Resource Discovery

1. Front Matter

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2. Immune-Inspired Method for Selecting the Optimal Solution in Web Service Composition

   • Cristina Bianca Pop, Viorica Rozina Chifu, Ioan Salomie, Mihaela Dinsoreanu

   Pages 1-17

3. Web Database Schema Identification through Simple Query Interface

   • Ling Lin, Lizhu Zhou

   Pages 18-34

4. Semantic Interoperability and Dynamic Resource Discovery in P2P Systems

   • Devis Bianchini, Valeria De Antonellis, Michele Melchiori

   Pages 35-48

5. Data Source Management and Selection for Dynamic Data Integration

   • Martin Husemann, Norbert Ritter

   Pages 49-65

6. A Provenance-Based Approach to Resource Discovery in Distributed Molecular Dynamics Workflows

   • Sérgio Manuel Serra da Cruz, Patricia M. Barros, Paulo M. Bisch, Maria Luiza M. Campos, Marta Mattoso

   Pages 66-80

7. On Building a Search Interface Discovery System

   • Denis Shestakov

   Pages 81-93

8. Building Specialized Multilingual Lexical Graphs Using Community Resources

   • Mohammad Daoud, Christian Boitet, Kyo Kageura, Asanobu Kitamoto, Mathieu Mangeot, Daoud Daoud

   Pages 94-109

9. An Efficient Semantic Web Services Matching Mechanism

   • Jing Li, Dianfu Ma, Zhuo Zhao, Hong Zhu, Lusong Li

   Pages 110-119

10. Efficiently Selecting the Best Web Services

    • Marlene Goncalves, Maria-Esther Vidal, Alfredo Regalado, Nadia Yacoubi Ayadi

    Pages 120-139

11. Back Matter

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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.

• Semantic Web
• Web Services
• data source management
• lexical graphs
• p2p
• query interface
• resource management

• Scientific Data Management Laboratory, Arizona State University, Tempe, USA

  Zoé Lacroix

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