Improving the usability of standard schemas

Due to the development of XML and other data models such as OWL and RDF, sharing data is an increasingly common task since these data models allow simple syntactic translation of data between applications. However, in order for data to be shared semantically, there must be a way to ensure that concepts are the same. One approach is to employ commonly usedschemas—called standard schemas —which help guarantee that syntactically identical objects have semantically similar meanings. As a result of the spread of data sharing, there has been widespread adoption of standard schemas in a broad range of disciplines and for a wide variety of applications within a very short period of time. However, standard schemas are still in their infancy and have not yet matured or been thoroughly evaluated. It is imperative that the data management research community takes a closer look at how well these standard schemas have fared in real-world applications to identify not only their advantages, but also the operational challenges that real users face. In this paper, we both examine the usability of standard schemas in a comparison that spans multiple disciplines, and describe our first step at resolving some of these issues in our Semantic Modeling System. We evaluate our Semantic Modeling System through a careful case study of the use of standard schemas in architecture, engineering, and construction, which we conducted with domain experts. We discuss how our Semantic Modeling System can help the broader problem and also discuss a number of challenges that still remain.

A web application to perform linkage disequilibrium and linkage analyses on a computational grid

Motivation: Unravelling the genetic architecture of complex traits requires large amounts of data, sophisticated models and large computational resources. The lack of user-friendly software incorporating all these requisites is delaying progress in the analysis of complex traits. Methods: Linkage disequilibrium and linkage analysis (LDLA) is a high-resolution gene mapping approach based on sophisticated mixed linear models, applicable to any population structure. LDLA can use population history information in addition to pedigree and molecular markers to decompose traits into genetic components. Analyses are distributed in parallel over a large public grid of computers in the UK. Results: We have proven the performance of LDLA with analyses of simulated data. There are real gains in statistical power to detect quantitative trait loci when using historical information compared with traditional linkage analysis. Moreover, the use of a grid of computers significantly increases computational speed, hence allowing analyses that would have been prohibitive on a single computer. © The Author 2009. Published by Oxford University Press. All rights reserved.

Social media and Web 2.0 : teacher-librarians, risk and inequity

This paper reports research into teacher-­‐librarians’ perceptions of using social media and Web 2.0 in teaching and learning. A pilot study was conducted with teacher-­‐librarians in five government schools and five private schools in southeast Queensland. The findings revealed that there was a strong digital divide between government schools and private schools, with government schools suffering severe restrictions on the use of social media and Web 2.0, leading to an unsophisticated use of these technologies. It is argued that internet ‘over-­‐ blocking’ may lead to government school students not being empowered to manage risks in an open internet environment. Furthermore, their use of information for academic and recreational learning may be compromised. This has implications particularly for low socioeconomic students, leading to further inequity in the process and outcomes of Australian education.

Collaborating to develop research data management services and collections

The Queensland University of Technology (QUT) Library, like many other academic and research institution libraries in Australia, has been collaborating with a range of academic and service provider partners to develop a range of research data management services and collections. Three main strategies are being employed and an overview of process, infrastructure, usage and benefits is provided of each of these service aspects. The development of processes and infrastructure to facilitate the strategic identification and management of QUT developed datasets has been a major focus. A number of Australian National Data Service (ANDS) sponsored projects - including Seeding the Commons; Metadata Hub / Store; Data Capture and Gold Standard Record Exemplars have / will provide QUT with a data registry system, linkages to storage, processes for identifying and describing datasets, and a degree of academic awareness. QUT supports open access and has established a culture for making its research outputs available via the QUT ePrints institutional repository. Incorporating open access research datasets into the library collections is an equally important aspect of facilitating the adoption of data-centric eresearch methods. Some datasets are available commercially, and the library has collaborated with QUT researchers, in the QUT Business School especially strongly, to identify and procure a rapidly growing range of financial datasets to support research. The library undertakes licensing and uses the Library Resource Allocation to pay for the subscriptions. It is a new area of collection development for with much to be learned. The final strategy discussed is the library acting as “data broker”. QUT Library has been working with researchers to identify these datasets and undertake the licensing, payment and access as a centrally supported service on behalf of researchers.

