This project analyzed CDC published mortality data of a dozen major causes since 1999, and applied the Exponential Smoothing (ETS) algorithm to simulate the 2020 mortality rates per cause, per month and per state, assuming there was no COVID-19 pandemic. The difference between the simulated rates and the actual rates revealed COVID-19 impacts on mortality of various causes in the United States. Results are published in...

Sponsored by NSF, this project is to build a comprehensive data repository of virus cases, associated social and natural information from different resources for sustainable archive; share data with the research communities through smart data discovery capabilities with easy access; utilize the spatiotemporal computing infrastructure built in IUCRC STC for computational needs of COVID 19 research with online collaboration; develop workflows in collaboration with public health...

Funded by OmniSci Technologies, LLC. as a member of the I/UCRC Spatiotemporal Innovation Center
Can be hosted on Harvard Cannon Cluster, Amazon AWS, Mass Open Cloud, MapD Cloud.

Use cases:

• Improving access to hydrological models used in water management and public safety
• Analyzing how political partisanship affects the geographic sorting of voters

See...

Toward an Open Platform for Collaborative Research in the Digital Humanities.  Based on WorldMap, this project will host historical maps of Japan.

Funded by Ritsumeikan University.

Investigator:  Prof. Keiji Yano...

A new collaboration between Zhejiang University and Harvard was launched on October 13th, 2017.   The joint effort will build upon Harvard CGA's WorldMap to develop a Chinese Academic Mapping Platform for research, teaching, and data sharing.  Please see the Zhejiang...