A template to define an outline structure for the clear and unambiguous definition of the discreet component data elements (atomic items of Entity/Attribute/Relationship/Rule) within the Logical layer of an Enterprise Information Model (a.k.a. Canonical Model).

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Example Data Specifications &
Information Requirements Framework
LOGICAL DATA DEFINITION
TEMPLATE
Alan D. Duncan
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

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1 Purpose
This document template defines an outline structure for the clear and unambiguous definition of the
discreet component data elements (atomic items of Entity/Attribute/Relationship/Rule) within the
Logical layer of an Enterprise Information Model (a.k.a. Canonical Model).
This template forms part of example data specification & information requirements framework. The
framework offers a set of outline principles, standards and guidelines to describe and clarify the
semantic meaning of data terms in support of an Information Requirements Management process.
(See the Framework Overview for further details.)

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2 Logical Data Definition
 The template should be completed for each individual data element required within the
Logical Data Model layer (to the extent that this information can be defined).
Data Element
Specification Item
Purpose
Data Element name
A clear, unambiguous and unique terminology for the atomic data
element, expressed as part of canonical model.
Data Element
description
A full elaboration of the semantic encoded meaning of the data element
and definition of its relationships with any other data elements within the
canonical model.
Data Rules
Any semantic rules or constraints that govern the expression and us of
the data element.
Note that row-level data rules may also exist.
Business requirements identified within the Business Data Requirements Specification must be
decomposed and modelled to their underlying granular atomic components, such that:
1. Each data element within the canonical model is clearly and unambiguously defined.
2. The relationship between atomic data elements is clearly and unambiguously defined.
3. There is no further decomposition possible.
4. Each atomic data element should map back to a business data definition.
5. Atomic data elements mapped to be commonly defined once across the Enterprise
Information Model
6. Component data elements within the canonical model should be defined once and once only,
with no duplication of terms across the model.
7. Atomic data elements create portable and inter-operable data definitions that support
exchange of data between all data recording systems within the organisation.
8. The Canonical Model is by definition abstracted from both the Business Requirements layer
and from the Physical layer, and should stand independent of any specific business or
technical usage of data.
9. Note that entity/attribute/relationship modelling is not sufficient; record-level modelling must
also be given due consideration.

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About the author
Alan D. Duncan is an evangelist for information and analytics as
enablers of better business outcomes, and a member of the
Advisory Board for QFire Software.
An executive-level leader in the field of Information and Data
Management Strategy, Governance and Business Analytics, he
has over 20 years of international business experience, working
with blue-chip companies in a range of industry sectors. Alan
was named by Information-Management.com in their 2012 list of
“Top 12 Data Governance gurus you should be following on
Twitter”.
Twitter: @Alan_D_Duncan
Blog: http://informationaction.blogspot.com.au/

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