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Title: Command and Control Ontology - Informal Technical Exchange - Use of Ontologies in a World in Flux National Center for Ontological Research (NCOR) Buffalo, NY, USA, January 15-16, 2009


1
Command and Control Ontology - Informal Technical
Exchange - Use of Ontologies in a World in Flux
National Center for Ontological Research
(NCOR) Buffalo, NY, USA, January 15-16, 2009
  • Werner CEUSTERS, MD
  • Center of Excellence in Bioinformatics and Life
    Sciences

2
Presentation overview
  • The SAS-050 approach to Command Control
  • How the SAS-050 model relates to Basic Formal
    Ontology and Referent Tracking
  • Referent Tracking for C2
  • A battlefield scenario
  • Technical implementation of Referent Tracking
  • How Basic Formal Ontology and Referent Tracking
    meet the wish-list of SAS-050
  • Conclusion

3
Background for this presentation
  • EXPLORING NEW COMMAND AND CONTROL
  • CONCEPTS AND CAPABILITIES
  • Final Report
  • Prepared for NATO
  • January 2006

http//www.dodccrp.org/files/SAS-05020Final20Rep
ort.pdf
4
SAS-050s view on C2
  • Three major dimensions
  • allocation of decision rights across an
    enterprise,
  • permissible interactions among entities within
    the enterprise and between enterprise entities
    and others,
  • the way information flows and is disseminated.

5
C2 in action
6
C2 in action
in a world in flux
7
C2 in action
in a world in flux
Ground truth
8
C2 in action
Information and ground truth
9
C2 in action
Information and ground truth
How do they relate ?
10
SAS-050s view on information and ground truth
11
Characteristics for Inf. Quality and Reality
Perception
  • Ambiguity inability to make sense out of a
    situation, regardless of available INF.
  • Complexity situation is being faced with a
    situation made up of an interrelated set of
    variables, solutions, and stakeholders, each
    individually understood but which together exceed
    the processing capacity of the individual, the
    team, or organisation to synthesize.
  • Equivocality having multiple interpretations of
    the same INF.
  • Uncertainty not having sufficient INF to
    describe a current state or to forecast future
    states, preferred outcomes, or the actions needed
    to achieve them.
  • Situational familiarity the characteristic of
    having encountered or seen, or having knowledge
    of a situation.
  • Temporal focus the time into the future of an
    understanding or plan.
  • Accuracy the degree to which INF quality matches
    what is needed.
  • Completeness extent to which INF relevant to
    ground truth is collected.
  • Consistency extent to which INF is consistent
    with prior INF and consistent across sources.
  • Correctness extent to which INF is consistent
    with ground truth.
  • Currency difference between the current point in
    time and the time the INF was made available.
  • Precision level of measurement detail of INF
    item.
  • Relevance extent to which INF quality is
    relevant to the task at hand.
  • Timeliness extent to which currency of INF is
    suitable to its use the relationship between
    availability of the INF and when it is needed.
  • Uncertainty a fundamental attribute of war and
    pervades the battlefield in the form of unknowns
    about the enemy, the surroundings, and our own
    forces.
  • Sharability extent to which an element of INF is
    in a form or format understandable by all nodes
    in a network.
  • Source characteristics the traits of tools used
    to develop facts, data, or instructions in any
    form or medium (and all INF sources are
    reporters).

12
Relationships between the SAS-050
objectives and Ontology / Referent Tracking
13
SAS-050 solution
  • A Conceptual Model (CM) consisting of
  • A Reference Model containing over 300 variables
    and a selected subset of the possible
    relationships among them that were felt to be
    important to understand C2 and the implications
    of different approaches to C2.
  • A Value View which posits links in the value
    chain that lead from characteristics of the force
    and its approach to C2 to measures of mission and
    policy effectiveness, and finally to agility.

