The Center for Geographic Analysis (CGA) of Harvard University and the China Data Institute, a Michigan based not-for-profit organization, are collaborating on the development of China Data Lab, a cloud-based geospatial data analysis platform for geospatial data gathering, management, analysis, visualization, and sharing. The initiative is sponsored through the Spatiotemporal Innovation Center of the NSF Industry-University Cooperative Research Centers (I/UCRC) Program. George Mason University, Wuhan University, All China Marketing Research Co., Ltd., and All Knowledge Share Tech Co., Ltd. are also key collaborators in this project.
The objective of the China Data Lab is to build a core infrastructure for disseminating and utilizing spatiotemporal data, particularly data from China, to support case-based study and training. It will allow researchers to discover geospatial data from multiple sources, conduct spatial data analysis with GIS and statistics tools on the cloud, develop data-driven study cases, and share data and results as a package with others online. The platform will also support case-based training programs on spatiotemporal data analysis for economic, social, public health, urban planning, and other research subjects.
The platform will be constructed on the foundations of Harvard’s WorldMap, China Data Institute’s China Geo-Explorer, and the Spatial Data Lab, a cloud-based system currently under development at Wuhan University. China Data Lab will provide a secure dissemination channel for data providers, and eliminate the burden of downloading data, installing analytical software, and managing data and tools locally from researchers.
In addition to platform development at the software level, this project also includes the development of data-driven study cases. They can be published on the platform, shared with remote colleagues for critique and revision, cited in academic publications, and verified by independent reviewers. The cases may also be packaged as educational materials for courses and training workshops.
The project will be guided by an independent academic advisory committee formed by world-renowned scholars with a diverse background of research domains.
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