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As an effort to promote replicable technology for spatial data analysis, the Spatial Data Lab concluded a highly productive Spatiotemporal Innovation Workshop in early 2024, which provided an extensive introduction to the KNIME Analytics Platform as well as its applications. This online event, held from January 15 to January 18 with a concluding lab/group report on January 22, 2024, brought together 27 participants and 5 instructors from various academic and professional backgrounds.
Throughout the four-day workshop, participants received detailed training on KNIME technology, including Geospatial Extension, WebPortal, GeoAI, and case studies on business and economy, environment, health, social media and remote sensing data applications. Participants were divided into five groups for practice projects, with each group receiving dedicated technical support. The final presentations of the group projects were particularly notable for the exceptional work produced by the groups, which not only demonstrated the effective technology for training but also helped establish collaborations on future research.
Workshop Agenda:
January 15 (Day One): Introduction to KNIME Analytics Platform
(1) KNIME Analytics Platform Basics; (2) Geospatial Analytics Extension for KNIME
January 16 (Day Two): KNIME Web Portal and GeoAI
(1) Deploying Workflows on KNIME Server; (2) Artificial Intelligence Analysis for Spatiotemporal Data
January 17 (Day Three): KNIME GeoImage and Social Media
(1) KNIME GeoImage and Remote Sensing Application; (2) Spatiotemporal Analysis with Social Media Data
January 18 (Day Four): KNIME GeoBI, Public Health and Data App
(1) Business Intelligence Analysis with Spatiotemporal Data; (2) Spatiotemporal Analysis in Healthcare Accessibility; (3) KNIME Data App and Geocoding Data App Application; (4) Conclusion and Discussion
January 22 (Day Five): Group Project Presentations
Group1: The distance of cross country healthcare accessibility between international countries, evidence from spatial spillover effect on different causes
Group2: Analyzing Households' Inequality in Spatial Accessibility To Water Point Source in Sibi, Ghana
Group3: Urban Inequality Index (UII) Evaluation and Visualization
Group4: Detection of heat waves and calculation of heat index using meteorological data
Group5: Entrepreneurship in the remote work age
For further information on the workshop and future events, please visit https://projects.iq.harvard.edu/chinadatalab/seminars or contact Spatialdatalab@lists.fas.harvard.edu.