Zoe Lacroix – författare

Life science data integration and interoperability is one of the most challenging problems facing bioinformatics today. In the current age of the life sciences, investigators have to interpret many types of information from a variety of sources: lab instruments, public databases, gene expression profiles, raw sequence traces, single nucleotide polymorphisms, chemical screening data, proteomic data, putative metabolic pathway models, and many others. Unfortunately, scientists are not currently able to easily identify and access this information because of the variety of semantics, interfaces, and data formats used by the underlying data sources. Bioinformatics: Managing Scientific Data tackles this challenge head-on by discussing the current approaches and variety of systems available to help bioinformaticians with this increasingly complex issue. The heart of the book lies in the collaboration efforts of eight distinct bioinformatics teams that describe their own unique approaches to data integration and interoperability. Each system receives its own chapter where the lead contributors provide precious insight into the specific problems being addressed by the system, why the particular architecture was chosen, and details on the system''s strengths and weaknesses. In closing, the editors provide important criteria for evaluating these systems that bioinformatics professionals will find valuable.* Provides a clear overview of the state-of-the-art in data integration and interoperability in genomics, highlighting a variety of systems and giving insight into the strengths and weaknesses of their different approaches. * Discusses shared vocabulary, design issues, complexity of use cases, and the difficulties of transferring existing data management approaches to bioinformatics systems, which serves to connect computer and life scientists. * Written by the primary contributors of eight reputable bioinformatics systems in academia and industry including: BioKris, TAMBIS, K2, GeneExpress, P/FDM, MBM, SDSC, SRS, and DiscoveryLink.

This book constitutes the thoroughly refereed joint post-proceedings of the VLDB 2002 Workshop on Efficiency and Effectiveness of XML Tools and Techniques, EEXTT and the CAiSE 2002 Workshop on Data Integration over the Web, DIWeb.The 10 revised full papers presented were carefully selected during two rounds of reviewing and revision. The papers are organized in topical sections on XML languages, XML modeling and integration, XML storage, benchmarking XML, and data integration over the Web.

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.

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.

This book constitutes the thoroughly refereed post-conference proceedings of the Third International Workshop on Resource Discovery, RED 2010, held in Paris, France, in November 2010.The 13 revised full papers - from 24 initial submissions - were carefully selected during a second round of reviewing and improvement from the lectures given at the workshop and are presented in extended version in the book. They deal with the following topics: resource discovery for composition; bioinformatics resource discovery; textual resource discovery; and Web service discovery.

This book constitutes the thoroughly refereed post-conference proceedings of the Third International Workshop on Resource Discovery, RED 2010, held in Paris, France, in November 2010.The 13 revised full papers - from 24 initial submissions - were carefully selected during a second round of reviewing and improvement from the lectures given at the workshop and are presented in extended version in the book. They deal with the following topics: resource discovery for composition; bioinformatics resource discovery; textual resource discovery; and Web service discovery.

This book constitutes the thoroughly refereed conference proceedings of the 5th International Workshop on Resource Discovery, RED 2010, co-located with the 9th Extended Semantic Web Conference, held in Heraklion, Greece, in May 2012.The 7 revised full papers presented were carefully reviewed and selected from 9 submissions. They deal with various issues related to resource discovery.