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This is the accepted version of the paper.This version of the publication may differ from the final published version. Abstract-We enhance a user-centered design process with techniques that deliberately promote creativity to identify opportunities for the visualization of data generated by a major energy supplier. Visualization prototypes developed in this way prove effective in a situation whereby data sets are largely unknown and requirements open -enabling successful exploration of possibilities for visualization in Smart Home data analysis. The process gives rise to novel designs and design metaphors including data sculpting. It suggests: that the deliberate use of creativity techniques with data stakeholders is likely to contribute to successful, novel and effective solutions; that being explicit about creativity may contribute to designers developing creative solutions; that using creativity techniques early in the design process may result in a creative approach persisting throughout the process. The work constitutes the first systematic visualization design for a data rich source that will be increasingly important to energy suppliers and consumers as Smart Meter technology is widely deployed. It is novel in explicitly employing creativity techniques at the requirements stage of visualization design and development, paving the way for further use and study of creativity methods in visualization design. Permanent repository link

SONYC Urban Sound Tagging (SONYC-UST) is a dataset for the development and evaluation of machine listening systems for realworld urban noise monitoring. It consists of 3068 audio recordings from the "Sounds of New York City" (SONYC) acoustic sensor network. Via the Zooniverse citizen science platform, volunteers tagged the presence of 23 fine-grained classes that were chosen in consultation with the New York City Department of Environmental Protection. These 23 fine-grained classes can be grouped into eight coarse-grained classes. In this work, we describe the collection of this dataset, metrics used to evaluate tagging systems, and the results of a simple baseline model.

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Open data programs have become increasingly established at national and local levels of government. While the degree of success these programs have had in achieving their objectives remains open to question, one factor that has been identified as important to any success is the role of open data intermediaries, individuals and organizations that help others to make use of open data. In this paper we investigate how people become engaged with open data, what their motivations are, and the barriers and facilitators program participants perceive with regard to using open data effectively. We interview participants from a variety of backgrounds with differing levels of experience and engagement with open data. Participants include students learning how to train others in open data techniques and tools; people who attend open data events and use open data for commercial or social benefit; and representatives from local government, municipal agencies and a civic tech non-profit. We identify pathways to successfully developing and nurturing a community of open data intermediaries, and make five recommendations for organizations planning and managing open data programs.