Modeling method of data logic model utilizing public conceptual sets

Abstract

The invention relates to a modeling method of a data logic model utilizing public conceptual sets. A set of symbolic languages supporting fast building of the data logic model is built. The modeling method comprises modeling elements such as relationship set and entity, basic attributes, conceptual attributes, and composite attributes, provides stronger semantic expression ability than traditional E-R (entity-relation) diagram, and can supports building of data models of various complex information systems. By using the public conceptual sets, building speed of the data models is increased, iterative development is avoided, data standardization is facilitated, visualized support systems are provided to building of logic models, the data models designed by a graphical interface can be exported into international XMI (XML metadata interexchange) format so as to be compatible with other model designing tools, building of the data models of the information systems is more convenient and faster, designing and implementation of a database mode are simplified greatly, and visualized fast building of the data models by developers during engineering is facilitated.

Description

technical field [0001] The invention belongs to the field of computer science database modeling, in particular to a data logic model modeling method using public concept sets. Background technique [0002] Data logical model modeling is an intuitive representation of the logical relationship of the database. At present, most logical models use the traditional entity-relationship model, that is, the E-R model, and there are many auxiliary tools that support E-R modeling. However, these data logic model modeling methods have limited expressive ability and are not suitable for expressing more complex logical relationships. At the same time, data logic models often have to be built from scratch, lack reusability, and often need to repeatedly build common entities, which not only hinders the improvement of model construction efficiency, but also is not conducive to the interconnection, intercommunication, and interoperability of information system data levels. Contents of the ...

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Problems solved by technology

However, these data logic model modeling methods have limited expressive ability and are not suitable for expressing more complex logical relationships.

At the same time, data logic models often have to be built from scratch, lacking reusability, and often need to repeatedly build common entities, which not only hinders the improvement of model construction efficiency, but also is not conducive to the interconnection, intercommunication, and interoperability of information system data levels.

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