Presentation is loading. Please wait.

Presentation is loading. Please wait.

Experiences Developing a User- centric Presentation of A Domain- enhanced Provenance Data Model Cynthia Chang 1, Stephan Zednik 1, Chris Lynnes 2, Peter.

Similar presentations


Presentation on theme: "Experiences Developing a User- centric Presentation of A Domain- enhanced Provenance Data Model Cynthia Chang 1, Stephan Zednik 1, Chris Lynnes 2, Peter."— Presentation transcript:

1 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 1. Tetherless World Constellation, Rensselaer Polytechnic Inst., Troy, NY, United States 2. NASA Goddard Space Flight Center, Greenbelt, MD, United States 3. 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. 2

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 3

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 4

5 South Pacific Anomaly Anomaly 5

6 …is caused by an Overpass Time Difference 6

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 7

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 8

9 Advisor Knowledge Base 9 Advisor Rules test for potential anomalies, create association between service metadata and anomaly 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 10

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

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 12

13 Domain-integrated Provenance Visualization 13

14 Domain-integrated detail view 14

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 15

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. 16

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


Download ppt "Experiences Developing a User- centric Presentation of A Domain- enhanced Provenance Data Model Cynthia Chang 1, Stephan Zednik 1, Chris Lynnes 2, Peter."

Similar presentations


Ads by Google