Presentation to Data Melb on Semantic Modeling and CQL.

1. The Constellation
Query Language
Clifford Heath, Data Constellation

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3. Copyright © 2010 Data ConstellationImage Copyright Andrew Lipson 2005. Used with permission. Not affiliated with Lego™
The Enterprise
is a mess

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One­way
communication
•Software folk translate user stories into
precise abstractions (UML, ER, etc)
•The abstractions are mostly unreadable
by the business ­> No backchannel!
•Only the built artefacts communicate
our misunderstandings ­> Late!

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Loss of Semantics

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Semantics
• Each term denotes a type of thing
• Each thing is associated with others
• These associations are connotations
• “Meaning” is the sum of all connotations
• Every person has different connotations
“The shared meanings of a community”

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Relations, Objects,
Graphs, or...
Facts?

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Constellation Query Language

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Insurance Simplified (contd.)

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Relational Mapping

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Insurance Claim (complete)
Schema has been modified to suit a Rails application

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Insurance (snippets)
Driver is a kind of Person;
Vehicle Incident is a kind of Incident;
Driving is where Driver drove vehicle in Vehicle Incident;
Vehicle Incident followed Intoxication;
Driving Charge is where Driving resulted in Charge;
Driving Charge is a warning;
These definitions support the example that follows.

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Instance Data

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Diplomacy Model
Object and fact types

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Diplomacy model ­ constraints
CQL supports many constraint types:
Mandatory, Uniqueness, Frequency,
Subset, Equality, Exclusion, Ring, Value, etc.

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ORM2
A graphical
language for
fact­oriented
modeling.

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Relational Mapping

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SQL

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Ruby
Ruby fact-oriented DSL
* uses meta-programming
* assert/retract, no new/delete
* fully co-referenced.

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Simple Query
Person has given Name ‘Daniel’?
Person has given Name,
given Name = ‘Daniel’?
... a contraction of the value join:

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Units conversion
Area is written as Real in mm^2;
Pane has Area:
Pane of glass has Width,
Pane of glass has Height,
Width * Height = Area;
large Pane:
Pane has Area, Area >= 5 foot^2;
large Pane?
Defined
in mm
Compatibility
is checked
Conversion
supplied
Query:

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Semantic Modeling
•Highly verbal, and verbalisable
•Based on user examples
•Mathematically formal (FOL)
•Fine­grained semantic structure
•Attribute­free (Doesn’t encode assumptions)
•Automatic mapping to O­O, ER and
code

23. Clifford Heath
Available for consulting and training
http://dataconstellation.com/