1. Distributed Common Ground System – Army (DCGS-A)
The Role of Ontology in the Era of Big (Military) Data
Barry Smith
Director
National Center for Ontological Research 1

2. 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:

4. 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

5. 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

6. 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

7. Success story in biomedicine Goal: 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 …)

8. The Open Biomedical Ontologies (OBO) Foundry
RELATION
TO TIME
GRANULARITY
CONTINUANT
OCCURRENT
INDEPENDENT
DEPENDENT
ORGAN AND
ORGANISM
Organism
(NCBI
Taxonomy)
Anatomical Entity
(FMA, CARO)
Organ
Function
(FMP, CPRO)
Phenotypic Quality (PaTO)
Biological Process
(GO)
CELL AND CELLULAR COMPONENT
Cell
(CL)
Cellular Component
(FMA, GO)
Cellular Function
MOLECULE
Molecule
(ChEBI, SO,
RnaO, PrO)
Molecular Function
Molecular Process
The Open Biomedical Ontologies (OBO) Foundry

9. Family, Community, Population
RELATION
TO TIME
GRANULARITY
CONTINUANT
OCCURRENT
INDEPENDENT
DEPENDENT
COMPLEX OF
ORGANISMS
Family, Community, Population
Organ
Function
(FMP, CPRO)
Population Phenotype
Population
Process
ORGAN AND
ORGANISM
Organism
(NCBI
Taxonomy)
Anatomical Entity
(FMA, CARO)
Phenotypic Quality (PaTO)
Biological Process
(GO)
CELL AND CELLULAR COMPONENT
Cell
(CL)
Cellular Component
(FMA, GO)
Cellular Function
MOLECULE
Molecule
(ChEBI, SO,
RnaO, PrO)
Molecular Function
Molecular Process
Population-level ontologies

10. Environment Ontology Environment Ontology TO TIME GRANULARITY
RELATION
TO TIME
GRANULARITY
CONTINUANT
OCCURRENT
INDEPENDENT
DEPENDENT
ORGAN AND
ORGANISM
Organism
(NCBI
Taxonomy)
Anatomical Entity
(FMA, CARO)
Organ
Function
(FMP, CPRO)
Phenotypic Quality (PaTO)
Biological Process
(GO)
CELL AND CELLULAR COMPONENT
Cell
(CL)
Cellular Component
(FMA, GO)
Cellular Function
MOLECULE
Molecule
(ChEBI, SO,
RnaO, PrO)
Molecular Function
Molecular Process
Environment
Ontology
Environment Ontology

11. Organism-Level Process
CONTINUANT
OCCURRENT
INDEPENDENT
DEPENDENT
ORGAN AND
ORGANISM
Organism
(NCBI
Taxonomy)
Anatomical Entity
(FMA, CARO)
Organ
Function
(FMP, CPRO)
Phenotypic Quality (PaTO)
Organism-Level Process
(GO)
CELL AND CELLULAR COMPONENT
Cell
(CL)
Cellular Component
(FMA, GO)
Cellular Function
Cellular Process
MOLECULE
Molecule
(ChEBI, SO,
RNAO, PRO)
Molecular Function
Molecular Process
RELATION TO TIME
GRANULARITY
rationale of OBO Foundry coverage

12. OBO Foundry approach extended into other domains
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

13. Basic Formal Ontology (BFO)
Modular organization + Extension strategy
top level
domain level
Basic Formal Ontology (BFO)
Anatomy Ontology
(FMA*, CARO)
Environment
Ontology
(EnvO)
Infectious Disease Ontology
(IDO*)
Biological Process
Ontology (GO*)
Cell Ontology
(CL)
Cellular
Component
(FMA*, GO*)
Phenotypic Quality
Ontology (PaTO)
Subcellular Anatomy Ontology (SAO)
Sequence Ontology
(SO*)
Molecular Function
(GO*)
Protein Ontology
(PRO*)
* = dedicated NIH funding

