As a part of the NSF Spatiotemporal Innovation Center project, the Spatial Data Lab is co-sponsored by the Center for Geographical Analysis at Harvard University, the Geo-Computation Center for Social Sciences at Wuhan University (a joint initiative with the Center for Spatial Data Science of the University of Chicago), the China Data Institute, and the Future Data Lab. The project aims to promote the development of a new generation of methodologies and technologies for spatial data analysis, spatial data sharing, and applied research in the fields of spatiotemporal innovation, including population, business, environment, and health. The main tasks of the spatial data lab include: (1) spatial data services; (2) development of spatial data analysis platform and tools; (3) development of case studies based on workflow data analysis for replicable, reproducible and expandable research; and (4) spatial data science training.
The project are guided by an independent academic advisory committee formed by world-renowned scholars with a diverse background of research domains.
About China Data Lab
Sponsored by the Spatial Data Lab, the China Data Lab is designed to build a core infrastructure for disseminating and utilizing spatiotemporal data, particularly data from China. It will allow researchers to discover the sptiotemporal changes of China with multiple data sources, conduct spatial data analysis with GIS and statistics tools, and to share data and results.
The China Data Lab offers a cloud platform provides 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. The cloud based platform will also support case-based training programs on spatiotemporal data analysis for economic, social, public health, urban planning, and other research subjects on China studies.
This project also includes the development of data-driven study cases for China studies. 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.
Even though this platform is focused on China data in the initial phase, the infrastructure and system design is suitable for any region and any geographic scale. The same platform can be adapted for other regions or at a global scale, as long as data content is available to support the new geographic focus.
Center for Geographic Analysis, Harvard University
1737 Cambridge Street, Suite 350, Cambridge MA 02138