The　vision　of　the　Semantic　Web　is　to　build　a　global　Web　of　machine-readable　data　to　be　consumed　by　intelligent　applications.　As　the　first　step　to　make　this　vision　come　true,　the　initiative　of　linked　open　data　has　fostered　many　novel　applications　aimed　at　improving　data　accessibility　in　the　public　Web.　Comparably,　the　enterprise　environment　is　so　different　from　the　public　Web　that　most　potentially　usable　business　information　originates　in　an　unstructured　form　(typically　in　free　text),　which　poses　a　challenge　for　the　adoption　of　semantic　technologies　in　the　enterprise　environment.　Considering　that　the　business　information　in　a　company　is　highly　specific　and　centred　around　a　set　of　commonly　used　concepts,　this　paper　describes　a　pilot　study　to　migrate　the　concept　of　linked　data　into　the　development　of　a　domain-specific　application,　i.e.　the　vehicle　repair　support　system.　The　set　of　commonly　used　concepts,　including　the　part　name　of　a　car　and　the　phenomenon　term　on　the　car　repairing,　are　employed　to　build　the　linkage　between　data　and　documents　distributed　among　different　sources,　leading　to　the　fusion　of　documents　and　data　across　source　boundaries.　Then,　we　describe　the　approaches　of　semantic　information　retrieval　to　consume　these　linkages　for　value　creation　for　companies.　The　experiments　on　two　real-world　data　sets　show　that　the　proposed　approaches　outperform　the　best　baseline　6.3-10.8%　and　6.4-11.1%　in　terms　of　top　five　and　top　10　precisions,　respectively.　We　believe　that　our　pilot　study　can　serve　as　an　important　reference　for　the　development　of　similar　semantic　applications　in　an　enterprise　environment.