RESUMEN
Aims: Global change studies need to manipulate large volume of observation and prediction data, most likely from multiple sources. From the researchers’ perspective, the whole research process consists of the follow stages: data discovery, data access, data processing, data analysis and result dissemination. The aim of paper is to review the state-of-the-art of geospatial data systems to reveal the way towards a better support of global change studies. Methodology: This paper reviews the capabilities of exemplar geospatial data systems. It further analyzes the needs of manipulating large volume of diverse data when performing global change studies. By comparing the available capabilities with the real needs, this study shows the strengths and limitations of existing data systems when supporting global change studies. Results: The analysis shows that data systems are helpful for researchers to fulfill data discovery and access, while most of them do not provide further functionalities to cover other stages in the whole research process. This suggests that a new generation of data systems is highly needed to provide efficient and enough support for scientists to perform global change studies. Instead of simply moving data from sources to researchers’ local archives, it will enable more on-line data manipulation functionality and the interoperability of data and systems. Conclusion: Traditional geospatial data systems are designed to operate locally without built-in interoperability and sharing capabilities. Such systems are operated under the paradigm of “everything-locally-owned-and-operated”. Conducting global change studies using such a system requires moving a large volume of data from providers’ sites to researchers’ site. Such a system does not provide strong support for the entire research process. Since climate research requires manipulating a huge volume of complex and diverse multi-source data, a new paradigm of “everything-shared-over-the-Web” is promising when designing a new generation of geospatial data systems, which are standard-based, interoperable, and sharable, for global change studies.