Geoscientific knowledge:
The limits of ontology and other
ways of knowing
Mark Gahegan
GeoVISTA Center, Department of Geography
The Pennsylvania State University, USA
Credits
GeoVISTA Center, Penn State (GEON, HERO, Dialog-Plus)
Junyan Luo,
Bill Pike,
Tawan Banchuen
Anuj AJ
Steve Weaver
San Diego Supercomputer Center (GEON)
Kai Lin
Chaitan Baru
GeoInformatics: Edinburgh, Ontology and other ways of knowing
CyberInfrastructure: The GEON GRID
Geological
Survey of
Canada
Chronos
Livermore
KGS
USGS
ESRI
CUAHSI
PoP node
Partner Projects
Compute cluster
Data Cluster
Partner services
1TF cluster
GeoInformatics: Edinburgh, Ontology and other ways of knowing
Some problems with current approaches
• Human knowledge that creates meaning out of
analyses is often unrecorded…
– for lack of a model of the scientific process that can
capture knowledge as it is created and used.
• We argue for an approach to representing scientific
concepts that reflects:
– the situated processes of science work,
– the social construction of knowledge, and
– the emergence and evolution of understanding over time.
• In this model, knowledge is the result of investigation,
negotiation, and collaboration by teams of researchers.
GeoInformatics: Edinburgh, Ontology and other ways of knowing
Representing living knowledge
• “Knowledge keeps no better than fish”
-- Alfred North Whitehead
• “You cannot put your foot in the same stream
twice”
-- Heraclitus
• “You can know the name of a bird in all the
languages of the world, but when you're finished,
you'll know absolutely nothing whatever about the
bird... So let's look at the bird and see what it's
doing -- that's what counts.”
-- Richard Feynman
GeoInformatics: Edinburgh, Ontology and other ways of knowing
Where does meaning come from?
• Domain understanding / theory (ontology)
• The way things are done (epistemology)
– How are resources created and used (work practices /
situations)?
• Negotiation among the community of users
(social network, group cognition)
• We ‘know’ things in many ways:
– Theoretical, Experiential, Procedural
• i.e. the interplay of top-down and bottom-up
knowledge played out in private and social
situations
GeoInformatics: Edinburgh, Ontology and other ways of knowing
Knowledge Goals of Cyber-Infrastructure
• Help communities of researchers and educators to do
better science by sharing their resources: computing
power, data, tools, models, protocols, results
• BUT…Making resources available is not the same as
making them useful to others
– Can we also share meaning?
• Litmus tests:
– Can we remember what we did?
– Will future generations of scientists be able to follow our
work?
GeoInformatics: Edinburgh, Ontology and other ways of knowing
“Knowledge soup” – Sowa, 2002
Little round planet in a big universe,
Sometimes it looks blessed,
sometimes it looks cursed.
It depends what you look at
obviously…
But even more, it depends on the way
that you see.
(Bruce Cockburn: “Child of the Wind”, 1994)
GeoInformatics: Edinburgh, Ontology and other ways of knowing
What’s in the soup? A nexus of knowledge
structures (Whitehead, 1923)
GeoInformatics: Edinburgh, Ontology and other ways of knowing
Why ontologies?
(Noy and McGuinness)
• To share common understanding of the structure of
information among people or software agents
• To enable reuse of domain knowledge
• To make domain assumptions explicit
• To automatically integrate disparate databases…
GeoInformatics: Edinburgh, Ontology and other ways of knowing
GEON: Multiple, different geological
ontologies
Genesis
Fabric
Texture
Kai Lin, SDSC
Boyan Brodaric, GSC
GeoInformatics: Edinburgh, Ontology and other ways of knowing
Geologic Map Integration in the Portal
•
After registering datasets, and their ontologies, mappings can be constructed
between the datasets via the ontologies—semantic mediation
Kai Lin, SDSC
GeoInformatics: Edinburgh, Ontology and other ways of knowing
Rock Taxonomy
(ontologically based)
Geological taxonomy
converted to an ontology
Gathered from experts
during a specially convened
workshop
Formalizes relationships
between concepts
Randy Keller (UTEP),
Bertram Ludaescher, Kai Lin,
Dogan Seber (SDSC), et al
GeoInformatics: Edinburgh, Ontology and other ways of knowing
An alternative rock taxonomy!
Rock music taxonomy
converted to a concept map
Gathered automatically from
consumer purchasing logs
Assumes relationships
between concepts
GeoInformatics: Edinburgh, Ontology and other ways of knowing
A continuum of knowledge
• We ‘know’ things in many ways:
– Theoretical, Experiential, Procedural
• Top-down, structured knowledge (concept maps,
ontologies)
– Formal knowledge structures (taxonomies, hierarchies,
rules)
• Bottom-up, informal knowledge (social networks,
use-cases)
– Situates e-resources and knowledge in Whitehead’s
nexus
GeoInformatics: Edinburgh, Ontology and other ways of knowing
Why Not Ontologies!
