Master Enterprise Architecture Meta-Model: 2. Appl Layer

Bridge the Gap Between Abstract Frameworks and Data-Driven Architecture

The Business Layer defined the "What" and "Who." Now, we tackle the "How." In many organizations, the Application Layer is a chaotic "black box" of legacy monoliths and fragmented microservices. To manage this complexity, you need more than just a list of names—you need a structured ontology.

This second installment of our 5-part series dives deep into the Application Layer of the Essential Architecture Store (EAS) Meta-Model v6.21. We move beyond static spreadsheets to model applications as dynamic assets that support business capabilities and drive digital transformation.

What You Will Learn in Part 2

This is a 100% hands-on deep dive into modeling the software landscape. We explore the critical relationships between business needs and technical implementation.

• Application Services vs. Functions: Learn to distinguish between what an application does for the user and how it operates internally.

• The Provider/Instance Logic: Master the complex EAS logic of distinguishing between a "Software Product" (the vendor's version) and an "Application Provider" (your organization's specific deployment).

• Integration & Data Flow: Stop drawing lines; start modeling interfaces. We will map how data moves between systems using a graph-based approach.

• Lifecycle & Disposition: Use the meta-model to drive strategy. We will model application roadmaps (Buy, Hold, Retire) to automate portfolio rationalization.

Module Breakdown

Module 1: Expanding the Schema

• Reviewing the connection: How the Application Layer anchors to the Business Layer.

• Setting up the Application Meta-Model in Protégé 5.6.9.

• Introduction to the Application Provider and Application Deployment classes.

Module 2: Modeling the Portfolio

• Application Capabilities: Mapping software to the Business Capabilities defined in Part 1.

• Application Types: Categorizing by Cloud, On-Premise, SaaS, and Custom-built.

• Logical vs. Physical: Separating the conceptual "System" from the physical "Installation."

Module 3: Integration and Interfaces

• Defining Application Services as the "contracts" between systems.

• Using arrows-app to prototype complex integration patterns (API, Batch, Message Queue).

• Capturing Data Objects: What information is being moved and who owns it?

Module 4: Advanced Graph Analysis in Neo4j

• Impact Analysis: Running Cypher queries to see which Business Processes break if an Application goes down.

• Portfolio Health: Visualizing application "technical debt" and lifecycle status using graph nodes.

• The "Application 360" View: Creating a holistic dashboard of an application's ecosystem.

The Tech Stack

Continuing our "Architecture as Code" philosophy, we use:

• Protégé 5.6.9: For managing the Application Layer ontology and slots.

• Neo4j: For high-performance visualization of application dependencies.

• arrows-app: To build prototype for neo4j graph database.

• GitHub: Access to updated Cypher scripts and updated Meta-Model templates.

Your Roadmap to Mastery

You’ve mastered the Business Layer. Now, connect it to the software. By the end of this course, you will have a functional, queryable model of your application landscape that provides real-time insights to stakeholders.

1. Business Layer (Completed)

2. Application Layer (Available Now)

3. Information Layer: Mastering data objects and flows.

4. Technology Layer: Modeling infrastructure and cloud.

5. Enterprise Support: Governance and Change.

Don't just catalog your apps—architect them. Join Part 2 and bring your application portfolio to life.