Generating database schemas for relational and markup language data from a conceptual model

An information processing system for generating a plurality of candidate database schemas including relational and mark-up language elements, the information processing system comprising:

• a memory;
• a processor communicatively coupled to the memory;
• and
• a database schema generator communicatively coupled to the memory and the processor, wherein the database schema generator is adapted to:
• receiving an information model comprising a plurality of entities and at least one relationship defined there between, wherein the information model has been annotated with at least one semantic characteristic, operational characteristic, and evolutional characteristic;
• analyzing the information model that has been annotated;
• associating a score, in response to the analyzing, with each entity based at least in part on attributes associated with each entity;
• classifying, in response to associating a score, each entity as one of a relational element and a mark-up language element;
• partitioning, in response to the classifying, the information model that has been annotated into a plurality of relational element mappings and a plurality of mark-up language element mappings;
• and
• generating, in response to the partitioning, a plurality of database schemas associated with the information model that has been annotated.

A computer readable medium for generating a plurality of candidate database schemas including relational and mark-up language elements, the computer readable medium comprising instructions for:

• receiving an information model comprising a plurality of entities and at least one relationship defined there between, wherein the information model has been annotated with at least one semantic characteristic, operational characteristic, and evolutional characteristic;
• analyzing the information model that has been annotated;
• associating a score, in response to the analyzing, with each entity based at least in part on attributes associated with each entity;
• classifying, in response to associating a score, each entity as one of a relational element and a mark-up language element;
• partitioning, in response to the classifying, the information model that has been annotated into a plurality of relational element mappings and a plurality of mark-up language element mappings;
• and
• generating, in response to the partitioning, a plurality of database schemas associated with the information model that has been annotated.