A resource corresponds to an information source such as a data repository or database management system (e.g., a query form or a textual search engine), a link between resources (an index or hyperlink), or a service such as an application or tool. Resources are characterized by core information including a name, a description of its input and its output (parameters or format), its address, and various additional properties expressed as metadata.

Resource discovery is the process of identifying and locating existing resources that have a particular property. Machine-based resource discovery relies on crawling, clustering, and classifying resources discovered on the Web automatically. Resources are organized with respect to metadata that characterize their content (for data sources), their semantics (in terms of ontological classes and relationships), their characteristics (syntactical properties), their performance (with metrics and benchmarks), their quality (curation, reliability, trust), etc. Resource discovery systems allow the expression of queries to identify and locate resources that implement specific tasks.

The Third International Workshop on Resource Discovery aims at bringing together researchers, developers, and practitioners to discuss research issues and experience in developing and deploying concepts, applications, and solutions addressing various issues related to resource discovery. Papers presenting either theoretical or applicative material are expected. Because of the dynamic research and development effort towards supporting resource discovery for the life sciences, we expect to receive many contributions in the scope of this very exciting application domain. However, we encourage the submission of generic solutions or the presentation of application experiences other than related to life sciences.

Workshop key dates

Abstract submission deadline: June 1st, 2010
Submission deadline: June 15th, 2010
Acceptance notification: July 15th, 2010
Camera ready: July 31st, 2010

Maximum number of pages: 15 pages (long papers) and 8 pages (short papers) in LNCS format

RED papers will be published in a volume of Lecture Notes in Computer Science by Springer.