A concept model is a concrete representation of the world that disambiguates concepts. This is not a design, but it can provide the basis for all system development phases, as well as generate schemas, code, and tests. This presentation describes how. This is a presentation given at the No Magic World Symposium in May, 2017.

1. Creating Systems from
Concept Models
Jim Logan
Director of Semantic Technologies and Interoperability
Product Manager of the Cameo Concept Modeler

2. Agenda
• Why model concepts?
• What is concept modeling?
• How do we know when a concept model is correct?
• Why would you create a system from a concept model?
• How can we create a system from a concept model?
 How does a concept model help analysis?
 How does a concept model help design?
 How does a concept model help implementation?
 How does a concept model help testing?
• What about legacy systems?
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3. Why Model Concepts?
• Designs often lose constraints, conflate things, simplify, and lose
meaning
• Systems therefore become difficult to integrate
• We want to describe the domain as it is, without coloring it
• Provides a “gold standard” for mapping designs to the domain
• Provides a basis for semantic interoperability

4. Why Model Concepts?
• Information is different from what exists in the world
• Information is something that exists in the world
• But, information is not the same as the thing it represents!
• Many ways to say what information represents
• EncodedIntoElementNames
• Data element descriptions
• Data dictionary
• Controlled vocabulary
• Taxonomy
• Ontology
• Concept Model!
• A reasoner can ensure logically consistency
• We can disambiguate roles (e.g., Pilot vs Pilot of a flight)
• We can untangle things from roles (e.g., Person vs. Customer)
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A concept model
provides meaning!

5. What is Concept Modeling?
• A concept model is a concrete description of a domain
• A way of disambiguating things:
• What sort of thing is this? (i.e., taxonomy)
• What distinguishes it from other things? (i.e., ontology)
• A concept model is not an abstraction of a prescriptive design
• Things we avoid:
• Data structures (e.g., tables / columns)
• Computer representations (e.g., “int” vs “char”)
• Units of measure (e.g., pounds on planet Earth vs. kilograms on Mars)
• Specific identifiers
• Optimizations for any application
• The Cameo Concept Modeler has been supporting concept modeling
for ten releases!
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6. How Do We Know A Concept Model Is Correct?
• Validation is critical!
• SMEs should own these concept models
• Three major rules for SME engagement:
 Represent the realities of the domain
 Use the language of the SME
 Make models self-evident
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7. How Does CCM Help?
• A natural language glossary explains a model in plain English
• High level diagrams omit computational concerns
• AutoStyler creates small, focused, hyperlinked defining diagrams
• CCM has been supporting this for ten releases!
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8. How Does the Cameo Collaborator Help?
• Publishes glossaries and diagrams to the web
• Only a web browser is needed
• SMEs review and comment directly on diagrams and glossaries
• CC has been supporting CCM models for FIBO since Summer 2016!
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9. Why Would You Create a System from a Concept
Model?
• Raises the level of abstraction above code and schemas
 Business fundamentals are relatively stable
 Business terminology should resonate through an organization
 Requirements should use unambiguous terms
• Provides a backbone for a system
• Enables other capabilities
 Querying across systems in the language of the business (coming in CCM
19.x!)
 Semantic interoperability among systems (Future)
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10. How Can We Create a System from a Concept Model?
• Continue with analysis, design, implementation, and testing
• Continue with waterfall, iterative, Agile, …
• But, raise the level of abstraction
• Favor “convention over configuration” (configure only
unconventional aspects)
• “Compile” high-level analysis-level models + action language
 This has been done since the 1980’s!
 No longer confined to proprietary meta-models
 We now have fUML, precise state machine semantics, and Alf
 The Cameo Simulation Toolkit has worked with Alf for over a year!
• Next, we’ll look at how a concept model helps in each phase
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11. How Does a Concept Model Help Analysis?
• Provides a controlled vocabulary and meaning for:
 Requirements
 Use cases
 User stories
 Business processes
• Concepts are directly usable in business process models
• “Cherry picking” from a concept model implies information
requirements
• Provides a starting point for design in the language of the business
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12. How Does a Concept Model Help Design?
• Provides a controlled vocabulary and meaning for designers
• Provides a first-cut of an information model:
 Copy cherry-picked concepts into a new namespace
 Retain traceability (i.e., information element «Represents» concept)
 Adjust the information model to address non-functional requirements
 Choose data types
 Use “convention over configuration”
 We are planning features to support all this in CCM 19.x!
• Provides a backbone for:
 Interfaces (i.e., operations / signal receptions)
 State transition models
 The Alf plug-in already works this way!
 Systems can already be simulated using the Cameo Simulation Toolkit!
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13. How Does a Concept Model Help Implementation?
• Provides a controlled vocabulary and meaning for implementation of
interfaces
• First:
 Implement interfaces using Alf
 Configure model compiler to address non-functional requirements
(security, reliability, maintainability, scalability, and usability)
 Configure model compiler for any unconventional aspects
• Second:
 Compile the information model into schemas (We are planning features
to support this in CCM 19.x!)
 Compile the model into executable components (Planned for Alf plug-in)
• A concept model explains the meaning of things in Alf
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14. How Does a Concept Model Help Testing?
• Provides a controlled vocabulary and meaning for clearer
requirements and clearer description of bugs
• Some testing can happen in the Cameo Simulation Toolkit right
now!
• Hypothesis: Alf can be used to generate automated tests
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15. What about Legacy Systems?
• A concept model can be used for semantic interoperability
• Short term: unidirectional mapping for querying across systems in
the language of the business (planned for CCM 19.x!)
• Long term: bidirectional mappings for full federation of data
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16. Summary
• We need to know what information represents
• A concept model is a concrete representation of the world that
disambiguates concepts
• A concept model is not a design
• The SMEs should own a concept model
• A concept model provides the basis for all development phases
 Expressing unambiguous requirements
 Transforming a concept model into an information model / analysis
model
 Augmenting with Alf
 Simulation with the Cameo Simulation Toolkit
 Generation of schemas, code, and tests
• CCM will be providing this functionality in 19.x
• A concept model paves the way for semantic interoperability
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17. Other Related Talks This Week
• Data Federation and Integration Using Conceptual Reference Models
 Cory Casanave
• Hands On with the Alf Action Language: Making Executable Modeling
Easier
 Ed Seidewitz
• Future of Data Models
 Rokas Bartkevicius and Jim Logan
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18. Jim Logan
Director and Product Manager
jlogan@nomagic.com