Modeling Data Complexity in Public History and Cultural Heritage

Abstract

The publication by Galleries, Libraries, Archives and Museums of metadataabout their collections is fundamental for the creation of our shared digital culturalheritage. Yet, we argue, these digital collections are, on one hand, of little use toscholars (because of the inconsistent quality of the published records), and, on theother hand, they fail to attract the interest of the general public (because of their drycontent). These problems are exacerbated by the current move towards public history,where citizens are no longer just passive actors, but play an active role in contribut-ing, maintaining and curating historical records, leading some to question the trust-worthiness of collections in which non-scholars have the ability to contribute. Thecore issue behind all these problems is, we believe, a (doomed) search for objectivity,often caused by the fact that data models ignore the derivative and stratified nature ofcultural objects, and allow only one point of view to be expressed. In turn this forcesthe publication of bowdlerized records and removes any venue for the expression ofdisagreement and different opinions. We propose an approach named“contexts”tosolve these issues. The adoption of contexts makes it possible to support multiplepoints of view inside the same dataset, not only allowing multiple scholars to providetheir own possibly contrasting points of view, but also making it possible to incorpo-rate additions, corrections and more complex kinds of commentaries from citizenswithout compromising the trustworthiness of the whole dataset.