Program your city: Designing an urban integrated open data API

Cities accumulate and distribute vast sets of digital information. Many decision-making and planning processes in councils, local governments and organisations are based on both real-time and historical data. Until recently, only a small, carefully selected subset of this information has been released to the public – usually for specific purposes (e.g. train timetables, release of planning application through websites to name just a few). This situation is however changing rapidly. Regulatory frameworks, such as the Freedom of Information Legislation in the US, the UK, the European Union and many other countries guarantee public access to data held by the state. One of the results of this legislation and changing attitudes towards open data has been the widespread release of public information as part of recent Government 2.0 initiatives. This includes the creation of public data catalogues such as data.gov.au (U.S.), data.gov.uk (U.K.), data.gov.au (Australia) at federal government levels, and datasf.org (San Francisco) and data.london.gov.uk (London) at municipal levels. The release of this data has opened up the possibility of a wide range of future applications and services which are now the subject of intensified research efforts. Previous research endeavours have explored the creation of specialised tools to aid decision-making by urban citizens, councils and other stakeholders (Calabrese, Kloeckl & Ratti, 2008; Paulos, Honicky & Hooker, 2009). While these initiatives represent an important step towards open data, they too often result in mere collections of data repositories. Proprietary database formats and the lack of an open application programming interface (API) limit the full potential achievable by allowing these data sets to be cross-queried. Our research, presented in this paper, looks beyond the pure release of data. It is concerned with three essential questions: First, how can data from different sources be integrated into a consistent framework and made accessible? Second, how can ordinary citizens be supported in easily composing data from different sources in order to address their specific problems? Third, what are interfaces that make it easy for citizens to interact with data in an urban environment? How can data be accessed and collected

Towards evaluation design for smart city development

Smart city developments integrate digital, human, and physical systems in the built environment. With growing urbanization and widespread developments, identifying suitable evaluation methodologies is important. Case-study research across five UK cities - Birmingham, Bristol, Manchester, Milton Keynes and Peterborough - revealed that city evaluation approaches were principally project-focused with city-level evaluation plans at early stages. Key challenges centred on selecting suitable evaluation methodologies to evidence urban value and outcomes, addressing city authority requirements. Recommendations for evaluation design draw on urban studies and measurement frameworks, capitalizing on big data opportunities and developing appropriate, valid, credible integrative approaches across projects, programmes and city-level developments

A Tale of Evaluation and Reporting in UK Smart Cities

Global trends towards urbanisation are associated with wide-ranging challenges and opportunities for cities. Smart technologies create new opportunities for a range of smart city development and regeneration programmes designed to address the environmental, economic and social challenges concentrated in cities. Whilst smart city programmes have received much publicity, there has been much less discussion about evaluation of smart city programmes and the measurement of their outcomes for cities. Existing evaluation approaches have been criticised as non-standard and inadequate, focusing more on implementation processes and investment metrics than on the impacts of smart city programmes on strategic city outcomes and progress. To examine this, the SmartDframe project conducted research on city approaches to the evaluation of smart city projects and programmes, and reporting of impacts on city outcomes. This included the ‘smarter’ UK cities of Birmingham, Bristol, Manchester, Milton Keynes and Peterborough. City reports and interviews with representative local government authorities informed the case study analysis. The report provides a series of smart city case studies that exemplify contemporary city practices, offering a timely, insightful contribution to city discourse about best practice approaches to evaluation and reporting of complex smart city projects and programmes

Fusion of Heterogeneous Earth Observation Data for the Classification of Local Climate Zones

This paper proposes a novel framework for fusing multi-temporal, multispectral satellite images and OpenStreetMap (OSM) data for the classification of local climate zones (LCZs). Feature stacking is the most commonly-used method of data fusion but does not consider the heterogeneity of multimodal optical images and OSM data, which becomes its main drawback. The proposed framework processes two data sources separately and then combines them at the model level through two fusion models (the landuse fusion model and building fusion model), which aim to fuse optical images with landuse and buildings layers of OSM data, respectively. In addition, a new approach to detecting building incompleteness of OSM data is proposed. The proposed framework was trained and tested using data from the 2017 IEEE GRSS Data Fusion Contest, and further validated on one additional test set containing test samples which are manually labeled in Munich and New York. Experimental results have indicated that compared to the feature stacking-based baseline framework the proposed framework is effective in fusing optical images with OSM data for the classification of LCZs with high generalization capability on a large scale. The classification accuracy of the proposed framework outperforms the baseline framework by more than 6% and 2%, while testing on the test set of 2017 IEEE GRSS Data Fusion Contest and the additional test set, respectively. In addition, the proposed framework is less sensitive to spectral diversities of optical satellite images and thus achieves more stable classification performance than state-of-the art frameworks.Comment: accepted by TGR

