January 2025
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Open Science 2.0: Revolutionizing Spatiotemporal Data Sharing And Collaboration
The Spatial Data Lab (SDL) represents a collaboration among the Center for Geographical Analysis at Harvard University, KNIME, Future Data Lab, China Data Institution, and George Mason University with co-sponsorship […]
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INNOVATIVE RESEARCH ENHANCES PM2.5 POLLUTION FORECASTING WITH TRANSFORMER MODELS
Phoebe Pan, Anusha Srirenganathan Malarvizhi, Chaowei Yang published their research on “Data Augmentation Strategies for Improved PM2.5 Forecasting Using Transformer Architectures”. This study addresses the challenge of predicting extreme air […]
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THE DISAPPEARANCE OF COVID-19 DATA DASHBOARDS: THE CASE OF EPHEMERAL DATA
Melinda Laituri, Yogya Kalra, and Chaowei Yang explored the ephemeral nature of COVID-19 data dashboards. While these dashboards were essential for tracking the pandemic, the study found that 66% of […]
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Delineating Urban Agglomeration Regions in China by Network Community Scanning: Structures and Policy Implications
Lingbo Liu and Fahui Wang published their research on “Delineating Urban Agglomeration Regions in China by Network Community Scanning: Structures and Policy Implications.” This study introduces the innovative Network Community […]
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DIGITAL TWIN IS ACCEPTED AS AN ITEM TO THE INTERNATIONAL ENCYCLOPEDIA OF GEOGRAPHY: PEOPLE, ENVIRONMENT AND POLICY
Digital Twins (DT) has been added as an entry to the International Encyclopedia of geography: People, Environment and Policy. DT is defined as a cutting-edge approach to integrating research, development, […]
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SPATIOTEMPORAL INNOVATION WEBINAR
The 2025 Spatiotemporal Innovation Webinars, offered by the Spatial Data Lab Fellows and sponsored by the Spatial Data Lab project, are free and open to the public. These webinars will […]
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ASSIP INTERN PHOEBE PAN SHINES AS A TOP 300 SCHOLAR IN PRESTIGIOUS REGENERON SCIENCE TALENT SEARCH
Congratulations to ASSIP intern Phoebe Pan! Phoebe Pan’s groundbreaking research on data augmentation strategies to improve PM2.5 forecasting using Transformer models (detailed in next news) has earned her a well-deserved […]
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A Multi-Constraint Monte Carlo Simulation Approach to Downscaling Cancer Data.
Lingbo Liu and others published their research on “A Multi-Constraint Monte Carlo Simulation Method for Downscaling U.S. Cancer Data from County to ZCTA.” This study introduces an innovative method that […]
Recent News
- Open Science 2.0: Revolutionizing Spatiotemporal Data Sharing And Collaboration
- INNOVATIVE RESEARCH ENHANCES PM2.5 POLLUTION FORECASTING WITH TRANSFORMER MODELS
- THE DISAPPEARANCE OF COVID-19 DATA DASHBOARDS: THE CASE OF EPHEMERAL DATA
- Delineating Urban Agglomeration Regions in China by Network Community Scanning: Structures and Policy Implications
- DIGITAL TWIN IS ACCEPTED AS AN ITEM TO THE INTERNATIONAL ENCYCLOPEDIA OF GEOGRAPHY: PEOPLE, ENVIRONMENT AND POLICY
- SPATIOTEMPORAL INNOVATION WEBINAR
- ASSIP INTERN PHOEBE PAN SHINES AS A TOP 300 SCHOLAR IN PRESTIGIOUS REGENERON SCIENCE TALENT SEARCH
- A Multi-Constraint Monte Carlo Simulation Approach to Downscaling Cancer Data.
- START INTERN TAYVEN STOVER WINS SECOND PLACE AT HONORS SYMPOSIUM FOR AIR QUALITY PREDICTION RESEARCH
- Digital Twin Webinar 11: Economic Impact By Climate Change