A Synchronous Multimedia Annotation System for Secure Collaboratories
E-SCIENCE '06 Proceedings of the Second IEEE International Conference on e-Science and Grid Computing
Realizing the Hydrogen Economy through Semantic Web Technologies
IEEE Intelligent Systems
Enhancing the semantic interoperability of multimedia through a core ontology
IEEE Transactions on Circuits and Systems for Video Technology
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Advances in scientific research techniques have led to an explosion of information-rich, multimedia data within the research sector. New high-throughput data capture and combinatorial experimentation techniques (involving advanced instruments capable of capturing extremely high resolution data streams) have resulted in the generation of research data in quantities that are too great for effective assimilation. The data is not only massive in volume but is also being produced in a broad range of mediums and formats, including: numerical data, spectrographic output, genomic arrays, images, 3D models, audio and video, for disciplines including nano-materials, bioinformatics, tele-medicine, geosciences, astronomy and the social sciences. Scientific discovery is increasingly dependent on reliable tools and services to support the storage, dissemination, analysis and correlation of these complex data sets by collaborating teams of globally distributed scientists. The volume, variety and multi-dimensional nature of the content exacerbates the difficulty of describing this data adequately so it can be confidently and appropriately incorporated into existing theories or models. In order to validate and authenticate scientific results, detailed provenance metadata describing the precise methodology and derived datasets needs to be recorded. Because today's scientists are working in large geographically distributed teams or "virtual organisations", the data and metadata has to be comprehensible to people, computers and software across many different organizations, platforms and disciplines. Metadata standards and semantic interoperability are essential to enable distributed querying, analysis, integration of mixed-media, heterogeneous scientific datasets in order to maximize its re-use, extract the inherent knowledge and build new knowledge layers on top of existing data The Semantic Web promotes interoperability through formal languages and rich semantics. It aims to build a web where information is exchanged easily between humans and machines. Through a combination of URIs, RDF, OWL ontologies, SWRL inferencing rules and SPARQL query language, the Semantic Web aims to define and expose the semantics associated with data or information, in order to facilitate automatic processing, integration, sharing and reuse of the data. The hypothesis we are trying to prove is that the application of semantic web technologies to the semantic annotation, integration and correlation of distributed mixed-media scientific datasets and data processing services, offers enormous potential for expediting the discovery of new knowledge. Semantic web/grid tools enhance interoperability through formal syntaxes, ontologies and inferencing rules. They enable innovative search data exploration, hypothesis development and evaluation interfaces and can assist researchers in managing, assimilating and distributing data to facilitate further scientific understanding and discovery. In this paper we present three e-Research applications that support this hypothesis -- they demonstrate three disciplines in which scientific problems may be solved more quickly through: richer, machine-processable descriptions, enhanced semantic interoperability and faster data integration: • Fuel Cell Optimization (Hunter 2004) • Semantic WildNet (Pullar 2007) • Ethnographic Media Analysis (Schroeter 2006) In particular our approach is to facilitate semantic interoperability across media types, vocabularies and disciplines through a common extensible ontology (Hunter 2003). The significant advantage of this approach is that it can easily be extended and adapted across disciplines through the incremental incorporation of domain-specific ontologies and rules.