PPT-Lecture 11: Provenance and Data privacy

December 8 2010 Dan Suciu CSEP544 Fall 2010 Outline Database provenance Slides based on Val Tannens Keynote talk at EDBT 2010 Data privacy Slides from my UW colloquium talk in 2005 Dan Suciu CSEP544 Fall 2010. 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. a . experiment was . run. . The . provenance of an experiment is its lineage or historical trace . [7] . that can capture experiment conditions, time ordering, and relationships within the experiment and across the experiment and infrastructure layer.. Ontologies. . to Query Meteorological Data . . Thiago Marcos da Silva Barbosa. ,. Ednaldo. O. . Santos. , Gustavo . B. . Lyra,. Sérgio . Manuel Serra da . Cruz. LabData. Federal Rural . University. . Lipstick. . on. . Pig:. Enabling. . Database-styleWorkflow. Provenance. YaelAmsterdamer,Susan. . B.Davidson,Daniel. . Deutch. Tova. . Milo,Julia. . Stoyanovich,ValTannen. Using slides by . Guozhang. 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. Why – How . – . Where. What’s up with this presentation?. Cannibalized from:. Val . Tannen’s. EDBT and AMW 2010 tutorials. Peter . Buneman. and Wang-. Chiew. Tan’s SIGMOD 2007 tutorial. Julie and . . 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 . 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. Research and data at the . Freer|Sackler. Jeffrey Smith. Assistant Registrar for Collections Information. Freer|Sackler. smithje@si.edu. | 202-633-0348. 21. st. –Century Digital Provenance. Carnegie Museum of Art Pittsburgh, Pennsylvania. 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. Data Provenance Task Force. Lisa Gallagher, C. hair. January 6, 2015. Agenda. Opening Remarks: Steve Posnack, Director, Office of Standards and Technology. Use of FACA Task Forces. Comments from 11/18/14 HITSC Meeting. HITPC Consumer Empowerment Workgroup Meeting. July 28, 2013.  . . . . . . Joy Pritts, JD. Data Provenance. What is “Provenance”? . Origin of clinical information when first created. Information about the source of the data. John M. Abowd. Cornell University . January 17, 2013. Acknowledgements and Disclaimer. This research uses data from the Census Bureau’s Longitudinal Employer-Household Dynamics (LEHD) Program, which was partially supported by the following grants: National Science Foundation (NSF) SES-9978093, SES-0339191 and ITR-0427889; National Institute on Aging AG018854; and grants from the Alfred P. Sloan .