Page Last Updated: Tuesday, 19 January 2016 11:02 EDT, © 2011, 2012, 2016

HARTLEY CONSULTING
Solving Complex Operational and Organizational Problems

PROJECT: Total IW Ontology

Dr. Dean S. Hartley III

Project Metadata Keywords
Label Name Other Year DurationYrs
Client Hartley Consulting none Commercial
Dates 2011 1
Employer Hartley Consulting
Partner N/A
Pubs Total IW Ontology Database programmer 2011
Configuration management
Consequence Management
Data Verification & Validation
Database design
DIME/PMESII Modeling
Documentation standards
Geopolitical analysis
Global War on Terrorism (GWOT)
Human factors
Human, Social, Cultural Behavior (HSCB) Modeling
Impact analysis
Independent Verification & Validation (IV&V)
Information storage and retrieval
Irregular Warfare (IW)
Knowledge Management (KM)
Metadata
Model/System integration
Modeling, Simulation & Gaming (MSG)
Ontologies
Operations Other Than War (OOTW)
Software issues
Software reuse
Stability Operations (SASO, SSTR)
Verification, Validation & Accreditation (VV&A)
Warfare modeling

Challenge:

Create a total ontology of the elements needed for modeling Irregular Warfare (IW).

Background:

The initiative is derived from the IW Metric Ontology project. That project developed the conceptual model shown in the figure below.

The central organizational principle for the development of the IW Metric Ontology is provided by the figure to the right. The Operational Environment that includes everything relevant to irregular warfare is divided into three parts: Actors, Actions, and the Environment.

Actors are human and natural entities that cause things to happen, thereby changing things.

Actions are the interventions, events, and ongoing processes that are performed by actors and which directly cause changes.

The Environment represents the rest of entities in the Operational Environment.

Actors perform Actions, which affect the Operational Environment (OE). The state of OE, including any changes, is described by State Variables. Actors perceive the OE by means of the State Variables.

State Variables include both numeric variables (true metrics) and categorical variables (e.g., type of government).  IW Metrics are defined to be these State Variables and provide the content of the IW Metric Ontology.

The IW Metric Ontology project developed the ontology for the metrics; however, it only identified the precursor elements, Actions, Environment, and Actors, without developing ontologies for them.

Process:

The process of creating a total IW ontology consisted of five tasks: element identification, ontology structures development, completeness checking, semantic coding, and extended LOE connection. In practice, these tasks were not completely separable, as new elements might require additions to the structures; the completeness tests might imply the needs for new elements; the structures themselves might suggest the need for new elements through completeness arguments; and semantic coding had to be done for new elements, which might suggest new semantic codes, relevant to old elements.

Identifying Elements:

Thirteen sources were used in identifying elements.  The first three were used to create the initial set and the remaining eight were connected to the initial eight, where possible, and used to generate additional elements where there were no matches.  The additional sources were also used in refining the names and definitions of the elements, broadening their meanings where appropriate.  This process ensured that multiple points of view were considered to maximize the coverage by the set of elements.

1.  Doing Windows Network

The Doing Windows Taxonomy is described in the diagram to the right.  The variables are contained in the four influence nets.  In addition the taxonomy is linked to a table of citations (reproduced toward the end of this page) - here "DoingWindows." The contents of the network are given in rptDoingWindowsNetwork.pdf. 

2.  ISSM Network

The Interim Semi-static Stability Model (ISSM) Taxonomy is described in the diagram to the right.  There are three levels to the taxonomy, each containing the influence variables.  In addition the taxonomy is linked to a table of citations (reproduced toward the end of this page) - here "ISSM AG."  The contents of the network are given in rptISSMNetwork.pdf. 

3.  VV&A Tool Ontology

The DIME/PMESII VV&A Tool Ontology is described in the diagram to the right.  There are three levels to the ontology, with the variables connected to the lowest level shown in the diagram.  DIME variables are connected both to the Status box and to the DIME box.  In addition the ontology is linked to a table of citations (reproduced toward the end of this page) - here "VV&A Tool."  The contents of the ontology are given in rptVVAToolOntology.pdf. 

4.  Haskins List

The Haskins List is described in the relational database design to the right.  There is only one level to the list, with a text description (Haskins).  In addition the taxonomy is linked to a table of citations (reproduced toward the end of this page) - here "Haskins."  The contents of the ontology are given in rptHaskinsList.pdf.

