Models in the Cloud: Exploring Next Generation Environmental Software Systems

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

Computing and mental health:intentionality and reflection at the click of a button

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 visualizatio

Models of everywhere revisited: a technological perspective

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

The Role of Digital Technologies in Responding to the Grand Challenges of the Natural Environment:The Windermere Accord

Digital technology is having a major impact on many areas of society, and there is equal opportunity for impact on science. This is particularly true in the environmental sciences as we seek to understand the complexities of the natural environment under climate change. This perspective presents the outcomes of a summit in this area, a unique cross-disciplinary gathering bringing together environmental scientists, data scientists, computer scientists, social scientists, and representatives of the creative arts. The key output of this workshop is an agreed vision in the form of a framework and associated roadmap, captured in the Windermere Accord. This accord envisions a new kind of environmental science underpinned by unprecedented amounts of data, with technological advances leading to breakthroughs in taming uncertainty and complexity, and also supporting openness, transparency, and reproducibility in science. The perspective also includes a call to build an international community working in this important area

Fluctuations and correlations for products of real asymmetric random matrices

We study the real eigenvalue statistics of products of independent real Ginibre random matrices. These are matrices all of whose entries are real i.i.d. standard Gaussian random variables. For such product ensembles, we demonstrate the asymptotic normality of suitably normalised linear statistics of the real eigenvalues and compute the limiting variance explicitly in both global and mesoscopic regimes. A key part of our proof establishes uniform decorrelation estimates for the related Pfaffian point process, thereby allowing us to exploit weak dependence of the real eigenvalues to give simple and quick proofs of the central limit theorems under quite general conditions. We also establish the universality of these point processes. We compute the asymptotic limit of all correlation functions of the real eigenvalues in the bulk, origin and spectral edge regimes. By a suitable strengthening of the convergence at the edge, we also obtain the limiting fluctuations of the largest real eigenvalue. Near the origin we find new limiting distributions characterising the smallest positive real eigenvalue

OurCity:understanding how visualization and aggregation of user-generated content can engage citizens in community participation

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

Data-driven decisions for flood risk management

Ensemble is an interdisciplinary research team, working to explore the opportunity of new and emergent digital technologies in understanding, mitigating and adapting to environmental change. Using methods drawn from computer science, environmental science, social science, statistics, art, design and writing the team aim to transform the work of environmental scientists and decision makers, and the experience of communities by addressing themes related to complexity, uncertainty and abstraction of data. This paper discusses activities undertaken within a research ‘sprint’ directed at addressing flood risk management through data driven decision making, communication and community engagement

On the role of digital consultation tools in public space design: a case study

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