Interoperability among Geospatial Ontologies Jerry R. Hobbs Information Sciences Institute University of Southern California Marina del Rey, California
Jan 18, 2018
Interoperability amongGeospatial Ontologies
Jerry R. HobbsInformation Sciences Institute
University of Southern CaliforniaMarina del Rey, California
My Interests
How do we use world knowledge in understanding natural language? What world knowledge do we have and how is it represented? What geospatial knowledge do we have and how is it represented?
Focus less on large compendia of geospatial facts, More on identifying those concepts that need to be explicated in a core theory of geospatial and other spatial representation and reasoning, Especially, concepts important in language.
Some Natural Language QueriesTopology of Space: Is Albania a part of Europe? Does Belize touch Honduras?
Dimensionality: How long is Chile?
Measures: How large is North Korea? Orientation and Shape: What direction is Las Vegas from Los Angeles?
Latitude and Longitude: How far is Los Angeles from Washington, as the crow flies?
Political Divisions: What are the counties of Virginia?
For complex queries, answer may be composed from several resources.
The QUARK System
A system built at SRI in the AQUAINT question- answering program of ARDA.
Work done with Richard Waldinger, Doug Appelt, Jennifer Dungan, John Fry, David Israel, Peter Jarvis, David Martin, Susanne Riehemann, Mark Stickel, Mabry TysonAnswered questions that required accessing multiple resources; focus on geospatial domain.Key ideas:1. Logical analysis/decomposition of questions into component questions, using a reasoning engine2. Bottoming out in variety of web resources and information extraction engine3. Use of analysis of questions to determine, formulate, and present answers.
Composition of Informationfrom Multiple Sources
Show me the region 100 km north of the capital of Afghanistan.
What is the capitalof Afghanistan?
What is the lat/long100 km north?
What is the lat/longof Kabul?
CIAFact Book Geographical
Formula
QuestionDecomposition
via Logical Rules
AlexandrianDigital Library
Gazetteer
Show thatlat/long
Terravision
ResourcesAttached toReasoning
Process
System Architecture
GEMINI
SNARK
Query
Logical Form
Web Resources Other Resources
parsing
decomposition and interpretation
Proof withAnswer
Inter-Operability
GEMINI
SNARK
Query
Logical Form
Web Resources Other Resources
parsing
decomposition and interpretation
Proof withAnswer
What is thislanguage and
ontology?
Inter-Operability
Resource-4
Resource-3Resource-5
Resource-2Resource-6
Resource-1
Resource-4
Resource-3Resource-5
Resource-2Resource-6
Resource-1
Inter-theory
via multiple translations:
via an “inter-theory”:
OR
Also a good excuse to develop a core theory.
Outline
Time Ontology (OWL-Time)
Event Ontology
“DAML-Space”/“OWL-Space”
Topics and Requirements
A Sketch of Topology
Granularity
Half Orders of Magnitude
Ontology of time for the Semantic Web for describing temporal content of web pages temporal properties of web pages temporal properties of web servicesDeveloped in collaboration with James Allen, Pat Hayes, George Ferguson, James Pustejovsky, Adam Pease, and other researchersMaps easily into other temporal theories/ontologies (e.g., Cyc, SUMO, PSL, ...)Connects easily with various temporal resourcesSupports reasoning about time
Growing number of users; W3C endorsement near
Aims of OWL-Time
Example
Need bookby nextTuesday
Ships bookswithin five
business days?
E-Commerce:
Coverage of Temporal Ontology
1. Topological relations2. Durations3. Clock and Calendar4. Temporal Aggregates5. Vague Temporal Concepts
Time: Topology
interval instants
start endinside
x ybefore(x,y)
T1
T2
t2
t3 t4
t1
intOverlaps(T1, T2):
Duration, Clock and Calendar
Measures of duration: second, minute, ...
Concatenation of temporal intervals
Time zones (includes a world time zone resource)
Clock times: 10:15:32am
Calendar dates: Tuesday, June 20, 2006
Temporal arithmetic
Temporal Aggregates
“five business days”
“every third Monday in 2001”
“every morning for the last four years”
“four consecutive Sundays”
“the first nine months of 1997”
“three weekdays after January 10”
“the fourth of six days of voting”
Typical Durations of Events
We have a lot of knowledge about how long events of various types last.