• Top down knowledge (ontology) only gets you so far…
– Experiences, use-cases (situations surrounding the use of
resources), Social networks.
• What happens to all the millions of geo- resources that
predate ontologies?
– The cost of retro-fitting ontologies can be prohibitive.
• Creating useful domain ontologies is very expensive and
problematic
– Can they be encouraged to emerge?
• Most current ontologies are static resources…
– Our understanding is dynamic & continually evolving…
– C.S. Peirce…
GeoInformatics: Edinburgh, Ontology and other ways of knowing
Learning from situations of use
–
–
–
–
–
–
Who created that resource?
When was it created?
How often has it been used?
Has it been modified recently?
Who has used it?
What has it been used with?
– Such questions add a rich context
by capturing situations surrounding
resource usage
GeoInformatics: Edinburgh, Ontology and other ways of knowing
Remembering situations of use
GeoInformatics: Edinburgh, Ontology and other ways of knowing
Situations
Creation
Application
Represented by
Who did it?
Who should use it?
Collections of people
Where was it made?
Where does it apply?
Collections of sites /
scales
When was it made?
When does it apply?
Collections of temporal
intervals
How was it made?
How should it be used?
Collections of methods
and data
Why was it made?
Why should it be used?
Collections of research
questions, motivations,
theories
GeoInformatics: Edinburgh, Ontology and other ways of knowing
What’s in the soup? A nexus of knowledge
structures (Whitehead, 1923)
GeoInformatics: Edinburgh, Ontology and other ways of knowing
Situating e-resources in the knowledge
nexus
GeoInformatics: Edinburgh, Ontology and other ways of knowing
GeoInformatics: Edinburgh, Ontology and other ways of knowing
GeoInformatics: Edinburgh, Ontology and other ways of knowing
Perspectives as filters
Perspectives filter an information space according to
particular situations.
Perspectives A and B
preferentially select different types of resources and
relations; the ability to view perspectives can show
how someone else made sense of a given set of
GeoInformatics: Edinburgh, Ontology and other ways of knowing
resources.
Four perspectives on a “seismic velocity” concept (red node). a) Intensional concept structure.
b) A task that describes how seismic velocity can be measured. c) A social network built around
users of the concept. d) Data resources
that have been used to describe seismic velocity.
GeoInformatics: Edinburgh, Ontology and other ways of knowing
Concept use and evolution
Evolution of “Depositional environment” concept through use by different researchers over time,
progressing from upper left to lower
right.
GeoInformatics:
Edinburgh, Ontology and other ways of knowing
What is wrong with this approach?
• Does not represent the importance of ontology as
a formal, fixed, sharable, community resource
– Can we still have ontology, but with perspectives?
• Knowledge horizons: an idea from Hermeneutics
– Creating flexible horizons
– Relations become properties (internalized), properties
become relations (externalized)
– Perspectives can be applied locally or globally
GeoInformatics: Edinburgh, Ontology and other ways of knowing
ConceptVista: What to represent?
• Basic types
–
–
–
–
–
–
–
Geon Themes:
Resources:
Methods:
Personnel:
Institutions:
Articles:
…
•
•
•
•
Styling…
Perspectives…
Situations…
Connections to web
resources
GeoInformatics: Edinburgh, Ontology and other ways of knowing
Perspectives for GEON
GeoInformatics: Edinburgh, Ontology and other ways of knowing
GeoInformatics: Edinburgh, Ontology and other ways of knowing
GeoInformatics: Edinburgh, Ontology and other ways of knowing
Navigating through conceptual universes
GeoInformatics: Edinburgh, Ontology and other ways of knowing
Combining perspectives: e.g. GEON
institutions, publications and personnel
GeoInformatics: Edinburgh, Ontology and other ways of knowing
Navigation strategies
Styling
independently serializable
(OGCs SLD)
Expand/collapse
remove or expand detail
Locality
limit the depth of expansion
Perspectives
visualized using SLD
Query
linking to other resources
Using a variety of ‘nym’ options
GeoInformatics: Edinburgh, Ontology and other ways of knowing
Summary
• Rich, Living Knowledge
– “Knowledge keeps no better than fish”
-- Alfred North Whitehead
– “You cannot put your foot in the same stream twice”
-- Heraclitus
– “…So let's look at the bird and see what it's doing -- that's what
counts.”
-- Richard Feynman
• Perspectives allow scientists to ‘describe what they
know’ onto shared ontological resources.
• Irony of Ontology is that ontologically-based
languages can be used to represent its obverse—
Epistemology.
GeoInformatics: Edinburgh, Ontology and other ways of knowing
Current work: integrating data analysis and
concepts in a single system
GeoInformatics: Edinburgh, Ontology and other ways of knowing
End
Questions?
GeoInformatics: Edinburgh, Ontology and other ways of knowing
GeoInformatics: Edinburgh, Ontology and other ways of knowing