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Manager’s Overview DoDAF 2.0 Meta Model (DM2) TBS dd mon 2009

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Presentation on theme: "Manager’s Overview DoDAF 2.0 Meta Model (DM2) TBS dd mon 2009"— Presentation transcript:

1 Manager’s Overview DoDAF 2.0 Meta Model (DM2) TBS dd mon 2009
VERSION 15 2/23/ :33 DoDAF 2.0 Meta Model (DM2) Manager’s Overview TBS dd mon 2009

2 Briefing Outline The DM2 Conceptual Data Model
DM2 and Core Process Relationships Overview Overview of the DM2 Foundation

3 Map of DM2 Description Documents and Briefings
You are here

4 Conceptual Data Model

5 (see “DM2 CDM Description document” for definitions)
Key Concepts Activity Resource Materiel Information Architecture Description Data Performer System Service Person Type Organization Capability Measure & Measure Type Desired Effect (alias Goal) Condition Location Project Vision Guidance Rule Standard Constraint Agreement Skill (see “DM2 CDM Description document” for definitions)

6 (see “DM2 CDM Description document” for definitions)
Conceptual Data Model 1 2 3 4 5 6 7 8 9 10 11 12 13 14 20 16 17 18 19 21 22 26 15 23 27 24 25 28 29 31 30 (see “DM2 CDM Description document” for definitions) 23 (+ 24 &25) 20 (+ 21 & 22) 30 34 33 32 Green lines are super-subtype. Read in direction of arrow, “is a type of” Blue lines are associations. See notes for key descriptions and examples. Read key in direction of arrow. Crows feet are associations between the association at the foot and the arrow, read according to the key. 36 Person Type 35 37

7 Interrogatives Relationship UCORE 2.0 Who, What, When, Where
WHY HOW WHAT WHO WHERE

8 DM2 and Core Processes Relationships Overview

9 Overview of the DM2 Foundation
Underlying the CDM is a foundation that utilizes common data modeling constructs that facilitate the reuse of common data patterns

10 Benefits of adopting the IDEAS formal foundation and common patterns
Model compactness through inheritance of superclass properties and common patterns. Agreed-upon analysis principles that provide a principled basis for issue analysis Improved ability to integrate and analyze multiple heterogeneous EA datasets to fulfill EA purposes

11 Questions?

12 Backup

13 Common Relationship Patterns Emerged -- Leveraged Ongoing IDEAS Foundation --
Mathematics type (~set) theory 4D mereotopology Deals with issues of states, powertypes, measures, space -- what is truly knowable vs. what is assumed Separates signs and representations from referents DM2 domain concepts are extensions to the formal foundation Rigorously worked-out common patterns are reused: Super-subtype, whole-part, temporal whole-part, type-instance, before-after, overlap Saved a lot of repetitive work – “ontologic free lunch” Result is higher quality and consistency throughout As we started figuring out relationships, we realized we were doing the same relationships over and over again. Decided to look into leveraging work we had been doing for several years with the international community on a formal .ontology. IDEAS foundation concepts are inherited into all the DM2 concepts. Saved us a lot of work – ontologic free lunch -- and part of the reason why the model is so small to this day -- ~ 300 classes, attributes, and values as compared to CADM’s 16, 000 pieces. Three types of Things: Types (which are like sets), Tuples (ordered relationships), and Individuals (not persons, but Things that have spatial and temporal extent – spatio-temporal extent.) mereology is a collection of axiomatic first-order theories dealing with parts and their respective wholes. In contrast to set theory, which takes the set–member relationship as fundamental, the core notion of mereology is the part–whole relationship. Mereology is both an application of predicate logic and a branch of formal ontology. Three types of Things: Individuals – Things with spatio-temporal extent (not people) Types – similar to sets Tuples – ordered relations between Things


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