An Interoperable Environment for Geospatial Data
Sara J. Graves, Ken Keiser, Helen Conover, Steve Tanner and Rahul Ramachandran
Information Technology and Systems CenterUniversity of Alabama in Huntsville
National Space Science and Technology Center256-824-6064
http://www.itsc.uah.edu
Reasons for Building an Interoperable Environment
Reasons for Building an Reasons for Building an Interoperable EnvironmentInteroperable Environment
To collect, organize, process and disseminate To collect, organize, process and disseminate geospatial information and geospatial information and tools/servicestools/servicesTo facilitate improved data usability in addition to To facilitate improved data usability in addition to accessibilityaccessibilityTo promote collaborations to address not only new To promote collaborations to address not only new science questions but also address areas such science questions but also address areas such homeland security, hazard detection/prediction, etc.homeland security, hazard detection/prediction, etc.
Collaborations• Accelerate research process
•Maximize knowledge discovery •Minimize data handling
•Contribute to both fields
Domain Scientists
Information Scientists
Functions Required in an Interoperable EnvironmentFunctions Required in an Functions Required in an Interoperable EnvironmentInteroperable Environment
Identification, development and dissemination of Identification, development and dissemination of geospatial data products and services from geospatial data products and services from distributed interoperable heterogeneous data distributed interoperable heterogeneous data centers and service centerscenters and service centersIntegration and analysis of remote sensing data with Integration and analysis of remote sensing data with other geospatial dataother geospatial data
–– Diverse data formats, requiringDiverse data formats, requiringdatasetdataset--specific software, orspecific software, ormore flexible and comprehensive metadata standards (e.g. Earth more flexible and comprehensive metadata standards (e.g. Earth Science Markup Language)Science Markup Language)
Development of web accessible real time interactive Development of web accessible real time interactive displays of layered informationdisplays of layered information
U.S. Government Geospatial Interoperability Initiatives
• Existing efforts such as these provide an impressive integrated capability of locating existing resources• However, these efforts do not address the actual access and utilization of available resources
Emerging Technologies
Emerging technologies are beginning to make fully interoperable environments a reality
Geospatial Data Interoperability
• Many different formats, types and structures
• Different states of processing ( raw, calibrated, derived, modeled or interpreted )
• Enormous volumes
• Heterogeneity leads to data usability problems
• One approach: Standard data formatsDifficult to implement and enforceCan’t anticipate all needs
Some data can’t be modeled or is lost in translation
The cost of converting legacy data• A better approach: Interchange Technologies
Earth Science Markup Language
Interoperability: Accessing Heterogeneous Data
The Problem
DATA FORMAT 1
DATA FORMAT 1
DATA FORMAT 2
DATA FORMAT 2
DATA FORMAT 3
DATA FORMAT 3
READER 1 READER 2
FORMATCONVERTER
APPLICATION
ESML LIBRARY
APPLICATION
DATA FORMAT 1
DATA FORMAT 1
DATA FORMAT 2
DATA FORMAT 2
DATA FORMAT 3
DATA FORMAT 3
The Solution
ESMLFILEESMLFILE
ESMLFILEESMLFILE
ESMLFILEESMLFILE
What is ESML?It is a specialized markup language for Earth Science metadata based on XML - NOT another data format.It is a machine-readable and -interpretable representation of the structure and semantics of any data file, regardless of data formatESML description files contain external metadata that can be generated by either data producer or data consumer (at collection, data set, and/or granule level)ESML provides the benefits of a standard, self-describing data format (like HDF, HDF-EOS, netCDF, geoTIFF, …) without the cost of data conversionESML is the basis for core Interchange Technology that allows data/application interoperabilityESML complements and extends data catalogs such as FGDC and GCMD by providing the use/access information those directories lack.
