To deal with issues of apparel facility list data quality and scale quickly and efficiently we need a machine learning tool that can capture the knowledge of domain experts, find commonalities in jumbled text, and confidently compare large lists without the need to compare each individual entry.
Since its launch on March 28, the Open Apparel Registry (OAR) has grown to include over 18,300 facilities in 92 countries. We’ve already heard of a few fascinating use cases where data from the OAR contributed to decision making by brands and facilities.
Raster Foundry and GeoTrellis now support WMS and WCS standards, enabling streamlined workflows that utilize multiple data sources.
Scoring Philadelphia City Council districts on assets and risks using a weighted spatial analysis model in R and Python.
Learn to create a series of data-driven infographics in the context of a project that evaluates bus performance in each Philadelphia City Council District.
A guide to transforming open geospatial data into slippy map tiles to display in Leaflet or OpenLayers using PostGIS, QGIS, and QTiles.
Use this open source data processing pipeline to convert geodatabase files to vector tiles for use in a web application.
This Azavea 10% Time project defines a process for converting big data files to vector tiles and allows a user to identify habitat areas in need of protection.