PPT-Open Provenance Model Tutorial

Session 3 OPM Serializations Luc Moreau LMoreauecssotonacuk University of Southampton Session 3 Aims In this session you will learn about The XML Schema for OPM The OWL ontology for OPM. 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. 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.. Murali. Mani, . Mohamad. . Alawa. , . Arunlal. . Kalyanasundaram. University of Michigan, Flint. Presented at IDEAS 2011.. Provenance Metadata. Data about origins of data. Applications:. Check whether data item is valid – in health records. impurity problems (QIP. ) and numerical renormalization group (NRG): quick introduction. Rok . Žitko. Institute . Jožef. Stefan. Ljubljana, Slovenia. June . 2013. , . SISSA, Trieste, Italy. Hubbard model on the B. . 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. . Session 6: Interoperability. Session 6: Aims. In this session, you will learn about:. Steps towards interoperability. Interoperability challenges. Next steps towards . achieving . interoperability. . Session 1: Background. Luc Moreau. L.Moreau@ecs.soton.ac.uk. University . of Southampton. Session 1: Aims. In this session, you will learn about:. The notion of provenance. The Open Provenance Vision. 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. Segments . Explaining APIs. Dalian University of Technology, China. Mar.. 201. 6. Presented by . Jingxuan. . Zhang. OSCAR Research Group. He Jiang, . Jingxuan. Zhang, . Xiaochen. Li, . Zhilei. . Christine L. Borgman. Professor and Presidential Chair in Information Studies. University of California, Los Angeles. Flickr Commons Photos. Big . Data, Little Data, No . Data: Scholarship . in the Networked . 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.