1. Copyright: SIPC Reference Data Architecture and Standards Ontologies and Databases: Use of ontology in database design Matthew West Shell

2. Reference Data Architecture and Standards 2 Sharing Data Human Other Parts of your Business Government Customers Suppliers Sales Finance Materials Resources Your Business

3. Reference Data Architecture and Standards 3 Life-Cycle Supply Chain Management & Control Different Dimensions to Integration

4. Reference Data Architecture and Standards 4 How important is shared data? Is the need to integrate the different parts of the business and their data vital to success? Is it important that a consistent message is given to external organizations? Are there problems reconciling data from different parts of the business? Are you dissatisfied with the time scale and cost of enhancing existing systems? Are you dissatisfied with the cost of obtaining data from existing systems for use elsewhere?

5. Reference Data Architecture and Standards 5 Financial and time penalties Translating data is expensive. – Interfaces can account for 25-70% of system costs. The need to translate data means that users can only share data sequentially, not concurrently. – Impact on key business processes. Slower response to the need for change in systems. – Interfaces cost time as well as money. Quality suffers. – Interfacing may give rise to errors, and to inferior business decisions. Time is wasted trying to locate and reconcile data.

6. Reference Data Architecture and Standards 6 Enterprise Information Architecture Operational & Transaction Data Summary Information Description Documents & Data Reference Data Products Processes Assets Organisation Location Property

7. Reference Data Architecture and Standards 7 Information Systems Architecture Operational Systems Decision Support Systems Management Information Systems Reference Data & Description Documents ProductsProcessesAssetsOrganisationLocationProperty

8. Reference Data Architecture and Standards 8 The Ladder of Control The Enterprise Activities on observe KPI's measure and summarise EnvironmentEnvironment Targets compare

9. Reference Data Architecture and Standards 9 Why do we need Data Models? A Data Model is a Language for Data You can only share information based on a common language. Each separate data model is it's own language (or rather a limited jargon). Creating a Standard Data Model gives the basis for sharing data within and between organizations and systems.

10. Reference Data Architecture and Standards 10 High Cost of Systems Repeated Development of same System Minor Changes Major Rework Component Redevelopment System Interfaces Inflexible Data Models Potential reuse not identified Insufficient Data Modelling Standards "Same" Data Model Redeveloped Same thing modelled differently Issues for data modelling

11. Reference Data Architecture and Standards 11 Data model wish list Conceptual data models should: – meet the data requirement – be stable in the face of changing data requirements – be flexible in the face of changing business practices – be re-useable by others – be consistent with other models covering the same scope – be able to reconcile conflicting data models – be clear and unambiguous to all (not just the authors) You should be able to develop data models that meet these requirements quickly, and at low cost