The hippocampus is a brain area involved in many memory processes. This structure can also be affected in neurological diseases such as mesial temporal lobe epilepsy. A better understanding of its electrophysiological activity could benefit both the neuroscientific and clinical communities. We proposed, in a previous paper, a detailed bio-realistic conductance-based mathematical model of more than thirty thousand neurons to reproduce the main oscillatory features of the healthy hippocampus during slow-wave sleep and wakefulness, from slow to very fast frequencies. One big challenge of this model is its parametrization. The aim of the present work is to combine neuroscientific expertise and systematic yet efficient exploration of the highly dimensional parameter space using well defined identification methods, namely the design of experiments and the Sobol's sensitivity analysis.