Undestanding Bayesian network with OpenMarkov
First off, I did not know OpenMarkov. Anyway, from its website it has a particular focus on learning Bayesian networks (Bayes nets). Thus, I assume your figure represents a Bayes net, yes. Syntactically, it also qualifies since it is a directed acyclic graph.

The arrows (edges) represent influences (conditional dependencies) observed in the data.
For instance, the conditional probability distribution of carb, P(carb | hp,cyl,disp), is defined by the values for hp,cyl,disp. However, arrows do not necessarily represent causal relationships.