14. ~100 ontologies using BFO US 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) …

15. Basic Formal Ontology BFO BFO:Entity BFO:Continuant BFO:Occurrent
BFO:Process
BFO:Independent Continuant
BFO:Dependent Continuant
BFO:Disposition
Mental functioning related anatomical structure: an anatomical structure in which there inheres the disposition to be the agent of a mental process
Behaviour inducing state: a bodily quality inhering in a mental functioning related anatomical structure which leads to behaviour of some sort
Affective representation: a cognitive representation sustained by an organism about its own emotions
Cognitive representation: a representation which specifically depends on an anatomical structure in the cognitive system of an organism
Mental process: a bodily process which brings into being, sustains or modifies a cognitive representation or a behaviour inducing state
Friday, September 21, 2018

16. Basic Formal Ontology and Mental Functioning Ontology (MFO)
BFO:Entity
BFO
BFO:Continuant
BFO:Occurrent
MFO
BFO:Process
BFO:Independent Continuant
BFO:Dependent Continuant
Bodily Process
Organism
BFO:Disposition
Mental functioning related anatomical structure: an anatomical structure in which there inheres the disposition to be the agent of a mental process
Behaviour inducing state: a bodily quality inhering in a mental functioning related anatomical structure which leads to behaviour of some sort
Affective representation: a cognitive representation sustained by an organism about its own emotions
Cognitive representation: a representation which specifically depends on an anatomical structure in the cognitive system of an organism
Mental process: a bodily process which brings into being, sustains or modifies a cognitive representation or a behaviour inducing state
Cognitive Representation
BFO:Quality
Mental Process
Mental Functioning Related Anatomical Structure
Behaviour inducing state
Affective Representation
Friday, September 21, 2018

17. Emotion Ontology extends MFO
BFO:Entity
BFO
MFO
BFO:Continuant
BFO:Occurrent
MFO-EM
BFO:Independent Continuant
BFO:Dependent Continuant
BFO:Process
Organism
Bodily Process
BFO:Disposition
Physiological Response to Emotion Process
Mental Process
Cognitive Representation
inheres_in
Appraisal Process
Emotional Action Tendencies
Affective Representation
is_output_of
Appraisal
Emotional Behavioural Process
Subjective Emotional Feeling
has_part
agent_of
Emotion Occurrent

18. Sample from Emotion Ontology: Types of Feeling
The subjective feeling component of the emotion. These avoid sounding tautological/repetitive by focusing on distinct separable aspects of the feeling. It would be strange to include subjective feelings as separate components in the ontology if the best we could manage would be terms such as ‘feeling angry’, ‘feeling frightened’. Still, those sorts of feelings are often referred to in the scientific literature.
Friday, September 21, 2018

19. The problem of joint / coalition operations Civil-Military Operations
Intelligence
Fire Support
Targeting
Maneuver &
Blue Force Tracking
Civil-Military Operations
Air Operations
Logistics

20. US DoD Civil Affairs strategy for non-classified information sharing
from Gerard Christman

21. Ontologies / semantic technology can help to solve this problem
Intelligence
Fire Support
Targeting
Maneuver &
Blue Force Tracking
Civil-Military Operations
Air Operations
Logistics

22. But each community produces its own ontology,
this will merely create new, semantic siloes
Intelligence
Fire Support
Targeting
Maneuver &
Blue Force Tracking
Civil-Military Operations
Air Operations
Logistics

23. What we are doing to avoid the problem of semantic siloes
Distributed Development of a Shared Semantic Resource
Pilot testing to demonstrate feasibility

24. Basic Formal Ontology (BFO)
creating the analog of this in the military domain
top level
domain level
Basic Formal Ontology (BFO)
Anatomy Ontology
(FMA*, CARO)
Environment
Ontology
(EnvO)
Infectious Disease Ontology
(IDO*)
Biological Process
Ontology (GO*)
Cell Ontology
(CL)
Cellular
Component
(FMA*, GO*)
Phenotypic Quality
Ontology (PaTO)
Subcellular Anatomy Ontology (SAO)
Sequence Ontology
(SO*)
Molecular Function
(GO*)
Protein Ontology
(PRO*)
* = dedicated NIH funding

25. 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 training

26. 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?

