The Role of Ontology in the Era of Big Military Data

Distributed Common Ground System – Army (DCGS-A)

Barry SmithDirector

National Center for Ontological Research

The Role of Ontology in the Era of Big (Military) Data

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Distributed Development of a Shared Semantic Resource (SSR)

in support of US Army’s Distributed Common Ground System Standard Cloud (DSC) initiative

with thanks to: Tanya Malyuta, Ron Rudnicki

Background materials: http://x.co/yYxN

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http://x.co/yYxN

http://x.co/yYxN

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Making data (re-)usable through common controlled vocabularies

• Allow multiple databases to be treated as if they were a single data source by eliminating terminological redundancy in ways data are described – not ‘Person’, and ‘Human’, and ‘Human Being’, and ‘Pn’,

and ‘HB’, but simply: person• Allow development and use of common tools and

techniques, common training, single validation of data, focused around – semantic technology– coordinated ontology development and use

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Ontology =def.

• controlled vocabulary organized as a graph• nodes in the graph are terms representing types in

reality • each node is associated with definition and

synonyms• edges in the graph represent well-defined relations

between these types• the graph is structured hierarchically via subtype

relations

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Ontologies

• computer-tractable representations of types in specific areas of reality

• divided into more and less general– upper = organizing ontologies, provide common

architecture and thus promote interoperability– lower = domain ontologies, provide grounding in

reality• reflecting top-down and bottom-up strategy

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Success story in biomedicineGoal: integration of biological and clinical data

– across different species– across levels of granularity (organ,

organism, cell, molecule)– across different perspectives (physical,

biological, clinical)– within and across domains (growth, aging,

environment, genetic disease, toxicity …)

RELATION TO TIME

GRANULARITY

CONTINUANT OCCURRENT

INDEPENDENT DEPENDENT

ORGAN ANDORGANISM

Organism(NCBI

Taxonomy)

Anatomical Entity(FMA, CARO)

OrganFunction

(FMP, CPRO) Phenotypic

Quality(PaTO)

Biological Process

(GO)CELL AND CELLULAR

COMPONENT

Cell(CL)

Cellular Compone

nt(FMA, GO)

Cellular Function

(GO)

MOLECULEMolecule

(ChEBI, SO,RnaO, PrO)

Molecular Function(GO)

Molecular Process

(GO)The Open Biomedical Ontologies (OBO) Foundry

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RELATION TO TIME

GRANULARITY



COMPLEX OFORGANISMS

Family, Community, Population

OrganFunction

(FMP, CPRO)

Population Phenotype

PopulationProcess

ORGAN ANDORGANISM

Organism(NCBI

Taxonomy)

Anatomical Entity(FMA, CARO) Phenotypic

Quality(PaTO)

Biological Process

(GO)CELL AND CELLULAR

COMPONENT

Cell(CL)

Cellular Componen

t(FMA, GO)

Cellular Function

(GO)

MOLECULEMolecule



Molecular Process

(GO)Population-level ontologies 10

RELATION TO TIME

GRANULARITY



ORGAN ANDORGANISM

Organism(NCBI

Taxonomy)

Anatomical Entity(FMA, CARO)

OrganFunction


Quality(PaTO)

Biological Process

(GO)

CELL AND CELLULAR

COMPONENT

Cell(CL)

Cellular Compone

nt(FMA, GO)

Cellular Function

(GO)

MOLECULEMolecule



Molecular Process

(GO)Environment Ontology

En

viro

nm

ent

On

tolo

gy

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ORGAN ANDORGANISM

Organism(NCBI

Taxonomy)

Anatomical Entity

(FMA, CARO)

OrganFunction


Quality(PaTO)

Organism-Level Process

(GO)

CELL AND CELLULAR

COMPONENT

Cell(CL)

Cellular Compone

nt(FMA, GO)

Cellular Function

(GO)

Cellular Process

(GO)

MOLECULEMolecule

(ChEBI, SO,RNAO, PRO)


Molecular Process

(GO)

rationale of OBO Foundry coverage

GRANULARITY

RELATION TO TIME

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OBO Foundry approach extended into other domains

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NIF Standard Neuroscience Information Framework

ISF Ontologies Integrated Semantic Framework

OGMS and Extensions Ontology for General Medical Science

IDO Consortium Infectious Disease Ontology

cROP Common Reference Ontologies for Plants

Anatomy Ontology(FMA*, CARO)

Environment

Ontology(EnvO)

Infectious Disease

Ontology(IDO*)

Biological Process

Ontology (GO*)

Cell Ontology

(CL)

CellularComponentOntology

(FMA*, GO*) Phenotypic Quality

Ontology(PaTO)Subcellular Anatomy Ontology

(SAO)

Sequence Ontology (SO*)

Molecular Function

(GO*)Protein Ontology(PRO*)

