Grid-Enabled Data Collection and Analysis - Semantic Annotation in Skills-Based Learning
This project will demonstrate how Semantic Grid technologies can be used to provide enhanced techniques for data collection and use within a grid-enabled environment, thus enhancing the capacity to address substantive social science research. It will achieve this by conducting a case study in which semantic annotation (i.e. machine-processable annotation using Semantic Web technologies) is used both in capturing and working with the digital record, in support of subsequent qualitative and quantitative analysis. As a demonstrator this will extend and inform existing NCeSS activities in video annotation and new forms of digital record being developed at the MixedMediaGrid and Digtal Record nodes, as well as producing a training output in the application of grid technologies for the wider social science community. This case study will set the agenda for future work in this area.
The case study focuses on the research and practice of skills-based learning in the context of health care education. The project utilises a significant facility in the School of Nursing and Midwifery in Southampton that provides a powerful testbed for the study, with very extensive data collection and replay capabilities. This enables new forms of data capture and analysis involving multiple simultaneous video and audio sources and video focus groups. Of particular relevance to the Digital Record and MixedMediaGrid nodes is the rich form of record including audiovisual data but also data streams from pervasive devices (e.g. the instrumented simulated patients), control event streams, scenario storyboards and multiple layers of annotation. The case study provides a social science research context in which to investigate the new techniques.
Type: Normal Research Project
Research Groups: Intelligence, Agents, Multimedia Group, Learning Societies Lab
Themes: Semantic Web, Pervasive Computing and Networks, Educational Enhancement, Human Computer Interaction, Web Science
Dates: 1st November 2006 to 31st October 2007
- Professor David C De Roure
- Mary Gobbi
- J. W. McDonald
- Dr Mark J Weal
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