5.  OCRS Taxonomy

The Office of the Coordinator for Reconstruction and Stabilization (OCRS) Essential Tasks Taxonomy is described in the relational database design to the right.  There are three levels to the taxonomy, each with a text description (OCRSLev1, OCRSLev2, and OCRSMatrixItem).  In addition the taxonomy is linked to a table of citations (reproduced toward the end of this page) - here "OCRS."  The contents of the taxonomy are given in rptOCRSTaxonomy.pdf.

6.  MPICE Ontology

The Measuring Progress in Conflict Environments (MPICE) Ontology is described in the diagram to the right.  There are four levels to the ontology, each with a text description (MPICECat and MPICEAltCat at the top level, MSubCat at the second level, MPICEdescription at the third level, and Metric Instance at the bottom level).  In addition the ontology is linked to a table of citations (reproduced toward the end of this page) - here "MPICE."  The contents of the ontology are given in rptMPICEOntology.pdf.

7.  Hillson Taxonomy

The Hillson Taxonomy is described in the relational database design to the right.  There are three levels to the taxonomy, each with a text description (HilsonCategory, HilsonItem and MOFE Indicator).  In addition the taxonomy is linked to a table of citations (reproduced toward the end of this page) - here "Hillson."  The contents of the ontology are given in rptHillsonTaxonomy.pdf.

8.  Corruption Model Ontology

The ontology for the Corruption Model, developed from a National Defense University (NDU) workshop, is described in the relational database design to the right.  There are two levels to the ontology, each with a text description (CorruptionCat and CorruptionItem).  In addition the taxonomy is linked to a table of citations (reproduced toward the end of this page) - here "Corruption."  The contents of the ontology are given in rptCorruptionOntology.pdf.

9.  IWDecomp List

The TRAC 2009 IW Decomposition TEO List is described in the relational database design to the right.  There is only one level to the list, with a text description (IWDecomp2009TEOsWorkshop subject).  In addition the taxonomy is linked to a table of citations (reproduced toward the end of this page) - here "IWDecomp."  The contents of the ontology are given in rptDecompList.pdf.

10.  Metrics V3 Taxonomy

The TRAC Metrics V3 Taxonomy is described in the relational database design to the right.  There are three levels to the taxonomy, each with a text description (MetV3Cat, MetV3SubCat and Metrics v3).  In addition the taxonomy is linked to a table of citations (reproduced toward the end of this page) - here "Metrics v3."  The contents of the ontology are given in rptMetricsV3Taxonomy.pdf.

11.  HSCB Taxonomy

Mitre's Human Social Cultural Behavior (HSCB) Taxonomy is described in the relational database design to the right.  There are five levels to the taxonomy, each with a text description (Taxon).  In addition the taxonomy is linked to a table of citations (reproduced toward the end of this page) - here "HSCB."  The contents of the taxonomy are given in rptHSCBTaxonomy.pdf.

12.  PRIME Taxonomy

SRI's PRIME Taxonomy is described in the relational database design to the right.  There are three levels to the taxonomy, each with a text description (PRIMELevel1-3).  In addition the taxonomy is linked to a table of citations (reproduced toward the end of this page) - here "PRIME."  The contents of the taxonomy are given in rptPRIMETaxonomy.pdf.

13.  FASP Taxonomy

The Department of State and USAID Foreign Assistance Standardized Program (FASP) Taxonomy is described in the relational database design to the right.  There are four levels to the taxonomy, each with a text description (ProgramName, ProgramArea, ProgramElement, and ProgramSubElement).  In addition the taxonomy is linked to a table of citations (reproduced toward the end of this page) - here "FASP."  The contents of the taxonomy are given in rptFASPTaxonomy.pdf.

 

Developing Ontology Structures:

The initial effort (the IW Metric Ontology project) focused on creating a metric ontology, using the actor, action, and environment elements as reference data.  This effort focuses on completing the actor, action, and environment ontologies, with the possibility of creating additional metric classes in the process.

1.  Metric Ontology

The figure below provides a sketch of the metric ontology.  All of the metrics are represented by a single class with an vertical arrow representing the connection(s) of the element to the PMESII subcategories and with a horizontal arrow representing the connection(s) to the DoD Lines of Effort (LOEs).

There are more than 600 elements in the metric ontology.  These elements are included with the categories and subcategories to which they are linked in a report that gives extended definitions by showing the elements from the 13 sources that relate to each ( rptMetricsExtendedDef.pdf).

