Geographically intelligent disclosure control for flexible aggregation of census data

This paper describes a geographically intelligent approach to disclosure control for protecting flexibly aggregated census data. Increased analytical power has stimulated user demand for more detailed information for smaller geographical areas and customized boundaries. Consequently it is vital that improved methods of statistical disclosure control are developed to protect against the increased disclosure risk. Traditionally methods of statistical disclosure control have been aspatial in nature. Here we present a geographically intelligent approach that takes into account the spatial distribution of risk. We describe empirical work illustrating how the flexibility of this new method, called local density swapping, is an improved alternative to random record swapping in terms of risk-utility

An unsupervised classification method for inferring original case locations from low-resolution disease maps

BACKGROUND: Widespread availability of geographic information systems software has facilitated the use of disease mapping in academia, government and private sector. Maps that display the address of affected patients are often exchanged in public forums, and published in peer-reviewed journal articles. As previously reported, a search of figure legends in five major medical journals found 19 articles from 1994–2004 that identify over 19,000 patient addresses. In this report, a method is presented to evaluate whether patient privacy is being breached in the publication of low-resolution disease maps. RESULTS: To demonstrate the effect, a hypothetical low-resolution map of geocoded patient addresses was created and the accuracy with which patient addresses can be resolved is described. Through georeferencing and unsupervised classification of the original image, the method precisely re-identified 26% (144/550) of the patient addresses from a presentation quality map and 79% (432/550) from a publication quality map. For the presentation quality map, 99.8% of the addresses were within 70 meters (approximately one city block length) of the predicted patient location, 51.6% of addresses were identified within five buildings, 70.7% within ten buildings and 93% within twenty buildings. For the publication quality map, all addresses were within 14 meters and 11 buildings of the predicted patient location. CONCLUSION: This study demonstrates that lowering the resolution of a map displaying geocoded patient addresses does not sufficiently protect patient addresses from re-identification. Guidelines to protect patient privacy, including those of medical journals, should reflect policies that ensure privacy protection when spatial data are displayed or published

Spatial confidentiality and GIS: re-engineering mortality locations from published maps about Hurricane Katrina

BACKGROUND: Geographic Information Systems (GIS) can provide valuable insight into patterns of human activity. Online spatial display applications, such as Google Earth, can democratise this information by disseminating it to the general public. Although this is a generally positive advance for society, there is a legitimate concern involving the disclosure of confidential information through spatial display. Although guidelines exist for aggregated data, little has been written concerning the display of point level information. The concern is that a map containing points representing cases of cancer or an infectious disease, could be re-engineered back to identify an actual residence. This risk is investigated using point mortality locations from Hurricane Katrina re-engineered from a map published in the Baton Rouge Advocate newspaper, and a field team validating these residences using search and rescue building markings. RESULTS: We show that the residence of an individual, visualized as a generalized point covering approximately one and half city blocks on a map, can be re-engineered back to identify the actual house location, or at least a close neighbour, even if the map contains little spatial reference information. The degree of re-engineering success is also shown to depend on the urban characteristic of the neighborhood. CONCLUSION: The results in this paper suggest a need to re-evaluate current guidelines for the display of point (address level) data. Examples of other point maps displaying health data extracted from the academic literature are presented where a similar re-engineering approach might cause concern with respect to violating confidentiality. More research is also needed into the role urban structure plays in the accuracy of re-engineering. We suggest that health and spatial scientists should be proactive and suggest a series of point level spatial confidentiality guidelines before governmental decisions are made which may be reactionary toward the threat of revealing confidential information, thereby imposing draconian limits on research using a GIS

Maintaining orientation within route following tasks : a developmental approach

SIGLEAvailable from British Library Document Supply Centre-DSC:DXN033975 / BLDSC - British Library Document Supply CentreGBUnited Kingdo

'Turn right at the King's Head': drivers' requirements for route guidance information

This thesis addresses a fundamental Human Factors question associated with the design of the Human-Machine Interface (HMI) for in-vehicle electronic route guidance systems: what navigation information should such systems provide to drivers? To avoid the development of systems which demand excessive amounts of drivers' attention and processing resources or which are not satisfactory to the intended user population, it is critical that appropriate information is provided when and where needed. However, a review of the relevant literature revealed a paucity of research concerning this issue. [Continues.

Evaluation of visualisations of geographically weighted regression, with perceptual stability

