Object identification is a crucial step in most information systems. Nowadays, we have many different ways to identify entities such as surrogates, keys and object identifiers. However, not all of them guarantee the entity identity. Many works have been introduced in the literature for discovering meaningful keys, but all of them work at the logical or data level and they share some inherent constraints. Addressing it at the logical level, we may miss some important data dependencies, while the cost to identify data dependencies at the data level may not be affordable. In this paper we propose an approach for discovering meaningful keys from domain ontologies. In our approach, we guide the process at the conceptual level and we introduce a set of pruning rules for improving the performance by reducing the number of key hypotheses generated and to be verified with data. Finally, we also introduce a simulation over a real world case study to show the feasibility of our method.
CitationRomero, O., Abelló, A., Montesó, J. "Discovering meaningful keys from ontologies". 2009.
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