DBPe­dia already is saved in a machine read­able for­mat (RDF). We’ve started a proof-of-concept to show that GraphDB is able to solve these require­ments too and to find out dif­fer­ences, advan­tages and dis­ad­van­tages of the dif­fer­ent con­cepts.
In RDF, the data model stands next to the data. Within sones GraphDB there is close con­nec­tion between each object (node) and it’s (Ver­tex) type. For exam­ple the node “Homer Simp­son” knows that he’s a “Fic­tion­alChar­ac­ter”.
Our expec­ta­tion was, that GraphDB requires less hard-disk space and also offers a bet­ter data store, since all infor­ma­tion about an object is saved in a unique node instead of  sev­eral triple-data-files. Besides, any rela­tion­ship between two objects (e.g. a per­son and its birth-place) is saved directly on that object. While load­ing a node, all infor­ma­tion is avail­able from a sin­gle loca­tion.
Dur­ing project run­time we’ve dis­cov­ered sev­eral prob­lems that can be solved with that idea. The aris­ing data net­work enables cus­tomers to find out com­plex rela­tion­ships between any node using graph-algorithms. Dis­am­bigua­tion of words is pos­si­ble, using the schema infor­ma­tion (e.g. Tuareg can be either nomads liv­ing in the Sahara or a vehi­cle built by a Ger­man car vendor).