Ontology Visualization Tools Recommender (OVTR) is built as a knowledge base for NEST expert system. On this web-page we provide additional information to the EKAW 2014 submission. First, we provide basic information about the knowledge base and then we provide links to the recommendation system and demonstrate its usage on the example from the paper.

Knowledge base

Knowledge base for Ontology Visualization Tools Recommender contains 8 attributes, 36 propositions, 32 compositional rules and 1 apriori rule. Abstracted inference network is depicted in Figure below. Relationships between attributes in Figure below indicate groups of compositional rules which are, in fact, based on their propositions. Full inference network is available below. Knowledge base has three layers. Upper layer only contains one node representing decision about suitable visualization tool: Protégé Entity Browser, TGVizTab, Ontoviz, Jambalaya, OWLViz, Ontograf, OWLGrEd, OntologyVisualizer, KC-Viz, SOVA and TopBraid. Middle layer contains two nodes which aggregate relevant answers from an user: Use case category (editing, inspection, learning and sharing) and OWL (expressing an importance of OWL features). Lower layer represents questions for an user:


Full inference network (as screenshot from NEST editor) is showed below:


Starting Ontology Visualization Tool Recommendation

Ontology Visualization Tools Recommender is available from three different user interfaces:

Demonstration of the recommender in action

The following screenshots demonstrate (using General web-based NEST user interface. Tailored web interface is more intuitive, therefore we only provide screenshots from the general web-based NEST user interface.) usage of the recommender according to the example from page 11-12 in the paper. Initial screenshot of the web-based NEST after clicking on the link provided within the section above. In order to start the recommender click on "consult" button.

Through the consultation the recommender asks as many questions as necessary in order to arrive to as precise conclusion as possible (this is not true for the tailored web user interface since all the questions are available at once). In order to demonstrate the example from the paper (p. 11-12) we will enter the same values. In general, NEST system allows us to enter weights (here within the interval <-3;3>) representing the importance of given attribute/feature: the more important, the higher positive weight. The less important, the lower negative weight. Weight zero represents indifference (default value). Let's enter the weights for the OWL features and click on "send" button:

Let's enter the weights regarding the intended usage and click on "send" button. Propositions without weights entered are interpreted as indifferent (weight zero):

Let's enter the weights regarding our favourite editor and click on "send" button:

Besides weights, the system can ask for numbers which are then automatically converted to fuzzy intervals with computed weights. Let's enter the size of given ontology and click on "send" button:

The size of an ontology was the last question of the system after which we can received recommendations:

Afterwards, you can check entered or computed weights for "all propositions" (at the bottom on the screenshot above) or you can even display all your answers (the link down on the right-hand side "change answers"). You can change any of your answer and receive new recommendations: