EA as a discipline encompasses a wide range of issues, most of them often handled through dedicated tools. Whatever the effectiveness of these tools their harnessing to EA objectives is bound to remain a nonstarter without a principled framework that could enable a reliable and sustainable interoperability.
With regard to engineering such a venture requires sound and stable interfaces with enterprises’ business and engineering resources. With regard to governance it requires dedicated access to consistent and actionable symbolic representations of these resources.
Using ontological prisms, EA user interfaces can be organised into seven basic use cases:
- Requirements (actual facts)
- Data analytics (virtual facts)
- Business analysis (facts/concepts)
- Business intelligence (concepts)
- Strategic planning (concepts/categories)
- Systems engineering (categories)
- Systems modeling (facts/categories)
Like with engineering interfaces, accesses across use cases are obtained through thesauruses (facts/concepts), taxonomies (facts/categories), and ontologies index (concepts/categories).