Rebecca C. Vandewalleab , William C. Barleyc , Anand Padmanabhanabd, Daniel S. Katzd & Shaowen Wangab* a Department of Geography and Geographic Information Science, University of Illinois at Urbana-Champaign, Urbana, IL, USAb CyberGIS Center for Advanced Digital and Spatial Studies, University of Illinois at Urbana-Champaign, Urbana, IL, USAc Department of Communication, University of Illinois at Urbana-Champaign, Urbana, IL, USAd National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana, IL, USARebecca Vandewalle is a PhD student at the University of Illinois at Urbana-Champaign. Her research interests include spatially-explicit agent-based modeling, spatial network analysis, coupled human and natural systems in emergency contexts, and cyberGIS.William C. Barley is an Assistant Professor in the Department of Communication at the University of Illinois Urbana-Champaign. His research interests include organizational communication, collaboration and coordination, data representation, and field studies of technology design, adoption, and use.Anand Padmanabhan is a Research Associate Professor in the Department of Geography and Geographic Information Science at the University of Illinois Urbana-Champaign. His research interests include distributed systems, cyberinfrastructure, and cyberGIS.Daniel S. Katz is Assistant Director for Scientific Software and Applications at the National Center for Supercomputing Applications and Research Associate Professor in Computer Science, Electrical and Computer Engineering, and the School of Information Sciences at the University of Illinois Urbana-Champaign. His research interests include the interaction of people and software.Shaowen Wang is a Professor and Head of the Department of Geography and Geographic Information Science; and an Affiliate Professor of the Department of Computer Science, Department of Urban and Regional Planning, and School of Information Sciences at the University of Illinois at Urbana-Champaign. His research interests include geographic information science and systems (GIS), advanced cyberinfrastructure and cyberGIS, complex environmental and geospatial problems, computational and data sciences, high-performance and distributed computing, and spatial analysis and modeling.CONTACT Shaowen Wang [email protected] the characteristics of the rapidly evolving geospatial software ecosystem in the United States is critical to enable convergence research and education that are dependent on geospatial data and software. This paper describes a survey approach to better understand geospatial use cases, software and tools, and limitations encountered while using and developing geospatial software. The survey was broadcast through a variety of geospatial-related academic mailing lists and listservs. We report both quantitative responses and qualitative insights. As 42% of respondents indicated that they viewed their work as limited by inadequacies in geospatial software, ample room for improvement exists. In general, respondents expressed concerns about steep learning curves and insufficient time for mastering geospatial software, and often limited access to high-performance computing resources. If adequate efforts were taken to resolve software limitations, respondents believed they would be able to better handle big data, cover broader study areas, integrate more types of data, and pursue new research. Insights gained from this survey play an important role in supporting the conceptualization of a national geospatial software institute in the United States with the aim to drastically advance the geospatial software ecosystem to enable broad and significant research and education advances.

The design of in-vehicle navigation systems fails to take into account the social nature of driving and automobile navigation. In this paper, we consider navigation as a social activity among drivers and navigators to improve design of such systems. We explore the implications of moving from a map-centered, individually-focused design paradigm to one based upon collaborative human interaction during the navigation task. We conducted a qualitative interaction design study of navigation among three types of teams: parents and their teenage children, couples, and unacquainted individuals. We found that collaboration varied among these different teams, and was influenced by social role, as well as the task role of driver or navigator. We also found that patterns of prompts, maneuvers, and confirmations varied among the three teams. We identify overarching practices that differ greatly from the literature on individual navigation. From these discoveries, we present design implications that can be used to inform future navigation systems.