Exchanging uncertainty: interoperable geostatistics?

Traditionally, geostatistical algorithms are contained within specialist GIS and spatial statistics software. Such packages are often expensive, with relatively complex user interfaces and steep learning curves, and cannot be easily integrated into more complex process chains. In contrast, Service Oriented Architectures (SOAs) promote interoperability and loose coupling within distributed systems, typically using XML (eXtensible Markup Language) and Web services. Web services provide a mechanism for a user to discover and consume a particular process, often as part of a larger process chain, with minimal knowledge of how it works. Wrapping current geostatistical algorithms with a Web service layer would thus increase their accessibility, but raises several complex issues. This paper discusses a solution to providing interoperable, automatic geostatistical processing through the use of Web services, developed in the INTAMAP project (INTeroperability and Automated MAPping). The project builds upon Open Geospatial Consortium standards for describing observations, typically used within sensor webs, and employs Geography Markup Language (GML) to describe the spatial aspect of the problem domain. Thus the interpolation service is extremely flexible, being able to support a range of observation types, and can cope with issues such as change of support and differing error characteristics of sensors (by utilising descriptions of the observation process provided by SensorML). XML is accepted as the de facto standard for describing Web services, due to its expressive capabilities which allow automatic discovery and consumption by ‘naive’ users. Any XML schema employed must therefore be capable of describing every aspect of a service and its processes. However, no schema currently exists that can define the complex uncertainties and modelling choices that are often present within geostatistical analysis. We show a solution to this problem, developing a family of XML schemata to enable the description of a full range of uncertainty types. These types will range from simple statistics, such as the kriging mean and variances, through to a range of probability distributions and non-parametric models, such as realisations from a conditional simulation. By employing these schemata within a Web Processing Service (WPS) we show a prototype moving towards a truly interoperable geostatistical software architecture.

An institutional perspective on management accounting change in the public sector : a case study from Canada

This thesis reports on a four-year field study conducted at the Saskatchewan regional office of the Department of Indian Affairs and Northern Development, a large department of the Government of Canada. Over the course of the study, a sweeping government-wide accounting reform took place entitled the Financial Information Strategy. An ethnographic study was conducted that documented the management accounting processes in place at the regional office prior to the Financial Information Strategy reform, the organization’s adoption of the new accounting system associated with this initiative, and the state of the organization’s management accounting system once the implementation was complete. This research, therefore, captures in detail a management accounting change process in a public sector organization. This study employs an interpretive perspective and draws on institution theory as a theoretical framework. The concept of loose coupling and insights from the literature on professions were also employed in the explanation-building process for the case. This research contributes to institution theory and the study of management accounting change by recognizing conflicting institutional forces at the organizational level. An existing Old Institutional Economics-based conceptual framework for management accounting change is advanced and improved upon through the development of a new conceptual framework that incorporates the influence of wider institutional forces, the concepts of open and closed organizational systems and loose coupling, and the recognition of varying rates of change and institutionalization of organizational activity sets. Our understanding of loose coupling is enhanced by the interpretation of institutional influences developed in this study as is the role of professionalization as a normative influence in public sector organizations.