GEOINFO 2013 – XIV Brazilian Symposium on Geoinformatics – November 2013
Putting Geographic Information
Ontologies to Work
The Case of Geospatial Science
Helen Couclelis
Geography Department
University of California
Santa Barbara
California, USA
Is GIScience ‘working’ hard enough for us?
great theoretical work = great practical benefits?
Werner Kuhn
VGI, trust, and clean wells in Africa
Kathleen Stewart & Christophe Claramunt
Call for papers:
Spatio-temporal theories and models for environmental, urban
and social sciences
Gilberto Câmara & team
geoinformatics and … and… and…
and Helen Couclelis?
Early enthusiasm
models! planning!
spatial interaction, CA, ABM
*
Mature doubts
uncertainty beyond data
forecasts and policy
Mature enthusiasm
the ‘big picture’
ontology
and representation in space and time
*EU’s FuturICT shortlisted project
Why ontology? What Ontology?...
from Plato to SUMO and DOLCE
World versus micro-worlds
at first
interoperability
then
cognition, language, structure, meaning, concepts,
measurements, physical /non-physical entities, space,
time, user, culture, reality, philosophy
recently
micro-ontologies
microtheories and the Semantic Web
http://keet.wordpress.com/category/philosophy/ontology/
Note Gruber’s agent-centered definition:
An ontology is “a formal, explicit specification of
a shared conceptualization”
“… an ontology is a description … of the
concepts and relationships that can exist for an
agent or a community of agents.”
Ontologies must “constrain the possible
interpretations for the defined terms.”
ontologies are social artifacts
“The ultimate source of meaning
is the physical world
and the agents who use signs
to represent entities in the world
and their intentions
concerning them”.
(Sowa)
Overview
(Introduction)
Representation and the Big Picture in GISc
Ontologies of Geographic Information
A micro-ontology generating engine?
Geodesign: an application
Questions & Discussion
This is not a pipe
The map is not the territory
The model is not reality
Representation and the Big Picture
GIScience and the big-picture questions
frameworks, general theories, ontologies, base models
“The challenge of representing fields-objects in a
computer environment” (Camara 2000)
“Field-object integration through a common base
model” (Kjenstad 2006)
“A general theory to bring many previous ideas under a
single umbrella” (Goodchild et al. 2007)
“Need for a conceptually unifying data model”
(Voudouris 2010)
Camara et al. 2000
Goodchild et al. 2007
Gangemi & Mika 2003 Kuhn 2001
Kjenstad 2006
Couclelis 2010
Voudouris 2010
Two different paradigms in geospatial representation. Spatial-primitives centered (left) and concept-centered
(right). Source: M. Kavouras and M. Kokla (2008) Theories of Geographic Concepts, p. 296.
X
X
X
context
X
data model
X
X
X
X
X
X
X
geo-unit
intentionality
X
language
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
operations
X
reification
X
semantics
X
X
X
X
X
uncertainty
user
X
X
design
X
Couclelis
X
X
cognition
field/object
Voudouris
Goodchild
Kjenstad
X
aggregation
many
commonalities
among
these
authors
Gangemi
Kuhn
Camara
activity
X
X
X
X
X
X
X
X
X
X
The same concepts are categorized differently
depending on the context
http://vissim.uwf.edu/VOTT/VOTT_desc.htm
‘Ontologies of geographic information’*
sense-perceptions
observations
data
information
knowledge
wisdom
???
?
At every step, we ask:
“what is the meaning of_?”
What gives information its meaning?
How are data transformed into knowledge?
Why model information and not directly the world?
*Couclelis 2010, IJGIS, December
What gives information its meaning?
semantics on top of structure (syntax)
How are data transformed into knowledge?
by being integrated into some coherent story
Why model information and not directly the world?
Information entails a source and a decoder (agent)
Modeling information, not the world:
three principles
Foregrounding the perspective of the user
Distinguishing a linked sequence layers of
varying degrees of semantic richness
Selecting data through criteria resulting from
the users’ purpose-oriented semantic choices
A representation is constructed in a particular way
for a purpose
weather maps for
scientific study
school text illustration
TV weather forecast
river models for
navigation company
water resource agency
cross-border regulation
Purpose comes from the intentionality
of the user
a GIScience representation (model) is constructed
in response to some user need
The popular DOLCE ontology
My 2010 framework: the static version
The foundations
information
spacetime framework
purpose
The key ingredients
spacetime granules
classes of properties
GI Constructs (GICs)
The structure
o representation levels
Most ontologies are
represented as trees
or semi-lattices
The foundations
information
spacetime framework
purpose
The key ingredients
spacetime granules
classes of properties
GI Constructs (GICs)
The structure
o representation levels
o lattice
This one is a lattice, with
information and spacetime
framework at one end, and
intentionality at the other
The foundations
information
spacetime framework
purpose
The key ingredients
spacetime granules
classes of properties
GI Constructs (GICs)
The structure
representation levels
o lattice
Actually, it should be
this way around
Geographic Information Constructs (GICs)
topons, chronons, and codes across 7 property domains
xt
GICi
P = {p7} + {p6} +…+ {p1}
{p7}
…. {p3}
p71, p72,… p7i
….
p31, p32,… p2j p21, p22,… p2k p1
g1
1 1 …0
….
