Currently, the main portion of knowledge is stored in electronic texts and documents and for transferring that knowledge effectively, we must use proper methods to gather and retrieve relevant information. Ontologies provide means to produce structured documents and use intelligent search instead of keyword search. Ontology defines the common words and concepts used to describe and represent an area of knowledge. However, developing ontologies is a time consuming and labor work, so many ontology developers try to facilitate and speed up this process by reusing other resources. In fact, thesaurus contains semantic information and hierarchical structure that make it an appropriate resource for ontology construction. Therefore, we determined to use the thesauri previously developed at Iranian Research Institute for Information Science and Technology (IRANDOC) to construct ontology in basic sciences domain. At first, we synchronized common concepts in thesauri before integrating them as a macro thesaurus and removed inconsistencies. To reduce the amount of time and human resources which were needed for synchronizing process, Thesaurus Synchronizer was developed to illustrate differences between matched cases of two thesauri. It provides powerful tools for demonstrating differences and suggestions for each of the existing matters. Thus, domain experts synchronized each two thesaurus semi-automatically. Then we merged thesauri and transform the data format into ISO 25964 standard. The conceptual model have been designed based on the terms and their relationships in the integrated thesaurus and the concept maps that were designed by domain experts for each of basic sciences (Chemistry, Physics, Biology, Geology and Mathematics). We used the methodology called METHONTOLOGY in this stage. The main activity in this methodology is conceptualization and it enables the construction of ontologies at the knowledge level. Ultimately, the ontology was generated by formalizing and implementing the conceptual model in OWL, a web ontology language which is recommended by the World Wide Web Consortium. The next step is to refine the relationships to more specific semantic relations. Our domain experts tried to refine some relationships manually but we decide to design an appropriate method for refining the ontology semi-automatically. Also we need to add more details to our ontology and turn it into heavyweight ontology to get more advantages from it in formal reasoning. The main aim of this project is to create a standard ontology to be used in information storage and retrieval system.