To assist residents affected by oil and gas development, public health professionals in a non-profit organization have collected community data, including symptoms, air quality, and personal stories. However, the organization was unable to aggregate and visualize these data computationally. We present the Environmental Health Channel, an interactive web-based tool for visualizing environmental sensing and public health data. This tool enables discussing and disseminating scientific evidence to reveal local environmental and health impacts of industrial activities.
EHC is an interactive system that supports citizen science, where amateurs and professionals form partnerships through actual participation or collaboration in producing scientific knowledge @cite_26 @cite_25 @cite_23 @cite_22 @cite_21 @cite_6 . Several existing tools equip citizens with the capabilities to curate data and share data-driven scientific knowledge among stakeholders and community members. Creek Watch @cite_12 is a mobile and web application tool for reporting images and descriptions about the local waterway condition to assist water management policymaking. Sensr @cite_4 is a framework for creating mobile applications to collect and manage citizen-contributed data without coding skills. @cite_3 , @cite_29 , and @cite_8 implemented air quality monitoring systems that measure particulate matters with commercial or customized sensors and visualize these data in browsers or mobile applications. Our work is distinguished from these projects by two aspects. First, EHC provides scientific evidence from various perspectives by visualizing multiple types of data from air quality sensors, health surveys, and personal stories. Second, instead of showing raw data, EHC aggregates data temporally and geographically to enable comparing different local areas.
@cite_26 @cite_4 @cite_22 @cite_8 @cite_29 @cite_21 @cite_6 @cite_3 @cite_23 @cite_25 @cite_12
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Citizen science projects can collect a wealth of scientific data, but that data is only helpful if it is actually used. While previous citizen science research has mostly focused on designing effective capture interfaces and incentive mechanisms, in this paper we explore the application of HCI methods to ensure that the data itself is useful. To provide a focus for this exploration we designed and implemented Creek Watch, an iPhone application and website that allow volunteers to report information about waterways in order to aid water management programs. Working with state and local officials and private groups involved in water monitoring, we conducted a series of contextual inquiries to uncover what data they wanted, what data they could immediately use, and how to most effectively deliver that data to them. We iteratively developed the Creek Watch application and website based on our findings and conducted evaluations of it with both contributors and consumers of water data, including scientists at the city water resources department. Our study reveals that the data collected is indeed useful for their existing practices and is already in use in water and trash management programs. Our results suggest the application of HCI methods to design the data for the end users is just as important as their use in designing the user interface. Our work explores the convergence between participatory sensing, political activism and public expressions. Unlike prior research, which focuses on personal sensing, we present low-cost, networked air quality sensors, designed to be repositioned across public landscapes by communities of citizen stakeholders. Our GPS-enabled sensors report dust, exhaust, or VOC's (volatile organic compounds), along with temperature, humidity and light levels to a website that visualizes this data in real time. The sensors can be attached to a variety of surfaces serving as research probes to demarcate ('tag') public spaces with environmental concerns. We deploy our fully functional system with four urban communities - parents, bicyclists, homeless and activists, positioning our system as a tool for studying and supporting community togetherness and public activism. Our findings highlight community sharing of the physical sensors and dialogues surrounding the collected data. Abstract. In principle, water quality can be managed through an integrative perspective on watersheds, facilitated by a web-based information system. This paper describes a prototype of a web-based Information System for Georgia watersheds called ‘GWIS: Georgia Watershed Information System’. The principal functionality of the system is to provide a platform for integrating state-wide efforts in environmental information collection, collation, storage, analysis, retrieval, and dissemination to all potential stakeholders. Several data management, modeling, visualization, mapping and resource management tools for watersheds, as well as interfaces for integration across diverse and dispersed data sources, are included in the system. As its initial point of departure — to provide substantial and specific content — GWIS has been populated with the high-volume high-quality (HVHQ; near continuous) water quality data acquired during field monitoring campaigns over the past 11 years with the Environmental Process Control Laboratory (EPCL) of the University of Georgia. Information Systems (EIS) modeling with artificial in Grassroots Participatory Sensing empowers people to collect and share sensor data using mobile devices across many applications, spanning intelligent transportation, air quality monitoring and social networking. In this paper, we argue that the very openness of such a system makes it vulnerable to abuse by malicious users who may poison the information, collude to fabricate information, or launch Sybils to distort that information. We propose and implement a novel trusted platform module (TPM), or angel based system that addresses the problem of providing sensor data integrity. The key idea is to provide a trusted platform within each sensor device to attest the integrity of sensor readings. We argue that this localizes integrity checking to the device, rather than relying on corroboration, making the system not only simpler, but also resistant to collusion and data poisoning. A "burned-in" private key in the TPM prevents users from launching Sybils. We also make the case for content protection and access control mechanisms that enable users to publish sensor data streams to selected groups of people and address it using broadcast encryption techniques.