14
SAS-050s view on models
  • A model is an abstraction of reality for a
    purpose, consisting of a subset of variables and
    relationships that represent reality well
    enough.
  • The variables found within the model are factors,
    characteristics, or attributes of an entity that
    can take on different values.
  • The variables within the model have a number of
    relationships that reflect connections between
    and among other variables.

15
The fit with Philosophical Realism
  • Three levels of reality
  • First-order reality what is on the side of
    persons, organizations,
  • Cognitive representations what cognitive agents
    assume to observe and know in their mind
  • Representational artefacts for communication,
    documentation,
  • Terms, definitions, drawings, images,
  • Assumption about the quality of an ontology is
    at least determined by the accuracy with which
    its structure mimics the pre-existing structure
    of reality.
  • In SAS-050
  • ground truth / situations
  • mental models
  • information
  • about the model
  • acceptance
  • fit for purpose
  • never complete

Smith B, Kusnierczyk W, Schober D, Ceusters W.
Towards a Reference Terminology for Ontology
Research and Development in the Biomedical
Domain. Proceedings of KR-MED 2006, November 8,
2006, Baltimore MD, USA
16
Generic versus Specific entities
Generic
Specific
3. Representation
weapon
person
tank
John Doe
Enola Gay
2. Beliefs (knowledge)
GOAL
John Does plan
SACEURs strategy
ATTACK STRATEGY
1. First-order reality
Private John Doe
PERSON
building
John Does platoon
John Does gun
CORPSE
WEAPON
TANK
SOLDIER
Tank with serial number TH1280A44V
17
A simple battlefield ontology
object
Ontology
building
person
vehicle
weapon
corpse
submachine gun
tank
soldier
POW
mortar
car
18
Ontology used for annotating a situation
Ontology
Situation
19
Referent Tracking in action
20
Referent Tracking (RT) for representing a
situation
Ontology
Situational model
Situation
21
Advantages of Referent Tracking
  • Preserves identity

22
Referent Tracking preserves identity
Ontology
6
8
7
uses
Situational model
uses
uses
uses
2
3
4
10
Situation
23
Advantages of Referent Tracking
  • Preserves identity
  • Allows to assert relationships amongst entities
    that are not generically true

24
Specific relations versus generic relations
Ontology
Situational model
Situation
25
Specific relations versus generic relations
Ontology
uses
NOT faithful
Situational model
Situation
26
Advantages of Referent Tracking
  • Preserves identity
  • Allows to assert relationships amongst entities
    that are not generically true
  • Appropriate representation of the time when
    relationships hold

27
Temporal validity of specific relationships (1)
soldier
Ontology
private
sergeant
sergeant-major
Situational model
3
Situation
28
Temporal validity of specific relationships (2)
Ontology
5
6
uses at t1
Situational model
uses at t1
1
2
Situation
29
Temporal validity of specific relationships (2)
Ontology
uses at t2
5
after the death of 1
Situational model
at t2
1
2
Situation
30
Advantages of Referent Tracking
  • Preserves identity
  • Allows to assert relationships amongst entities
    that are not generically true
  • Appropriate representation of the time when
    relationships hold
  • Deals with conflicting representations by keeping
    track of sources

31
Source of information
Ontology
corpse
asserts at t2
5
6
uses at t2
Situational model
uses at t1
uses at t1
at t3
1
2
Situation
32
Source of information
Ontology
corpse
asserts at t4
5
6
uses at t2
Situational model
uses at t1
uses at t1
at t3
1
2
Situation
33
Advantages of Referent Tracking
  • Preserves identity
  • Allows to assert relationships amongst entities
    that are not generically true
  • Appropriate representation of the time when
    relationships hold
  • Deals with conflicting representations by keeping
    track of sources
  • Mimics the structure of reality

34
Referent Tracking and the structure of reality
Level 1, 2 or 3
Level 2 or 3
Level 3
Level 1
unique identifiers
35
Remind the 3-level distinction
  • Level 1
  • 120 an incident that happened
  • Level 2
  • 213 the interpretation by some cognitive agent
    that 120 is an security breach
  • 31 the expectation by some cognitive agent that
    similar incidents might happen in the future
  • Level 3
  • 402 an entry in and information system
    concerning 120
  • 1503 an entry in some other information system
    about 31 for mitigation or prevention purposes.

