Profiling and understanding student information behaviour: Methodologies and meaning

This paper draws on work conducted under the Joint Information Systems Committee (JISC) User Behaviour Monitoring and Evaluation Framework to identify a range of issues associated with research design that can form a platform for enquiry about knowledge creation in the arena of user behaviour. The Framework has developed a multidimensional set of tools for profiling, monitoring and evaluating user behaviour. The Framework has two main approaches: one, a broad‐based survey which generates both a qualitative and a quantitative profile of user behaviour, and the other a longitudinal qualitative study of user behaviour that (in addition to providing in‐depth insights) is the basis for the development of the EIS (Electronic Information Services) Diagnostic Toolkit. The strengths and weaknesses of the Framework approach are evaluated. In the context of profiling user behaviour, key methodological concerns relate to: representativeness, sampling and access, the selection of appropriate measures and the interpretation of those measures. Qualitative approaches are used to generate detailed insights. These include detailed narratives, case study analysis and gap analysis. The messages from this qualitative analysis do not lend themselves to simple summarization. One approach that has been employed to capture and interpret these messages is the development of the EIS Diagnostic Toolkit. This toolkit can be used to assess and monitor an institution's progress with embedding EIS into learning processes. Finally, consideration must be given to integration of insights generated through different strands within the Framework

Methodology for profiling literature in healthcare simulation

The publications that relate to the application of simulation to healthcare have steadily increased over the years. These publications are scattered amongst various journals that belong to several subject categories, including Operational Research, Health Economics and Pharmacokinetics. The simulation techniques that are applied to the study of healthcare problems are also varied. The aim of this study is to present a methodology for profiling literature in healthcare simulation. In our methodology, we have considered papers on healthcare that have been published between 1970 and 2007 in journals with impact factors that belonging to various subject categories reporting on the application of four simulation techniques, namely, Monte Carlo Simulation, Discrete-Event Simulation, System Dynamics and Agent-Based Simulation. The methodology has the following objectives: (a) to categorise the papers under the different simulation techniques and identify the healthcare problems that each technique is employed to investigate; (b) to profile, within our dataset, variables such as authors, article citations, etc.; (c) to identify turning point (strategically important) papers and authors through co-citation analysis of references cited by the papers in our dataset. The focus of the paper is on the literature profiling methodology, and not the results that have been derived through the application of this methodology. The authors hope that the methodology presented here will be used to conduct similar work in not only healthcare but also other research domains

Collaborative recommendations with content-based filters for cultural activities via a scalable event distribution platform

Nowadays, most people have limited leisure time and the offer of (cultural) activities to spend this time is enormous. Consequently, picking the most appropriate events becomes increasingly difficult for end-users. This complexity of choice reinforces the necessity of filtering systems that assist users in finding and selecting relevant events. Whereas traditional filtering tools enable e.g. the use of keyword-based or filtered searches, innovative recommender systems draw on user ratings, preferences, and metadata describing the events. Existing collaborative recommendation techniques, developed for suggesting web-shop products or audio-visual content, have difficulties with sparse rating data and can not cope at all with event-specific restrictions like availability, time, and location. Moreover, aggregating, enriching, and distributing these events are additional requisites for an optimal communication channel. In this paper, we propose a highly-scalable event recommendation platform which considers event-specific characteristics. Personal suggestions are generated by an advanced collaborative filtering algorithm, which is more robust on sparse data by extending user profiles with presumable future consumptions. The events, which are described using an RDF/OWL representation of the EventsML-G2 standard, are categorized and enriched via smart indexing and open linked data sets. This metadata model enables additional content-based filters, which consider event-specific characteristics, on the recommendation list. The integration of these different functionalities is realized by a scalable and extendable bus architecture. Finally, focus group conversations were organized with external experts, cultural mediators, and potential end-users to evaluate the event distribution platform and investigate the possible added value of recommendations for cultural participation

ConCall: An information service for researchers based on EdInfo

In this paper, we present new types of web information services, where users and information brokers collaborate in creating a user-adaptive information service. Such services impose a novel task on information brokers: they become responsible for maintaining the inference strategies used in user modeling. In return, information brokers obtain more accurate information about user needs, since the adaptivity ensures that user profiles are kept up to date and consistent with what users actually prefer, not only what they say that they prefer. We illustrate the approach by an example application, in which conference calls are collected and distributed to interested readers

SPEIR: Scottish Portals for Education, Information and Research. Final Project Report: Elements and Future Development Requirements of a Common Information Environment for Scotland

The SPEIR (Scottish Portals for Education, Information and Research) project was funded by the Scottish Library and Information Council (SLIC). It ran from February 2003 to September 2004, slightly longer than the 18 months originally scheduled and was managed by the Centre for Digital Library Research (CDLR). With SLIC's agreement, community stakeholders were represented in the project by the Confederation of Scottish Mini-Cooperatives (CoSMiC), an organisation whose members include SLIC, the National Library of Scotland (NLS), the Scottish Further Education Unit (SFEU), the Scottish Confederation of University and Research Libraries (SCURL), regional cooperatives such as the Ayrshire Libraries Forum (ALF)1, and representatives from the Museums and Archives communities in Scotland. Aims; A Common Information Environment For Scotland The aims of the project were to: o Conduct basic research into the distributed information infrastructure requirements of the Scottish Cultural Portal pilot and the public library CAIRNS integration proposal; o Develop associated pilot facilities by enhancing existing facilities or developing new ones; o Ensure that both infrastructure proposals and pilot facilities were sufficiently generic to be utilised in support of other portals developed by the Scottish information community; o Ensure the interoperability of infrastructural elements beyond Scotland through adherence to established or developing national and international standards. Since the Scottish information landscape is taken by CoSMiC members to encompass relevant activities in Archives, Libraries, Museums, and related domains, the project was, in essence, concerned with identifying, researching, and developing the elements of an internationally interoperable common information environment for Scotland, and of determining the best path for future progress