Download - Walking Up and Down the Abstraction Ladder: Reflections about the TAMI Project Carlos Delgado Kloos
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Walking Up and Down the Abstraction Ladder: Reflections about the TAMI ProjectCarlos Delgado Kloos<[email protected]><[email protected]>
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Logic and Law
The first logicians were lawyers... there are famous mathematicians
that were also lawyers (Leibniz)... but Legal Systems are far
from being Logic Systems.
Why is it taking so long?
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Two Essential Points
1) The concepts Defining the right concepts Evolving them over time
2) The reasoning Finding the right logic
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Scenario 3
JOHN DOEFlies LGA-ORD
(LaGuardia – O’Hare)June 2004
AIRLINECreates a PNR
(“Passenger Name Record”)
COMMERCIAL DATA VENDOR
Provides match data
Terrorism ScreeningCenter (TSC)
Provides “no fly” list
National CounterterrorismCenter (NCTC)
Provides “stripped” version of aggregated dataset -
known & suspected terrorists
Transportation SecurityAdministration (TSA)
Finds a “possible” matchwhile testing
Secure Flight program
Joint Terrorism Task Force (JTTF)
Seeks evidence of other clear legal violation
NY StateDept. of State
Website search revealsJohn Doe is
“deadbeat dad”
JOHN DOEIs arrested
Scenario 5
Scenario 3
JOHN DOEFlies LGA-ORD
(LaGuardia – O’Hare)June 2004
AIRLINECreates a PNR
(“Passenger Name Record”)
COMMERCIAL DATA VENDOR
Provides match data
Terrorism ScreeningCenter (TSC)
Provides “no fly” list
National CounterterrorismCenter (NCTC)
Provides “stripped” version of aggregated dataset -
known & suspected terrorists
Transportation SecurityAdministration (TSA)
Finds a “possible” matchwhile testing
Secure Flight program
Joint Terrorism Task Force (JTTF)
Seeks evidence of other clear legal violation
NY StateDept. of State
Website search revealsJohn Doe is
“deadbeat dad”
JOHN DOEIs arrested
Scenario 4
TAMI Scenarios
Scenario 3
JOHN DOEFlies LGA-ORD
(LaGuardia – O’Hare)June 2004
AIRLINECreates a PNR
(“Passenger Name Record”)
COMMERCIAL DATA VENDOR
Provides match data
Terrorism ScreeningCenter (TSC)
Provides “no fly” list
National CounterterrorismCenter (NCTC)
Provides “stripped” version of aggregated dataset -
known & suspected terrorists
Transportation SecurityAdministration (TSA)
Finds a “possible” matchwhile testing
Secure Flight program
Joint Terrorism Task Force (JTTF)
Seeks evidence of other clear legal violation
NY StateDept. of State
Website search revealsJohn Doe is
“deadbeat dad”
JOHN DOEIs arrested
Scenario 3
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Scenario 3:pnr-1
a :Transfer
:flight-test-search-1a :Search
:transfer-1a :Transfer
:open-investigation-1a :OpeningCase
:assignment-1a :Assignment
:assignment-2a :Assignment
:open-source-search-2a :Search
j:Arrest
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Architecture
cwm
Schema
Rules
Data Data’
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Rules# if data transferred to SOR, purposes intersect with purposes of appl.
SORN{ X a ProofNode. G a TamiData. G log:includes { X ts:purpose P; ts:recipient R }. G log:includes { R ts:notice S }. G log:includes { S a ts:SORN; ts:purpose P }.} => { X sorn S; purpose P; a JustifiedNode; recipient R }.
# if data transferred out of SOR, intersect with purposes of routine use { X a ProofNode. G a TamiData. G log:includes { X ts:purpose P; ts:source R; ts:antecedent Y }. G log:includes { R ts:notice S }. G log:includes { S a ts:SORN; ts:routineUse [ ts:purpose P ] }.} => { X purpose P; a JustifiedNode; source R }.
# if transaction has no purpose, it retains the purpose of its antecedent{ X a JustifiedNode; purpose P. G a TamiData. G log:includes { Y ts:antecedent X }. G log:includes { Y ts:purpose tb:any-purpose }.} => { Y purpose P; a JustifiedNode. }.
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An Ontology for TAMI Scenario 3
Classes defined in RDF/Notation3: Person
PersonName, Location, Organization
DataRecord Database, Flight, File
Event Search, Transfer, Assignment, CaseOpening,
WarrantIssue
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Person PersonName
Subject
Official
name
LocationhomeAddress
Organization
work
xsd:DatebirthDate
Person
Employment
position
EmploymentPosition
employer
Location
address
Victim Suspect
domain range
subClassOf
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PersonName
u:personSurName
u:personMiddleName
u:personGivenName
Literal
Location
u:locationStateName
u:locationCityName
u:locationAddress
Organization organizationName
u:locationPostalCodeIDAddress
Person (cont.)
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PassengerNameRecord
Databasesource
Personpassenger
Flightflight
Flight
xsd:Datedate
Literalnumber
air:Iataorigin
air:Iatadestination
DataRecord
DataRecordxsd:Datedate
Organization
owner
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Event
xsd:Datedate
Literalname
Search Transfer Assignment CaseOpening WarrantIssue
Reasontrigger
Event
OrganizationlogOwner
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John Doe lives in New York
Lifting up the strings
Web
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Lifting up the strings
Person homeAddress Location
name u:locationStateName
John Doe lives in New YorkWeb
SW
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Lifting up the strings
PersonName homeAddress Location
u:personGivenName u:locationStateName
Person
name
u:personLastName
John Doe lives in New YorkWeb
SW
SWSSW
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Questions
Which concepts (classes and properties) to define? How are they related?
