Papers for

historical data curators

Papers whose findings have a practical use for this group, as judged from the abstract. Open a paper to read what it means in practice.

Knowledge graphs capture complex contexts in cultural heritage data

Preserving contextual information in cultural heritage metadata through multidimensional knowledge graphs

Abstract: Using Knowledge Graphs (KGs) to describe Cultural Heritage Objects (CHOs) supports semantic richness and interoperability. However, standard KGs fail to capture the context-dependent validity of statements. This limitation is critical for cultural heritage metadata, which must often accommodate evolving or conflicting viewpoints, such as colonial versus post-colonial perspectives or shifting scientific consensus. While current knowledge representation methods address basic contextualization via provenance, qualifiers or reification, they lack a unified framework to simultaneously model and query data across multiple social, cultural, and political dimensions. To bridge this gap, we introduce the conceptual foundations of Multi-dimensional Knowledge Graphs (MKGs) and discuss how they preserve complex, multi-layered contexts in CHO metadata.

Mon 7 SeptDatabases

The gist

Information about cultural heritage objects often has many viewpoints and changes depending on social or political context. Traditional ways of storing this information don’t keep these changing contexts clear and easy to understand. The authors explain a new way called Multi-dimensional Knowledge Graphs that can store and connect different social, cultural, and political perspectives all at once. This helps preserve the full story behind cultural heritage objects in a more complete and organized way.

Open → 2609.07695v1