  Ontological knowledge modelling of epics, though being an established
research arena backed by concrete multilingual and multicultural works, still
suffer from two key shortcomings. Firstly, all epic ontological models
developed till date have been designed following ad-hoc methodologies, most
often, combining existing general purpose ontology development methodologies.
Secondly, none of the ad-hoc methodologies consider the potential reuse of
existing epic ontological models for enrichment, if available. The paper
presents, as a unified solution to the above shortcomings, the design and
development of GENOME - the first dedicated methodology for iterative
ontological modelling of epics, potentially extensible to works in different
research arenas of digital humanities in general. GENOME is grounded in
transdisciplinary foundations of canonical norms for epics, knowledge modelling
best practices, application satisfiability norms and cognitive generative
questions. It is also the first methodology (in epic modelling but also in
general) to be flexible enough to integrate, in practice, the options of
knowledge modelling via reuse or from scratch. The feasibility of GENOME is
validated via a first brief implementation of ontological modelling of the
Indian epic - Mahabharata by reusing an existing ontology. The preliminary
results are promising, with the GENOME-produced model being both ontologically
thorough and performance-wise competent
