and invent futures is often not extended to vulnerable communities, nor does it take into account the differing authority and agency depending on who is telling and who feels able to tell stories. The collision between these different stories and backgrounds in #Patchworks, the co-design project informing this paper, has produced contradictions and negotiations between the speculative practice of ‘tinkering’ used by DIY hackers that act as ‘openings’, an academic focus on innovation and the ‘anchoring’ inherent in the need to produce practical prototypes that solve urgent problems.

The realization that software has a far reaching impact on politics, society and the environment is not new. However, only recently software impact has been explicitly described as `systemic' and framed around complex social problems such as sustainability. We argue that `wicked' social problems are consequences of the interplay between complex economical, technical and political interactions and their underlying value choices. Such choices are guided by specific sets of human values that have been found in all cultures by extensive evidence-based research. The aim of this paper is to give more visibility to the interrelationship between values and SE choices. To this end, we first introduce the concept of Values-First SE and reflect on its implications for software development. Our contribution to SE is embedding the principles of values research in the SE decision making process and extracting lessons learned from practice.

For many people living with conditions such as autism, anxiety manifests so powerfully it has a big impact on quality of life. By investigating the suitability of truly customizable wearable health devices we build on prior research that found each experience of anxiety in people with autism is unique, so 'one-suits all' solutions are not suitable. In addition, users desire agency and control in all aspects of the system. The participative approach we take is to iteratively co-develop prototypes with end users. Here we describe a case study of the co-development of one prototype, a digital stretch wristband that records interaction for later reflection called Snap. Snap has been designed to sit within a platform that allows the distributed and sustainable design, manufacture and data analysis of customizable digital health technologies. We contribute to HCI with (1) lessons learned from a DIY co-development process that follows the principles of modularity, participation and iteration and (2) the potential impact of technology in self-management of anxiety and the broader design implications of addressing unique anxiety experiences.

In many parts of the world, the electricity supply industry makes the task of dealing with unpredictable spikes and dips in production and demand invisible to consumers, maintaining a seemingly unlimited supply. A future increase in reliance on time-variable renewable sources of electricity may lead to greater fluctuations in supply. We engaged remote islanders as equal partners in a research project that investigated through technology-mediated enquiry the topic of synchronising energy consumption with supply, and together built a prototype renewable energy forecast display. A number of participants described a change in their practices, saving high energy tasks for times when local renewable energy was expected to be available, despite having no financial incentive to do so. The main contributions of this paper are in: 1) the results of co-development sessions exploring systems supporting synchronising consumption with supply and 2) the findings arising from the deployment of the prototype.

Part 2: Late Breaking Results; International audience; Designing with the community brings about a number of benefits, including tacit and contextual knowledge about the problem domain; this is especially apparent in rural settings. However, designing for problems that have yet to embed themselves in the fabric of society (i.e. future problems) poses a number of challenges, as they typically present intangible scenarios and concepts that have yet to be experienced by the wider-community. Using the OnSupply project as a case study, we share our experience in working with the Tiree community to address a future problem through a technology-mediated enquiry. Furthermore, we present a novel process that uses creative workshops augmented with physical artefacts to inform and learn from the community about a problem space, and to seed the design of a system that addresses it.

We are exploring attitudes to renewable energy supply with the remote island community of Tiree. As part of this engagement, we are working with local children to introduce the topic of the energy generation potential of renewables (i.e. from wind and solar power). In this paper, we report on our early attempts to broker this engagement using a physical, co-constructed artefact (the PREP energy detector). Through making and co-construction, our goal was to encourage an ownership in the artefact, and thus foster enthusiasm for exploring energy potential. Observations from a recent workshop based on PREP suggest a high level of engagement and enthusiasm was engendered, which we believe was facilitated through co-construction of the artefact.

This paper presents Clasp, a novel tactile anxiety management, communication and peer support tool developed with, by and for adults diagnosed with High Functioning Autism (HFA). Clasp connects a tactile anxiety coping device to a smartphone, which records and communicates anxiety levels for self-feedback and reflection. By adopting an iterative prototyping approach, we gained a deep insight into anxiety experienced by adults with HFA and evaluated the role of digital technology in its management. The paper describes our development approach, which we argue is unique to this multidisciplinary and multiorganizational design context involving hard-to-reach and vulnerable groups. Finally, we reflect on lessons learned from this process and share a set of design implications for the future development of digital tools that, like Clasp, are specifically designed with, by and for adults with HFA.

