Schema matching is critical problem within many applications to integration of data/information, to achieve interoperability, and other cases caused by schematic heterogeneity. Schema matching evolved from manual way on a specific domain, leading to a new models and methods that are semi-automatic and more general, so it is able to effectively direct the user within generate a mapping among elements of two the schema or ontologies better. This paper is a summary of literature review on models and prototypes on schema matching within the last 25 years to describe the progress of and research chalenge and opportunities on a new models, methods, and/or prototypes.

Schema matching is critical problem within many applications to integration of data/information, to achieve interoperability, and other cases caused by schematic heterogeneity. Schema matching evolved from manual way on a specific domain, leading to a new models and methods that are semi-automatic and more general, so it is able to effectively direct the user within generate a mapping among elements of two the schema or ontologies better. This paper is a summary of literature review on models and prototypes on schema matching within the last 25 years to describe the progress of and research chalenge and opportunities on a new models, methods, and/or prototypes.

Schema matching is an important process in the Enterprise Information Integration (EII) which is at the level of the back end to solve the problems due to the schematic heterogeneity. This paper is a summary of preliminary result work of the model development stage as part of research on the development of models and prototype of hybrid schema matching that combines two methods, namely constraint-based and instance-based. The discussion includes a general description of the proposed models and the development of models, start from requirement analysis, data type conversion, matching mechanism, database support, constraints and instance extraction, matching and compute the similarity, preliminary result, user verification, verified result, dataset for testing, as well as the performance measurement. Based on result experiment on 36 datasets of heterogeneous RDBMS, it obtained the highest P value is 100.00% while the lowest is 71.43%; The highest R value is 100.00% while the lowest is 75.00%; and FMeasure highest value is 100.00% while the lowest is 81.48%. Unsuccessful matching on the model still happens, including use of an id attribute with data type as autoincrement; using codes that are defined in the same way but different meanings; and if encountered in common instance with the same definition but different meaning.

Schema matching is an important process in the Enterprise Information Integration (EII) which is at the level of the back end to solve the problems due to the schematic heterogeneity. This paper is a summary of preliminary result work of the model development stage as part of research on the development of models and prototype of hybrid schema matching that combines two methods, namely constraint-based and instance-based. The discussion includes a general description of the proposed models and the development of models, start from requirement analysis, data type conversion, matching mechanism, database support, constraints and instance extraction, matching and compute the similarity, preliminary result, user verification, verified result, dataset for testing, as well as the performance measurement. Based on result experiment on 36 datasets of heterogeneous RDBMS, it obtained the highest P value is 100.00% while the lowest is 71.43%; The highest R value is 100.00% while the lowest is 75.00%; and F-Measure highest value is 100.00% while the lowest is 81.48%. Unsuccessful matching on the model still happens, including use of an id attribute with data type as autoincrement; using codes that are defined in the same way but different meanings; and if encountered in common instance with the same definition but different meaning.