This Project is built for the open data connector and case studies based on KNIME Geospatial Extension. KNIME AG and Harvard’s Center for Geographic Analysis have launched a joint project to advance spatial data science. The project is part of the Spatiotemporal Thinking, Computing, and Applications (STC) Center which is funded by the NSF to enable pre-competitive research in partnerships among industry, academia, and government. The two-year project “Developing Workbenches for Spatial Data Science (HVD-21-07)” will explore methodologies to advance spatial data science research and teaching. To open up spatial analytics to a more diverse group of users, the partners will develop freely accessible KNIME Analytics Platform extensions for spatial statistics, modeling, and visualization. KNIME’s visual, no-code/low-code environment will enable multi-discipline users to more easily and efficiently collaborate, explore data, and surface insights. Further resources in the form of workbooks, workflow-based case studies, and best-practice workflows will be developed to help users get started with replicable and reproducible spatial data science across scientific disciplines.
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KNIME US Census Data Connector
Oct 12, 2022
Liu,Lingbo, 2022, "KNIME US Census Data Connector", https://doi.org/10.7910/DVN/LILUPH, Harvard Dataverse, V1
This workflow provides the prototype components of open dataset tools in KNIME Python-based Geospatial Extension, Users can acquire the data by easily defining the variable and geographic level. It contains 4 nodes: US2020 TIGER for US Basemap( Census Block, Block Group, Tract, and County), US2020 Census for Decennial Census P.L. 94-171 Redistricti...
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