Cultural Bias in Linked Open Data

Cultural heritage collections often reflect the societal values and norms prevalent at the time when objects were created, collected, cataloged, and described. As a result, they may include outdated, stereotypical, or offensive terminology relating to people and cultures. In this presentation, we examine the presence of such contentious language within cultural heritage collections. Our analysis spans multiple layers: the cultural objects themselves, the structured and unstructured metadata used to describe and interlink them, and the controlled vocabularies, thesauri, and knowledge graphs that underpin these systems. Across all levels, we identify significant forms of bias. We will present methods for detecting these biases at scale, and discuss approaches for mitigation. In conclusion, we reflect on what the linked open data community can learn from cultural heritage institutions in confronting and addressing cultural bias in large-scale datasets.