A Bidirectional Collaboration Framework for Bio-Model Development

Abstract

High-level graph data structures have gained favour in representing biological
knowledge in a computationally executable form, but the information contained
therein must remain accessible to all users no matter their background. Bidirectional
graph transformations may be used to synchronise and maintain the consistency
of these graph data structures as they evolve through the process of creating
and refining a bio-model knowledge base. We outline a bidirectional collaboration
framework by which users with vastly differing backgrounds may contribute to the
development and evolution of such a knowledge base, and examine a simple example to illustrate its merits. We also identify avenues for further research necessary to refine the framework. No prior biological knowledge is assumed.