“George W. Bush met with Vladimir Putin in Moscow.”
How long did the meeting last?
10 seconds? One year? Probably between 1 hour and 2 days
We annotated events in news articles with judgments like these to create corpus and used it in machine learning
Controversial Issuesand What to do about Them
Are the end points of an interval a part of the interval? Can there be intervals of zero length? Is an interval of zero length an instant? ==> Avoid these issues; keep ontology silent. (Many problems arise when trying to identify 0-D and 1-D entities)
Is time totally ordered?Are there points at infinity? ==> Optional extensions with triggers
Total-order() --> (A t1,t2)[before(t1,t2) v t1=t2 v before(t2,t1)]
Use similar devices for a geospatial core theory
Outline
Time Ontology (OWL-Time)
Event Ontology
“DAML-Space”/“OWL-Space”
Topics and Requirements
A Sketch of Topology
Granularity
Half Orders of Magnitude
IKRIS Scenarios Inter-Theory
Define an ontology or “inter-theory” that will allow various resources and languages to inter-translate statements about events, processes, and scenarios, their structure, and their causal relations
Target resources: Process Specification Language (PSL), ResearchCyc, FLOWS/SWSO, SPARK (son of PRS)
Funded by ARDA; April 2005 - September 2006
Coverage
Event and state types and tokens (general rules and specific facts)
Precondition-effect view of processes
Input-output view of processes
Control structure of processes
Relation to knowledge about causality and enablement
State of execution of processes (continuing, aborting, resuming, ...)
Outline
Time Ontology (OWL-Time)
Event Ontology
“DAML-Space”/“OWL-Space”
Topics and Requirements
A Sketch of Topology
Granularity
Half Orders of Magnitude
ContextThe Semantic Web requires common ontologies with wide acceptance and use.OWL-S: an ontology of services Development began February 2001 About a dozen people in inner circle Growing community of users Institutional status at W3C
OWL-Time: a temporal ontology Development began February 2002 Most work by 1-3 people 10 < | Users | < 100 Public review stage at W3C
OWL-Space: a spatial ontology Organizational meeting April 2003 Effort suspended after early 2004 because of lack of funding Good signs of revival, including this workshop
Aims A widely available ontology of geographical and other spatial properties and relations
Provide convenient markup and query capabilities for spatial information in Web resources
Adequate abstract coverage for most spatial applications (not necessarily efficient)
Link with special purpose reasoning engines for spatial theories and large-scale GIS databases
Link with various ontological resources and annotation schemes
Link with various standards for geographical information
Structure of Effort
Abstract Theoryof Space
(FOL)
Complete or Partial Realization in
OWL / RuleML / ...
SUMO ResearchCyc
Cohn Hayes
Annotation Standards
etc
Existing Standards NLP ExtractionTechniques
EgenhofferGalton
OpenGISSDTS
Some Principles
Delimiting the effort: Not a theory of physical objects, properties of materials, qualitative physics Link with numerical computation, don’t axiomatize it Link with large geographical DBs, don’t duplicate them Navigate past controversial issues, as in OWL-Time, by Keeping silent on issue Provide easily exercised options Use Common Logic (CL) for abstract theory; OWL-ize predicate and function declarations Provide simple, useful entry subontologies
Topics SPACE TIME
Topology Topology
Dimension --
Orientation & Shape --
Length, area, volume Duration
Lat/long, elevation Clock & calendar
Geopolitical subdivisions --
Aggregates, distributions Temporal aggregates
Vagueness Vagueness
Outline
Time Ontology (OWL-Time)
Event Ontology
“DAML-Space”/“OWL-Space”
Topics and Requirements
A Sketch of Topology
Granularity
Half Orders of Magnitude
Target Applications
Some of the applications as drivers for what has to be represented
Flight planning with no-fly zonesTravel planning system involving lat/longs, political divisions, weatherSmart meeting room systemAlexandrian Digital Library Space (NASA) applications involving the structure and trajectory of rockets (3-D)Cell biology Image interpretation and descriptionRobotics
We collected brief descriptions of the requirements for spatial representation and reasoning for these applications
(as of 2003)
Topology