36
Advantages of Referent Tracking
  • Preserves identity
  • Allows to assert relationships amongst entities
    that are not generically true
  • Appropriate representation of the time when
    relationships hold
  • Deals with conflicting representations by keeping
    track of sources
  • Mimics the structure of reality
  • Allows for corrections without distorting what
    was originally believed

37
Mismatches between reality and representations
  • Some possibilities
  • 120 with unjustified absence of 213
  • 120 was not perceived at all, or not assessed as
    being a security breach
  • Unjustified presence of 213
  • There was no 120 at all, or 120 was not a
    security breach
  • Unjustified absence of 402
  • Same reasons as under (1) above
  • Justified presence of 213 but not reported in
    the information system

Ceusters W, Smith B. A Realism-Based Approach to
the Evolution of Biomedical Ontologies. Proceeding
s of AMIA 2006, Washington DC, 2006121-125.
38
Multiple scenarios of co-existence
Past incident related Past incident related Past incident related Mitigation related Mitigation related
breach happened incident perception Information system entry Interpreted Registered
Case 120 213 402 31 1503
1 - - - -
2 - - -
3 - -
4 -
5 - -
6 -
7
8 - - - - -
9 - - - -
10 - - -
11 - -
12 - - -
13 - -
14 -
Only cases 7 and 8 are faithful, justified
presence and absence respectively
39
Need for change and belief management
  • Distinct sensors may hold different beliefs about
    whether a specific incident (e.g. 1)
  • really happened,
  • is of a specific sort,
  • counts as a security breach
  • depending on what definition or rules they apply.
  • They may differ in beliefs about
  • what caused the incident,
  • how to prevent future happenings of incidents of
    the same sort.
  • They may change their beliefs over time.

40
Keep in mind
  • Whether an incident is a security breach (under
    one or more definitions)
  • is a matter of objective fact,
  • is not a matter of consensus.
  • What are matters of consensus, are
  • definitions for what should be counted security
    breaches
  • but,
  • they can be applied wrongly,
  • they can be themselves in error
  • policies about registration,
  • policies about mitigation and prevention,
  • although, whether they are effective, is again a
    matter of objective fact.

41
Advantages of Referent Tracking
  • Preserves identity
  • Allows to assert relationships amongst entities
    that are not generically true
  • Appropriate representation of the time when
    relationships hold
  • Deals with conflicting representations by keeping
    track of sources
  • Mimics the structure of reality
  • Allows for corrections without distorting what
    was originally believed
  • Fully compatible with semantic web technologies

