Search for: All records

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. 

This paper investigates the tools and practices used by Orientation and Mobility (O&M) specialists in instructing people who are blind or have low vision in concepts, skills, and techniques for safe and independent travel. Based on interviews with experienced instructors who practice in different O&M settings we find that a shortage of qualified specialists and restrictions on in-person activities during COVID-19 has accelerated interest in remote instruction and assessment, while widespread adoption of smartphones with accessibility support has driven interest in assistive apps. This presents both opportunities and challenges for a practice that is traditionally conducted in-person and assessed through qualitative observations. In response we identify multiple opportunities for HCI research in service of O&M, including: supporting a 'physician's assistant' model of remote O&M instruction and assessment, matching O&M instructors' clients with guide dogs, highlighting clients' progress towards O&M goals, and collaboratively planning routes and monitoring clients' independent travel progress. 

Background Remote patient monitoring (RPM) technologies can support patients living with chronic conditions through self-monitoring of physiological measures and enhance clinicians’ diagnostic and treatment decisions. However, to date, large-scale pragmatic RPM implementation within health systems has been limited, and understanding of the impacts of RPM technologies on clinical workflows and care experience is lacking. Objective In this study, we evaluate the early implementation of operational RPM initiatives for chronic disease management within the ambulatory network of an academic medical center in New York City, focusing on the experiences of “early adopter” clinicians and patients. Methods Using a multimethod qualitative approach, we conducted (1) interviews with 13 clinicians across 9 specialties considered as early adopters and supporters of RPM and (2) speculative design sessions exploring the future of RPM in clinical care with 21 patients and patient representatives, to better understand experiences, preferences, and expectations of pragmatic RPM use for health care delivery. Results We identified themes relevant to RPM implementation within the following areas: (1) data collection and practices, including impacts of taking real-world measures and issues of data sharing, security, and privacy; (2) proactive and preventive care, including proactive and preventive monitoring, and proactive interventions and support; and (3) health disparities and equity, including tailored and flexible care and implicit bias. We also identified evidence for mitigation and support to address challenges in each of these areas. Conclusions This study highlights the unique contexts, perceptions, and challenges regarding the deployment of RPM in clinical practice, including its potential implications for clinical workflows and work experiences. Based on these findings, we offer implementation and design recommendations for health systems interested in deploying RPM-enabled health care. 

Urban planning is increasingly data driven, yet the challenge of designing with data at a city scale and remaining sensitive to the impact at a human scale is as important today as it was for Jane Jacobs. We address this challenge with Urban Mosaic, a tool for exploring the urban fabric through a spatially and temporally dense data set of 7.7 million street-level images from New York City, captured over the period of a year. Work- ing in collaboration with professional practitioners, we use Urban Mosaic to investigate questions of accessibility and mobility, and preservation and retrofitting. In doing so, we demonstrate how tools such as this might provide a bridge between the city and the street, by supporting activities such as visual comparison of geographically distant neighborhoods, and temporal analysis of unfolding urban development.