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The World as Database
Barry Smith
University at Buffalo
Institute for Formal Ontology and Medical Information Science,
University of Leipzig
http://ontologist.com
The riddle of representation
two humans, a monkey, and a robot are looking at a piece of cheese; what is common to the representational processes in their visual systems?
Answer:
The cheese, of course
The Technological Background
How the world became part of the World Wide Web
the cheese
Sources
“Motion in Databases: Issues and Possible Solutions”
Ouri Wolfson (University of Illinois)
“Intersection of GI and IT Spatial Databases”
Max J. Egenhofer (University of Maine)
Information Technologies
Global Positioning Systems (GPS)
Digital cameras
Information Technologies
Digital video cameras
Information Technologies
• chemical
• biological
Information Technologies
Microsensors
Location based services
Examples:
Where is the closest gas station? How do I get there?
Track my pet/child/prisoner
Location based services
Wall Street Journal May 8, 2000: Location-based services a killer application for the wireless internet
Strategy Analytics: consumer lbs a $7B market in North America by 2005
Why now? – Proliferation of portable/wearable/wireless devices
Moving Objects Database Technology
Query example:How often is bus #5 late by more than 10
minutes at station 20?
GPS
GPS
GPS
Wireless link
Moving Objects Database Technology
Trigger example:Send message when helicopter in a given
geographic area (trigger)
GPS
GPS
GPS
Wireless link
Moving Objects Database Technology
Query example:List trucks that will reach destination
within 20 minutes (future query)
GPS
GPS
GPS
Wireless link
Moving Objects Database Technology
Present query:
List taxi cabs within 1 mile of my location
GPS
GPS
GPS
Wireless link
PalmPilot context aware
Automatically display the resume of a person I am speaking with
Display the wiring/plumbing behind this wall
Display seismographic charts, maps, graphics, images, concerning a terrain a geologist is viewing
European Media Lab, Heidelberg
Tourism information services
Intelligent, speaking camera plus map display
Display all non-smoking restaurants within walking distance of the castle
Read out a history of the building my camera is pointing to
Mobile e-commerce
Inform a person located at L who needs items of a given sort where he can them (a) most quickly (b) most cheaply (c) at 2am.
Inform a person walking past a bar of his buddies in the bar
Further Applications
Digital battlefieldEmergency responseAir traffic controlSupply chain managementMobile workforce managementDynamic allocation of bandwidth in
cellular network
Syntax and Semantics
Traditional Syntactic/Semantic Approach to Information Systems
011011101010001000100010010010010010010001001111001001011011110110111011
String-Arrays vs. Objects
ghjui123
xxxxx xxxxx
Fodor’s Methodological Solipsism
011011101010001000100010010010010010010001001111001001011011110110111011
Humans, Machines, and the Structure of Knowledge
Harry M. CollinsSEHR, 4: 2 (1995)
Knowledge-down-a-wire
Imagine a 5-stone weakling having his brain loaded with the knowledge of a champion tennis player. He goes to serve in his first match -- Wham! -- his arm falls off.
He just doesn't have the bone structure or muscular development to serve that hard.
Sometimes it is the world which knows
I know where the book is
= I know how to find it
I know what the square root of 2489 is
= I know how to calculate it
I know how to recognize the presencfe of a tiger
= Smell, noise … (in real-world context)
A. Clark, Being There
humans can accomplish much without building detailed, internal models; we rely on
Epistemic action = manipulating Scrabble tiles – using the re-arranged pieces as basis for brain's pattern-completing abilitieswriting one large number above another to multiply them with pen on paper
and on
External scaffolding = maps, models, tools, language, culture
we act so as to simplify cognitive tasks by "leaning on" the structures in our environment.
Not all calculations done inside the head
Gibson: the world is not all chaos
the information outside of the head (the environment) is structured in a way that the brain can process
Types of knowledge/ability/skill
1. those that can be transferred simply by passing signals from one brain/computer to another.
