An intermediate representation-based approach for query translation using a syntax-directed method

We aspire to make one query reasonably sufficient to extract data regardless of the data model used in our research. In such a way, users can freely use any query language they master to interrogate the heterogeneous database, not necessarily the query language associated with the model. Thus, overcoming the needing to deal with multiple query languages, which is, usually, an unwelcome matter for non-expert users and even for the expert ones. To do so, we proposed a new translation approach, relying on an intermediate query language to convert the user query into a suitable query language, according to the nature of data interrogated. Which is more beneficial rather than repeat the whole process for each new query submission. On the other hand, this empowers the system to be modular and divided into multiple, more flexible, and less complicated components. Therefore, it increases possibilities to make independent transformations and to switch between several query languages efficiently. By using our system, querying each data model with the corresponding query language is no longer bothersome. As a start, we are covering the eXtensible Markup Language (XML) and relational data models, whether native or hybrid. Users can retrieve data sources over these models using just one query, expressed with either the XML Path Language (XPath) or the Structured Query Language (SQL). © 2020, Science and Information Organization.