Individual neighborhoods within large cities can benefit from independent analysis of public data in the context of ongoing efforts to improve the community. Yet existing tools for public data analysis and visualization are often mismatched to community needs, for reasons including geographic granularity that does not correspond to community boundaries, siloed data sets, inaccurate assumptions about data literacy, and limited user input in design and implementation phases. In Atlanta this need is being addressed through a Data Dashboard developed under the auspices of the Westside Communities Alliance (WCA), a partnership between Georgia Tech and community stakeholders. In this paper we present an interactive analytic and visualization tool for public safety data within the WCA Data Dashboard. We describe a human-centered approach to understand the needs of users and to build accessible mapping tools for visualization and analysis. The tools include a variety of overlays that allow users to spatially correlate features of the built environment, such as vacant properties with criminal activity as well as crime prevention efforts. We are in the final stages of developing the first version of the tool, with plans for a public release in fall of 2016.
The idea of talking to users to elicit their needs is not a new one, and has been formalized into a general set of principles under Human User Centered Design, User Driven Development, and Participatory Design @cite_2 . While the specific methods employed depend on the domain and the kinds of users, the general idea is to talk with community members early in the design process to determine their needs via focus groups, interviews, or site visits. User-centered design is well-suited for PPGIS, and provides a framework for establishing the needs of community members in learning about and utilizing GIS within the context of neighborhood planning @cite_3 . The WCA has been working with the Westside community for years, and is well versed with the needs of the community. Our weekly meetings with them helped us better understand the people and data we were working with and also prioritize the features we hoped to include.
@cite_3 @cite_2
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Public Participation GIS (PPGIS) is a field of research that, among other things, focuses on the use of GIS by non-experts and occasional users. These users tend to have a diverse range of computer literacy, world views, cultural backgrounds and knowledge. These aspects require that the systems used within PPGIS are accessible and easy to use. Human-Computer Interaction (HCI) and the related usability evaluation techniques focus on how to make computer systems more accessible, while focusing on user needs and requirements. Thus, the synergy between PPGIS and HCI seems natural. In this paper, we discuss the aspects of this synergy, building on our experience from three workshops. We demonstrate how usability evaluation can contribute to PPGIS research, and how PPGIS research can contribute to the HCI aspects of GIS in general. We conclude this paper with a call for a user-centred design approach to PPGIS projects. Working with three domain specialists we investigate human-centered approaches to geovisualization following an ISO13407 taxonomy covering context of use, requirements and early stages of design. Our case study, undertaken over three years, draws attention to repeating trends: that generic approaches fail to elicit adequate requirements for geovis application design; that the use of real data is key to understanding needs and possibilities; that trust and knowledge must be built and developed with collaborators. These processes take time but modified human-centred approaches can be effective. A scenario developed through contextual inquiry but supplemented with domain data and graphics is useful to geovis designers. Wireframe, paper and digital prototypes enable successful communication between specialist and geovis domains when incorporating real and interesting data, prompting exploratory behaviour and eliciting previously unconsidered requirements. Paper prototypes are particularly successful at eliciting suggestions, especially for novel visualization. Enabling specialists to explore their data freely with a digital prototype is as effective as using a structured task protocol and is easier to administer. Autoethnography has potential for framing the design process. We conclude that a common understanding of context of use, domain data and visualization possibilities are essential to successful geovis design and develop as this progresses. HC approaches can make a significant contribution here. However, modified approaches, applied with flexibility, are most promising. We advise early, collaborative engagement with data - through simple, transient visual artefacts supported by data sketches and existing designs - before moving to successively more sophisticated data wireframes and data prototypes. In the era of big data, collaborative tagging (a.k.a. folksonomy) systems have proliferated as a consequence of the growth of Web 2.0 communities. Constructing user profiles from folksonomy systems is useful for many applications such as personalized search and recommender systems. The identification of latent user communities is one way to better understand and meet user needs. The behavior of users is highly influenced by the behavior of their neighbors or community members, and this can be utilized in constructing user profiles. However, conventional user profiling techniques often encounter data sparsity problems as data from a single user is insufficient to build a powerful profile. Hence, in this paper we propose a method of enriching user profiles based on latent user communities in folksonomy data. Specifically, the proposed approach contains four sub-processes: (i) tag-based user profiles are extracted from a folksonomy tripartite graph; (ii) a multi-faceted folksonomy graph is constructed by integrating tag and image affinity subgraphs with the folksonomy tripartite graph; (iii) random walk distance is used to unify various relationships and measure user similarities; (iv) a novel prototype-based clustering method based on user similarities is used to identify user communities, which are further used to enrich the extracted user profiles. To evaluate the proposed method, we conducted experiments using a public dataset, the results of which show that our approach outperforms previous ones in user profile enrichment. Historically, the development of computer systems has been primarily a technology-driven phenomenon, with technologists believing that "users can adapt" to whatever they build. Human-centered design advocates that a more promising and enduring approach is to model users' natural behavior to begin with so that interfaces can be designed that are more intuitive, easier to learn, and freer of performance errors. In this paper, we illustrate different user-centered design principles and specific strategies, as well as their advantages and the manner in which they enhance users' performance. We also summarize recent research findings from our lab comparing the performance characteristics of different educational interfaces that were based on user-centered design principles. One theme throughout our discussion is human-centered design that minimizes users' cognitive load, which effectively frees up mental resources for performing better while also remaining more attuned to the world around them.