Cultural mapping for digital data interrogation

The abundance of openly accessible datasets, including institutional Open Government Data (OGD) and crowdsourced OpenStreetMap (OSM), presents opportunities and challenges for cultural planning. Recognizing that data are not neutral representations but are shaped by the institutional, social, and political dimensions that produce them, our study presents a methodologically innovative approach to address how and whether community perceptions align with or differ from digital data representations. Using a critical GIS perspective, we conducted a proof-of-concept study leveraging cultural mapping as our method and Kevin Lynch’s concept of imageability as our theoretical lens to develop a systematic multilevel analytical approach to compare digital datasets with community perceptions. At the macro level, we compared spatial patterns from individuals’ cultural maps with digital representations. At the community level, we identified the most salient cultural assets for community members. At the individual level, we identified factors that are often overlooked in digital datasets, including accessibility, meaning, perceptions, and everyday practices. Our findings revealed perceived spatial discrepancies and a lack of conceptual consensus on what constitutes culture between institutional data and community-sourced data. This approach provides opportunities to evaluate planning outcomes and develop community-centered cultural datasets, which can advance just, data-driven cultural planning.