The Role of Schema Matching in Large Enterprises
Authors:
Preprint
Abstract
To date, the principal use case for schema matching research has been as a precursor for code generation, i.e., constructing mappings between schema elements with the end goal of data transfer. In this paper, we argue that schema matching plays valuable roles independent of mapping construction, especially as schemata grow to industrial scales. Specifically, in large enterprises human decision makers and planners are often the immediate consumer of information derived from schema matchers, instead of schema mapping tools. We list a set of real application areas illustrating this role for schema matching, and then present our experiences tackling a customer problem in one of these areas. We describe the matcher used, where the tool was effective, where it fell short, and our lessons learned about how well current schema matching technology is suited for use in large enterprises. Finally, we suggest a new agenda for schema matching research based on these experiences.Keywords
All Related Versions
This publication has 8 references indexed in Scilit:
- Semantically-Assisted Integration Query Editing in the AquaLogic Data Services Platform2008
- A Cognitive Support Framework for Ontology Mapping2007
- Integration Workbench: Integrating Schema Integration Tools2006
- Industrial-strength schema matchingACM SIGMOD Record, 2004
- An interactive clustering-based approach to integrating source query interfaces on the deep Web2004
- Learning to Match the Schemas of Data Sources: A Multistrategy ApproachMachine Learning, 2003
- COMA — A system for flexible combination of schema matching approaches2002
- A comparative analysis of methodologies for database schema integrationACM Computing Surveys, 1986