observations data model 2.0
DESCRIPTION
Observations Data Model 2.0. A community information model for interoperability among feature -based earth observations. Jeff Horsburgh , USU. Project PI. Anthony K. Aufdenkampe , Stroud Water Research Center Kerstin Lehnert , IEDA/ Columbia Emilio Mayorga , UW-APL - PowerPoint PPT PresentationTRANSCRIPT
Observations Data Model 2.0
Jeff Horsburgh, USU. Project PI.Anthony K. Aufdenkampe, Stroud Water Research Center
Kerstin Lehnert, IEDA/ColumbiaEmilio Mayorga, UW-APLIlya Zaslavsky, SDSCDavid Valentine, SDSCDavid Tarboton, USUDavid Lubinski, UC-Boulder
A community information model for interoperability among
feature-based earth observations
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
MinutesDecades
Millenia Eons
CZO Disciplines• Biogeochemistry• Biology/Ecology• Biology/Molecular• Climatology/
Meteorology• Data
Management/CyberInfrastructure
• Engineering/Method Development
• Geochemistry/Mineralogy
• Geology/Chronology
• Geomorphology• Geophysics• GIS/Remote Sensing• Hydrology• Modeling/
Computational Science• Outreach/
Education Research• Soil Science/Pedology• Water Chemistry
CZO DisciplinesBig Data Long Tail Data
BiogeochemistryBiology/EcologyBiology/MolecularClimatology/MeteorologyData Management/CyberInfrastructureEngineering/Method DevelopmentGeochemistry/MineralogyGeology/Chronology
GeomorphologyGeophysicsGIS/Remote SensingHydrologyModeling/Computational ScienceOutreach/Education ResearchSoil Science/PedologyWater Chemistry
CZO DisciplinesBig Data Long Tail Data
Sample-based
Sensor-based
Geospatial Grids & Vectors
Categorical
ObservationsCore
SensorExtension
Domain Cyberinfrastructures
CUAHSIHIS EarthChem CZOData IOOS
FeatureModel
Equipment & LabExtensions
GenericExtension
Common Semantics for Earth Observations
ODM2: Common to Most Data Types
Catalog
Data Server Clients
MetadataCatalog
Data Storage
Metada
ta Har
vesti
ngData Discovery
Data Delivery
MetadataTransfer
MetadataTransfer
DataTransfer
DatabaseEncoding
XML SchemaEncoding
Legend
Data and Metadata Transfer
Information Model
ODM2: Common to All Components
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
ODM2Core
ODM2Core
ODM2SamplingFeatures
ODM2Results
ODM2ExternalIdentifiers
ODM2Provenance
ODM2Annotations
ODM2Equipment
ODM2DataQuality
ODM2LabAnalyses
ODM2Sensors
NSF Scientific Software Integration
BiG CZ SSI project (2014-2015): 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
Thank YouFunded by the
National Science FoundationEAR 1224638EAR 1332257ACI 1339834
ODM2 is on GitHUB: https://github.com/UCHIC/ODM2
ODM2: Object-Relation Map
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
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
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
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
Information Model(All)
StorageEncoding
(USU/LDEO)
CatalogEncoding(SDSC)
Web Service Interface
(UW)
Archival Encoding
(USU)
XML Schema Encoding(SDSC)
ODM2 Functional Use Cases
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
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, USUJeff 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. TuckerUniv. of Delaware: Jan. 21-23, 2013
103 Participants from 16 Disciplines• Biogeochemistry (30)• Biology/Ecology (15)• Biology/Molecular (3)• Climatology/
Meteorology (15)• Data
Management/CyberInfrastructure (46)
• Engineering/Method Development (8)
• Geochemistry/Mineralogy (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)