A Semantic Model for the Authorisation of Context-Aware Content Adaptation
published: Dec. 18, 2008, recorded: December 2008, views: 183
Report a problem or upload filesIf you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Nowadays, users want to be able to access their computing resources and all kind of content using different types of devices, from wireless portable devices to stationary devices connected to local area networks in a way that context-based content adaptation has become essential for Universal Multimedia Access (UMA) scenarios. This content adaptation represents the modification of an object possibly subjected to the Intellectual Property (IP) law, and the original author or rights holder should be able to retain the possibility of vetoing or restricting the operation. Whereas MPEG-21 addresses the adaptation in the part 7 of the standard (DIA, Digital Item Adaptation), and the Rights Expressions Language (REL) in the part 5, it still lacks of an integrated approach of them. This paper considers the authorisation of context-aware content adaptation in a generic multimedia scenario based on the integration of two new standard-based ontologies providing a bridge between them at a semantic level. First, it is presented the Context Aware Ontology (CAO), which models the Universal Environment Descriptor (UED) tool contained in the MPEG-21 DIA standard. Then, it is introduced the Adaptation Authoriser based on the RRDOnto (Represent Rights Data) ontology, which grants that IP rights will be respected along the Value Chain while supporting the MPEG-21 License model. Finally, the integration of both is described, providing a joint model that allows the adaptation to be controlled by Content Creators and Content Distributors.
Download slides: samt08_rodriguez_doncel_smac_01.pdf (191.4 KB)
Download slides: samt08_rodriguez_doncel_smac_01.ppt (518.5 KB)
Link this pageWould you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !