Survey: Models and Prototypes of Schema Matching

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

Analyzing Mappings and Properties in Data Warehouse Integration

The information inside the Data Warehouse (DW) is used to take strategic decisions inside the organization that is why data quality plays a crucial role in guaranteeing the correctness of the decisions. Data quality also becomes a major issue when integrating information from two or more heterogeneous DWs. In the present paper, we perform extensive analysis of a mapping-based DW integration methodology and of its properties. In particular, we will prove that the proposed methodology guarantees coherency, meanwhile in certain cases it is able to maintain soundness and consistency. Moreover, intra-schema homogeneity is discussed and analysed as a necessary condition for summarizability and for optimization by materializing views of dependent queries