1. Tools For Resolving Heterogeneity Computer Science Department.
Tools For Resolving Heterogeneity
in Ontologies
SKC Project
Computer Science Department
Stanford University
Gio Wiederhold, PI
10/13/2018
Gio Wiederhold SKC RKF 1

2. Problem Addressed by SKC
Ontologies come from many autonomous sources
Differing viewpoints (by source)
differing coverage vehicles (DMV, AIA)
differing granularity trucks (shipper, manuf.)
differing terms for similar items { lorry, truck }
same terms for dissimilar items trunk(luggage, car)
Created by focused groups
high quality used in commerce
ongoing maintenance annual models
Poor precision when merged
ok for web browsing , poor for business
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3. Domains and Consistency .
a domain will contain many objects
the object configuration is consistent
within a domain all terms are consistent &
relationships among objects are consistent
context is implicit
No committee is needed to forge compromises * within a domain
Domain Ontology
Compromises hide valuable details
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4. Heterogeneity among Domains
If interoperation involves distinct
domains mismatch ensues
Autonomy conflicts with consistency,
Local Needs have Priority,
Outside uses are a Byproduct
Heterogeneity must be addressed
Platform and Operating Systems 4 4
Representation and Access Conventions 4
Naming and Ontology :
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5. SKC Objective Provide for Maintainable Ontologies
devolve maintenance onto many domain-specific experts / authorities
provide an algebra to compute composed ontologies that are limited to their articulation terms
enable interpretation within the source contexts
SKC
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6. An Ontology Algebra A knowledge-based algebra for ontologies
The Articulation Ontology (AO) consists of matching rules that link domain ontologies
Intersection create a subset ontology
keep sharable entries
Union create a joint ontology
merge entries
Difference create a distinct ontology
remove shared entries
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7. Sample Operation: INTERSECTION
Result contains
shared terms,
useful for purchasing
Articulation
Source Domain 1:
Owned and maintained
by Store
Source Domain 2:
Owned and maintained
by Factory
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8. Tools to create articulations
Graph matcher
for
Articulation-
creating
Expert
Vehicle
ontology
Transport
ontology
Suggestions
for articulations
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9. continue from initial point
Also suggest similar terms
for further articulation:
by spelling similarity,
by graph position
by term match repository
Expert response:
1. Okay
2. False
3. Irrelevant
to this articulation
All results are recorded
Okay’s are converted into articulation rules
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10. Candidate Match Repository
Term linkages automatically extracted from 1912 Webster’s dictionary *
* free, other sources being processed.
Based on processing headwords ý definitions using algebra primitives
Notice presence of 2 domains: chemistry, transport
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11. Using the Match Repository
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12. Using the Match Repository
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13. Rules for Real-Time Data
if [base_station.receiving] = true
then satellite_data = [base_station]
satellite_data.timestamp = now
if [satellite_data.age] < 24 hours
or [radio_jamming.level] > 30%
then recon_data = [satellite_data]
except when [flight_data.age] < 1 hour
or [rain_sensor.daytotal] > 1 inch
then recon_data = [flight_data]
assert [recon_data]
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14. INTERSECTION support Articulation ontology Matching rules that use
terms from the
2 source domains
Terms useful
for purchasing
Store
Ontology
Factory
Ontology
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15. Other Basic Operations
UNION: merging
entire ontologies
DIFFERENCE: material
fully under local control
Arti-
culation
ontology
typically prior
intersections
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16. Features of an algebra Operations can be composed
Operations can be rearranged
Alternate arrangements can be evaluated
Optimization is enabled
The record of past operations can be
kept and reused when sources change
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17. Knowledge Composition
Composed knowledge for
applications using A,B,C,E
Articulation
knowledge
for U (A B) (B C) (C E)
Articulation
knowledge
Legend:
U : union U
: intersection U (C E)
Articulation
knowledge
for
Knowledge
resource E
Knowledge
resource C (A B) U U (B C) U (C D)
Knowledge
resource A
Knowledge
resource B
Knowledge
resource D
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18. Primitive Operations Model and Instance Constructors create object
create set
Connectors
match object
match set
Editors
insert value
edit value
move value
delete value
Converters
object - value
object indirection
reference indirection
Unary
Summarize -- abstract
Glossarize - list terms
Filter - reduce instances
Extract - move into context
Binary
Match - data corrobaration
Difference - distance measure
Intersect - use of articulation
Union - search broadening
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19. Exploiting the result . Processing & query evaluation is best
Avoid n2 problem of interpreter
mapping [Swartout HPKB year 1]
Result has links
to source
Processing & query
evaluation is best
performed within
Source Domains
& by their engines
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20. Sample Processing in HPKB
What is the most recent year an OPEC member nation was on the UN security council?
Related to DARPA HPKB Challenge Problem
SKC resolves 3 Sources
CIA Factbook ‘96 (nation)
OPEC (members, dates)
UN (SC members, years)
SKC obtains the Correct Answer
1996 (Indonesia)
Problems resolved by SKC
Factbook has out of date OPEC & UN SC lists
Indonesia not listed
Gabon (left OPEC 1994)
different country names
Gambia => The Gambia
historical country names
Yugoslavia
UN lists future security council members
Gabon 1999
intent of original question
Temporal variants
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21. Domain Specialization .
Knowledge Acquisition (20% effort) &
Knowledge Maintenance (80% effort *)
to be performed
Domain specialists
Professional organizations
Field teams
of modest size
Empowerment
automously
maintainable
* based on experience with software
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