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

Multi-criteria aggregation for sensistive parcel-based census data

Modern urban planning considers various socio-economic issues and hence requires fine-grained, potentially sensitive spatial data, raising the disclosure dilemma: Whilst it is imperative to aggregate fine-grained sensitive records large enough to avoid disclosure, aggregation blurs the information, potentially hindering insights about spatially explicit relationships. MASC is an aggregation algorithm for sensitive data, balancing five aggregation criteria

Identifying the challenges of creating an optimal dissemination geography for census

The importance of census data in government and private-sector planning cannot be underestimated. However, the geographic level at which it is made available for different users, is a highly debateable issue. It is crucial that census data is disseminated in such a way that it satisfies most user needs as far as possible, to ensure that there is optimum use of the information and that maximum value for money is provided. In the past, Statistics South Africa disseminated data at the same geographic level created for data collection. This causes problems for data users and calls for the creation of a separate output geography rather than using the original collection geography.The research was done on two levels: first, an overview of output geographies, as well as examples of developed and successfully used tools to generate these areas within a geographical information system. Some of these could be used in the South African milieu. Secondly the paper discuss aspects such as the population size variation of EAs, in order to inform the criteria for the creation of the ideal small area (SA) layer to satisfy the majority of user needs. Lastly the paper describes briefly the challenges faced to create the 2011 output geography. The results indicate a strong resemblance between the two EA population size patterns of 2001 and 2011, influenced by the EA demarcation rules. The challenges identified in the process of creating the SAL as a census output geography need to be taken into consideration to enable a more useful and user-friendly output

Green building management practices model for Malaysia Green Building

Presently, there are serious environmental problems caused by natural and man-made sources. Climate change issues have become a global phenomenon, in particular greenhouse gas emissions such as carbon dioxide (CO2) emissions, recognized as an important factor contributing to climate change. Previous research has revealed that the building sector is one of the largest sources of greenhouse gas emissions globally. The concept of green building emerged during the late 19th and early 20th centuries and it was designed to reduce negative environmental effects and preserves natural resource. The review of the world green building standard shows that management of green building is a critical issue to attain sustainable development. Presently, Malaysia does not have a set of structured green building management key practices in its green building rating system. Therefore, the main objective of the current study was to ascertain appropriate management key practices to attain sustainable development in Malaysian green buildings. Data was collected in two phases and the respondents comprised of 35 Malaysian green building experts, facilitators and managers in phase one, and 89 respondents in phase two. Phase one involved an expert survey to identify the list of key practices to manage the green building and data were analysed by Relative Importance Index. In phase two, questionnaire survey was utilised to identify management key practices appropriate for Malaysian green buildings. Structural Equation Modeling-Partial Least Square was used to analyse the data. This study identified five management key practices, which play a critical role for green building performance, which include sustainable operation, sustainable procurement, environmental health, resource management and repair and maintenance management. However, only four management key practices effect on optimal performance of green buildings in Malaysia were identified which include environmental health, sustainable procurement, sustainable operation and resource management. The contribution of knowledge of this study is the development of a structural equation modeling green building management key practices for Malaysia

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

Investigating the impact of GIS modelled daily exposures to the retail food environment on routinely linked child health data

Obesity continues to be a huge public health concern around the globe, and numbers are projected to continue to increase. There is particular concern around the issue of obesity in children because obese children are far more likely become obese adults than children who are a healthy weight. We have so far been ineffective in developing successful public health policies and interventions that report population level reductions in obesity. In order to tackle obesity on a large scale, we need to be creative and develop interventions and policies that drive societal change.The cause of obesity has been found to be not a linear relationship of cause and effect but a complex and multifaceted system. Geographic Information Systems (GIS) are being used to more fully understand the role of the environment on obesity. There has been a particular focus on exposure to the ‘retail food environment’ (RFE) and how this may be linked with obesity. Currently, GIS modelled exposures to the RFE along routes to and from school are not adequate to make reliable predictions about exposure. Instead, GPS data are used to obtain accurate exposures. This thesis has developed a GIS method to generate population level exposures to the RFE. In order to advise policies and interventions that will effectively cause societal change, population level research must be undertaken. A novel way that this type of research can be undertaken is through data linkage. This study has calculated exposures to the RFE for school children aged 13-14 years in south Wales and linked these exposures to individual level health data held within the Secure Anonymised Information Linkage Databank (SAIL). These results contribute to the evidence base and shed light on new aspects of the built environment that can be altered to encourage healthy lifestyles