http://esml.itsc.uah.edu
ESML in Numerical Modeling
ESMLfile
ESMLfile
ESMLfile
ESML Library
255
256
257
258
259
260
261
262
263
264
265
200 210 220 230 240 250 260 270 280 290 300
Sea Surface Temperature (TMI) Degree Kelvin
Chn
5 T
empe
ratu
re (A
MSU
) Deg
ree
Kel
vin
GOESSkin Temp
InsolationProducts
Soundings,Others
Network
Prediction
Scientists can:• Select remote files across the
network• Select different observational
data to increase the model prediction accuracy
Purpose:• Use ESML to incorporate
observational data into the numerical models for simulation
NUMERICAL WEATHERMODELS (MM5, ETA, RAMS)
Smart Applications/Services using ESML Schema and Ontology
DATA
ESMLFILE
CORE ESML LIBRARY
ESMLSCHEMA
RULES TO DESCRIBETHE STRUCTURE
OF THE DATA
ONTOLO-GIES
TERMS DEFINING THE MEANING OF THE DATA
SEMANTIC PARSER(INFERENCE ENGINE)
SMART APPLICATION/ SERVICES
ESML will allow embedding semantic terms for data fields in the description file to provide complete structural and semantic description of the dataVarious science communities can create their own ontologies and link them with ESML description files for their dataApplication developers can add semantic parsers on top of the core ESML library to build “smart”applications/services
Data
Web Mapping Services (WMS)
Data Files
ESML
Application Server
Web Map ServiceESML Lib
Data Files
KnowledgeBase
Web Map ServicesProvide access to visual map representations of distributed data sets. Request protocol is HTTP and the response is in conventional image formats (GIF, PNG, JPG). ESML provides interoperability with different formatted datasets without having to rewrite WMS software.
Integration of Remote Sensing and Geospatial Data using Web Mapping Services
Globe AMSU-A KnowledgeBaseITSC
Coastlines
Countries
MCS Events
Cyclone EventsAMSU-A Channel 01
AMSU-A data overlaid with MCS and Cyclone events for September 2000, merged with world boundaries from Globe.
Data Mining
Mining is needed to utilize geospatial data for critical decision-making in the real worldOn-board mining will provide more timely analysis and information Mining is the automated discovery of patterns, anomalies from vast observational data sets with the derived knowledge used for decision making, predictions and disaster response Two such mining tools are:
– ADaM – Algorithm Development and Mining System– EVE – EnVironmEnt for On-board Processing
http://datamining.itsc.uah.edu
Mining on Data Ingest: Tropical Cyclone Detection
Advanced Microwave
Sounding Unit (AMSU-A) Data
Calibration/Limb Correction/Converted to Tb
ADaM Mining Environment
Data Archive
ResultResults are placed on the web, made available to
National Hurricane Center & Joint Typhoon Warning Center,and stored for further analysis
Mining Plan:• Water cover mask to eliminate land• Laplacian filter to compute temperature
gradients• Science Algorithm to estimate wind speed• Contiguous regions with wind speeds
above a desired threshold identified• Additional test to eliminate false positives• Maximum wind speed and location
produced
Hurricane Floyd
Further Analysis
http://pm-esip.msfc.nasa.gov/cyclone
KnowledgeBase
Mesocyclone Signature Detection Using ADaM
Problem: Detecting mesocyclone signatures in Radar dataScience Rationale: Improved accuracy and reduced false alarm rate for indicators of tornadic activityTechnique: Developing an algorithm based on wind velocity shear signatures
On-Board Real-Time Processing
• Anomaly detection• Data Mining• Autonomous
Decision Making• Immediate
response• Direct satellite to
Earth delivery of results
• Intelligent sensor control
EVE – Environment for On-board Processing
Sensor Web Services
Sensor Planning/Collection Requests Event Notifications and Alerts
Mining Results & Customized Data Products
Planning and Scheduling
On-
Boa
rd P
roce
ssor
an
d O
S
Sensor Sensor Sensor
EVE Mining Framework
Operations Library
Feature Extraction
Hazard Detection …
Cart A Cart B
Mining Plan
Mining plans are constructed from a series of operations packaged as platform-specific executables, or carts
Sensor Control
EVE On-Board Framework
Interoperable Environment Challenges
Interoperable Environment Interoperable Environment ChallengesChallenges
Define common/standard interfaces for interoperability of servicesIncorporate current standards/definitions (Earth Science Markup Language (ESML), OGC Classification, OGC Services, etc.)Design new data models for handling streamed inputEstablish network-accessible data sets (data pool concept)Design and develop distributed standardized catalog capabilitiesSupport Grid environments such as NASA’s Information Power Grid and NSF’s TeraGrid
Develop interactive web-based user interfaces for• Visually connecting processes in interface• Querying information on algorithms/services• Interfacing with distributed components• Supporting interactive inspection of data results at
processing pointsDevelop ontologies for scientific data and services Incorporate Internet-2 capabilities…thinking beyond what is possible with current network bandwidthsSupport a reasonable level of reliability with respect to distributed data and services availabilitySupport network interactions between componentsSupport language and system independent components
Interoperable Environment Challenges
Interoperable Environment Interoperable Environment ChallengesChallenges
