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Observations Data Model 2.0 Jeff Horsburgh, USU. Project PI. Anthony K. Aufdenkampe, Stroud Water Research Center Kerstin Lehnert, IEDA/Columbia Emilio.

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Presentation on theme: "Observations Data Model 2.0 Jeff Horsburgh, USU. Project PI. Anthony K. Aufdenkampe, Stroud Water Research Center Kerstin Lehnert, IEDA/Columbia Emilio."— Presentation transcript:

1 Observations Data Model 2.0 Jeff Horsburgh, USU. Project PI. Anthony K. Aufdenkampe, Stroud Water Research Center Kerstin Lehnert, IEDA/Columbia Emilio Mayorga, UW-APL Ilya Zaslavsky, SDSC David Valentine, SDSC David Tarboton, USU David Lubinski, UC-Boulder A community information model for interoperability among feature-based earth observations

2 Critical Zone Science Atmosphere Biosphere Hydrosphere Lithosphere Earth's permeable near- surface layer from the tops of the trees to the bottom of actively cycling groundwater. Where rock, soil, water, air, and living organisms interact and shape the Earth's surface. Critical to sustaining the earth’s sustaining services Clean water Productive soil Balanced atmosphere Hillslope Catchment Watershed Minutes Decades Millenia Eons

3 CZO Disciplines Biogeochemistry Biology/Ecology Biology/Molecular Climatology/Meteorolog y Data Management/CyberInfr astructure Engineering/Method Development Geochemistry/Mineralo gy Geology/Chronology Geomorphology Geophysics GIS/Remote Sensing Hydrology Modeling/ Computational Science Outreach/ Education Research Soil Science/Pedology Water Chemistry

4 CZO Disciplines Big DataLong Tail Data Biogeochemistry Biology/Ecology Biology/Molecular Climatology/Met eorology Data Management/CyberIn frastructure Engineering/Method Development Geochemistry/ Mineralogy Geology/Chronology Geomorphology Geophysics GIS/Remote Sensing Hydrology Modeling/ Computational Science Outreach/ Education Research Soil Science/Pedology Water Chemistry

5 CZO Disciplines Big DataLong Tail Data Sample-based Sensor-based Geospatial Grids & Vectors Categorical

6 Observations Core Observations Core Sensor Extension Sensor Extension Domain Cyberinfrastructures CUAHSI HIS CUAHSI HIS EarthChem CZOData IOOS Feature Model Feature Model Equipment & Lab Extensions Equipment & Lab Extensions Generic Extension Generic Extension Common Semantics for Earth Observations ODM2: Common to Most Data Types

7 Catalog Data ServerClients Metadata Catalog Data Storage Metadata Harvesting Data Discovery Data Delivery Metadata Transfer Metadata Transfer Data Transfer Database Encoding XML Schema Encoding Legend Data and Metadata Transfer Information Model ODM2: Common to All Components

8 ODM2: Additional Goals Driven by Community & Use Cases: 3 workshops + ~12 data models + much feedback use cases: CZOData, Little Bear River, PetDB, IOOS Balance between general vs. understandable External unique identifiers, vocabularies & taxonomies Rich Specimen, Site & other Sampling Features Granular Methods, Data Quality & Equipment Dataset publishing & archiving via: Result “packages”, Versions, Citations, Provenance Strong Annotations & general extensibility

9 ODM2Core

10

11 ODM2SamplingFeatures

12 ODM2Results

13 ODM2ExternalIdentifiers

14 ODM2Provenance

15 ODM2Annotations

16 ODM2Equipment

17 ODM2DataQuality

18 ODM2LabAnalyses

19 ODM2Sensors

20 NSF Scientific Software Integration BiG CZ SSI project ( ): The community-driven BiG CZ software system for integration and analysis of bio- and geoscience data in the critical zone Community Engagement in Software Design through co-design, training & testing workshops. BiG CZ Portal web application for high-performance map-based discovery, visualization, access & publication of data on critical zone structure & function BiG CZ Toolbox to enable cyber-savvy CZ scientists & data managers to manage and publish the data they produce through a single scientist-focused toolkit BiG CZ Central software stack to bridge data systems developed for multiple critical zone domains

21 Thank You Funded by the National Science Foundation EAR EAR ACI ODM2 is on GitHUB: https://github.com/UCHIC/ODM2

22 ODM2: Object-Relation Map

23 What can we do with ODM2? (that we couldn’t do before) Add multiple comments/annotations to any entity Represent Actions and sequences of Actions that lead to observation Results More granularly represent people and organizations Store information about Actions that do not have Results

24 What can we do with ODM2? (that we couldn’t do before) Separate Results from ResultValues – enables multiple ResultTypes Move DataValues out of the Core – better facilitates cataloging Add taxonomic classifiers to Results, adding an additional dimension to observations Create relationships among Results and store provenance Group Results into Datasets

25 What can we do with ODM2? (that we couldn’t do before) Store information about the equipment used to create observations Add extension properties to any record in any entity Link many entities to external identifier systems Support SamplingFeatures of multiple types - Sites and Specimens, among others Not limited to a single spatial offset Not Limited to a single qualifier

26 Observation Data Model 2.0 NSF funded project: PI. Jeff Horsburgh “Developing a Community Information Model and Supporting Software to Extend Interoperability of Sensor and Sample Based Earth Observations” To achieve interoperability between IEDA, EarthCHEM, CUAHSI HIS, and other data systems Better support for samples and unique identifiers (IGSN/SESAR) Extensibility to table attributes Better annotation and provenance Enable integrated web service based publication of a broader class of CZO data

27 ODM2 Functional Use Cases

28 Future Directions for CZO Science Develop a unifying theoretical framework of CZ evolution; Develop coupled systems models to explore how CZ services respond to anthropogenic, climatic, and tectonic forcings; Develop four dimensional data sets that document differing CZ geologic and climatic settings, inform our theoretical framework, constrain our conceptual and coupled systems models, test model-generated hypotheses. Report prepared by CZO community, Dec. 2010

29 EarthCube Critical Zone Domain Workshop Engaging the Critical Zone community to bridge long tail science with big data Organizing Committee: Kerstin Lehnert, IEDA/Columbia. Ilya Zaslavsky, SDSC. David Tarboton, USU Jeff Horsburgh, USU. Emilio Mayorga, UW-APL James Syvitski, CSDMS. Susan Brantley, PSU & SH-CZO. Susan Gill, SWRC. Convened by A.K. Aufdenkampe, C.J. Duffy, G.E. Tucker Univ. of Delaware: Jan , 2013

30 103 Participants from 16 Disciplines Biogeochemistry (30) Biology/Ecology (15) Biology/Molecular (3) Climatology/ Meteorology (15) Data Management/CyberInfra structure (46) Engineering/Method Development (8) Geochemistry/Mineralog y (13) Geology/Chronology (14) Geomorphology (15) Geophysics (8) GIS/Remote Sensing (31) Hydrology (46) Modeling/ Computational Science (36) Outreach/ Education Research (7) Soil Science/Pedology (16) Water Chemistry (14) Early-Career (28)


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