How many levels of abstraction to use? Is there a natural number of them? Is there such a thing as the semantics?
How do the defined concepts relate to concepts defined elsewhere? How to define categories of concepts?
How useful for future scenarios are the concepts defined?
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Conceptualization
Ontologies are used in many areas with success
has an commonsense ontology with 300,000 terms
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Conceptualization: Difficulties "Concepts are the glue that
holds our mental world together" Necessity of category fuzziness,
typicality of items:is a telephone furniture,is an olive a fruit?
Absence of transivityfor category membership: a chair is furniture,a car seat is a chair,but is a car seat furniture?
– Gregory L. Murphy:The Big Book of Concepts, MIT Press 2004
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Example 1: Concept ‘Book’
What is a book? It is a clear concept!
It has an author a title ...
Right? Wrong!
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FRBR: 4 Concepts for ‘Book’
Functional Requirementsfor Bibliographic Records 1) Work: distinct intellectual or artistic creation 2) Expression: specific intellectual or artistic
form that a work takes each time it is 'realized' 3) Manifestation: physical embodiment of an
expression of a work 4) Item: a single exemplar of a manifestation
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Book Hierarchy
Work Expression Manifestation Item
EN
ES
DE
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Book in RDF
Work
realized through
Expression
embodied in
Manifestation
exemplified by
Item
Don Quijote
Don Quijote
Don Quijote
Don Quijote
realized through
embodied in
exemplified by
written byM. Cervantes
John Ormsby
8420467286
Shelf A.1
translated by
ISBN
location
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Equivalences forWorks and Expressions
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Example 2: Carlos I am Carlos No, this is my name in Spanish
(in English it would be Charles) No, this is the textual representation of my
name in Spanish (the sound representation is )
No, this is a particular image of … (another is Carlos)
No, this is what you see of the image… …
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Carlos Hierarchy
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Equivalence
Notion of equivalence Going up one level, implies putting a
number of objects in the same equivalence class
We might characterize by means of a representative
Semantics is abstraction
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Carlos in RDF
Person nameES Word
Carlos CarlosnameES
text String
Carlostext
…
…
semantics syntax
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Eliminating levels
Is the left lane turning left,or the cars on it?
Do you get an e-mailor an e-mail message?
What is “Carlos”?(a Person, a Name,a Text, an Image, …)
What do you mean by “book”?
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Implicit Abstraction Levels
It is fundamental to recognize
that normal text will make
some abstraction levels implicit
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Implicit Abstraction Levels
At any moment, it is possible to introduce additional abstraction levels
When I say this, I mean that
Lifting to complex data structures with no explicit symbol [1,2,3] + [4,5,6] = [5,7,9]
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Example 3:Through the Looking Glass `The name of the song is called "Haddocks' Eyes".' `Oh, that's the name of the song, is it?' Alice said, trying
to feel interested. `No, you don't understand,' the Knight said, looking a little
vexed. `That's what the name is called. The name really is "The Aged Aged Man".'
`Then I ought to have said "That's what the song is called"?' Alice corrected herself.
`No, you oughtn't: that's quite another thing! The song is called "Ways and Means": but that's only what it's called, you know!'
`Well, what is the song, then?' said Alice, who was by this time completely bewildered.
`I was coming to that,' the Knight said. `The song really is "A-sitting On a Gate": and the tune's my own invention.'
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Through the Looking Glassin RDF
Song named Name
calledLiteral
A-sittingOn a Gate
The AgedAged Man
Haddocks' Eyes
named
called
calledLiteral
Ways andMeans
called
domaindomaindomain
range
range range
Classes
Instances
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“The” TAMI Ontology?
Some decisions: We’ll simplify this for the moment… We might want to change this in the next scenario… Better to take this big existing ontology for that…
The ontology will necessarily need to evolve continuously Might need to introduce more abstraction levels Might need to make other kind of changes
Better be prepared for that How and how well is RDF prepared for it?
US Constitution
establishes
Legislative Executive Judiciary
Territories
States
enacts
Statutes
President
issues
HomelandSecurity
PresidentialDirectives
National Security
PresidentialDirectives
ExecutiveOrders
Agencies
issue
Regulations
Resultingin
Policies
Practices
issues
Decisions
CommonLaw
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Evolution
Finding the final solution at the beginning is impossible, because you don’t know where you are going
Intermediate decisions are necessary, but they bind and have implications (backward compatibility) Radio: Mono → Stereo Television: B/W → Color Credit card processing: Manual → Computerized Phone: Pulse → Tone
Refactoring
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How to Represent Evolution in RDF?
Possibilities: More classes (code relation into the name) Use the subclass mechanism Relate classes outside of RDF rather than
inside the language
Use syntax to mean semantics
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Context
What is my (place of) residence? Where I live presently Where I have lived on a permanent basis
(until next change) For the Immigration Authorities For Tax Purposes (Federal or State?)
The importance of the context “Yo soy yo y mi circunstancia”
– José Ortega y Gasset
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Evolution
Context Concurrent systems: model the system and
the environment (what is importamt about the rest of the world)
Evolution Notion of refinement to relate different
versions
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Conclusions: Conceptualization
Knowledge Representation more complex than what I thought Psychological, philosophical questions as well
as Software Engineering considerations No predefined number of right abstraction
levels Lift up the strings Beware of/introduce additional levels
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Conclusions: Evolution
Careful balance between finding the final solution and intermediate ones The importance of taking evolution into
account from the very beginning It would be good if the representation
language (RDF) took care of this, but it is not necessary
Modelling in the small vs modelling in the large
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Law and Logic
The art of finding the right abstraction levels