A Geo-Semantic Framework for Integrating Long-Tail Data and Models

Project description

"Our vision is to develop a decentralized knowledge-based platform that can be easily adapted across geoscience communities comprised of individual and small group researchers, to allow semantically heterogeneous system to interact with minimum human intervention. It will allow the automatic reference of data from data resources to model by: (i) leveraging the Semantic Web; (ii) developing an automated semantic mediation tool; and (iii) developing a semantic knowledge discovery system that can be used by long-tail models. The developed approach will be evaluated based on a case study of integrating two examples of long-tail modeling and data: the Community Surface Dynamic Modeling System (CSDMS) and Sustainable Environment Actionable Data (SEAD)."

Objectives

"To develop a framework rooted in semantic techniques and approaches to support “long-tail” models and data integration"

Time-line

Start: Summer 2014
Expected length: 2 years

Models in use

As this project is supposed to integrate all the models in CSDMS, we will utilize as much models as we could for testing.

Results

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Users

Peishi JIANG

Funding

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HPCCprojects:A Geo-Semantic Framework for Integrating Long-Tail Data and Models