27. 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

28. Reference Ontology Application Ontology
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

29. Reference Ontology Application Ontology
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

30. AIRS Reference Ontologies
Basic Formal Ontology (BFO)
Extended Relation Ontology
Information Entity Ontology
Agent Ontology
Event Ontology
Time Ontology
Artifact Ontology
Geospatial Ontology
Quality Ontology

31. Agent Ontology
Social Network, Skills, and Occupations

32. Event Ontology
Actions, Natural Events and Time-Dependent Attributes

33. Geospatial Ontology
Regions, Geopolitical Entities, Geographic Features, and Locations

38. An example of agile application ontology development: The Bioweapons Ontology (BWO)

39. Kinds of chemical and biological weapons
Nerve agents (sarin gas)
Blister agents (mustard gas)
Blood agents (cyanide gas)
Biological
Infectious agents – BWO(I)
Toxic agents (botulinum toxin, ricin) – BWO(T)

40. We focus here on BWO(I) Infectious agents
Bacterial (anthrax, bubonic plague, tularemia, brucellosis, cholera …)
Viral (Ebola, Marburg …)

41. Examples of ontology terms
BFO
IDO
StaphIDO
Independent Continuant
Infectious disorder
Staph. aureus
disorder
Dependent Continuant
Infectious disease
Protective resistance
MRSA
Methicillin resistance
Occurrent
Infectious disease course
MRSA course

42. Infectious Disease Ontology (IDO)
with thanks to Lindsay Cowell (University of Texas SW Medical Center) and Albert Goldfain (Blue Highway, Inc.)
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
Aims to overcome some of these obstacles.
Ontologically correct natural language defs.

43. 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)
Subscribing to IDO core means agreeing to a semantics. Without bias to any dimension.

44. Examples of ontology terms
BFO
IDO
StaphIDO
Independent Continuant
Infectious disorder
Staph. aureus
disorder
Dependent Continuant
Infectious disease
Protective resistance
MRSA
Methicillin resistance
Occurrent
Infectious disease course
MRSA course

45. IDO Extensions IDO – Brucellosis IDO – Dengue Fever IDO – Influenza
IDO – Malaria
IDO – Staphylococcus Aureus Bacteremia
IDO – Vector Surveillance and Management
IDO – Plant
VO – Vaccine Ontology
BWO(I) – Bioweapons Ontology (Infectious Agents)

46. How IDO evolves: the case of Staph. aureus
IDOMAL
IDOCore
IDOHIV
HUB and
SPOKES:
Domain
ontologies
IDOFLU
IDORatSa
IDORatStrep
IDOStrep
IDOSa
SEMI-LATTICE:
By subject matter experts in different communities of interest.
IDOMRSa
IDOAntibioticResistant
Growth
Micro ontologies for particular diseases that inherit terms and axioms about host-pathogen interaction. Evolve in a cross-producty way…so if you are interested in frog pneumonia, IDO Core has you covered.
IDOHumanSa
IDOHumanStrep
IDOHumanBacterial

50. 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

51. Strategy used to build BWO(I) with thanks to Lindsay Cowell and Oliver He (Michigan)
Start with a glossary such as:
Select corresponding terms from IDO core and related ontologies such as the CHEBI Chemistry Ontology terms needed to describe bioweapons
All ontology terms keep their original definitions and IDs.
The result is a spreadsheet

52. no corresponding ontology term
5. Where glossary terms have no ontology equivalent, create BWO ontology terms and definitions as needed
no corresponding ontology term

53. 6. Use the Ontofox too to create the first version of the BWO(I) application ontology (
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

54. 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

55. 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