42
Implementing Referent Tracking
43
Explicit referential semantics through RT-tuples
(1)
Situational model tuples
Tuple name Attributes Description Tuple name Attributes Description
A-tuple lt IUIa, IUIp, tapgt
Act of assignment of IUIp to a particular at time tap by the particular referred to by author IUIa Act of assignment of IUIp to a particular at time tap by the particular referred to by author IUIa
PtoP-tuple ltIUIa, ta, r, IUIo, P, trgt
The particular referred to by IUIa asserts at time ta that the relationship r from ontology IUIo obtains between the particulars referred to in the set of IUIs P at time tr. The particular referred to by IUIa asserts at time ta that the relationship r from ontology IUIo obtains between the particulars referred to in the set of IUIs P at time tr.
PtoN lt IUIa, ta, ntj, ni, IUIp, tr, IUIcgt
The particular referred to by IUIa asserts at time ta that ni is the name of the nametype ntj used by IUIc to denote the particular referred to by IUIp at tr. The particular referred to by IUIa asserts at time ta that ni is the name of the nametype ntj used by IUIc to denote the particular referred to by IUIp at tr.
44
Explicit referential semantics through RT-tuples
(2)
Linking situational models with ontologies and
terminologies
Tuple name Attributes Description Tuple name Attributes Description
PtoU-tuple ltIUIa, ta, inst, IUIo, IUIp, UUI, trgt
The particular referred to by author IUIa asserts at time ta that the particular referred to by IUIp instantiates by means of the inst relation defined in ontology IUIo the universal UUI at time tr. The particular referred to by author IUIa asserts at time ta that the particular referred to by IUIp instantiates by means of the inst relation defined in ontology IUIo the universal UUI at time tr.
PtoC-tuple ltIUIa, ta, IUIc, IUIp, CUI, trgt
The particular referred to by IUIa asserts at time ta that at time tr concept code CUI from terminology system IUIc is an accurate term for IUIp The particular referred to by IUIa asserts at time ta that at time tr concept code CUI from terminology system IUIc is an accurate term for IUIp
PtoU(-) -tuple ltIUIa, ta, r, IUIo, IUIp, UUI, trgt
The particular referred to by IUIa asserts at time ta that the relation r of ontology IUIo does not obtain at time tr between the particular referred to by IUIp and any of the instances of the universal denoted by UUI at time tr. The particular referred to by IUIa asserts at time ta that the relation r of ontology IUIo does not obtain at time tr between the particular referred to by IUIp and any of the instances of the universal denoted by UUI at time tr.
45
Explicit referential semantics through RT-tuples
(3)
Validity and availability of information
Tuple name Attributes Description Tuple name Attributes Description
D-tuple lt IUId, IUIA, td, E, C, S gt
The particular referred to by IUId registers the particular referred to by IUIA (the IUI for the corresponding A-tuple) at time td. E is either the symbol I (for insertion) or any of the error type symbols as defined in 1. C is the reason for inserting the A-tuple. S is a list of IUIs denoting the tuples, if any, that replace the retired one. The particular referred to by IUId registers the particular referred to by IUIA (the IUI for the corresponding A-tuple) at time td. E is either the symbol I (for insertion) or any of the error type symbols as defined in 1. C is the reason for inserting the A-tuple. S is a list of IUIs denoting the tuples, if any, that replace the retired one.
  • A D-tuple is inserted
  • to resolve mistakes in RTS, and
  • whenever a new tuple other than a D-tuple is
    inserted in the RTS.

1 Ceusters W. Dealing with Mistakes in a
Referent Tracking System. In Hornsby KS (eds.)
Proceedings of Ontology for the Intelligence
Community 2007 (OIC-2007), Columbia MA, 28-29
November 20075-8.
46
Referent Tracking System Components
  • Referent Tracking Software
  • Manipulation of statements about facts and
    beliefs
  • Referent Tracking Datastore
  • IUI repository
  • A collection of globally unique singular
    identifiers denoting particulars
  • Referent Tracking Database
  • A collection of facts and beliefs about the
    particulars denoted in the IUI repository

