A method of identifying possible errors/inconsistencies within an electronic map representation of a network of navigable elements within a geographic area, the method comprising: obtaining at a server positional data relating to the movement over time of a plurality of devices travelling around the navigable network; processing the obtained positional data at the server with reference to a current version of the electronic map representing the navigable network in order to identify potential inconsistencies in the map in the form of one or more locations within the navigable network where an observed behaviour of devices in the vicinity of, or at, an intersection or other decision point within the navigable network as indicated by the obtained positional data is not consistent with a behaviour that would be expected based on manoeuvres that a user can perform at the intersection or decision point according to the current version of the electronic map, wherein the processing of the obtained positional data uses a classification algorithm wherein the classification algorithm was trained using historic positional data obtained for the navigable network as input in combination with the current or an earlier version of the electronic map, the training of the classification algorithm accounting for a relative incentive for a user to perform a certain manoeuvre such that the classification algorithm when identifying potential inconsistencies in the map takes into account the relative incentive to perform a particular manoeuvre and weights this accordingly such that if there is relatively lower incentive to perform a particular manoeuvre relatively more data is to be obtained before identifying that this manoeuvre is prohibited. obtaining at a server positional data relating to the movement over time of a plurality of devices travelling around the navigable network; processing the obtained positional data at the server with reference to a current version of the electronic map representing the navigable network in order to identify potential inconsistencies in the map in the form of one or more locations within the navigable network where an observed behaviour of devices in the vicinity of, or at, an intersection or other decision point within the navigable network as indicated by the obtained positional data is not consistent with a behaviour that would be expected based on manoeuvres that a user can perform at the intersection or decision point according to the current version of the electronic map, wherein the processing of the obtained positional data uses a classification algorithm wherein the classification algorithm was trained using historic positional data obtained for the navigable network as input in combination with the current or an earlier version of the electronic map, the training of the classification algorithm accounting for a relative incentive for a user to perform a certain manoeuvre such that the classification algorithm when identifying potential inconsistencies in the map takes into account the relative incentive to perform a particular manoeuvre and weights this accordingly such that if there is relatively lower incentive to perform a particular manoeuvre relatively more data is to be obtained before identifying that this manoeuvre is prohibited. <EOS>