Semantic Annotation and Search for Educational Resources Supporting Distance Learning
Multimedia educational resources play an important role in education, particularly for distance learning environments. With the rapid growth of the multimedia web, large numbers of education articles video resources are increasingly being created by several different organizations. It is crucial to explore, share, reuse, and link these educational resources for better e-learning experiences. Most of the video resources are currently annotated in an isolated way, which means that they lack semantic connections. Thus, providing the facilities for annotating these video resources is highly demanded. These facilities create the semantic connections among video resources and allow their metadata to be understood globally. Adopting Linked Data technology, this paper introduces a video annotation and browser platform with two online tools: Notitia and Sansu-Wolke. Notitia enables users to semantically annotate video resources using vocabularies defined in the Linked Data cloud. Sansu-Wolke allows users to browse semantically linked educational video resources with enhanced web information from different online resources. In the prototype development, the platform uses existing video resources for education articles. The result of the initial development demonstrates the benefits of applying Linked Data technology in the aspects of reusability, scalability, and extensibility. In the modern world e-learning activities are essential for distance learning in higher education. Digital video as one type of multimedia resource plays a vital role in distance learning. With the increased number of video resources being created , it is important to accurately describe the video content and enable searching of potential videos to enhance the quality and features of e-learning. It is critical to efficiently search for all related distributed educational video resources together to enhance the e-learning activities of the students. This paper adopts Semantic Web technology, more precisely; the Linked Data approach identified some primary challenges. Video resources should be described precisely, Descriptions of video resources should be accurate and machine-readable to support related search, Link the video resources to useful knowledgeable data from the web. Video annotation ontology is designed by following Linked Data principles and reusing existing ontologies. It provides the foundation for annotating videos based on both time instance and duration in the video streams and more precise description details to be added to the video. A semantic video annotation tool (Notitia) is implemented for annotating and publishing education articles video resources based on the video annotation ontology. Notitia allows annotators to use domain specific vocabularies from the Linked Open Data cloud to describe the video resources. These annotations link the video resources to other web resources. A semantic-based video searching browser (Sansu-Wolke) is provided for searching videos. It generates links to further videos and education articles video resources from the Linked Open Data cloud and the web.