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

DataChopin: A collaborative interface for data visualisation and composition on large interactive screens

DataChopin is a research prototype that explores the democratisation of data analytics and sensemaking capabilities. The collaborative interface is a major outcome of sustained research efforts at the Urban Informatics Research Lab, part of the QUT Design Lab, in citizen science and public engagement with urban data. It was developed over the course of multiple iterations spanning across three use cases. Its distinctive characteristics are the use of large, interactive displays as a shared desktop, as well as flexible composition mechanisms for incremental construction of visualisations. By studying interfaces for composing data and visual forms, this research contributes to the understanding of the fundamental components and structure of visualisations, resulting in a general and flexible compositional model. This lays the groundwork for data exploration tools that allow non-expert users to mix, match, and manipulate datasets to obtain visual representations requiring little to no programming knowledge

A customisable dashboard display for environmental performance visualisations

We conducted an exploratory study of a mobile energy monitoring tool: The Dashboard. Our point of departure from prior work was the emphasis of end-user customisation and social sharing. Applying extensive feedback, we deployed the Dashboard in real-world conditions to socially linked research participants for a period of five weeks. Participants were encouraged to devise, construct, place, and view various data feeds. The aim of our study was to test the assumption that participants, having control over their Dashboard configuration, would engage, and remain engaged, with their energy feedback throughout the trial. Our research points to a set of design issues surrounding the adoption and continued use of such tools. A novel finding of our study is the impact of social links between participants and their continued engagement with the Dashboard. Our results also illustrate the emergence of energy-voyeurism, a form of social energy monitoring by peers

Participatory data analytics: Designing visualisation and composition interfaces for collaborative sensemaking on large interactive screens

This thesis proposes the development of interfaces to support collaborative, community-led inquiry into data, which is referred to as Participatory Data Analytics. Over the course of multiple iterations spanning across three use cases, we developed a novel visualisation interface named DataChopin. Its distinctive characteristics are the use of large-scale, vertical displays as a shared desktop, along with natural, touch-based interactions for incremental construction of visualisations. The evaluation of this prototype has yielded recommendations for participatory research practitioners and designers of data exploration interfaces. In doing so, this research takes steps towards greater accessibility and democratisation of data analytics capabilities

Participatory data analytics: Collaborative interfaces for data composition and visualisation

This research proposes the development of interfaces to support collaborative, community-driven inquiry into data, which we refer to as Participatory Data Analytics. Since the investigation is led by local communities, it is not possible to anticipate which data will be relevant and what questions are going to be asked. Therefore, users have to be able to construct and tailor visualisations to their own needs. The poster presents early work towards defining a suitable compositional model, which will allow users to mix, match, and manipulate data sets to obtain visual representations with little-to-no programming knowledge. Following a user-centred design process, we are subsequently planning to identify appropriate interaction techniques and metaphors for generating such visual specifications on wall-sized, multi-touch displays

Developing a dashboard for real-time data stream composition and visualization

Technological advances have led to an influx of affordable hardware that supports sensing, computation and communication. This hardware is increasingly deployed in public and private spaces, tracking and aggregating a wealth of real-time environmental data. Although these technologies are the focus of several research areas, there is a lack of research dealing with the problem of making these capabilities accessible to everyday users. This thesis represents a first step towards developing systems that will allow users to leverage the available infrastructure and create custom tailored solutions. It explores how this notion can be utilized in the context of energy monitoring to improve conventional approaches.\ud \ud The project adopted a user-centered design process to inform the development of a flexible system for real-time data stream composition and visualization. This system features an extensible architecture and defines a unified API for heterogeneous data streams. Rather than displaying the data in a predetermined fashion, it makes this information available as building blocks that can be combined and shared. It is based on the insight that individual users have diverse information needs and presentation preferences. Therefore, it allows users to compose rich information displays, incorporating personally relevant data from an extensive information ecosystem.\ud \ud The prototype was evaluated in an exploratory study to observe its natural use in a real-world setting, gathering empirical usage statistics and conducting semi-structured interviews. The results show that a high degree of customization does not warrant sustained usage. Other factors were identified, yielding recommendations for increasing the impact on energy consumption

Street computing: Towards an integrated open data application programming interface (API) for cities

This special issue of the Journal of Urban Technology brings together five articles that are based on presentations given at the Street Computing workshop held on 24 November 2009 in Melbourne in conjunction with the Australian Computer-Human Interaction conference (OZCHI 2009). Our own article introduces the Street Computing vision and explores the potential, challenges and foundations of this research vision. In order to do so, we first look at the currently available sources of information and discuss their link to existing research efforts. Section 2 then introduces the notion of Street Computing and our research approach in more detail. Section 3 looks beyond the core concept itself and summarises related work in this field of interest

Street computing: Towards an integrated open data Application Programming Interface (API) for cities

This special issue of the Journal of Urban Technology brings together five articles that are based on presentations given at the Street Computing Workshop held on 24 November 2009 in Melbourne in conjunction with the Australian Computer- Human Interaction conference (OZCHI 2009). Our own article introduces the Street Computing vision and explores the potential, challenges, and foundations of this research trajectory. In order to do so, we first look at the currently available sources of information and discuss their link to existing research efforts. Section 2 then introduces the notion of Street Computing and our research approach in more detail. Section 3 looks beyond the core concept itself and summarizes related work in this field of interest. We conclude by introducing the papers that have been contributed to this special issue

DataChopin - Designing interactions for visualisation composition in a co-located, cooperative environment

This article presents our interaction design for DataChopin, based on an extensive survey and classification of visualisation software for exploratory data analysis. Its distinctive characteristics are the use of a large-scale display wall as a shared desktop, as well as flexible composition mechanisms for incremental and piece-wise construction of visualisations. We chose composability as a guiding principle in our design, since it is essential to open-ended exploration, as well as collaborative analysis. For one, it enables truly exploratory inquiry by letting users freely examine different combinations of data, rather than offering a predetermined set of choices. Perhaps more importantly, it provides a foundation for data analysis through collaborative interaction with visualisations. If data and visualisations are composable, they can split into independent parts and recombined during the analytical process, allowing analysts to seamlessly transition between closely- and loosely-coupled work