Structural　Engineering　Cloud　Platform　(SECP)　is　a　resource　sharing　platform　oriented　to　structural　engineering　domain,　and　the　share　of　structural　engineering　experimental　data　is　one　of　its　main　functions.　In　SECP,　there　are　two　kinds　of　experimental　data,　which　are　Experimental　Description　Data　(EDD)　and　Experimental　Result　Data　(ERD).　The　model　of　EDD　was　built　based　on　OWL　ontology　for　shielding　the　heterogeneity　of　experimental　data　from　different　experimental　sites.　With　the　increasing　of　data　scale,　the　query　of　EDD　has　been　a　bottleneck　of　the　whole　management　system　in　SECP.　Based　on　MapReduce,　this　paper　designed　and　implemented　a　EDD　query　system　(EDDQS).　EDDQS　supports　query　based　on　SPARQL　and　there　are　four　core　modules　named　Data　Splitter,　Query　Generator,　Job　Generator　as　well　as　Job　Executor.　Furthermore,　the　algorithm　of　job　generation　from　SPARQL　query　and　job　execution　algorithms　are　presented.　Finally,　the　results　of　our　experiments　reveal　that　our　MapReduce　based　query　system　can　handle　large　amount　of　EDD　efficiently.　©　2010　IEEE.