Indigeneity and spatial information science

Spatial information science has given rise to a set of concepts, tools, and techniques for understanding our geographic world. In turn, the technologies built on this body of knowledge embed certain ways of knowing. This vision paper traces the roots and impacts of those embeddings and explores how they can sometimes be inherently at odds with or completely subvert Indigenous Peoples\u27 ways of knowing. However advancements in spatial information science offer opportunities for innovation whilst working towards reconciliation. We highlight as examples four active research topics in the field to support a call to action for greater inclusion of Indigenous perspectives in spatial information science

Developing Error Handling Software for Object-Oriented Geographical Information

The inclusion of error handling capabilities within geographical information systems (GIS) is seen by many as crucial to the future commercial and legal stability of the technology. This thesis describes the analysis, design, implementation and use of a GIS able to handle both geographical information (GI) and the error associated with that GI. The first stage of this process is the development of an error-sensitive GIS, able to provide core error handling functionality in a form flexible enough to be widely applicable to error-prone GI. Object-oriented (OO) analysis, design and programming techniques, supported by recent developments in formal OO theory, are used to implement an error-sensitive GIS within Laser-Scan Gothic OOGIS software. The combination of formal theory and GIS software implementation suggests that error-sensitive GIS are a practical possibility using OO technology. While the error-sensitive GIS is an important step toward full error handling systems, it is expected that most GIS users would require additional high level functionality before use of error- sensitive GIS could become commonplace. There is a clear need to provide error handling systems that actively assist non-expert users in assessing, using and understanding error in GI. To address this need, an error-aware GIS offering intelligent domain specific error handling software tools was developed, based on the core error-sensitive functionality. In order to provide a stable software bridge between the flexible error-sensitive GIS and specialised error-aware software tools, the error-aware GIS makes use of a distributed systems component architecture. The component architecture allows error-aware software tools that extend core error-sensitive functionality to be developed with minimal time and cost overheads. Based on a telecommunications application in Kingston-upon-Hull, UK, three error-aware tools were developed to address particular needs identified within the application. First, an intelligent hypertext system in combination with a conventional expert system was used to assist GIS users with error-sensitive database design. Second, an inductive learning algorithm was used to automatically populate the error-sensitive database with information about error, based on a small pilot error assessment. Finally, a visualisation and data integration tool was developed to allow access to the error-sensitive database and error propagation routines to users across the Internet. While a number of important avenues of further work are implied by this research, the results of this research provide a blueprint for the development of practical error handling capabilities within GIS. The architecture used is both robust and flexible, and arguably represents a framework both for future research and for the development of commercial error handling GIS

SPATIAL 2015

This report summarizes the first in a new series of interdisciplinary unconferences, called SPATIAL. SPATIAL 2015 was focused on applying spatial information to human health, and was held at the Center for Spatial Studies at the University of California, Santa Barbara, 9-11 December 2015

Decentralized Monitoring of Moving Objects in a Transportation Network Augmented with Checkpoints

This paper examines efficient and decentralized monitoring of objects moving in a transportation network. Previous work in moving object monitoring has focused primarily on centralized information systems, like moving object databases and geographic information systems. In contrast, in this paper monitoring is in-network, requiring no centralized control and allowing for substantial spatial constraints to the movement of information. The transportation network is assumed to be augmented with fixed checkpoints that can detect passing mobile objects. This assumption is motivated by many practical applications, from traffic management in vehicle ad hoc networks to habitat monitoring by tracking animal movements. In this context, this paper proposes and evaluates a family of efficient decentralized algorithms for capturing, storing and querying the movements of objects. The algorithms differ in the restrictions they make on the communication and sensing constraints to the mobile nodes and the fixed checkpoints. The performance of the algorithms is evaluated and compared with respect to their scalability (in terms of communication and space complexity), and their latency (the time between when a movement event occurs, and when all interested nodes are updated with records about that event). The conclusions identify three key principles for efficient decentralized monitoring of objects moving past checkpoints: structuring computation around neighboring checkpoints; taking advantage of mobility diffusion and separating the generation and querying of movement informatio

Identifying surrounds and engulfs relations in mobile and coordinate-free geosensor networks

This paper concerns the definition and identification of qualitative spatial relationships for the full and partial enclosure of spatial regions. The paper precisely defines three relationships between regions, 'surrounds', 'engulfs', and 'envelops', highlighting the correspondence to similar definitions in the literature. An efficient algorithm capable of identifying these qualitative spatial relations in a network of dynamic (mobile) geosensor nodes is developed and tested. The algorithms are wholly decentralized, and operate in-network with no centralized control. The algorithms are also ``coordinate-free,'' able to operate in distributed spatial computing environments where coordinate locations are expensive to capture or otherwise unavailable. Experimental evaluation of the algorithms designed demonstrates the efficiency of the approach. Although the algorithm communication complexity is dominated by an overall worst-case O(n^2) leader election algorithm, the experiments show in practice an average-case complexity approaching linear, O(n^{1.1})