2. those that can’t: -- here the "hardware" is important(a) abilities/skills contained in the body(b) abilities/skills contained in the world
From
The Methodological Solipsist Approach to Information Processing
ToThe Ecological Approach to Information
Processing
… J. J. Gibson
Functioning of Information System intelligible only as part of environment
0110
1110
1010
0010
0010
0010
0100
1001
0010
0100
0100
1111
0010
0101
1011
1101
1011
1011
Ontology
… a branch of philosophy
the science of what is
the science of the kinds and structures of objects, properties, events, processes and relations in reality
Ontology is in many respects comparable to the theories produced by science
… but it is radically more general than these
It can be regarded as a kind of generalized chemistry or zoology
(Aristotle’s ontology grew out of biological classification)
(Russell: Logic is a zoology of facts)
Aristotle
First ontologist
First ontology
(from Porphyry’s Commentary on Aristotle’s Categories)
Linnaean Ontology
Sources for ontological theorizing:
thought experiments
the study of ancient texts
development of formal theories
the results of natural science
now also: working with computers
The existence of computers
and of large databases
allows us to express old philosophical problems in a new light
The problem of the unity of science
The logical positivist solution to this problem addressed a world in which sciences are identified with
printed textsWhat if sciences are identified with
Information Systems ?
Each information system
has its own idiosyncratic terms and concepts by means of which it represents the information it receives How to resolve the incompatibilities which result when information systems (sciences) need to be merged?
The Information System Tower of Babel Problem
Opportunities
Sensor-based information systems
Massively parallel data acquisition
location per second of each person
SIG-INT and HUM-INT
Result: The World Wide Web
Vast amount of heterogeneous data sources
Needs dramatically better support for richly structured ontologies in databases
Ability to query and integrate across different ontologies (Semantic Web)
The term ‘ontology’
came to be used by information scientists to describe the construction of standardized taxonomies designed to make information systems mutually compatibleand thus to make data transportable from one information environment to another
An ‘ontology’
is a dictionary of terms formulated in a canonical syntax and with commonly accepted definitions and axioms designed to yield a shared frameworkfor use by different information systems communities
An ontology
is a concise and unambiguous description of the principal, relevant entities of an application domain and of their potential relations to each other
SO FAR
SO GOOD
But how was this idea in fact realized?
How did information systems engineers proceed to build ontologies? By looking at the world, surely Well, NoThey built ontologies by looking at what people think about the world
(methodological solipsism …)
Quine
For Quineans
Ontology studies, not reality,
but scientific theories
From ontology
… to ontological commitment
Quine:
each natural science has its own preferred repertoire of types of objects to the existence of which it is committed
Quineanism:
ontology is the study of the ontological commitments or presuppositions embodied in the different natural sciences
Quine:
only natural sciences can be taken ontologically seriously The way to do ontology is exclusively through the investigation of scientific theories
Thus it is reasonable to identify ontology
– the search for answers to the question: what exists? –
with the study of the ontological commitments of natural scientists
All natural sciences are compatible with each other
PROBLEM
The Quinean view of ontology becomes strikingly less defensible
when the ontological commitments of various non-scientists are allowed into the mix
How, ontologically, are we to treat the commitments of
astrologists,
clairvoyants,
believers in voodoo?
How, ontologically, are we to treat the commitments of
patients who believe that their illness is caused by evil spirits or magic spells?
Growth of Quinean ontology outside philosophy:
Psychologists and cognitive anthropologists have sought to elicit the ontological commitments (‘ontologies’, in the plural) of different cultures and groups.
This is not ontology
Not all the things that people believe in are genuine objects of ontological investigation
Only what exists is a genuine object of ontological investigation
Why, then,
do information systems ontologists study peoples’ beliefs, thoughts, concepts (STRING-ARRAYS)
rather than the objects themselves?
Arguments for Ontology as Conceptual Modeling
Ontology is hard.
Life is short.
Let’s do conceptual modeling instead
programming real ontology into computers is hard
therefore:
we will simplify ontology
and not care about reality at all
Painting the Emperor´s Palace is
h a r d
therefore
we will not try to paint the Palace at all
... we will be satisfied instead with a grainy snapshot of some other building
Ontological engineers
neglect the standard of truth to reality
in favor of other, putatively more practical, standards:
above all programmability
They turn to substitutes:
to models, to conceptualizations to STRING-ARRAYS
because these are easier to handle
For an information system ontology
there is no reality other than the one created through the system itself, so that the system is, by definition, correct
Only those objects exist which are represented in the system
(constructivism)
Tom Gruber (1995):
‘For AI systems what “exists” is
what can be represented’
Ontological engineering
concerns itself with conceptualizations
It does not care whether these are true of some independently existing reality.
