Resource Discovery Second International Workshop, RED 2009, Lyon, France, August 28, 2009, Revised Papers

Resource discovery is the process of identifying and locating existing resources thathavea particularproperty. Aresourcecorrespondsto aninformationsource such as a data repositoryor databasemanagement system (e. g. , a query form or a textual search engine), a link between resources (an index or hyperlink), or a servicesuchasanapplicationoratool. Resourcesarecharacterizedbycoreinf- mation including a name, a description of its input and its output (parameters or format), its address, and various additional properties expressed as me- data. 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 - cate resources that implement speci?c tasks. Machine-based resource discovery relies on crawling, clustering, and classifying resources discovered on the Web automatically. The First Workshop on Resource Discovery (RED) took place on November 25, 2008 in Linz, Austria. It was organized jointly with the 10th International Conference on Information Integration and Web-Based Applications and S- vices and its proceedings were published by ACM. The second edition of the workshop was co-located with the 35th International Conference on Very Large Data Bases (VLDB) in the beautiful city of Lyon, France. Nine papers were selected for presentation at this second edition. Areas of researchaddressedby these papers include the problem of resource characterization and classi?cation, resourcecomposition,andontology-drivendiscovery.