Research programs involving genetic, genomic and epigenetic of have become fast growing areas of biology. Once the computational challenges of analyzing datasets have been dealt with; large and complex biological data still remain in the hands of biologists for interpretation. Projects such as Biomart and Intermine have been developed to facilitate exchange and comparison of complex biological data; however access and interrogation can be time consuming for biologists and integrate all publicly available data still remains a challenge. Moreover for non-model organisms; large heterogeneous biological datasets can be difficult to associate in order to obtain a comprehensive view. The notion of “linked data” from semantic technologies benefits to biologists. Using RDF (Reference Description Framework); biological data can be stored in triples (subject, predicate, object) that define a relationship between two entities. Thanks to the SPARQL query language, RDF data can be queried to join different datasets. Nevertheless, understanding and acquiring the query language can be a daunting task for biologists. Here we present AskOmics, a tool supporting both intuitive data integration and querying while shielding the user from most of the technical difficulties underlying RDF and SPARQL. For data integration, the user loads his data as tabulation-separated files structured according to simple principles. This structure allows AskOmics to generate automatically RDF triples, and to store them. Finally, for data querying, AskOmics provides a visually intuitive interface. AskOmics has been applied successfully to the analysis of large scale datasets including lncRNA, miRNA, piRNA and transcriptomic profiles of the aphid embryogenesis.