Integration and Management of Diverse Environmental Data Sets - Presentation Transcript
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
Data Challenges - Acquisition
Many different data sources
Different regulations/mechanisms for accessing data
Lack of automation
Finding the right data
Summit 09 Oct. 14, 2009
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
Summit 09 Oct. 14, 2009
Data Challenges – Pre-processing
Raw data typically cannot be directly analyzed
Significant amount of time spent preparing data for analysis
Lack of automation
Summit 09 Oct. 14, 2009
GeoChronos
Partners
CANARIE (NEP-1)
Center for Earth Observation Sciences, University of Alberta
Cybera
Grid Research Centre, University of Calgary
Summit 09 Oct. 14, 2009
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
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
Presentation I gave as part of the New Frontiers in more
Presentation I gave as part of the New Frontiers in Data Integration session at Summit 09 in Banff on Oct. 14, 2009. It discusses some current work that the Grid Research Centre is doing in relation to data management and integration. less
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