This is one of the possible Use Cases.
1. Abstract
A user wishes to obtain a single consolidated view of data that is located in a variety of possibly heterogeneous systems. This particular use case describes a real-world system which has been used to integrate data from an SQL and another non-standard database system. The system was implemented based on ontologies and queries expressed in FLogic.
2. Status
Originally proposed by Markus Krötzsch (FZI Karlsruhe), introduced as use case FZI-2 at F2F1.
Based on research and development of Software AG in cooperation with FZI Karlsruhe.
- A proprietary implementation of this use case is developed and employed by Software AG.
3. Links to Related Use Cases
to be added ...
Also feel free to add a pointer to your own use case, if appropriate. It's a wiki!
4. Relationship to OWL/RDF Compatibility
This use case does not involve OWL ontologies, since the rule language is used for modeling, combining and querying data.
5. Examples of Rule Platforms Supporting this Use Case
- Primarily, the use case is supported by the proprietary system employed by Software AG.
In general, various FLogic reasoners, such as the Ontobroker from ontoprise, can support the chosen rule language.
6. Benefits of Interchange
- Integration of data residing and described in possibly heterogeneous systems and languages.
- Re-use of existing rules tailored toward similar data integration tasks.
7. Requirements on the RIF
- Rules need to describe some mappings between ontology entities.
- Mappings are not only one-to-one and might also need to do transformations on values.
- The rule language should at the same time be the query language.
- Extensibility in the sense that users can add customized functionality (data transformations, access to new data sources).
- Access to data sources requires transport of meta data (datatype, name in external data source, …).
- There needs to be an identified set of “features” which can be implemented efficiently and allow for high-performance data access.
- For a query execution/inferencing engine on a consolidated view, it has to be possible to consider performance, i.e. the execution has to take different access characteristcs to external data sources into account (subject: query optimization).
8. Breakdown
8.1. Actors and their Goals
- Data Source Owners: own (maintain, use) some data sources
- Data Source Applications: applications consuming data of a dedicated set of data sources
- New Applications: consuming data independent of the concrete data source (data access transparency)
8.2. Main Sequence
- create description of data in a data source independent format (ontological specification),
- create consolidated view, i.e. create rules that describe relations (mappings),
- applications accessing data via consolidated view.
9. Narratives
Within a company, a support information system maintains data about customers, including their contact information, and active or closed support requests. A separate customer information system contains information about customers, contracts etc. The systems are heterogeneous with respect to data model and access capabilities, and employ different data base systems. A consolidated data view is exposed in a browser based application to various parties inside the company.
Within further integration steps other systems can be integrated. Integration is a step within the development of a companie’s SOA. Therefore, the integration of web services (not only databases) which expose some data has to be considered.
This use case can be realized using F-logic or WRL (WebRuleLanguage).