1 0 …0
1 0 …1
1
g2
1
….
0 1… 1
1 1 … 1
1
…
….
….
….
gm
1
1…1
….
1
0
….
….
1 1
{p2}
0 0 1 … 0
{p1}
1
The principle of semantic contraction
Semantic resolution
levels
Decoder
capabilities
7
intentionality
[
purpose
6 function
instrumentality
5 complex objects
association
4 simple objects
categorization
3 patterns
classification
2 observables
perception
1 space-time framework
awareness
Representation
objects
fields
7 Purpose
6 Function
A road map of region X
Facilitate vehicular travel
planning and navigation
A map of roads in region X
Identify and mitigate barriers
to wildlife movements
Represent possible routes
from place A to place B
Represent the locations where
wildlife corridors intersect with
roads
A wildlife corridor network
intersecting with a road network
5 Composite objects A road network
4 Simple objects
Places, freeways, arterials,
collectors, intersections,
ramps, roundabouts,…
Roads, wildlife corridor segments,
underpasses, culverts, highconflict intersections,…
3 Classes
Fields of properties
(corresponding to surface
material, slope, network
structure,…) aggregated in
diverse geometrical patterns
Fields of properties
(corresponding to incident
frequency, barrier permeability,
height, width…) aggregated in
diverse geometrical patterns
2 Observables
Hard, rough, green, brown,
wet,…
Open, blocked, green, hard, kill,
dry, wet…
1 Space-time Exist.
“Task-relevant information
exists here-now at such-andsuch appropriate granularity”
“Task-relevant information exists
here- now at such-and-such
appropriate granularity”
A somewhat similar idea from more practical folks…
A review and assessment of land-use change models: dynamics of space, time, and human choice
By Agarwal, Chetan; Green, Glen M.; Grove, J. Morgan; Evans, Tom P.; Schweik, Charles M. (2002)
Gen. Tech. Rep. NE-297. Newton Square, PA: U.S. Department of Agriculture, Forest Service,
Northeastern Research Station.
The framework, 3 years later…
A micro-ontology generating engine?...
Ontology >> language for model design
ontologies are models of models
micro-theories are models
a model is a micro-theory
modeling is a language
a model is a statement about the world
language has semantics, syntax and pragmatics
building a model is design-ing
designed things reflect designer’s purpose
purpose is supported by function
A structure emerges…
Syntactics
structure
Model designer
purpose
perspective
Semantics
meaning
Pragmatics
context
Unpacking the ‘Ontologies’ framework
Data structures
Semantics
Pragmatics
Purpose
SS
Patterns
Interpretations
context
measurements
Syntax
context
Micro-ontologies
The temporal extension
One additional key ingredient:
R-event
For each level, a change in information
that significantly alters the structure of GICs at that level
‘significant’ is relative to purpose!
“Information: a difference that makes a difference”
Gregory Bateson
And the R-event types by level are…
R-events change the context of the situation described
Semantic resolution
levels
[
7 purpose
Decoder
capabilities
R-event types
intentionality
change of purpose or
objectives
functionally relevant
change
6 function
instrumentality
5 complex objects
association
4 simple objects
categorization
3 patterns
classification
2 observables
perception
addition, loss of parts
dissolution
Identity change
behavior change
relevant field
properties change
Gestalt change
Adding uncertainties and times
Semantic resolution
levels
Uncertainties
(examples)
Times
relating to purpose
and purpose change
as to function:
fitness, repurposing
experiential
5 complex objects
assignment parts-to
objects; changing
part-whole relations
multiple clocks
various timescales
4 simple objects
linguistic factors
‘lifespans’
3 patterns
classification
clock time
2 observables
perception
punctuated time
[
7 purpose
6 function
discrete-event
Some features of the framework
 Guides construction of micro-ontologies (and
possibly process models)
 Integrates design & analysis through user
perspective
 Adds context-relevant notions of time,
change and uncertainty
 Is compatible with much other work in
geographic information science
And now, something more applied!
Geodesigning from the inside out
My advisor used to say…
“there is nothing as practical
as a good theory”
Searching for practical solutions by becoming
more abstract
What next?...
Tentative, but a different way of looking at
geospatial representation
Continue connecting with literature
Formalize!
Try deriving micro-ontologies for
use with the Semantic Web
Experiment with environmental
and other process models