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.
 Across HCI and social computing platforms, mobile applications that support citizen science, empowering non-experts to explore, collect, and share data have emerged. While many of these efforts have been successful, it remains difficult to create citizen science applications without extensive programming expertise. To address this concern, we present Sensr, an authoring environment that enables people without programming skills to build mobile data collection and management tools for citizen science. We demonstrate how Sensr allows people without technical skills to create mobile applications. Findings from our case study demonstrate that our system successfully overcomes technical constraints and provides a simple way to create mobile data collection tools.  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. This paper describes inAir, a tool for sharing measurements and visualizations of indoor air quality within one's social network. Poor indoor air quality is difficult for humans to detect through sight and smell alone and can contribute to the development of chronic diseases. Through a four-week long study of fourteen households as six groups, we found that inAir (1) increased awareness of, and reflection on air quality, (2) promoted behavioral changes that resulted in improved indoor air quality, and (3) demonstrated the persuasive power of sharing for furthering improvements to indoor air quality in terms of fostering new social awareness and behavior changes as well as strengthening social bonds and prompting collaborative efforts across social networks to improve human health and well being.   In 2012, air pollution in both cities and rural areas was estimated to have caused 3.7 million premature deaths, 88 of those in at risk communities. The primary pollutant was small airborne particulate matter of 10 microns or less in diameter which led to the development of cardiovascular and respiratory diseases. In response, we developed MyPart, the first personal, portable, and accurate particle sensor under $50 capable of distinguishing and counting differently sized particles. We demonstrate how MyPart offers substantial enhancements over most existing air particle sensors by simultaneously improving accessibility, flexibility, portability, and accuracy. We describe the evolution and implementation of the sensor design, demonstrate its performance across twenty everyday urban environments versus a calibrated instrument, and conduct a preliminary user study to report on the overall user experience of MyPart. We also present a novel smart-phone visualization interface and a series of simple form factor adaptations of our design.   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.