A business perspective of legacy systems

Abstract Legacy information systems evolved incrementally in response to changes in business strategy and information technology. Organizations are now being forced to change much more radically and quickly than previously and this change places new demands on information systems. Legacy information systems are usually considered from a technical perspective, addressing issues such as age, complexity, maintainability, design and technology. We wish to demonstrate that the business dimension to legacy information systems, represented by the organisation structure, business processes and procedures that are bound up in the design and operation of the existing IT systems, is also significant. This paper identifies the important role of legacy information systems in the formation of new strategies. We show that the move away from a stable to an unstable business environment accelerates the rate of change. Furthermore, the gap between what the legacy information systems can deliver and the strategic vision of the organization widens when the legacy information systems are unable to adapt to meet the new requirements. An analysis of fifteen case studies provides evidence that legacy information systems include business and technical dimensions and that the systems can present problems when there is a misalignment between the strategic vision of the business, the IT legacy and the old business model embodied in the legacy.

The choice of spatial scales and spatial smoothness priors for various spatial patterns

Given the drawbacks for using geo-political areas in mapping outcomes unrelated to geo-politics, a compromise is to aggregate and analyse data at the grid level. This has the advantage of allowing spatial smoothing and modelling at a biologically or physically relevant scale. This article addresses two consequent issues: the choice of the spatial smoothness prior and the scale of the grid. Firstly, we describe several spatial smoothness priors applicable for grid data and discuss the contexts in which these priors can be employed based on different aims. Two such aims are considered, i.e., to identify regions with clustering and to model spatial dependence in the data. Secondly, the choice of the grid size is shown to depend largely on the spatial patterns. We present a guide on the selection of spatial scales and smoothness priors for various point patterns based on the two aims for spatial smoothing.

Practical visual odometry for car-like vehicles

A method for calculating visual odometry for ground vehicles with car-like kinematic motion constraints similar to Ackerman's steering model is presented. By taking advantage of this non-holonomic driving constraint we show a simple and practical solution to the odometry calculation by clever placement of a single camera. The method has been implemented successfully on a large industrial forklift and a Toyota Prado SUV. Results from our industrial test site is presented demonstrating the applicability of this method as a replacement for wheel encoder-based odometry for these vehicles.