Points, arcs, regions, volumesClosed loops and surfacesOrdering relations & “between” in arcs; directions on lines and loopsConnectedness, continuityBoundaries & surfaces, interior & exterior, directed boundaries; “airspace above”Disjoint, touching, bordering, overlapping, containing regions (RCC8); location atHoles, knotsNOT open and closed setsNOT pathological topologies
Dimension and Orientation
Abstract characterization of dimension, projections on component dimensions, embedding dimensionLinks w topological notions of dimensionFrames of reference: earth-based, person-based, vehicle-based, force-basedRelative orientations: parallel, perpendicularCartesian vs polar coordinate systems, bearing & rangeTransformations between coordinate systemsDegrees of freedomQualitative trigonometry: granularities on orientations2 1/2 dimensions: elevation as 2nd class dimension, system mostly thought of as planarElevation from sea level vs ground levelPlanar vs spherical geometry
Shape
2D vs 3D shapesLinking w shape descriptions in geographical databasesShape descriptors: round, tall, narrow, convex,...Relative shapes: rounder, sharper, ...Same shape as, negative-shape, fits-inBounding boxes and their problems (e.g., USA with American Samoa includes Mexico)SymmetryLinks w functionality of shape In artifacts, shape is almost always functional In natural objects, shape often has consequences? Texture
Size
Length, distance, area, and volumePrecise and qualitative measuresEnglish-metric conversionsCoarse granularities: order of magnitude, half order of magnitude, implied precision, qualitative measures (large, medium, small) relative to comparison setEncoding uncertainty: bounded error, egg yolk theoriesUncertainty of location vs imprecise regions
Spatial Aggregates
What are the most common ways of describing spatial aggregates?
A qualitative theory of distributions (e.g., heavily populated)
? Texture
Geopolitical Regions
Latitude and Longitude
Natural geographical regions: Land masses: continent, island, ... Bodies of water: ocean, lake, river, ... Terrain features: mountain, valley, forest, desert, ...
Political regions: Countries Political subdivisions: state, province, county, ... Municipalities: city, town, village, ... Residences and street addresses Other: Indian reservations, regulatory zones, ...
Outline
Time Ontology (OWL-Time)
Event Ontology
“DAML-Space”/“OWL-Space”
Topics and Requirements
A Sketch of Topology
Granularity
Half Orders of Magnitude
Topology: Some PrinciplesTerminology: OpenGIS > ResearchCyc > SUMO > new
Distinguish between physical objects and their geometric realizations
Stay neutral on the question of whether: A curve is composed of points. A boundary is part of a region.Invent new predicates, not , for cross-dimensional relations
Ignore topological oddities (space-filling curves, ...)
Stay as neutral as possible on issues of infinity
Topology: Some Concepts
Dimension: dimension of geometric figure: point, curve, surface, solid embedding dimension, e.g., curve in 3-space
Interior, Exteriors, and Boundaries Primitive predicates inside, outside, boundary
Possible Relations among geometric objects of various dimensions RCC8; Egenhoffer’s relations and operators E.g., what are the possible relations between a curve and a solid? All defined in terms of inside, outside, boundary
Topology: Some ConceptsConnectedness and continuity: connected objects in terms of overlap and tangents self-connected: no disconnected decomposition mean-value theorem or property: g1 and g2 self-connected and g1 overlaps with interior(g2) and with exterior(g2) --> g1 overlaps with boundary(g2) notions of continuity, given structure on domain and range (Galton)
Holes, cavities, indentations, tunnels: n-connectedness: how many holes? n-tunnels: how many holes in surface? shape of tunnels: in terms of knot theory’s “crossings” composition by addition and subtraction of these objects
Composite geometric objects
Outline
Time Ontology (OWL-Time)
Event Ontology
“DAML-Space”/“OWL-Space”
Topics and Requirements
A Sketch of Topology
Granularity
Half Orders of Magnitude
Granularity
A city can be viewed as a point, a region, or a volume.How should these different perspectives be accommodated?
One approach: City is an entity with 3D, 2D, and 0D realizations.User can pick which one(s) to use.
Build granularity considerations into spatial ontology from the beginning, not as an add-on.