Manzoor S, Ceusters W, Rudnicki R. Implementation
of a Referent Tracking System. International
Journal of Healthcare Information Systems and
Informatics 20072(4)41-58.
47
Referent Tracking System Environment
48
Networks of Referent Tracking systems
49
An example Tracking a Request to View a Web Page
50
Tuple insertions
A-tuples A-tuples A-tuples A-tuples A-tuples
n IUIp IUIa tap Key
1 24 2 (EVENT("24 assignment") has-occ AT TP(time-18)) 25
3 27 2 (EVENT("27 assignment") has-occ AT TP(time-20)) 28
9 34 2 (EVENT("34 assignment") has-occ AT TP(time-26)) 35
D-tuples D-tuples D-tuples D-tuples D-tuples D-tuples D-tuples D-tuples
n IUId IUIA td E C S Key
2 2 25 (EVENT("25 inserted") has-occ AT TP(time-19)) I CE 26
4 2 28 (EVENT("28 inserted") has-occ AT TP(time-21)) I CE 29
6 2 30 (EVENT("30 inserted") has-occ AT TP(time-23)) I CE 31
8 2 32 (EVENT("32 inserted") has-occ AT TP(time-25)) I CE 33
10 2 35 (EVENT("35 inserted") has-occ AT TP(time-27)) I CE 36
12 2 37 (EVENT("37 inserted") has-occ AT TP(time-29)) I CE 38
PtoP-tuples PtoP-tuples PtoP-tuples PtoP-tuples PtoP-tuples PtoP-tuples PtoP-tuples PtoP-tuples
n IUIa ta r IUIo P tr Key
5 2 (EVENT("30 is asserted") has-occ AT TP(time-22)) MainContentCopyOf 022 27, 12 (EPISODE("30 is true") has-occ SINCE TI(time-20)) 30
7 2 (EVENT("32 is asserted") has-occ AT TP(time-24)) InstigatorOf 022 24, 27 (EVENT ("32 is true") has-occ AT TP(time-18)) 32
11 2 (EVENT("37 is asserted") has-occ AT TP(time-28)) ChecksumOf 022 34, 27 (EPISODE("37 is true") has-occ SINCE TI(time-26)) 37
51
Another example domotics and RFID systems
  • Avoiding adverse events in a hospital because of
    insufficient day/night illumination
  • Light sensors and motion detectors in rooms and
    corridors
  • and representations thereof in an Adverse Event
    Management System (AEMS)
  • What are sufficient illumination levels for
    specific sites is expressed in defined classes,
  • Each change in a detector is registered in real
    time in the AEMS,
  • Action-logic implemented in a rule-base system,
    f.i. to generate alerts.

52
RT-based representation (1) IUI assignment
Reality level 1
1 that corridor
2 that lamp
3 that motion detector
4 that light detector
5 that RFID reader
6 that patient with RFID 7
8 that RFID reader
9 this elevator
10 2nd floor of clinic B
53
RT-based representation (2) relationships
  • (Semi-)stable relationships
  • 1 instance-of ReMCorridor since t1
  • 2 instance-of ReMLamp since t2
  • 2 contained-in 1 since t3
  • 6 member-of ReMPatient since t4
  • 6 adjacent-to 7 since t4
  • 18 instance-of ReMIllumination since t1
  • 18 inheres-in 1 since t1
  • Semi-stable because of
  • lamps may be replaced
  • persons are not patients all the time
  • ? keeping track of these changes provides a
    history for each tracked entity

54
RT-based representation (3) rule base
  • Setting illumination requirements for lamp 2
  • 18 member-of ReMInsufficient illumination
    during ty
  • if
  • tx part-of ReMDaytime
  • y1 instance-of ReMMotion-detection
  • y1 has-agent 3 at ty
  • ty part-of tx
  • y2 instance-of ReMIllumination measurement
  • y2 has-agent 4 at ty
  • y2 has-participant 18 at ty
  • y2 has-result imrz at ty
  • imrz less-than 30 lumen
  • else
  • tx part-of ReMNight time
  • endif

Exact format to be discussed with ReMINE
partners
55
RT-based representation of events
  • Imagine 6 (with RFID 7) walking through 1
  • 2345 instance-of ReMMotion-detection
  • 2345 has-agent 3 at t4
  • 2346 instance-of ReMRFID-detection
  • 2346 has-agent 5 at t4
  • 2346 has-participant 7 at t4
  • Here, the happening of 2345 fires the rule
    explained on the previous slide.
  • If imrz turns out to be too low, that might
    invoke another rule which sends an alert to the
    ward that lamp 2 might be broken.
  • 2346 might trigger yet another rule, namely an
    alert for imminent danger for AE with respect to
    patient 6

56
Suitability of Basic Formal Ontology and
Referent Tracking for a SAS-050 implementation
  • (Focus on Information Quality)

