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

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

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

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

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

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 …)

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

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

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

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

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

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

~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) …

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

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

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

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

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

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

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

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

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

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

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

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?

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

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

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

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

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

http://milportal.org

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

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) http://www.enquirer.com/editions/1999/01/09/loc_types_of_chemical.html

We focus here on BWO(I) Infectious agents Bacterial (anthrax, bubonic plague, tularemia, brucellosis, cholera …) Viral (Ebola, Marburg …) http://www.slic2.wsu.edu:82/hurlbert/micro101/pages/101biologicalweapons.html#viralBW

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

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.

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.

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

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)

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

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

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

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

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