Granularity
Tolerances, epsilon-neighborhoods:
But granularity is not just tolerances:Map of South America:
Hiking Map:
Bouldertrail
GranularityIndistinguishability Relation (or Set Covering): ≈
Partition: ≈ transitive, e.g., countries
Overlapping Sets: ≈ not transitive, e.g., within 1 cm
Often functionality-determined, e.g. hiking map.
Different granularities for different purposes. e.g. discrete vs continuous for conceptualizations of space and time.
Much of our knowledge involves knowledge of various available granularities, articulations between them, and ways of shifting granularities for particular purposes.
ScalesSet of elements with a partial ordering <
Can define subscale, total ordering, dense, top, bottom, reverse, relations among subscales,
Examples: distance, time, happiness, damage, preference, ...
Various perspectives on space built out of independent scales
Levels of Structure on Scalesokaynot okay
-- 0 +
orders of magnitude
half orders of magnitude
integers
reals
qualitative amounts
LoMd
Hi
Other Perspectives on Granularity
Composite Entities can be viewed structurally: with their internal structure visible functionally: undecomposed, with their relations to the environment visible
. ...
.
...
.
Other Perspectives on Granularity
Complex events/actions have hierarchical structure:
goal(a,q)
goal(a,r) goal(a,p)
.... .... ....
Depth of decomposition defines the Granularity at which behavior is viewed.
Other Perspectives on GranularityRefining granularity thru transitivity axioms:
change(e1,e2) & change(e2,e3) --> change(e1,e3)
subevents of this
out(v,c) --> in(v,c)viruscell
virus
cell
out(v,c) --> penetrating(v,wl(c)) --> in(v,c)
wallLooking at
components ofcell
Outline
Time Ontology (OWL-Time)
Event Ontology
“DAML-Space”/“OWL-Space”
Topics and Requirements
A Sketch of Topology
Granularity
Half Orders of Magnitude
Some Multiple Choice Questions
1. About how many children are there in the average family? a) 1 c) 10 e) 100
2. About how many children are there in the average classroom? a) 1 c) 10 e) 100
Some Multiple Choice Questions
1. About how many children are there in the average family? a) 1 b) 3 c) 10 d) 30 e) 100
2. About how many children are there in the average classroom? a) 1 b) 3 c) 10 d) 30 e) 100
Often the best answer is in terms of half orders of magnitude (HOMs)
Some Examples
Cash: 1 cent, 5 cents, 10 cents, 25 cents, $1, $5, $10, $20, $100
Volume: 1cup, 1pint, 1 quart, 1 gallon, 1 peck, 1 bushel
Time: 1 minute, 1 quarter hr, 1 hr, morning..., 1 day, 1 week, 1 month, 1 quarter/semester/season, 1 year, Olympiad/pres.admin...., 1 decade
Opposing Tensions
We want a rough logarithmic categorization scheme for sizes in which the categories arelarge enough that Aggregation operations have reasonably predictable results, Normal variation does not cross category boundariesBut small enough that Our interactions with objects is predictable from their category.
Natural HOMsLinear extent: Examples: 6 feet person, door, chair, table, desk can be moved by one person, can accommodate one person 2 feet TV set, dog, basket, watermelon, sack can be held in two arms 8 inches book, football, cantelope can be held in one hand, manipulated with difficulty in one hand 3 inches pen, mouse, hamburger,orange, cup can be held with the fingers
1 inch french fry, eraser, peppermint candy can be bitten, can be manipulated easily with two fingers and thumb
1/4 inch M&M, thumb tack, diamond handled with care between two fingers
Natural HOMsLinear extent: Examples: 6 feet person, door, chair, table, desk can be moved by one person, can accommodate one person 18 feet office, room one person can move around can accommodate several people 20 yards house, restaurant, small yard, class 60 yards commercial building, large yard 200 yards small factory, field 600 yards large factory, large bridge, dam 1 mile town, airport 3 miles small city 10 miles large city, small county 30 miles large county 100 miles small state 300 miles large state, small nation 1000 miles typical large European nation 3000 miles the United States, China
Summary
An “inter-theory” of the geospatial domain explicating its core concepts would enable use of multiple geographic databases; link to multiple geospatial reasoning engines; link to natural language
(and should be fairly straightforward to do)