The influences of user generated ‘Big data’ on urban development

Cities are the nucleus for creativity and ideas, as it has all the potentials for people to work, explore and live. People always come to cities because they want to be part of something, this magnet in the cities created the problem of population (Ericsson: Thinking Cities in the Networked Society, 2012). Approximately 50% of world’s population lives in urban areas, a number which is expected to increase to nearly 60% by 2030. (Mutizwa-Mangiza ND, Arimah B C, Jensen I, Yemeru EA, Kinyanjui MK, 2011). According to the rapid change in cities’ population there exists a need to utilize intelligent prediction tools to deliver a better way of living. Smart cities provide an opportunity to connect people and places using innovative technologies that help in better city planning and management ( Khan, Anjum, Soomro, & Tahir, 2015). Data is never a new thing, but data sources are always in change. The internet made everything easier and more reachable. This wide range of technologies such as IOT (internet of things) and M2M (machine to machine) (Gartner, 2015), is believed to offer a new potential to deliver an analytical framework for urban optimization. The real value of such data is gained by new knowledge acquired by performing data analytics using various data mining, machine learning or statistical methods. According to this technologically mutated, data comes from weather channels, street security cameras, Facebook, Twitter, sensor networks, in-car devices, location-based smartphone apps, RFID tags, smart meters, among other sources (Hinssen, 2012). This massive amount of information that comes from real-time based tools, made the world in front of a new era of data called ‘Big Data’. However, turning an ocean of messy data into knowledge and wisdom is an extremely challenging task. The proposed paper will discuss the IOT developed frameworks which are used to improve cities infrastructure and their vital systems. Analyzing these frameworks will help developing a conceptual proposal of data visualizing software; with the aim of helping urban planners get a better and easier way to comprehend the usage of multi-data sources for city planning and management. The full control of data is an open challenge, however proposing the fundamental bases of framework with the ability to extend and having an application layer above would be very helpful for urban process shifting. The Egyptian case is our main scope to have a smarter city that provides an opportunity to connect people and places using innovative technologies

Trends in Smart City Development

This report examines the meanings and practices associated with the term 'smart cities.' Smart city initiatives involve three components: information and communication technologies (ICTs) that generate and aggregate data; analytical tools which convert that data into usable information; and organizational structures that encourage collaboration, innovation, and the application of that information to solve public problems

Communication on Smart City Evaluation and Reporting In UK cities: Pilots, Demos and Experiments Case

Global trends towards urbanisation are associated with wide-ranging challenges and opportunities for cities. Smart technologies create new opportunities for a range of smart city development and regeneration programmes designed to address the environmental, economic and social challenges concentrated in cities. Whilst smart city programmes have received much publicity, there has been much less discussion about the evaluation and measurement of smart city programme outcomes. Existing evaluation approaches have been criticised as non-standard and inadequate, focusing more on implementation processes and investment metrics than on city outcomes and the impacts of smart city programmes. Addressing this, the SmartDframe project aimed to examine city approaches to the evaluation of smart city projects and programmes and reporting of their impacts on city outcomes. A number of ‘smarter’ UK cities were invited to participate, with agreement by city authorities from Birmingham, Bristol, Manchester, Milton Keynes and Peterborough to be interviewed about their smart city work. The findings provide a series of smart city case studies that exemplify contemporary city practices, offering a timely, insightful contribution to city discourse about existing and best practice approaches to evaluation and reporting of complex smart city projects and programmes

Connected systems in smart cities: use-cases of integration of buildings information with smart systems

Realisation of smart cities is highly dependent on innovative connections between the deployed systems in the cities. This implies that successfully deployment of individual smart systems which meet citizens’ needs, is not sufficient to make a city smart. Indeed, the smart cities require to innovate and connect establish infrastructures for the citizens and organisations. To enable connected systems in smart cities, the possibilities to exchange and integration information between different systems is essential. Construction industry is one of the domains which owns huge amount of valuable information asset. Buildings information can be utilised to create initiatives associated with various domains like, urban and infrastructure planning, maintenance/facility management, and energy monitoring. However, there are some barriers to realise these initiatives. This paper introduces and elaborates the details about three use-cases which need to utilise buildings information to present innovative smart services. The three use cases are: 1) Energy Usage Monitoring for positive energy usage district areas in Smart Cities (a use case from River City-anonymous name of the city); 2) Services for Facility Management Industry (a use-case from Estates office in Quay University); 3) Safety & risk management for buildings in 3D Hack event in Dublin. Each use-case considers various stakeholders’ perspectives. Also they include elaborated details related to the barriers and challenges associated with utilisation and integration of buildings information. This paper concludes by the detailed barriers to benefit from valuable buildings information to create innovative smart services. Further, recommendations are provided to overcome the presented challenges

A Framework for Integrating Transportation Into Smart Cities

In recent years, economic, environmental, and political forces have quickly given rise to “Smart Cities” -- an array of strategies that can transform transportation in cities. Using a multi-method approach to research and develop a framework for smart cities, this study provides a framework that can be employed to: Understand what a smart city is and how to replicate smart city successes; The role of pilot projects, metrics, and evaluations to test, implement, and replicate strategies; and Understand the role of shared micromobility, big data, and other key issues impacting communities. This research provides recommendations for policy and professional practice as it relates to integrating transportation into smart cities

Identifying the practice components of youth councils: contributions of theory

Social workers are involved in numerous efforts to engage youth in programs, communities, and civic life. One potential strategy has focused on engagement and empowerment of youth through the form of youth councils. Multiple theoretical frames have characterized the scholarly literature. This has limited the conceptual coherence of the field. In this paper, we report empirical data on the operation of several youth councils. We analyze the data to identify the implicit frameworks in use and apply the data from our study to sort practice components within frameworks. This effort is designed to improve conceptualization of youth councils, to inform the development of councils, and eventually to improve outcomes of councils.Published versionAccepted manuscrip