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top level

domain level

Basic Formal Ontology (BFO)

Modular organization + Extension strategy

~100 ontologies using BFOUS Army Biometrics Ontology

Brucella Ontology (IDO-BRU)

eagle-i and VIVO (NCRR)

Financial Report Ontology (to support SEC through XBRL)

IDO Infectious Disease Ontology (NIAID)

Malaria Ontology (IDO-MAL)

Nanoparticle Ontology (NPO)

Ontology for Risks Against Patient Safety (RAPS/REMINE)

Parasite Experiment Ontology (PEO)

Subcellular Anatomy Ontology (SAO)

Vaccine Ontology (VO)

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Basic Formal Ontology

Monday, April 10, 2023 16

BFO:Entity

BFO:Continuant BFO:Occurrent

BFO:ProcessBFO:Independent Continuant

BFO

BFO:Dependent Continuant

BFO:Disposition

Basic Formal Ontology and Mental Functioning Ontology (MFO)


BFO:Entity


BFO:Process

Organism

BFO:Independent Continuant

BFOMFO


Behaviour inducing state

Mental Functioning Related Anatomical

Structure

Cognitive Representation

BFO:Quality

Affective Representation

Mental Process

Bodily ProcessBFO:Disposition

BFO:Entity


BFO:ProcessBFO:Independent

Continuant

BFOMFO


Cognitive Representation

Affective Representation

Mental Process

Bodily ProcessBFO:Disposition

MFO-EM

Emotion Occurrent

Organism

Emotional Action Tendencies

Appraisal

Subjective Emotional Feeling

Physiological Response to

Emotion Process

inheres_in

is_output_of

Emotional Behavioural Process

Appraisal Process

has_part

agent_of

Emotion Ontology extends MFO


Sample from Emotion Ontology: Types of Feeling

The problem of joint / coalition operations

Fire Support

Logistics

Air Operation

s

Intelligence

Civil-Military

Operations

Targeting

Maneuver &Blue Force

Tracking

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US DoD Civil Affairs strategy for non-classified information sharing

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Ontologies / semantic technologycan help to solve this problem

Fire Support

Logistics

Air Operation

s

Intelligence

Civil-Military

Operations

Targeting

Maneuver &

Blue Force

Tracking

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But each community produces its own ontology, this will merely create new, semantic siloes

Fire Support

Logistics

Air Operation

s

Intelligence

Civil-Military

Operations

Targeting

Maneuver &Blue Force

Tracking

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What we are doing to avoid the problem of semantic siloes

Distributed Development of a Shared Semantic Resource

Pilot testing to demonstrate feasibility

Anatomy Ontology(FMA*, CARO)

Environment

Ontology(EnvO)

Infectious Disease

Ontology(IDO*)

Biological Process

Ontology (GO*)

Cell Ontology

(CL)

CellularComponentOntology

(FMA*, GO*) Phenotypic Quality

Ontology(PaTO)Subcellular Anatomy Ontology

(SAO)

Sequence Ontology (SO*)

Molecular Function

(GO*)Protein Ontology(PRO*)

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top level

domain level

Basic Formal Ontology (BFO)

creating the analog of this in the military domain

Semantic Enhancement

Annotation (tagging) of source data models using terms from coordinated ontologies

– data remain in their original state (are treated at arms length)

– tagged using interoperable ontologies created in tandem– can be as complete as needed, lossless, long-lasting

because flexible and responsive– big bang for buck – measurable benefit even from first

small investments

Coordination through shared governance and training29

Main challenge: Will it scale?

The problem of scalability turns on • the ability to accommodate ever increasing

volumes and types of data and numbers of users

• can we preserve coordination (consistency, non-redundancy) as ever more domains become involved?

• can we respond in agile fashion to ever changing bodies of source data?

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Strategy for agile ontology creation

• Identify or create carefully validated general purpose plug-and-play reference ontology modules for principal domains

• Develop a method whereby these reference ontologies can be extended very easily to cope with specific, local data through creation of application ontologies

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vehicle =def: an object used for transporting people or goods

tractor =def: a vehicle that is used for towing

crane =def: a vehicle that is used for lifting and moving heavy objects

vehicle platform=def: means of providing mobility to a vehicle

wheeled platform=def: a vehicle platform that provides mobility through the use of wheels

tracked platform=def: a vehicle platform that provides mobility through the use of continuous tracks

artillery vehicle = def. vehicle designed for the transport of one or more artillery weapons

wheeled tractor = def. a tractor that has a wheeled platform

Russian wheeled tractor type T33 = def. a wheeled tractor of type T33 manufactured in Russia

Ukrainian wheeled tractor type T33 = def. a wheeled tractor of type T33 manufactured in Ukraine

Reference Ontology Application Ontology

AIRS Reference Ontologies

Basic Formal Ontology

(BFO)

