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Experiences Developing a User-centric Presentation of A Domain-enhanced Provenance Data Model

Experiences Developing a User-centric Presentation of A Domain-enhanced Provenance Data Model. Cynthia Chang 1 , Stephan Zednik 1 , Chris Lynnes 2 , Peter Fox 1 , Deborah McGuinness 1 , Gregory Leptoukh 2 , Jianfu Pan 3.

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Experiences Developing a User-centric Presentation of A Domain-enhanced Provenance Data Model

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  1. Experiences Developing a User-centric Presentation of A Domain-enhanced Provenance Data Model Cynthia Chang1, Stephan Zednik1, Chris Lynnes2, Peter Fox1, Deborah McGuinness1, Gregory Leptoukh2, Jianfu Pan3 Tetherless World Constellation, Rensselaer Polytechnic Inst., Troy, NY,United States NASA Goddard Space Flight Center, Greenbelt, MD, United States Adnet Systems, Inc. IN43C-06

  2. Giovanni Earth Science Data Visualization & Analysis Tool • Developed and hosted by NASA/GSFC • Multi-sensor and model data analysis and visualization online tool • Supports dozens of visualization types • Generate dataset comparisons • ~1500 Parameters • Used by modelers, researchers, policy makers, students, teachers, etc.

  3. Challenge • Giovanni allows users to run analyses with most of the data processing performed before or in Giovanni • This is the primary value add of Giovanni, but it presents the possibility of users generating and using results they do not fully understand • We are challenged to instrument the system to help users understand results

  4. Challenge (cont.) Particularly when the fitness for use of the results may be in question… • Unexpected and unexplained anomalies possible in analysis and comparison results • Users may not have the expertise to recognize or understand anomalous results • Many anomalies/biases the result of complex sets of interrelated conditions

  5. South Pacific Anomaly Anomaly

  6. …is caused by an Overpass Time Difference

  7. Multi-Sensor Data Synergy Advisor (MDSA) • Construct knowledge base of service operations and inputs • Giovanni service operations to be performed • Provenance of selected data sources • Analyze knowledgebase for potential or known anomalies • Expert rules • Utilize provenance, science, and data processing info • Semantic comparison of data source and processing provenance properties • Advise • Compile an advisory report for the user

  8. Multi-Domain Knowledgebase • Capture Giovanni and Data Source provenance • Associate provenance entities with domain metadata described by independent domain models • Expert Rules operate over multi-domain knowledgebase, test for conditions that may affect result’s fitness for use

  9. Advisor Knowledge Base Advisor Rules test for potential anomalies, create association between service metadata andanomaly metadata in Advisor KB

  10. Advisor Presentation Requirements • Present metadata that can affect fitness for use of result • When analysis is a comparison • Make obvious which properties are comparable • Highlight differences where present • Present visuals (where possible) and descriptive text for any anomalies predicted by expert ruleset • Presentation must be understandable by Earth Scientists

  11. Advisory Report • Tabular representation of the semantic equivalence of comparable data source and processing properties • Advise of and describe potential data anomalies/bias

  12. Giovanni Provenance Visualization Requirements • Exercise existing provenance visualization tools to show Giovanni processing provenance • Visualization tool must support access to multi-domain metadata knowledgebase (not just provenance metadata) • Science metadata adds domain context to entities in the provenance trace • Presentation must be understandable by Earth Scientists

  13. Domain-integrated Provenance Visualization

  14. Domain-integrated detail view

  15. Conclusion, Q&A • Different provenance needs = different provenance presentation requirements • Science User feedback • “Advisory report is very helpful” • “Too much provenance metadata to dig through, I need a simplified abstraction/view” • Future Work • Advisor suggestions to correct for potential anomalies • Views/abstractions of provenance based on specific user group requirements • Continued iteration on visualization tools based on user requirements

  16. References • System Transparency, Or How I Learned to Worry about Meaning and Love Provenance!, Zednik, S., Fox, P., McGuinness, D., IPAW 2010, to appear in Springer conference proceedings.

  17. Links • Giovanni Earth Science Data Analysis Tool • http://disc.sci.gsfc.nasa.gov/giovanni/ (Production site) • http://giovanniplus-ts1.sci.gsfc.nasa.gov/daac-bin/G3/gui.cgi?instance_id=MDSA-case1 (MDSA site) • MDSA • http://tw.rpi.edu/web/project/MDSA (Project site) • PML • http://inference-web.org (Inference Web) • http://inference-web.org/2007/primer/ (PML Primer, 2007)

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