An Exploratory Study of Database Integration Processes

Abstract

One of the central problems of database integration is schema matching, that is, the identification of similar data elements in two or more databases or other data sources. Existing definitions of "similarity" in this context vary greatly. As a result, schema matching has given rise to a large number of heuristics software tools. However, the empirical understanding of this process in humans is very limited so that little guidance can be offered to the further development of heuristics and tools. This paper presents an exploratory process tracing study of the similarity judgement process in humans. The similarity judgements of 12 data integration professionals on a range of integration problems are recorded and analyzed. Implications for future empirical and applied research in this area are discussed.Index Terms-Human factors, human information processing, database integration, database design, modeling and management, relational database.

Smarter Cities: Cleaning Electricity, Gas and Water Metered Consumption Data for Social and Urban Research

“…Duplicated data. An important aspect of joining datasets is the identification of duplicate records that have occurred during merging [29]. A general approach to Talent, M. Smarter Cities: Cleaning Electricity, Gas and ... Year 2019 Volume 7, Issue 3, pp 466-481 identifying duplicate records is to cluster similar items together and then compare items in each cluster [24].…”

Survey: Models and Prototypes of Schema Matching

“…Refers to [18], [30], [31], the study [4] was to integrate heterogeneous database based on semantic ontology, and tested on academic database that is defined using MS Access and MySQL. Discovery a model for connecting between data sources on the web by [32], [33] is also a research area in which development of a semantic approach to the relationship between entities is required and is valid for widespread availability of ontology.…”

“…Usage constraint in the on schema matching assumes that constraint has a meaning to set a similarity database element, for example, attribute AT1 in table X is defined as a character was same as attribute AT2 in the table Y which is defined as a text [31]. According to [19], the use of constraint-based is part of model group on schema matching which is included in level structure, but not described in more about what properties which explored and included as constraint.…”

Building a Customer Inquiry Database System

“…We have come up with meaningful data for each table. We made sure data integrity (Evermann, 2008) is maintained while preparing data set for each table. In the forms development we made sure that the forms are intuitive, friendly and users can see a row including the one being inserted real-time.…”