2.  Actor Ontology

The figure to the right is a sketch of the actor ontology. In this case, the PMESII representation is abbreviated to the category level to reduce clutter. The actor categories and subcategories are fully populated to show that taxonomy. As in the figure above, each element is connected to one or more of the PMESII subcategories and one or more of the Actor subcategories.

There are more than 80 actor elements in the ontology.  These elements are included with the action and environment elements in a report that gives extended definitions by showing the elements from the 13 sources that relate to each (rptOEElementsExtendedDefs.pdf).

3.  Action Ontology

The figure to the right is a sketch of the action ontology. The PMESII representation is abbreviated to the category level to reduce clutter. The action taxonomy is fully populated, but has no subcategories. As in the figure above, each element is connected to one or more of the PMESII subcategories and one or more of the Action categories.

There are more than 300 action elements in the ontology.  These elements are included with the action and environment elements in a report that gives extended definitions by showing the elements from the 13 sources that relate to each (rptOEElementsExtendedDefs.pdf).

4.  Environment Ontology

The figure to the right is a sketch of the environment ontology. The PMESII representation is abbreviated to the category level to reduce clutter. The environment categories and subcategories are fully populated to show that taxonomy. As in the figure above, each element is connected to one or more of the PMESII subcategories and one or more of the Environment subcategories.

There are more than 160 environment elements in the ontology.  These elements are included with the action and environment elements in a report that gives extended definitions by showing the elements from the 13 sources that relate to each (rptOEElementsExtendedDefs.pdf).


 

Defining the Elements

The elements of an ontology are "a controlled vocabulary" according to the definition of ontologies.  A controlled vocabulary can be a set of terms that are identified as being special, but are not defined.  (Pure mathematics uses this technique for its fundamental terms.)  However, IW ontologies need to have identifiable referents to the real world to be useful.  The structure of the ontologies supports this need.

Each element (three are shown in the figure to the right) has certain attributes that help define it. In addition, the ontological structure provides additional information that helps define the element.  Further, the links to the sources provide information about the concepts that are meant to be included in the definition of the element.

Each element has a name that provides a very short description of the element.  This is followed by a phrase that defines the element more formally.  Finally, each element is identified as an actor, environment, or action element (or as more than one of these).

Each of the three elements in the figure has its PMESII category or categories and subcategories listed with the "PMESII" cite.  For example, the third element is contained in both the Political and the Social categories.  Depending on the type of element, it will also have its Actor, Action, or Environment structure links identified.  These three elements have single links; however, other elements have multiple links, as in the third elements PMESII structure.

Finally, each element displays the name of each source from which it is derived (here PRIME, Corruption, and HSCB are cited) and the Major, Minor, and Detail information for the particular link.

Together, these parts of the extended definition enable the user to develop a good understanding of what is meant by the element.

Checking Completeness:

Three of the completeness checking processes are fairly well-defined.  However, the fourth process is definitely more art than science.

1.  Action-Object Completeness:

The action-object pairing relates to modeling objects with size or quantity attributes that are variable.  For these objects, a measure of the current size or quantity is required and methods that change the size or quantity are also required.

    a. Each object (actor or environmental object) may need actions to change its size or composition.  This can be particular actions such as birth and death actions for populations or training and retirement/completion of enlistment/desertion for military personnel or it may be simple increase and decrease actions.

    b. Each action may need an object that represents the status (both before and after the change).  For example, training new political leaders implies a change in the set of political leaders and improving HN executive function requires a HN executive branch.

2.  Actor-Action Completeness:

The actor-action pairing relates to the realization that an actor that doesn't initiate any actions in a model is really just an environmental attribute (in that model) and that while some actions might be considered as spontaneously occurring, most are initiated by an actor.

    a. Each action may need an actor or actors that can initiate the action.  For example, rebuilding actions may require both local workers and businesses and external contractors.

    b. Each actor may need an action or actions that it can initiate.  For example courts conduct judicial activities.

3.  Object-Actor Completeness:

The object (environmental object or actor object)-actor pairing also has a pair of tests; however, these approach the semantic completeness check in regards to art versus science.

    a. Some actors imply additional objects by their nature.  For example external contractors implies a need for key external contractors.

    b. Some objects imply particular actors by their nature.  For example freedom of international media to report implies a need for international media and key international media leaders.

4.  Semantic Completeness:

The semantic completeness check involves generating a set of terms that relate to the elements through similar meanings (semantics).  Each of the elements is checked for the existence of a relation to each term.  Then the collections of elements that relate to each term are examined to see if any elements are "missing."  (See the next section.)  Any missing elements are added to the set of elements, categorized and checked for completeness using the first three processes.