Extended Relation Ontology

Time OntologyQuality

Ontology

Information Entity

OntologyGeospatial Ontology

Event OntologyArtifact

Ontology

Agent Ontology

Agent Ontology

Social Network, Skills, and Occupations

Event Ontology

Actions, Natural Events and Time-Dependent Attributes

Geospatial Ontology

Regions, Geopolitical Entities, Geographic Features, and Locations

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http://milportal.org

An example of agile application ontology development:

The Bioweapons Ontology (BWO)

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Kinds of chemical and biological weapons

Chemical Nerve agents (sarin gas)Blister agents (mustard gas)Blood agents (cyanide gas)

BiologicalInfectious agents – BWO(I)

Toxic agents (botulinum toxin, ricin) – BWO(T)

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We focus here on BWO(I)

Infectious agents–Bacterial (anthrax, bubonic plague,

tularemia, brucellosis, cholera …)–Viral (Ebola, Marburg …)

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BFO IDO StaphIDO

Independent Continuant

Infectious disorder

Staph. aureusdisorder

Dependent Continuant

Infectious disease

Protective resistance

MRSA

Methicillin resistance

Occurrent Infectious disease course MRSA course

Examples of ontology terms

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Infectious Disease Ontology (IDO)

IDO Core (Reference Ontology)• General terms in the ID domain.

IDO Extensions (Application Ontologies)• Disease-, host-, pathogen-specific.

• Developed by subject matter experts.

The hub-and-spokes strategy ensures that logical content of IDO Core is automatically inherited by the IDO Extensions

•with thanks to Lindsay Cowell (University of Texas SW Medical Center) and Albert Goldfain (Blue Highway, Inc.)

IDO Core

• Contains general terms in the ID domain:– E.g., ‘colonization’, ‘pathogen’, ‘infection’

• A contract between IDO extension ontologies and the datasets that use them.

• Intended to represent information along several dimensions:– biological scale (gene, cell, organ, organism, population)– discipline (clinical, immunological, microbiological) – organisms involved (host, pathogen, and vector types)

BFO IDO StaphIDO

Independent Continuant

Infectious disorder

Staph. aureusdisorder

Dependent Continuant

Infectious disease

Protective resistance

MRSA

Methicillin resistance

Occurrent Infectious disease course MRSA course

Examples of ontology terms

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IDO Extensions

IDO – BrucellosisIDO – Dengue FeverIDO – InfluenzaIDO – MalariaIDO – Staphylococcus Aureus BacteremiaIDO – Vector Surveillance and ManagementIDO – Plant VO – Vaccine OntologyBWO(I) – Bioweapons Ontology (Infectious Agents)

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How IDO evolves: the case of Staph. aureus

IDOCore

IDOSa

IDOHumanSa

IDORatSa

IDOStrep

IDORatStrep

IDOHumanStrep

IDOMRSa

IDOHumanBacterial

IDOAntibioticResistant

IDOMAL IDOHIVHUB and SPOKES:Domain ontologies

SEMI-LATTICE:By subject matter experts in different communities of interest.

IDOFLU

BWO:disease by infectious agent = def. a disease that is the consequence of the presence of

pathogenic microbial agents, including pathogenic viruses, pathogenic bacteria, fungi, protozoa, multicellular parasites, and aberrant proteins known as prions

Strategy used to build BWO(I)with thanks to Lindsay Cowell and Oliver He (Michigan)

1. Start with a glossary such as: http://www.emedicinehealth.com/biological_warfare/

2. Select corresponding terms from IDO core and related ontologies such as the CHEBI Chemistry Ontology terms needed to describe bioweapons

3. All ontology terms keep their original definitions and IDs.

4. The result is a spreadsheet

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http://www.emedicinehealth.com/biological_warfare/

5. Where glossary terms have no ontology equivalent, create BWO ontology terms and

definitions as needed

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no corresponding ontology term

6. Use the Ontofox too to create the first version of the BWO(I) application ontology (http://ontofox.hegroup.org/)

7. Use BWO(I) in annotations, and where gaps are identified create extension terms, for instance – weaponized brucella – aerosol anthrax– smallpox incubation period

This establishes a virtuous cycle between ontology development and use in annotations

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http://ontofox.hegroup.org/

Potential uses of BWO

– semantic enhancement of bioweapons intelligence data– results will be automatically interoperable with relevant bioinformatics and public health IT tools for dealing with infections, epidemics, vaccines, forensics, …–to annotate research literature and research data on bioweapons – to create computable definitions to substitute for definitions in free text glossaries

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Why do people think they need lexicons

• Training• Compiling lessons learned• Compiling results of testing, e.g. of proposed new

doctrine• Collective inferencing• Official reporting• Doctrinal development• Standard operating procedures• Sharing of data• People need to (ensure that they) understand each other

The Role of Ontology in the Era of Big Military Data

Education

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