  One of the main challenges of modern cosmology is to investigate the nature
of dark energy in our Universe. The properties of such a component are normally
summarised as a perfect fluid with a (potentially) time-dependent
equation-of-state parameter $w(z)$. We investigate the evolution of this
parameter with redshift by performing a Bayesian analysis of current
cosmological observations. We model the temporal evolution as piecewise linear
in redshift between `nodes', whose $w$-values and redshifts are allowed to
vary. The optimal number of nodes is chosen by the Bayesian evidence. In this
way, we can both determine the complexity supported by current data and locate
any features present in $w(z)$. We compare this node-based reconstruction with
some previously well-studied parameterisations: the Chevallier-Polarski-Linder
(CPL), the Jassal-Bagla-Padmanabhan (JBP) and the Felice-Nesseris-Tsujikawa
(FNT). By comparing the Bayesian evidence for all of these models we find an
indication towards possible time-dependence in the dark energy
equation-of-state. It is also worth noting that the CPL and JBP models are
strongly disfavoured, whilst the FNT is just significantly disfavoured, when
compared to a simple cosmological constant $w=-1$. We find that our node-based
reconstruction model is slightly disfavoured with respect to the $\Lambda$CDM
model.
