Information Requirements for Integrating Spatially Discrete, Feature- Based Earth Observations Jeffery S. Horsburgh Anthony Aufdenkampe, Kerstin Lehnert,

Information Requirements for Integrating Spatially Discrete, Feature-

Based Earth Observations

Jeffery S. HorsburghAnthony Aufdenkampe, Kerstin Lehnert, Emilio Mayorga,

Leslie Hsu, Lulin Song, Ilya Zaslavsky, David Valentine

Support: 1224638

Challenge

• Information models of current geoscience cyberinfrastructures:– Represent common information elements in

inconsistent ways (e.g., people, units, measured variables, etc.)

– Lack extensibility required for supporting additional data types

Given data sharing requirements from funding agencies:

What information must accompany observational data for them to be archivable and discoverable within a publication system as well as interpretable once retrieved from such a system for analysis and (re)use?

Overarching Goals

• Create an information model (ODM2) that is integrative and extensible– Accommodating a wide range of observational data– Aimed at achieving interoperability across multiple

disciplines and systems that support publication of earth observations

• Allow a diverse range of geoscience observations to be consistently managed, shared, discovered, accessed, and interpreted

Common Semantics for Earth Observations

ObservationsInformation

Model

Domain Cyberinfrastructures

CUAHSIHIS EarthChem CZOData IOOS

Storage Schema

TransferSchema

Metadata Catalog Schema

Design Process

• Series of community design and prototyping workshops over the past 2 years– Scientists from multiple domains– Cyberinfrastructure experts representing multiple

domains/systems• Extract requirements, data use cases, test

preliminary designs

Requirement: Describe Observed Feature(s)

Sampling Features

Stream Gage

Source: http://pubs.usgs.gov/tm/tm3-a7/

Weather Station

Monitoring Site:• A location

established for making observations• Represented as a

point• May have a

geospatial footprint that is not a point

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Specimens

Sampling Features in ODM2

From OGC’S Observations & Measurements:Sampling Feature = the entities on which or at which observations are made

Requirement: Support Diverse Data Types

Time Series Result

Z

X

Y

Fixed Sensor Position

Date Temperature (Deg. C)

12/1/2014 8:00 AM 10.1

12/1/2014 9:00 AM 10.2

12/1/2014 10:00 AM 10.4

12/1/2014 11:00 AM 10.8

. . . . . .

Time Series Result

Space = FixedTime = ControlledVariable = Measured

Measurement Result

Z

X

Y

Fixed Sampling Position and TimeSpecimen

Total phosphorus = 0.04 mg/LTotal suspended solids = 10 mg/L

Space = FixedTime = FixedVariable = Measured

Section Result

Z

X

Y

Discrete point measurements within a section

Velocity = 2.5 ft/s

Space = ControlledTime = Fixed or ControlledVariable = Measured

Transect Result

Z

X

Y

Measurements along a transect

pH = 7.2

pH = 7.5

pH = 7.3

pH = 7.0

Space = ControlledTime = Fixed or ControlledVariable = Measured

ODM2 Core Schema + Results

• People and organizations• Actions• Results• Measured variables• Units• Processing levels

Time Series

Measurement

Transect

. . .

• Space• Time• Measured Values

TransectResult

ODM2 Results

Attributes that are fixed

Attributes that are variable or measured

MeasurementResult

Time SeriesResult

SectionResult

ODM2 Results: Measurement Frameworks

• Documents how space, time, and measured variables are handled

Requirement: Support Observation Provenance

Monitoring Equipment ManagementWhich sensors were

deployed at this site? Who installed them?

Which soil moisture sensor is buried at 40 cm?

Has this turbidity sensor been serviced

at the factory?Who programmed

this datalogger?

How long has that battery been

deployed?

What is this dissolved oxygen

sensor’s calibration history?

When was the last time we cleaned this

sonde?

What were the field conditions of our

discharge measurement?

Sensor Workflows

Site visits

Equipment

Field activities

• Location• Date• People• Conditions

• Activity type• Description• Date

• Model• Serial number• Owner• Vendor• Manufacturer• Service history

Deployments

• Deployment type• Description• Dates• Offsets

Calibrations

• Method • Standard

Time Series Observations

Sampling WorkflowsSample collection Sample splitting Sample processing Sample analysis

Sample analysis actions result in observations

• Sample type• Location / sampled feature• Collection method• Date• People• Preservation• Identifiers• Sampled medium

• Sample hierarchy• Parent/child relationships

• Preparation method• Processing method• People

• Analytical method• Instrument• People• Date

Actions and Results

• An Action is performed on or at a SamplingFeature using a Method• Actions can be related to each other• Some Actions produce Results• Results have a Variable, Units, and a ProcessingLevel

Monitoring Equipment Management• Record site information, site visits, and field activity details• Store information on physical equipment• Track equipment deployments, calibrations, service events

Requirement: Support Multiple Functional Use Cases

Catalog

Data Server Clients

MetadataCatalog

Data Storage

Met

adata

Har

vesti

ngData Discovery

Data Delivery

MetadataTransfer

MetadataTransfer

DataTransfer

Information Model

DatabaseEncoding

XML Schema

Encoding

Legend

Data and Metadata Transfer

Storage Implementation • Multiple platform support• Storage implementation available for multiple

Relational Database Management Systems (RDBMS) • Python-based software tools for multiple platforms

ODM2

Summary and Status

• ODM2 is an information model for spatially discrete, feature-based earth observations

• ODM2 supports sensor and sample based data – and many other result types

• Integration of sensor and sample-based data in the Critical Zone Observatory Integrated Data Management System (CZOData)

• Implementation of ODM2 in production systems at IEDA• Development of supporting software tools for more general

use via BiG CZ SSI project• Storage of time series and sample-based data for HydroShare

ODM2 on• Available now:

– Storage implementations for Microsoft SQL Server, MySQL, PostgreSQL, SQLite

– Documentation and use cases for information model– Python API for database interaction

• Coming soon:– ODM2 data loader(s) and input templates– CUAHSI HIS WaterOneFlow web services– ODM Tools for QA/QC of sensor data– Web interface for recording field activities and sampling workflows

Questions?

https://github.com/UCHIC/ODM2 Support: 1224638