DAML-Space

Document Sample
DAML-Space Powered By Docstoc
					Interoperability among
Geospatial Ontologies


           Jerry R. Hobbs
   Information Sciences Institute
  University of Southern California
     Marina 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 Queries
Topology 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 Tyson
Answered questions that required accessing
   multiple resources; focus on geospatial domain.
Key ideas:
1. Logical analysis/decomposition of questions into
   component questions, using a reasoning engine
2. Bottoming out in variety of web resources and
   information extraction engine
3. Use of analysis of questions to determine,
   formulate, and present answers.
             Composition of Information
               from Multiple Sources
    Show me the region 100 km north of the capital of Afghanistan.
    Question
 Decomposition
via Logical Rules

    What is the capital                 What is the lat/long
     of Afghanistan?                     100 km north?
                    What is the lat/long                       Show that
                       of Kabul?                                lat/long


                                                               Terravision
         CIA           Alexandrian
      Fact Book                            Geographical             Resources
                      Digital Library                               Attached to
                        Gazetteer            Formula                Reasoning
                                                                     Process
   System Architecture
                 Query


                 parsing
                                             Proof with
   GEMINI                                     Answer

             Logical Form

SNARK


  decomposition and interpretation


 Web Resources             Other Resources
                    Inter-Operability
                            Query

 What is this
language and                parsing
  ontology?                                             Proof with
                 GEMINI                                  Answer

                          Logical Form

           SNARK


                decomposition and interpretation


            Web Resources             Other Resources
                      Inter-Operability
  via multiple translations:

                                       OR
             Resource-1

                                            via an “inter-theory”:
Resource-6                Resource-2
                                                         Resource-1
Resource-5                Resource-3
                                            Resource-6                  Resource-2
             Resource-4                                  Inter-theory

                                            Resource-5                  Resource-3

                                                         Resource-4


                            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
               Aims of OWL-Time
Ontology of time for the Semantic Web for describing
  temporal content of web pages
  temporal properties of web pages
  temporal properties of web services
Developed in collaboration with James Allen, Pat Hayes,
  George Ferguson, James Pustejovsky, Adam Pease,
   and other researchers
Maps easily into other temporal theories/ontologies
  (e.g., Cyc, SUMO, PSL, ...)
Connects easily with various temporal resources
Supports reasoning about time

Growing number of users; W3C endorsement near
              Example



E-Commerce:

 Need book               Ships books
  by next        ?        within five
  Tuesday               business days
Coverage of Temporal Ontology


     1. Topological relations
     2. Durations
     3. Clock and Calendar
     4. Temporal Aggregates
     5. Vague Temporal Concepts
                Time: Topology
                                                         instants
                                interval




                start              inside          end



                       x                      y
                                before(x,y)

intOverlaps(T1, T2):
          T1                                  t2
  t1
                           t3                                t4
                                                   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 Issues
       and 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
                       Context
The 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
               Galton           Egenhoffer
    Cohn
                                             Hayes
                    Abstract Theory
      etc              of Space
                         (FOL)

     SUMO         Complete or Partial          ResearchCyc
                    Realization in
                   OWL / RuleML / ...
                                               SDTS
   OpenGIS

Existing Standards                     NLP Extraction
                                        Techniques
                  Annotation Standards
                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
                                                    (as of 2003)

Some of the applications as drivers for what has to be
  represented

Flight planning with no-fly zones
Travel planning system involving lat/longs, political divisions,
   weather
Smart meeting room system
Alexandrian Digital Library
Space (NASA) applications involving the structure and
   trajectory of rockets (3-D)
Cell biology
Image interpretation and description
Robotics

We collected brief descriptions of the requirements for
  spatial representation and reasoning for these
  applications
                   Topology

Points, arcs, regions, volumes
Closed loops and surfaces
Ordering relations & “between” in arcs; directions
   on lines and loops
Connectedness, continuity
Boundaries & surfaces, interior & exterior, directed
   boundaries; “airspace above”
Disjoint, touching, bordering, overlapping, containing
   regions (RCC8); location at
Holes, knots
NOT open and closed sets
NOT pathological topologies
       Dimension and Orientation

Abstract characterization of dimension, projections on
   component dimensions, embedding dimension
Links w topological notions of dimension
Frames of reference: earth-based, person-based, vehicle-based,
   force-based
Relative orientations: parallel, perpendicular
Cartesian vs polar coordinate systems, bearing & range
Transformations between coordinate systems
Degrees of freedom
Qualitative trigonometry: granularities on orientations
2 1/2 dimensions: elevation as 2nd class dimension, system
   mostly thought of as planar
Elevation from sea level vs ground level
Planar vs spherical geometry
                     Shape


2D vs 3D shapes
Linking w shape descriptions in geographical databases
Shape descriptors: round, tall, narrow, convex,...
Relative shapes: rounder, sharper, ...
Same shape as, negative-shape, fits-in
Bounding boxes and their problems (e.g., USA with
   American Samoa includes Mexico)
Symmetry
Links w functionality of shape
   In artifacts, shape is almost always functional
   In natural objects, shape often has consequences
? Texture
                       Size


Length, distance, area, and volume
Precise and qualitative measures
English-metric conversions
Coarse granularities: order of magnitude, half order of
   magnitude, implied precision, qualitative measures
   (large, medium, small) relative to comparison set
Encoding uncertainty: bounded error, egg yolk theories
Uncertainty 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 Principles
Terminology:
   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 Concepts
Connectedness 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:
              Boulder
     trail
                  Granularity
Indistinguishability 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.
                       Scales
Set 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 Scales
              not okay                okay

                          0
         --                              +


                qualitative amounts

                              Md
    Lo                                       Hi

                orders of magnitude


              half orders of magnitude


                     integers


                         reals
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 Granularity
   Refining granularity thru transitivity axioms:
         change(e1,e2) & change(e2,e3) --> change(e1,e3)

                    subevents of this




 virus
                                            out(v,c) --> in(v,c)
                           cell



                                                     Looking at
                                     wall          components of
 virus
                                                        cell

                                  cell

    out(v,c) --> penetrating(v,wl(c)) --> in(v,c)
         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 are
large enough that
  Aggregation operations have reasonably
    predictable results,
  Normal variation does not cross category
    boundaries
But small enough that
  Our interactions with objects is predictable
    from their category.
                 Natural HOMs
Linear 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 HOMs
Linear 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)

				
DOCUMENT INFO