DERA: From Document Centric to Entity Centric Knowledge Modelling

S.R. Ranganathan, is credited with developing the analytico-synthetic faceted classification. He proposed five ‘fundamental categories’ which were deemed as necessary and sufficient to characterise all documents in a library. However, in the context of the web and digital resources we find that resources are no longer limited to mere academic disciplines, which must be extended to consider plethora of domains in real world. While domains provide the context, it is the entities in the domains that need unambiguous representation. Hence, we advocate an entity- centric approach, where examples of entities are people, locations, mind products and organisations. Entities are either abstract or concrete. Within each domain, entities are described with a set of properties. There should be a logical progression of representation techniques to transit from books in the library to entities on the web. As there is a transition from subject to domain, we need to come up with ‘fundamental categories’ that will be necessary and sufficient to characterise web resources. The collaborative research work between the University of Trento and DRTC - Indian Statistical Institute resulted in a new faceted knowledge representation model, DERA -- [Domain, Entity, Relations, Attributes], achieved through a faceted entity-centric approach. DERA makes use of the principled approach of Ranganathan's analytico-synthetic classification to help build and reuse knowledge. A key advantage of DERA is that it is amenable to logical formalisation. This paper aims at showcasing the mapping of Ranganathan’s fundamental categories (BS)[P][M][E][S][T] to the faceted entity-centric model - DERA.