57
RT and SAS-050 INF quality everything is
computable!
  • Accuracy the degree to which INF quality matches
    what is needed.
  • Completeness extent to which INF relevant to
    ground truth is collected.
  • Consistency extent to which INF is consistent
    with prior INF and consistent across sources.
  • Correctness extent to which INF is consistent
    with ground truth.
  • Currency difference between the current point in
    time and the time the INF was made available.
  • Precision level of measurement detail of INF
    item.
  • Relevance extent to which INF quality is
    relevant to the task at hand.
  • Timeliness extent to which currency of INF is
    suitable to its use the relationship between
    availability of the INF and when it is needed.
  • Uncertainty a fundamental attribute of war and
    pervades the battlefield in the form of unknowns
    about the enemy, the surroundings, and our own
    forces.
  • Sharability extent to which an element of INF is
    in a form or format understandable by all nodes
    in a network.
  • Source characteristics the traits of tools used
    to develop facts, data, or instructions in any
    form or medium (and all INF sources are
    reporters).
  • Representation of need and relevance in
    ontologies, plans and policies,
  • INF accumulates in RT-tuples,
  • Accuracy and relevance computable over the
    difference between the former and the latter.

58
RT and SAS-050 INF quality everything is
computable!
  • Accuracy the degree to which INF quality matches
    what is needed.
  • Completeness extent to which INF relevant to
    ground truth is collected.
  • Consistency extent to which INF is consistent
    with prior INF and consistent across sources.
  • Correctness extent to which INF is consistent
    with ground truth.
  • Currency difference between the current point in
    time and the time the INF was made available.
  • Precision level of measurement detail of INF
    item.
  • Relevance extent to which INF quality is
    relevant to the task at hand.
  • Timeliness extent to which currency of INF is
    suitable to its use the relationship between
    availability of the INF and when it is needed.
  • Uncertainty a fundamental attribute of war and
    pervades the battlefield in the form of unknowns
    about the enemy, the surroundings, and our own
    forces.
  • Sharability extent to which an element of INF is
    in a form or format understandable by all nodes
    in a network.
  • Source characteristics the traits of tools used
    to develop facts, data, or instructions in any
    form or medium (and all INF sources are
    reporters).
  • Remain essentially unknown at T0,
  • Can for the past be calculated using
  • Can be forecasted using
  • Ceusters W. Applying Evolutionary
    Terminology Auditing to the Gene Ontology.
    Journal of Biomedical Informatics 2009 (in
    press).

59
RT and SAS-050 INF quality everything is
computable!
  • Accuracy the degree to which INF quality matches
    what is needed.
  • Completeness extent to which INF relevant to
    ground truth is collected.
  • Consistency extent to which INF is consistent
    with prior INF and consistent across sources.
  • Correctness extent to which INF is consistent
    with ground truth.
  • Currency difference between the current point in
    time and the time the INF was made available.
  • Precision level of measurement detail of INF
    item.
  • Relevance extent to which INF quality is
    relevant to the task at hand.
  • Timeliness extent to which currency of INF is
    suitable to its use the relationship between
    availability of the INF and when it is needed.
  • Uncertainty a fundamental attribute of war and
    pervades the battlefield in the form of unknowns
    about the enemy, the surroundings, and our own
    forces.
  • Sharability extent to which an element of INF is
    in a form or format understandable by all nodes
    in a network.
  • Source characteristics the traits of tools used
    to develop facts, data, or instructions in any
    form or medium (and all INF sources are
    reporters).
  • Can be computed using the author-attributes of
    the RT-tuples and the presence of D-tuples using
    corrections,
  • Allows even to compute the quality of sources.

