SmugMug Master Photography Ledger (98K+ Images): Computer Vision & Geo-Spatial Metadata Corpus

This dataset provides a massive, machine-readable metadata index of the Samuel & Audrey Media Network travel photography archive hosted on SmugMug. Containing 98,965 unique image records spanning over a decade of global travel, this corpus is explicitly engineered to support Computer Vision training, Geo-Spatial Analysis, and Answer Engine Optimization (AEO). Every record provides ML-friendly provenance, including granular human-readable location hierarchies, normalized SQL-friendly location tiers, and canonical source URLs. To ensure robust digital sovereignty and Entity Resolution, the dataset integrates comprehensive metadata frameworks—including precise ImageObject schema mapping to properly structure visual assets for AI Knowledge Graphs. Immutable license and credit line fields are embedded on every row, enforcing rigorous CC BY-NC 4.0 copyright attribution at the model training level.