Supporting Complexity and Conjectures in Cultural Heritage Descriptions

Data and metadata once hidden in dusty card cabinets of thousands of galleries, libraries, archives and museums worldwide are now available online in digital formats. An incredible explosion of metadata has been expanding in the quantity of digitized data, the richness and sophistication of data models, the number of institutions and private citizens that contribute and their interconnection. A fundamental issue, however, limits this undeniable success: current data models force the expression of a single point of view. For example, the field author is either set to a value or to another one. Any disagreement about the content of a field is resolved before the publication of the data and forever lost. Yet, we argue, the expression of different and contrasting points of views is a keystone of scholarship, as well as one of the most engaging aspects for everyone. Bowdlerized, sterile, conflict-free data records fails to capture the core of important scholarly debates and thus fails to attract the interest of the general public. The root cause of this issue is technical rather than cultural: current standards for data models (e.g. RDF, OWL) do not simply support the expression of contrasting statements. In this paper we propose both a methodological approach to address this problem, and a proof of concept of how this problem could be fully and cleanly overcome with modest extensions to the existing standards. We name this approach “contexts and conjectures”.