 

Coding Semantics:

More than 200 semantic terms were generated by the metric ontology classes.  For convenience, these were organized into semantic classes.  The contents are given in rptSemanticTerms.pdf.  Each of the more than 600 metric ontology classes were associated with several semantic terms, yielding more than 2600 associations, as illustrated below.

Once these associations were determined to be approximately complete, they were reordered by the semantic terms, as shown below.  This reordering permitted an examination for semantic association completeness in this other direction and an examination for missing metric classes.

The connection of the associated semantic terms with the metric classes (and, through the connection between the metric ontology and the actor, action, and environment ontologies, an association of the semantic terms with these ontologies) permits computer programs to make semantic inferences about the connections among ontology elements.

 

Extending the LOE connections:

At the end of the IW Ontology Project, the TRAC working group created ontologies for the other stakeholders involved in their model and generated connections among the new LOEs and the metrics.  The parties were:

The new LOEs included both "official" LOEs (those openly admitted) and unofficial LOEs (not openly admitted LOEs).  The complete list of official LOEs is given in rptAllOfficialLOEsNoSubtasks.pdf.  Another report (rptAllOfficialLOEs.pdf) shows the official LOES and the subtasks for each LOE.  A third report (rptOfficialLOEsWithMetricsByLOEOwner.pdf) shows the metrics that were assigned to each of the official LOEs.

 

Conclusions:

Developing the Total IW Ontology provides several benefits in understanding Irregular Warfare.

Recommendations:

Citations:

# Citation Authors Title Date Publisher URL
1 DoingWindows Hayes, Bradd C. & Jeffrey I. Sands Doing Windows: Non-Traditional Military Responses to Complex Emergencies 1998 CCRP, Washington, DC
2 ISSM AG Hartley, Dean S., III Operations Other Than War (OOTW) Flexible Asymmetric Simulation Technologies (FAST) Prototype Toolbox: ISSM v4.00 Analysts' Guide 2006 DRC, Orlando, FL ISSM
3 VV&A Tool Hartley, Dean S., III DIME/PMESII VV&A Tool (Software) 2009 Hartley Consulting, Oak Ridge, TN VVATool
4 Haskins Haskins, Casey "A Practical Approach to Cultural Insight," Military Review Sept-Oct 2010
5 OCRS Office of the Coordinator for Reconstruction and Stabilization Post-Conflict Reconstruction Essential Tasks 2005 US Dept of State, Washington, DC http://www.crs.state.gov/index.cfm?fuseaction=public.display&id=10234c2e-a5fc-4333-bd82-037d1d42b725
6 MPICE Dziedzic, Michael; Barbara Sotirin; and John Agoglia Measuring Progress in Conflict Environments (MPICE): A Metrics Framework for Assessing Conflict Transformation and Stabilization, Version 1.0 2008 US Institute for Peace, Washington, DC
7 Hillson Hillson, Roger; et al. Requirements for a Government Owned DIME/PMESII Model Suite 2009 Office of the Secretary of Defense Modeling & Simulation Steering Committee, Washington, DC
8 Corruption Hartley, Dean S., III Corruption in Afghanistan: Conceptual Model 21 August 2010 Hartley Consulting, Oak Ridge, TN NDUHSCB
9 IWDecomp US Army TRAC IW Decomposition Analytic Strategy, TRAC, Overview Briefing for IW WG 6 January 2009 TRAC, Ft Leavenworth, KS
10 Metrics v3 Works, Paul Metrics v3.xls 2010 TRAC, Ft Leavenworth, KS
11 HSCB Klein, G. "A Taxonomy for HSCB Research and Operations" Proceedings of the HSCB Focus 2011 Conference February 8-10, 2011 Chantilly, VA listing
12 PRIME Lowrance, J.D. & J. L. Murdock Political, Military, Economic, Social, Infrastructure, Information (PMESII) Effects Forecasting for Course of Action (COA) Evaluation 2009 Air Force Research Laboratory, Rome, NY picture
13 FASP Department of State & USAID Foreign Assistance Standardized Program Structure and Definitions 10/20/2006 Washington, DC
14 FM3-24.2 US Army FM 3-24.2 APR 09 Washington, DC
15 OntWS3 TRAC Ontology Workshop 3 Non-DoD LOEs 7/15/2011 TRAC, Ft Leavenworth, KS

Sharing Results:

The work has been presented in several venues during and after the project, as shown below.

 

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