60
RT and SAS-050 INF quality everything is
computable!
  • Accuracy the degree to which INF quality matches
    what is needed.
  • Completeness extent to which INF relevant to
    ground truth is collected.
  • Consistency extent to which INF is consistent
    with prior INF and consistent across sources.
  • Correctness extent to which INF is consistent
    with ground truth.
  • Currency difference between the current point in
    time and the time the INF was made available.
  • Precision level of measurement detail of INF
    item.
  • Relevance extent to which INF quality is
    relevant to the task at hand.
  • Timeliness extent to which currency of INF is
    suitable to its use the relationship between
    availability of the INF and when it is needed.
  • Uncertainty a fundamental attribute of war and
    pervades the battlefield in the form of unknowns
    about the enemy, the surroundings, and our own
    forces.
  • Sharability extent to which an element of INF is
    in a form or format understandable by all nodes
    in a network.
  • Source characteristics the traits of tools used
    to develop facts, data, or instructions in any
    form or medium (and all INF sources are
    reporters).
  • Can be computed using the various temporal
    attributes of the RT-tuples
  • D-tuples specify when INF was entered,
  • Other tuples specify when relationships hold or
    when entities come and go.

61
RT and SAS-050 INF quality everything is
computable!
  • Accuracy the degree to which INF quality matches
    what is needed.
  • Completeness extent to which INF relevant to
    ground truth is collected.
  • Consistency extent to which INF is consistent
    with prior INF and consistent across sources.
  • Correctness extent to which INF is consistent
    with ground truth.
  • Currency difference between the current point in
    time and the time the INF was made available.
  • Precision level of measurement detail of INF
    item.
  • Relevance extent to which INF quality is
    relevant to the task at hand.
  • Timeliness extent to which currency of INF is
    suitable to its use the relationship between
    availability of the INF and when it is needed.
  • Uncertainty a fundamental attribute of war and
    pervades the battlefield in the form of unknowns
    about the enemy, the surroundings, and our own
    forces.
  • Sharability extent to which an element of INF is
    in a form or format understandable by all nodes
    in a network.
  • Source characteristics the traits of tools used
    to develop facts, data, or instructions in any
    form or medium (and all INF sources are
    reporters).
  • Determined by
  • The sensor which identifies an entity as a
    distinct being,
  • The ontology used to characterize the entity as
    being of a specific type.

62
RT and SAS-050 INF quality everything is
computable!
  • Accuracy the degree to which INF quality matches
    what is needed.
  • Completeness extent to which INF relevant to
    ground truth is collected.
  • Consistency extent to which INF is consistent
    with prior INF and consistent across sources.
  • Correctness extent to which INF is consistent
    with ground truth.
  • Currency difference between the current point in
    time and the time the INF was made available.
  • Precision level of measurement detail of INF
    item.
  • Relevance extent to which INF quality is
    relevant to the task at hand.
  • Timeliness extent to which currency of INF is
    suitable to its use the relationship between
    availability of the INF and when it is needed.
  • Uncertainty a fundamental attribute of war and
    pervades the battlefield in the form of unknowns
    about the enemy, the surroundings, and our own
    forces.
  • Sharability extent to which an element of INF is
    in a form or format understandable by all nodes
    in a network.
  • Source characteristics the traits of tools used
    to develop facts, data, or instructions in any
    form or medium (and all INF sources are
    reporters).
  • Guaranteed through
  • The standard syntax and referential semantics of
    RT-tuples,
  • The P2P and service oriented architecture of the
    RT system.

63
Summary and Conclusion
64
Summary and Conclusion
  • SAS-050, perhaps unknowingly, follows a realist
    agenda to achieve specific goals,
  • Basic Formal Ontology (BFO) and Referent Tracking
    (RT), on purpose, follow this agenda with broader
    objectives in mind
  • BFO to represent what is generic in reality
  • RT to represent what is specific and relevant
  • Implementations of BFO and RT do not replace
    C2-systems, but, when integrated with them,
    provide added value in terms of, for example
  • Enhanced sharability and semantic
    interoperability,
  • Unambiguous understanding of data using reality
    as benchmark,
  • Complete history of what happened, what was
    believed about it, and what communicated.
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