Qualitative geographic information systems (GIS) have come a long way since the original call from critical GIS scholars in the 1990s. The invention of the geoweb as well as big data sources for qualitative information have enabled qualitative GIS to actually be implemented. Academic researchers are now grappling with how best to engage with and use qualitative spatial data. Our focus is on using qualitative data from social media sources. We review the process of collecting and analyzing patterns based on qualitative spatial data using methods from GIScience as well as new techniques from computational linguistics. We review these methods through the lens of critical qualitative GIScience. We reflect critically on the ethics associated with implementation of social qualitative data. Qualitative GIS has reached a critical juncture where the data, methods, and tools have enabled new questions to be asked that were previously not possible to pose. In this article we look to provide guidance and clarity for researchers engaging with geo-social and spatial qualitative data.

Sensitive geographic data are invaluable assets for the people to whom they belong and their disclosure should be decided by the sovereign data owner (SDO). Due to several high‐profile data breaches and business models that commercialize user data, the need for new approaches to geoprivacy and data sovereignty has grown. We propose MapSafe, a client web application that first obfuscates datasets using donut masking or hexagonal binning, separately, and thereafter implements a multi‐level encryption scheme that permits SDOs to share the final encrypted volume containing the geospatial information when they choose and at a level of detail which they are comfortable. The authenticity verification of the volume is facilitated by storing the hash value corresponding to the encrypted volume immutably on the Blockchain as a public record. Our approach places geoprivacy under data guardians'’ control, and its integration capabilities promote its adoption in existing and future geospatial web systems.

Park rangers hold a unique set of knowledge—of science, of publics, of institutional structures, of place, and of self—that should be recognised as valuable. For too long, models of the knowledge of scientists and publics have set people like rangers in an inbetweener position, seeing them as good at communicating, translating or negotiating from one side to the other, but not as making knowledge that is powerful in its own right. In this paper we argue that focus groups with park rangers across regional and conservation parks in Aotearoa/New Zealand reveal the complexity and multiplicity of rangers’ knowledge-making that shows the science-public model as incomplete. We argue further that the model is flawed for its focus on the making and holding of knowledge and not also on how it is enacted. Rangers, we argue, are responsible every day for making knowledgeable decisions for the health and well-being of parks and people. Making good decisions, though, requires not just knowledge but also care. An understanding of the many ways rangers know and enact their knowledge is important for biosecurity practice, especially in models of adaptive governance.

As data science gains traction, it often brings quantitative approaches and positivist epistemologies. While these can generate powerful insights, we argue for methodological hybridity in modern data science. We demonstrate the power of complementary qualitative approaches and flexible ontologies. Using an example of classifying segments™ on Strava, neither quantitative nor qualitative approaches alone were adequate to meaningfully classify segments, but together allowed accurate, useful, and intuitive categories to emerge. Drawing on this experience, we discuss qualitative data science and argue the ontological discussions within Critical GIS from the 1990s and 2000s are increasingly relevant and informative amidst our platial paradigms.

Developing a security solution for spatial files within today’s enterprise Geographical Information System (GIS) that is also usable presents a multifaceted challenge. These files exist in “data silos” of different file server types, resulting in limited collaboration and increased vulnerability. While cloud-based data storage offers many benefits, the associated security concerns have limited its uptake in GIS, making it crucial to explore comparable alternative security solutions that can be deployed on-premise and are also usable. This paper introduces a reasonably usable security solution for spatial files within collaborative enterprise GIS. We explore a Database File System (DBFS) as a potential repository to consolidate and manage spatial files based on its enterprise document management capabilities and security features inherited from the underlying legacy DBMS. These files are protected using the Advanced Encryption Standard (AES) algorithm with practical encryption times of 8 MB per second. The final part focuses on an automated encryption solution with schemes for single- and multi-user files that is compatible with various GIS programs and protocol services. Usability testing is carried out to assess the solution’s usability and focuses on effectiveness, efficiency, and user satisfaction, with the results demonstrating its usability based on the minimal changes it makes to how users work in a collaborative enterprise GIS environment. The solution furnishes a viable means for consolidating and protecting spatial files with various formats at the storage layer within enterprise GIS.

Background: In Canada, access to palliative care is a growing concern, particularly in rural communities. These communities have constrained health care services and accessing local palliative care can be challenging. The Site Suitability Model (SSM) was developed to identify rural “candidate” communities with need for palliative care services and existing health service capacity that could be enhanced to support a secondary palliative care hub. The purpose of this study was to test the feasibility of implementing the SSM in Ontario by generating a ranked summary of rural “candidate” communities as potential secondary palliative care hubs. Methods: Using Census data combined with community-level data, the SSM was applied to assess the suitability of 12 communities as rural secondary palliative care hubs. Scores from 0 to 1 were generated for four equally-weighted components: (1) population as the total population living within a 1-h drive of a candidate community; (2) isolation as travel time from that community to the nearest community with palliative care services; (3) vulnerability as community need based on a palliative care index score; and (4) community readiness as five dimensions of fit between a candidate community and a secondary palliative care hub. Component scores were summed for the SSM score and adjusted to range from 0 to 1. Results: Population scores for the 12 communities ranged widely (0.19–1.00), as did isolation scores (0.16–0.94). Vulnerability scores ranged more narrowly (0.27–0.35), while community readiness scores ranged from 0.4–1.0. These component scores revealed information about each community’s particular strengths and weaknesses. Final SSM scores ranged from a low of 0.33 to a high of 0.76. Conclusions: The SSM was readily implemented in Ontario. Final scores generated a ranked list based on the relative suitability of candidate communities to become secondary palliative care hubs. This list provides information for policy makers to make allocation decisions regarding rural palliative services. The calculation of each community’s scores also generates information for local policy makers about how best to provide these services within their communities. The multi-factorial structure of the model enables decision makers to adapt the relative weights of its components.