Given the large volume of data that is regularly accumulated, the need to properly manage, efficiently display and correctly interpret, becomes more important. Complex analysis of data is best performed using statistical models and in particular those with a geographical element are best analysed using Spatial Statistical Methods, including local regression. Spatial Statistical Methods are employed in a wide range of disciplines to analyse and interpret data where it is necessary to detect significant spatial patterns or relationships. The topic of the research presented in this thesis is an exploration of the most effective methods of visualising results. A human being is capable of processing a vast amount of data as long as it is effectively displayed. However, the perceptual load will at some point exceed the cognitive processing ability and therefore the ability to comprehend data. Although increases in data scale did increase the cognitive load and reduce processing, prior knowledge of geographical information systems did not result in an overall processing advantage. The empirical work in the thesis is divided into two parts. The first part aims to gain insight into visualisations which would be effective for interpretation and analysis of Geographically Weighted Regression (GWR), a popular Spatial Statistical Method. Three different visualisation techniques; two dimensional, three dimensional and interactive, are evaluated through an experiment comprising two data set sizes. Interactive visualisations perform best overall, despite the apparent lack of researcher familiarity. The increase in data volume can present additional complexity for researchers. Although the evaluation of the first experiment augments understanding of effective visualisation display, the scale at which data can be adequately presented within these visualisations is unclear. Therefore, the second empirical investigation seeks to provide insight into data scalability, and human cognitive limitations associated with data comprehension. The general discussion concludes that there is a need to better inform researchers of the potential of interactive visualisations. People do need to be properly trained to use these systems, but the limits of human perceptual processing also need to be considered in order to permit more efficient and insightful analysis

The Role of Cognitive Effort in Decision Performance Using Data Representations :;a Cognitive Fit Perspective

A major goal of Decision Support (DSS) and Business Intelligence (BI) systems is to aid decision makers in their decision performance by reducing effort. One critical part of those systems is their data representation component of visually intensive applications such as dashboards and data visualization. The existing research led to a number of theoretical approaches that explain decision performance through data representation\u27s impact on users\u27 cognitive effort, with Cognitive Fit Theory (CFT) being the most influential theoretical lens. However, available CFT-based literature findings are inconclusive and there is a lack of research that actually attempts to measure cognitive effort, the mechanism underlying CFT and CFT-based literature. This research is the first one to directly measure cognitive effort in Cognitive Fit and Business Information Visualization context and the first one to evaluate both self-reported and physiological measures of cognitive effort. The research provides partial support for CFT by confirming that task characteristics and data representation do influence cognitive effort. This influence is pronounced for physiological measures of cognitive effort while it minimal for self-reported measure of cognitive effort. While cognitive effort was found to have an impact on decision time, this research suggests caution is assuming that task-representation fit is influencing decision accuracy. Furthermore, this level of impact varies between self-reported and physiological cognitive effort and is influenced by task complexity. Research provides extensive cognitive fit theory, business information visualization and cognitive effort literature review along with implications of the findings for both research and practic

The Role of Cognitive Effort in Decision Performance Using Data Representations :;a Cognitive Fit Perspective

A major goal of Decision Support (DSS) and Business Intelligence (BI) systems is to aid decision makers in their decision performance by reducing effort. One critical part of those systems is their data representation component of visually intensive applications such as dashboards and data visualization. The existing research led to a number of theoretical approaches that explain decision performance through data representation\u27s impact on users\u27 cognitive effort, with Cognitive Fit Theory (CFT) being the most influential theoretical lens. However, available CFT-based literature findings are inconclusive and there is a lack of research that actually attempts to measure cognitive effort, the mechanism underlying CFT and CFT-based literature. This research is the first one to directly measure cognitive effort in Cognitive Fit and Business Information Visualization context and the first one to evaluate both self-reported and physiological measures of cognitive effort. The research provides partial support for CFT by confirming that task characteristics and data representation do influence cognitive effort. This influence is pronounced for physiological measures of cognitive effort while it minimal for self-reported measure of cognitive effort. While cognitive effort was found to have an impact on decision time, this research suggests caution is assuming that task-representation fit is influencing decision accuracy. Furthermore, this level of impact varies between self-reported and physiological cognitive effort and is influenced by task complexity. Research provides extensive cognitive fit theory, business information visualization and cognitive effort literature review along with implications of the findings for both research and practic

Elements of design for indoor visualisation

Indoor visualisation has received little attention. Research related to indoor environments have primarily focussed on the data structuring, localisation and navigation components (Zlatanova et al., 2013). Visualisation is an integral component in addressing the diverse array of indoor environments. In simple words, 'What is the most efficient way to visualise the surrounding indoor environment so that the user can concisely understand their surroundings as well as facilitating the process of navigation?' This dissertation proposes a holistic approach that consists of two components. The significance of this approach is that it provides a robust and adaptable method in providing a standard to which indoor visualisation can be referenced against. The first component is a theoretical framework focussing on indoor visualisation and it comprises of principles from several disciplines such as geovisualisation, human-perception theory, spatial cognition, dynamic and 3D environments as well as accommodating emotional processes resulting from human-computer interaction. The second component is based on the theoretical framework and adopts a practical approach towards indoor visualisation. It consists of a set of design properties that can be used for the design of effective indoor visualisations. The framework is referred to as the "Elements of Design" framework. Both these components aim to provide a set of principles and guidelines that can be used as best practices for the design of indoor visualisations. In order to practically demonstrate the holistic indoor visualisation approach, multiple indoor visualisation renderings were developed. The visualisation renderings were represented in a three-dimensional virtual environment from a first-person perspective. Each rendering used the design framework differently. Also, each rendering was graded using a parallel chart that compares how the different visual elements were used per the rendering. The main findings were that the techniques/ renderings that used the visual elements effectively (enhanced human-perception) resulted in better acquisition and construction of knowledge about the surrounding indoor environment