Software engineering for ‘social good’ is an area receiving growing interest in recent years. Software is increasingly seen as a way to promote positive social change: this includes initiatives such as Code for America and events such as hackathons, which strive to build innovative software solutions with a social conscience. From a software engineering perspective, existing software processes do not always match the needs of these social software projects, which are primarily aimed at social change and often involve vulnerable communities. In this paper, we argue for new software processes that combine elements of agile, iterative development with principles drawn from action research and participatory design. The former allow social software projects to be built quickly with limited resources; the latter allow for a proper understanding of the social context and vulnerable user groups. The paper describes Speedplay, a software development management framework integrating these approaches, and illustrates its use in a real social innovation case study.

Patchworks is a citizen-led co-design project to design innovative technologies for and with homeless people in the North West of England. The project involved 3 quite distinct communities: Signposts, a community resource centre that works with homeless people in Morecambe; Madlab, a community of DIY hackers and creative technologists in Manchester; and an interdisciplinary community of academics from bio-medicine, computing, art-design, anthropology and management science from Lancaster University, as part of the Catalyst project (www.catalystproject.org.uk). This video was made to communicate the Patchworks research to a wider public audience. It shows how through a series of practical electronics workshops and discussions the co-design team developed a prototype to help homeless people, whose lives are often characterised as 'chaotic', to access important appointments.

This paper reports on VoiceYourView, a kind of intelligent kiosk, which uses speech recognition and natural language processing to gather the public's creative input on the public space designs. Over a six week period, VoiceYourView was deployed in a public space and 2000 design critiques were collected from 600 people. The paper shows that people are capable of providing creative input on their environment using unstructured speech or text and that a good proportion of these comments are actionable. The paper also investigates the use of public displays to auto-summarize comments left by the public so far. Although there is anecdotal evidence that this encourages participation, an experiment found that filtering comments (e.g., to display only positive responses) had no effect on what people had to say.

Much has been documented in the literature on sentiment analysis and document summarisation. Much of this applies to long structured text in the form of documents and blog posts. With a shift in social media towards short commentary (see Facebook status updates and twitter tweets), the difference in comment structure may affect the accuracy of sentiment analysis techniques. From our VoiceYourView trial, we collected over 2000 individual short comments on the topic of library refurbishment, many of which are transcribed spoken comments. We have shown success in determining the theme of comments by looking for the first noun and using a semantic tag set to categorise this noun and hence the comment for short comments. Sentiment is a measure of how positive or negative a comment is, and the actionability metric is a measure of how actionable the comment is, i.e. how useful it is. This paper looks towards applying methods from the literature to our dataset with the aim of evaluating methods of automatic sentiment and actionability analysis for our VoiceyourView application data and has relevance to data from other applications, e.g. those from the social media. With many social media commentary applications moving to add speech platforms, VoiceYourView data may be representative of the type of free-form spoken text input to be expected in such platforms.

Self-adaptive systems (SASs) have the ability to reconfigure their behavior to respond to changing external conditions. A key element of a SAS, therefore, is how to monitor the environment so that appropriate adaptations can be triggered. In complex systems, monitoring the environment in its entirety is either impossible or too expensive. As a result, some adaptations are not possible because there is no monitor in place to trigger them. This paper discusses the role of human input, given as speech or text, as a way to provide environmental information to a SAS. The idea is that, given the limitations of monitoring the environment in full, human commentary can potentially be used to build up a more complete picture of the operating context of a SAS. The paper describes existing technology that could be used to realize this idea and describes a number of scenarios where the idea could be useful.

This paper details the signal processing techniques used to produce novel speech metrics for the quantitative assessment of dysarthric speech. A number of different processing methods are used to produce measures designed to aid speech therapists and patients alike in therapy and the assessment of speech quality. The three measures also have the potential for diagnosis of condition and tracking of trends in speech.

With peak oil behind us, nuclear generation capacity dwindling, and increasingly daunting looking carbon emissions targets, we are moving to a world where we must consider transitioning to renewable energy sources. Renewables are time varying and their inherent unpredictability must challenge our everyday assumptions around energy availability—leading, we believe, to an emphasis on ‘supply’ rather than ‘demand’. Using a range of methods including action research, participatory design and technology mediated enquiry, we report on our work in partnership with the community of Tiree as an exemplar of this future. Tiree is the outermost of the Scottish Inner Hebrides— a remote island on the edge of the national electricity grid with a precarious grip on energy—here we uncover the role of renewables and the resilience of a community in moving away from traditional energy provision. We offer opportunities for designing ICT to support supply driven practices in this context, and a simple framework for exploiting under and over supply.