Using Knowledge to Facilitate Better Data Discovery, Access, and Utilization for CloudGIS

1. Using Knowledge to Facilitate Better Data Discovery, Access, and Utilization for CloudGIS Chaowei Phil Yang, Co-Director Center of Intelligent Spatial Computing for Water/Energy Science Zhipeng Gui, Kai Liu, Abdelmounaam Rezgui, Qunying Huang and Chen Xu, CISC, COS, GMU, Fairfax, VA, 22030-4444

2. Why a CloudGIS? flooding analyses

3. Why a CloudGIS? • What if we can • Integrate all geospatial data, information, knowledge, processing in a few minutes • Generate and send the right information in real time to the people including decision makers, first responders, and other stakeholders • This dream requires a platform and GIS that • can be ready in a few minutes • can reach out to all people needed • only cost for the amount of system used • won’t cost to maintain after the emergency response • This requires a new generation of GIS -- CloudGIS

4. GEOSS Clearinghouse • Objectives • Share Global Earth Observation Data Among 140+ Countries to Address Global Challenges of Natural Hazards and Emergency Responses • Support Global End Users to Discover, Access, and Utilize EO Data • Provide Responses to End Users in Seconds • Advanced Computing Technologies • Ontology and semantics indexing of metadata elements • Cloud Computing (EC2 & Azure) Responds to Spike Massive Concurrent End Users • Cloud DB (SQLAzure) Manages Millions to Billions of Metadata Records • WebGIS & 5D Vis Tools to Visualizes EO Data

5. Dynamic Distributed Search for Federated Catalogs Vocabularies and Semantics • Rank Results • Support Provenance

6. Use Ontology (of Resource Categorization and Quality) to Support Utilization

7. Demo

8. Pooled, Elastic, On-Demand, Pay-as-you-go CloudGIS Yang C., Wu H., Li Z., Huang Q., Li J., 2011, Utilizing Spatial Principles to Optimize Distributed Computing for Enabling Physical Sciences, Proceedings of National Academy of Sciences, 108(14): 5498-5503.

9. Pooled, Elastic, On-Demand, Pay-as-you-go CloudGIS Yang C., Goodchild M., Huang Q., Nebert D., Raskin R., Bambacus M., Xu Y., Fay D., 2011. Spatial Cloud Computing - How can geospatial sciences use and help to shape cloud computing, International Journal of Digital Earth. (4), 305-329.

10. A Conceptual Framework for CloudGIS Yang C., Bambacus M., Benedict K., Nebert D., Mochuney D., Hazlett S., Houser P., Raskin R., Xu Y., Fay D., Rezgui A., Huang Q., and Xu C., 2011. Using Metadata, Data/Service Quality and Knowledge to Facilitate Better Data Discovery, Access, and Utilization for Supporting EarthCube, http://semanticommunity.info/@api/deki/files/13812/=024_Yang.pdf.

11. Ontology Related Research Needs • The interoperably integrating currently isolated clouds from multiple domains • The evolution of cloud from a technology-centered to a human-centered paradigm • The advancement of cloud to enable multiple science domains in simulating complex phenomena • More study in social sciences is urgently needed to enable efficient governance and collaboration among team members, communities, and domains • Work must be done to improve knowledge capturing/sharing/utilizing • Improved methods for generating and capturing metadata as a parallel process with data product generation • Thinking and computing in a spatiotemporal fashion will provide an enabling capability for the new geoscience frontier by contributing essential computing architectures, algorithms, and methodologies • To investigate the connections and interactions across different geospatial subsystems

12. Sponsors and Collaborators