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<p>This paper presents a visual query language called VQL for interacting with an object-oriented schema-intensive data model. VQL allows convenient access to the various types of knowledge captured by the semantic model. It consists of a set of "graphical primitives" along with a combination grammar for creating graphical queries. The visual language is internally supported by a prolog-like predicate based query language. The formal grammar underlying the predicate based language is also presented. Apart from being able to create simple queries that can be specified in SQL or QBE, VQL can be used for making queries on any object-oriented data model including the generalization of the E-R model. VQL also handles complicated, indirect queries, specially those that require a reasoning system for query interpretation and response generation. Further, recursive queries on graph structures such as finding transitive closures of graphs may be easily specified. Perhaps the most powerful feature of VQL is its ability to provide high semantic expressibility (in being able to specify highly complex queries) while maintaining simplicity in the user's query formulation process. VQL is embedded in an object-oriented graphical database interaction environment that supports schema creation and manipulation in addition to database querying and updation. The prototype has been implemented in Smalltalk-80 running on a Sun 3/60 workstation. All the illustrations of visual interaction presented are taken from actual interaction sessions.</p>
graphical interaction; visual query language; schema-intensive databases; VQL; object-oriented schema-intensive data model; semantic model; graphical primitives; graphical queries; prolog-like predicate based query language; formal grammar; recursive queries; graph structures; Smalltalk-80; Sun 3/60 workstation; object-oriented databases; query languages; visual databases; visual languages

L. Mohan and R. Kashyap, "A Visual Query Language for Graphical Interaction with Schema-Intensive Databases," in IEEE Transactions on Knowledge & Data Engineering, vol. 5, no. , pp. 843-858, 1993.
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