Semantic Seeds: Maintainable Configuration Dataload using Ontologies
Stu Baurmann
Lead Instructor
LogicU
Business applications have long used RDBMs to store configuration data alongside user transactions. Such configurations are increasingly complex, and their proper seeding during testing and production presents a significant challenge that often falls, unrecognized, into the gap between Data Management and Software Development organizations. Part of the solution lies in using more efficiently maintainable artifacts to control the dataload process. Hand-edited SQL scripts are sufficient for some seeding tasks, but when schemas grow in complexity to encompass rich typing systems, a more expressive paradigm is required to bridge the gap from the RDBMS view to the application layer, which is usually driven by a set of nested classifications (e.g. object-oriented inheritance).
Our experience shows that ontologies form an appropriate substrate for building such dataload solutions. In this advanced talk, we discuss the adaptation of object-relational systems to accept frame-based configurations for a spectrum of deployment scenarios. We draw upon examples in the financial and legal domains. Topics include:
- How configuration data impacts system quality
- Making dataload repeatable and maintainable
- The role of metadata in system configuration
- Relating ontologies to UML/ERD models
- Mapping from RDF/OWL to SQL
- Making frame mappings simple and flexible
- Exploiting web services for configuration
Key Takeaways
* Semantic artifacts have the potential for high, durable, enterprise-wide value (compared with code).
* Ontology based dataload enables deeper participation by the business in crucial "Middle Workflow" decision making.
* Flexibility of RDF as a platform permits customized approaches to metadata administration (e.g. federation, dynamic merging)
* Open-source and commercial GUI/server tool platforms are both viable alternatives
* Clean, articulate, repeatable dataload leads directly to higher application quality
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