A broad view of the nature and potential of computational information geometry in statistics is offered.   This new area suitably extends the manifold-based approach of classical information geometry to a simplicial setting, in order to obtain an operational universal model space.   Additional underlying theory and illustrative real examples are presented.  In the infinite-dimensional case, challenges inherent in this ambitious overall agenda are highlighted and promising new methodologies indicated.