PPT-Update Exchange with Mappings and Provenance

Todd J Green Grigoris Karvounarakis Zachary G Ives Val Tannen University of Pennsylvania VLDB 2007 Vienna Austria September 26 2007 Adoption of data integration tools Structured information . Key components of the business plan. Customers. Who will use your product. Who will see value in it. Channel. How you plan to reach these customers / users. Key resources / skills. What do you need to make sure that you can keep servicing your customer. SHM. identifies matching by . incrementally shifting. . the read against the reference. . Mechanism:. Use bit-wise XOR to . find all matching bps. . Then use bit-wise AND to . merge them together. Susan B. . Davidson. University of Pennsylvania. Eleanor . Ainy. , Daniel . Deutch. , . Tova. Milo. Tel Aviv University. The engagement of crowds of Web users for data procurement and knowledge creation.. Mappings and Provenance. Todd J. Green. Grigoris Karvounarakis Zachary G. Ives Val Tannen. University of Pennsylvania. VLDB 2007 Vienna, Austria. September 26, 2007. Adoption of data integration tools. Ontologies. A specification of a conceptualization (Gruber, 1993). Design: . Subjective . Depends on the purpose they serve, the aspect(s) they cover . Ontologies Mismatches. Different Types:. Conceptualization . Middleware for Database Queries. , Updates, and . Transactions. Bahareh. Sadat . Arab. 1. , . Dieter . Gawlick. 2. , . Venkatesh. . Radhakrishnan. 2. , . Hao. . Guo. 1. , . Boris . Glavic. 1. . IIT DBGroup. . Session 6: Interoperability. Session 6: Aims. In this session, you will learn about:. Steps towards interoperability. Interoperability challenges. Next steps towards . achieving . interoperability. Materialized Instances After Changes to Mappings and Data. Todd J. Green. Zachary G. Ives. ICDE ’12 Washington, DC April 2, 2012. &. Change is a Constant in Data Management. Databases are highly . University of California, Davis. Efficiently Supporting Changes to Declarative Schema Mappings. January 28, 2011. @Stanford InfoSeminar. Change is a Constant in Data Management. Databases are highly . Bibi . Raju, Todd Elsethagen, Eric . Stephan. 1. Pacific Northwest National Laboratory, Richland, WA. Provenance Goals. Provenance Overarching . Goals. Provide thorough results explanation. Reuse, repeat, or reproduce workflows. Todd J. Green. University of Pennsylvania. Spring 2009 . The Case for a Collaborative . Data Sharing System (CDSS). Scientists build data repositories, need to share with collaborators. Goal: import, transform, modify (curate) each other’s data. 5/21/2018. 1. UW. Val Tannen. University of Pennsylvania. . 5/21/2018. 2. UW. . Collaborators. . ORCHESTRA. . . Life Sciences . Linked Open Data Cloud. Ali . Hasnain et. al. Insight . Center for Data . Analytics. . National University of Ireland, . Galway. Agenda. Motivation. Linked Life Sciences Roadmap. Cataloguing and Linking. Raju, Todd Elsethagen, Eric . Stephan. 1. Pacific Northwest National Laboratory, Richland, WA. Provenance Goals. Provenance Overarching . Goals. Provide thorough results explanation. Reuse, repeat, or reproduce workflows.