- RDS/WIP Introduction
- Models, Data & Meta-Data
- Paths to Interoperability
- Automated Mapping
- Thought and Language
- Coarse to Fine
- Fine to Coarse
- Template Methodologies
- Choice of System
- RDS/WIP Sample Queries
- RDS/WIP Staging Diagrams
- RDS/WIP 1.0 Plan
- RDS/WIP 1.0 Testing
- RDS/WIP 1.0 Process
- RDS/WIP 1.0 Inventory
- RDS/WIP 2.0 Plan
- RDS/WIP ID Generator
- RDS/WIP Domain Proposal
- RDS/WIP Requirements Table
- RDS/WIP Use Case: Discrete Editing
- RDS/WIP Use Case: CSV Upload
- RDS/WIP 1.0 General Use Cases
- RDS/WIP 2.0 General Use Cases
- RDS/WIP ISO 15926 Template Definitions
- RDS/WIP OWL/RDF Definition
- RDS/WIP OWL/RDF Project Plan
- RDS/WIP Forums
- RDS/WIP Use Case: Bulk Upload
POSC-Caesar FIATECH IDS-ADI Projects
Intelligent Data Sets Accelerating Deployment of ISO15926
Realizing Open Information Interoperability
RDS/WIP World View: Choice of System
The RDS/WIP is intended to be able to hold reference data for many systems, so in order to contribute to the RDS/WIP, the submitter must decide which system (or systems) to contribute to, or whether to create a new system.
1. The first step is to identify the methodology that was used (or will be used) to create your models. Find those systems that support similar methodologies. From that, strike off the systems that do not have other methodologies that you might want to use to prove your models. Also strike off models that are closed or otherwise inaccessible to the submitter.
2. Step two is to reduce the candidate models to some rough templates, and identify the classes and templates required. From the list of systems in step one, keep those systems that have the base classes that support your models, or at least ones that provide a good foundation.
3. Step three is to eliminate those systems that do not provide any additional methodologies that the submitter considers necessary to prove the models they produce, and those which do not provide a path towards specific standardization regimes otherwise necessary.
The remaining systems should be targets for the new reference data. In practice, many systems could fit the bill, and the difference between them may lie in personal or political preference, user community presence, degree of rigour and so on. Fundamentally though, it is the methodology that is most important to get right, since it is the methodology that usually leads standardization.