Personalised information gathering and recommender systems : techniques and trends

With the explosive growth of resources available through the Internet, information mismatching and overload have become a severe concern to users. Web users are commonly overwhelmed by huge volume of information and are faced with the challenge of finding the most relevant and reliable information in a timely manner. Personalised information gathering and recommender systems represent state-of-the-art tools for efficient selection of the most relevant and reliable information resources, and the interest in such systems has increased dramatically over the last few years. However, web personalization has not yet been well-exploited; difficulties arise while selecting resources through recommender systems from a technological and social perspective. Aiming to promote high quality research in order to overcome these challenges, this paper provides a comprehensive survey on the recent work and achievements in the areas of personalised web information gathering and recommender systems. The report covers concept-based techniques exploited in personalised information gathering and recommender systems.

Using Wikipedia to improve web service discovery

Building and maintaining software are not easy tasks. However, thanks to advances in web technologies, a new paradigm is emerging in software development. The Service Oriented Architecture (SOA) is a relatively new approach that helps bridge the gap between business and IT and also helps systems remain exible. However, there are still several challenges with SOA. As the number of available services grows, developers are faced with the problem of discovering the services they need. Public service repositories such as Programmable Web provide only limited search capabilities. Several mechanisms have been proposed to improve web service discovery by using semantics. However, most of these require manually tagging the services with concepts in an ontology. Adding semantic annotations is a non-trivial process that requires a certain skill-set from the annotator and also the availability of domain ontologies that include the concepts related to the topics of the service. These issues have prevented these mechanisms becoming widespread. This thesis focuses on two main problems. First, to avoid the overhead of manually adding semantics to web services, several automatic methods to include semantics in the discovery process are explored. Although experimentation with some of these strategies has been conducted in the past, the results reported in the literature are mixed. Second, Wikipedia is explored as a general-purpose ontology. The benefit of using it as an ontology is assessed by comparing these semantics-based methods to classic term-based information retrieval approaches. The contribution of this research is significant because, to the best of our knowledge, a comprehensive analysis of the impact of using Wikipedia as a source of semantics in web service discovery does not exist. The main output of this research is a web service discovery engine that implements these methods and a comprehensive analysis of the benefits and trade-offs of these semantics-based discovery approaches.

Internet usage trends in medical informatics

Technological growth in the 21st century is exponential. Simultaneously, development of the associated risk, uncertainty and user acceptance are scattered. This required appropriate study to establish people accepting controversial technology (PACT). The Internet and services around it, such as World Wide Web, e-mail, instant messaging and social networking are increasingly becoming important in many aspects of our lives. Information related to medical and personal health sharing using the Internet is controversial and demand validity, usability and acceptance. Whilst literature suggest, Internet enhances patients and physicians’ positive interactions some studies establish opposite of such interaction in particular the associated risk. In recent years Internet has attracted considerable attention as a means to improve health and health care delivery. However, it is not clear how widespread the use of Internet for health care really is or what impact it has on health care utilisation. Estimated impact of Internet usage varies widely from the locations locally and globally. As a result, an estimate (or predication) of Internet use and their effects in Medical Informatics related decision-making is impractical. This open up research issues on validating and accepting Internet usage when designing and developing appropriate policy and processes activities for Medical Informatics, Health Informatics and/or e-Health related protocols. Access and/or availability of data on Internet usage for Medical Informatics related activities are unfeasible. This paper presents a trend analysis of the growth of Internet usage in medical informatics related activities. In order to perform the analysis, data was extracted from ERA (Excellence Research in Australia) ranked “A” and “A*” Journal publications and reports from the authenticated public domain. The study is limited to the analyses of Internet usage trends in United States, Italy, France and Japan. Projected trends and their influence to the field of medical informatics is reviewed and discussed. The study clearly indicates a trend of patients becoming active consumers of health information rather than passive recipients.