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Generally, the interoperability is the key feature to any widely used application or an information system. A system build on the basis of semantic data interpretation can also lead to an easy extensible and adaptable system, in the future. Otherwise, you have to deal with a lack of agreed terminologies or codes between standards e.g. DASTA vs. HL7, different coding structures and even variety of file formats or inconsistent database table schema. The most of these difficulties can be solved by the semantically interoperable system. We present our implementation strategy and meta data extraction methods for a research information system with an heterogeneous medical data. The medical data can have different origin, type, file format and even its version. We discuss the research information system that we primarily use for cerebrovascular brain diseases research.