Concepts and collections: A case study using objects from the brooklyn museum

Abstract

In this paper, we present a browsing framework for digitised cultural collections. Using a data analysis technique called Formal Concept Analysis (FCA), units of thought can be constructed from a series of objects and their tags. FCA can dynamically generate links in between objects and induce a serendipitous browsing experience using a relatively simple data structure. We evaluate the utility and scalability of our approach to a collection of 15,000 objects from the Brooklyn Museum's collections. We describe how we use natural language processing techniques and external lexical resources to synthesise key terms from museum documentation. We then combine this term extraction process with FCA to effectively demonstrate links between and within collections of objects. In doing so we present a versatile, generalizable term extraction and browsing framework suitable for digital libraries and archives within the art and architecture domain.