With the development of WebGIS, metadata, Geographic Information (GI) Service and Web 2.0, geospatial data is widely utilized and shared in the geoscience field via the Internet. How to accurately find the desirable geospatial data and recommend related geospatial data to users are the urgent issue for the geographic information sharing. 

The essential point of accurate geospatial discovery and intelligent recommendation via the Internet is the semantic interlinking among the geospatial data. Since lacking the semantic interlink, current geospatial data and services are independent or weak-interlinking only through keywords match. It leads to the bad recall and precision, and fails to provide automatic and heuristic service in the data discovery scenario. It may also badly restrain efficient geospatial data sharing. 

Linked data is supposed to be an implementation of semantic web. Linked data is able to make the data from different fields, sources and structures be interlinked, and fosters data discovery, integration and utilization. It is a foundation for building a sematic, machine-understandable and interconnected global data network. 

Prof ZHU Yunqiang, Institute of Geographic Sciences and Natural Resources Research (IGSNRR), Chinese Academy of Sciences (CAS) and his collaborators explored the data-link factors, multiple dimension interlink relations and data similarity computation model.  

They are applied in the automatic recommendation for the input of geospatial model and the metadata interlink for the geospatial data sharing.  

The results found that the linked data was an effective way to solve the semantic heterogeneity problem and also provides an effective approach for accurate data discovery and intelligent recommendation. The work could promote scientific information resources sharing across categories and agencies. The research articles were published on the International Journal of Geographical Information Science and International Journal of Digital Earth.  

The study is supported by the Natural Science Foundation of China, the National Special Program on Basic Works for Science and Technology of China.

The results have been published in the International Journal of Geographical Information Science  and International Journal of Digital Earth.