In the world of information systems
there are many surrogate world models
and thus many ontologies
… and all ontologies,
are equalboth good and bad,
ATTEMPTS TO SOLVE THETOWER OF BABEL PROBLEM
VIA ONTOLOGIES AS“CONCEPTUAL MODELS” HAVE
FAILED
Can we do better?
Test Domain:
Medical Terminology
IFOMIS
Institute for Formal Ontology and Medical Information Science
University of Leipzig
Example 1: UMLS
Universal Medical Language SystemTaxonomy system maintained by National Library
of Medicine in Washington DC
134 semantic types800,000 concepts10 million inter-concept relationships
Example 2: SNOMED
Systematized Nomenclature of Medicine
Taxonomy system maintained by the College of American Pathologists
121,000 concepts
340,000 relationships
SNOMED
designed to foster interoperability
to serve as a“common reference point for comparison and aggregation of data throughout the entire healthcare process”
Problems with UMLS and SNOMED
Each is a fusion of several source vocabulariesThey were fused without an ontological system being established first They contain circularities, taxonomic gaps, unnatural ad hoc determinations… several billion dollars still being wasted in the making of retrospective fixes
Blood
Representation of Blood in UMLS
Blood
Tissue
EntityPhysical Object
Anatomical StructureFully Formed Anatomical Structure
An aggregation of similarly specialized cells and the associated intercellular substance.
Tissues are relatively non-localized in comparison to body parts, organs or organ components
Body SubstanceBody Fluid Soft Tissue
Blood as tissue
Representation of Blood in SNOMED
Blood
Liquid Substance
Substance categorized by physical state
Body fluid
Body Substance
Substance
Blood as fluid
So what is the ontology of blood?
We cannot solve this problem just by looking at concepts
concept systems may be simply incommensurable
the problem can only be solved
by taking the world itself into account
“golem”
objects are in the worldnot all concepts correspond to objects
not all concepts are relevant to ontology
concepts are in the head
problem of ‘merging’ ontologies
“golem”
“phantasy”
Another Example: Statements of Accounts
Company Financial statements may be prepared under either the (US) GAAP or the (European) IASC standards Under the two standards, cost items are often allocated to different revenue and expenditure categories depending on the tax laws and accounting rules of the countries involved.
Ontology’s job
is to develop an algorithm for the automatic conversion of income statements and balance sheets between the two systems.
Not even this relatively simple problem has been satisfactorily resolved
… why not?
because the two concept systems are simply incommensurable
the problem can only be solved
by taking the world itself into account
How to solve the Tower of Babel Problem?
How to fuse the two mutually incompatible ‘conceptual models’ of revenue ?
By drawing on the results of philosophical work in ontology carried out over the last 2000 years
This implies a view of ontology
not as a theory of concepts
but as a theory of reality
But how is this possible?
How can we get beyond our concepts?
answer: ontology must be maximally opportunistic
it must relate not to beliefs, concepts, syntactic strings but to the world itself
Maximally opportunistic
means:
look at concepts and beliefs critically
and always in the context of a wider view which includes independent ways to access the objects themselves
at different levels of granularity
Ontology must be maximally opportunistic
This means:
don’t just look at beliefs
look at the objects themselves
from every possible direction,
formal and informal
scientific and non-scientific …
Maximally opportunistic
means:look at the same objects at different levels of granularity:
Second step: select out the good conceptualizations
these have a reasonable chance of being integrated together into a single ontological system
• based on tested principles
• robust
• conform to natural science
Ontology
like cartography
must work with maps at different scales
Medical ontologies
at different levels of granularity:
cell ontology
drug ontology *
protein ontology
gene ontology *
anatomical ontology *
epidemiological ontology
Medical ontologies
disease ontology
therapy ontology
pathology ontology *
and also
physician’s ontology
patient’s ontology
There are many compatible map-like partitions
many maps at different scales,
all transparent to the reality beyond
the mistake arises when one supposes
that only one of these partitions is a true map of what exists
Partitions should be cuts through reality
a good medical ontology should NOT be compatible with the conceptualization of disease as:
caused by evil spirits and demons and cured by golems
The End