Self-optimising data farming for web applications

Many Web applications walk the thin line between the need for dynamic data and the need to meet user performance expectations. In environments where funds are not available to constantly upgrade hardware inline with user demand, alternative approaches need to be considered. This paper introduces a ‘Data farming’ model whereby dynamic data, which is ‘grown’ in operational applications, is ‘harvested’ and ‘packaged’ for various consumer markets. Like any well managed agricultural operation, crops are harvested according to historical and perceived demand as inferred by a self-optimising process. This approach aims to make enhanced use of available resources through better utlilisation of system downtime - thereby improving application performance and increasing the availability of key business data.

Towards the design of a portal framework for web services integration

Web services based systems have recently found their way into many applications such as e-commerce, corporate integration and e-learning. Construction of new services or introducing new functions to existing services requires composition of web services. Current approaches to service composition often require major programming effort; this is time consuming and requires considerable developer expertise. In this paper, we explore the real and rich scenarios found in e-learning where education services are offered through the Internet by networked universities to potentially millions in the world. These services are derived from existing/emerging business operation processes and commonly offered through a web interface, combined with other services such as email and ftp services, to support partial/full business processes. We identify the requirements for a generic portal framework for easy integration of existing expertise and services of individual institutions (enterprises). We examine the existing technologies and standards, and point out the gaps to be filled in designing the architecture of the framework

Semantic web and e-learning

With emergence of "Semantic Web" there has been much discussion about the impact of technologies such as XML and RDF on the way we use the Web for developing e-learning applications and perhaps more importantly on how we can personalise these applications. Personalisation of e-learning is viewed by many authors (see amongst others Eklund & Brusilovsky, 1998; Kurzel, Slay, & Hagenus, 2003; Martinez, 2000; Sampson, Karagiannidis, & Kinshuk, 2002; Voigt & Swatman, 2003) as the key challenge for the learning technologists. According to Kurzel (2004) the tailoring of e-learning applications can have an impact on content and how it's accesses; the media forms used; method of instruction employed and the learning styles supported. This paper will report on a research project currently underway at the eCentre in University of Greenwich which is exploring different approaches and methodologies to create an e-learning platform with personalisation built-in. This personalisation is proposed to be set from different levels of within the system starting from being guided by the information that the user inputs into the system down to the lower level of being set using information inferred by the system's processing engine.