Mining and Utilizing Dataset Relevancy from Oceanographic Dataset Metadata, Usage Metrics, and User Feedback to Improve Data Discovery and Access


With the increasing number of resources available online, many Spatial Data Infrastructure (SDI) components (e.g. catalogues and portals) have been developed to help manage and discover resources, such as Oceanographic Distributed Active Archive Center. However, efficient and accurate resource discovery is still a big challenge because of the lack of data relevancy information. In this article, we propose a search engine framework for mining and utilizing dataset relevancy from oceanographic dataset metadata, usage metrics, and user feedback. The objective is to improve data discovery accuracy and access through better ranked results, recommendation and ontology navigation. Experiments and a search example show that the propose engine helps both scientists and general users search for more accurate resources.

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Liu, K., Yang, C., Li, W., Gui Z., Xia, J., 2013. Using semantic search and knowledge reasoning to improve the discovery of Earth science records: an example with the ESIP Semantic Testbed. International Journal of Applied Geospatial Research.
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