Integration and Management of Diverse Environmental Data Sets Cameron Kiddle Research Fellow Grid Research Centre University of Calgary
Jun 13, 2015
Integration and Management of Diverse Environmental
Data Sets
Cameron Kiddle
Research Fellow
Grid Research Centre
University of Calgary
Outline Data Challenges GeoChronos (Spectral Libraries) Spectral Library Demonstration Cloud Services for Water Management Cloud Services for Water Management
Demonstration
Summit 09 Oct. 14, 2009
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Data Challenges - Acquisition Many different data sources
Different regulations/mechanisms for accessing data
Lack of automation
Finding the right data
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Data Challenges - Management Scattered and unorganized data
Inadequate tools for recording/maintaining metadata Data without metadata is meaningless Lack of suitable metadata standards Validation of metadata
Tracking provenance of data
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Data Challenges – Pre-processing Raw data typically cannot be directly
analyzed
Significant amount of time spent preparing data for analysis
Lack of automation
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GeoChronos Partners
CANARIE (NEP-1) Center for Earth Observation Sciences,
University of Alberta Cybera Grid Research Centre, University of Calgary
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GeoChronos An on-line platform (http://geochronos.org/)
For: Earth Observation Scientists
Facilitating: Collaboration between scientists Application access, management and sharing Data access, management and sharing
Leveraging: Web 2.0 and social networking technologies Cloud computing technologies Semantic Web technologies
Summit 09 Oct. 14, 2009
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GeoChronos Data Solutions - Spectral Libraries
Store, share and browse spectral data View spectral plots, metadata, ancillary data and maps Manage and generate metadata for spectra Create and share metadata schemas
Technology iRODS (http://www.irods.org/) for data storage/management Semantic Web technologies such as RDF (Resource
Description Framework) to link/relate data Next Steps
Generalization of spectral library solution - acquire, store, manage, browse and share other types of data (i.e., satellite, flux, phenology, meteorological, etc.)
Automate data workflows (i.e., mosaic, reproject and subset MODIS data) using cloud-based services
Summit 09 Oct. 14, 2009
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Spectral Library - Demonstration
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Spectral Library - Browse
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Spectral Library - Metadata
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Spectral Library - Ancillary Data
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Cloud Services for Water Management
Partners Alberta Advanced Education and Technology Alberta WaterSMART Cybera Geosensor Web Lab, University of Calgary Grid Research Centre, University of Calgary Tesera Systems Inc
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Cloud Services for Water Management In preliminary stages of project Explore use of cloud services to store,
manipulate and expose data related to water management
Link and correlate a wide variety of data from a large number of sources
Cloud-based analysis and visualization tools Investigate integration with existing Alberta
WaterPortal (http://www.albertawater.com/)
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Cloud Services for Water Management - Demonstration
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Data Types and Locations Displayed on Google Earth
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Water Flow Data Shown using Google Visualization API
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Integrating and Visualizing Different Data Sets From Calgary’s Flood in 2005 on Google Earth
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Contact Information
Summit 09 Oct. 14, 2009
Cameron [email protected]://pages.cspc.ucalgary.ca/~kiddlec/
http://grid.ucalgary.ca/
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