Bibliographic Analysis on Research Publications using Authors, Categorical Labels and the Citation Network

Bibliographic analysis considers the author's research areas, the citation network and the paper content among other things. In this paper, we combine these three in a topic model that produces a bibliographic model of authors, topics and documents, using a nonparametric extension of a combination of the Poisson mixed-topic link model and the author-topic model. This gives rise to the Citation Network Topic Model (CNTM). We propose a novel and efficient inference algorithm for the CNTM to explore subsets of research publications from CiteSeerX. The publication datasets are organised into three corpora, totalling to about 168k publications with about 62k authors. The queried datasets are made available online. In three publicly available corpora in addition to the queried datasets, our proposed model demonstrates an improved performance in both model fitting and document clustering, compared to several baselines. Moreover, our model allows extraction of additional useful knowledge from the corpora, such as the visualisation of the author-topics network. Additionally, we propose a simple method to incorporate supervision into topic modelling to achieve further improvement on the clustering task.Comment: Preprint for Journal Machine Learnin

Panning for gold: designing pedagogically-inspired learning nuggets

Tools to support teachers and learning technologists in the creation of effective learning designs are currently in their infancy. This paper describes a metadata model, devised to assist in the conception and design of new learning activities, that has been developed, used and evaluated over a period of three years. The online tool that embodies this model was not originally intended to produce runtime executable code such as IMS-LD, but rather focussed on assisting teachers in the thought processes involved in selecting appropriate methods, tools, student activities and assessments to suit the required learning objectives. Subsequently, we have modified the RELOAD editor such that the output from our tool can be translated into IMS-LD. The contribution of this paper is the comparison of our data model with that of IMS-LD, and the analysis of how each can inform the other

Lirolem: A virtual studio/Institutional Repository for the University of Lincoln

Gives an account of the Lirolem project at the University of Lincoln which was to build a repository capable of handling multimedia material as well as providing a repository for the University's research output

Skills and Knowledge for Data-Intensive Environmental Research.

The scale and magnitude of complex and pressing environmental issues lend urgency to the need for integrative and reproducible analysis and synthesis, facilitated by data-intensive research approaches. However, the recent pace of technological change has been such that appropriate skills to accomplish data-intensive research are lacking among environmental scientists, who more than ever need greater access to training and mentorship in computational skills. Here, we provide a roadmap for raising data competencies of current and next-generation environmental researchers by describing the concepts and skills needed for effectively engaging with the heterogeneous, distributed, and rapidly growing volumes of available data. We articulate five key skills: (1) data management and processing, (2) analysis, (3) software skills for science, (4) visualization, and (5) communication methods for collaboration and dissemination. We provide an overview of the current suite of training initiatives available to environmental scientists and models for closing the skill-transfer gap

Creating virtual communities of practice for learning technology in higher education: Issues, challenges and experiences

The need for a Web portal to support the rapidly growing field of learning technology has been well established through a number of national surveys and scoping studies over recent years. The overarching vision has been the provision of a virtual environment to assist in informing and developing professional practice in the use of learning technologies. This paper outlines the issues and challenges in creating such a portal through the experiences of developing the RESULTs Network. In the paper, design and participation issues are considered within the wider context of online and networked approaches to supporting practice and professional development. User participation methodologies and technical developments for RESULTs are described in relation to a review of existing representations of practice and a comprehensive survey amongst the learning technology users’ community. An outline of key achievements and experiences is presented, followed by some conclusions regarding the cultural and political issues in creating a viable and sustainable facility and suggestions for possible future direction in national provision

Supporting sustainable e‐learning

This paper draws upon work carried out within phase one of a national forum for support staff, funded by the UK Learning and Teaching Support Network Generic Centre. It sets out themes in current Learning Technology research within the context of institutional practice. It reports the responses of a range of e‐learning support staff to new developments in the reuse and sharing of Learning Objects. The article highlights tensions across support units, inconsistencies in support provision and confusion over issues concerning different modes of teaching. It also forewarns a growing gap between institutional practice and research in the development of approaches to sustainable e‐learning

Keeping Research Data Safe 2: Final Report

The first Keeping Research Data Safe study funded by JISC made a major contribution to understanding of long-term preservation costs for research data by developing a cost model and indentifying cost variables for preserving research data in UK universities (Beagrie et al, 2008). However it was completed over a very constrained timescale of four months with little opportunity to follow up other major issues or sources of preservation cost information it identified. It noted that digital preservation costs are notoriously difficult to address in part because of the absence of good case studies and longitudinal information for digital preservation costs or cost variables. In January 2009 JISC issued an ITT for a study on the identification of long-lived digital datasets for the purposes of cost analysis. The aim of this work was to provide a larger body of material and evidence against which existing and future data preservation cost modelling exercises could be tested and validated. The proposal for the KRDS2 study was submitted in response by a consortium consisting of 4 partners involved in the original Keeping Research Data Safe study (Universities of Cambridge and Southampton, Charles Beagrie Ltd, and OCLC Research) and 4 new partners with significant data collections and interests in preservation costs (Archaeology Data Service, University of London Computer Centre, University of Oxford, and the UK Data Archive). A range of supplementary materials in support of this main report have been made available on the KRDS2 project website at http://www.beagrie.com/jisc.php. That website will be maintained and continuously updated with future work as a resource for KRDS users