Joost Breuker

1
Ontology, ontologies and ontological reasoning1.
historical account

• Joost Breuker
• Leibniz Center for Law
• University of Amsterdam

2
Overview

• Philosophical roots (-500 now)
• Ontology as metaphysics
• Formal Ontology
• Lingua Univeralis Philosophica (17th 18th
  century)
• AI and knowledge engineering
• 80-ies Naïve physics manifesto
• 90-ies Knowledge acquisition
• 2nd millennium Semantic Web

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Ontology as part of philosophical meta-physics

• the theory or study of being as such ie of the
  basic characteristics of all reality
  (Encyclopedia Brittanica)
• Greek roots
• Heraclitus --gt Aristotle (categories
  universalia)
• physis/logos tangible/intangible
  (concrete/abstract)
• Plato ideas (forms) shape our understanding of
  the changing reality
• See John Sowa, Knowledge Representation,
  Brooks/Cole, 2000, chapter 2
• Aristotle,Kant, Peirce, Husserl, Brentano,
  Heidegger,
• A synthesis

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Aristotles categories by Brentano
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Kants categories
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Sowas synthesis as a lattice
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Formal ontology philosophical views in
ontological engineering

• Formal axiomatically defined terms
• Active community
• Applied Ontology Journal (IOS-Press)
• FOIS bi-annual conferences (www.formalontology.org
  /)
• Association (www.iaoa.org/)
• Focus on top-ontologies
• (meta-)properties) rather than concepts
• Typical examples
• Sowas
• SUMO (IEEE)
• DOLCE (Nicola Guarino)
• BFO (Barry Smith)

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And SUMO
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Top of DOLCE
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BFO (Basic Formal Ontology)
..... ..... .... .....
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(Meta)-properties vs entities

• Abstract vs Concrete (Sowa, CyC)
• Is a thought, a process, a circle abstract?
  tangible?
• Occurrent vs Continuant (DOLCE, BFO)
• About process vs object
• Process time-perspective (duration)
• Object space-perspective (position)
• However
• Time processes are as continuant as objects
  (eg gravitation)
• Processes and objects have life-cycles/duration
  
• Space processes are localised in/by objects
• Even fields
• It cannot be a dichotomy!

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Paradox-1

• these top ontologies have been reused
  extensively as the basic structure of many domain
  ontologies
• Eg BFO (Smith, Ontobra 2008)

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AstraZeneca - Clinical Information Science
BioPAX-OBO BIRN Ontology Task Force (BIRN OTF)
Computer Task Group Inc. Duke University
Laboratory of Computational Immunology Dumontier
Lab INRIA Lorraine Research Unit Kobe
University Graduate School of Medicine Language
and Computing National Center for Multi-Source
Information Fusion Ontology Works Science
Commons - Neurocommons University of Texas
Southwestern Medical Center
Groups and Organizations using BFO
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BioTop A Biomedical Top-Domain Ontology
Common Anatomy Reference Ontology (CARO)
Foundational Model of Anatomy (FMA) Gene
Ontology (GO) Infectious Disease Ontology
Ontology for Biomedical Investigations
(OBIOntology for Clinical Investigations (OCI)
Phenotypic Quality Ontology (PaTO) Protein
Ontology (PRO) RNA Ontology (RnaO) Senselab
OntologySequence Ontology (SO)Subcellular
Anatomy Ontology (SAO) Vaccine Ontology (VO)
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Paradox-1 explained??

• these top ontologies have been reused
  extensively as the basic structure of many domain
  ontologies
• They are not really used in an axiomatic way!
• The pre-structuring is very thin
• This philosophical heritage is
• confusing, and
• based on false parenthood
• Ontology is concerned with reality and existence
  ontologies with knowledge

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• However, there are far more interesting roots of
  ontologies in philosophy than in its metaphysical
  reflections

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Artificial Universal Language (lingua univeralis
philosophica)

• Middle age eg Ockham
• Babel is due to the fact the semantics do not
  transpire in the word-image or syntax
• The artificial language should therefore focus on
  the semantics (vs Latin, Esperanto, )
• A revival in the 17th century

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John Locke (1632-1704) on the language delusion
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17th century philosophers

• many proposals, but most noteworthy
• John Wilkins
• Gottfried Leibniz
• For more see J.L. Borges, The analytic language
  of John Wilkins Umberto Eco (1995) The search
  for the perfect language Steve Pinker (1994)
  Words and Rules

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The first ontological engineer John Wilkins
(1614-1672)
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The first ontological engineer John Wilkins
(1614-1672)

• Basic assumptions
• to repair the ruins of Babel
• There is a limited number of primitive categories
  (elements)
• Other concepts are combinations of primitives
  (molecules)
• --gt taxonomy/lattice
• Classified about 2000 concepts
• 40 top categories and many subcategories
• A word is constructed by assigning a fixed
  syllable/letter to a string in descending this
  graph
• Eg Zita animal (Z) beast (i) canine (t)
  dog (a)
• NB the basis for Rogets thesaurus (1852, now)

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An example on measurement
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distinguishing count/mass nouns
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even including a definitions of NIL and of
concept

• Nihil
• whatever can be named but cannot be thought
• Concept
• thought in so far as it is a thought of
  something

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Gottfried Leibniz (1646-1716)

• Lingua Characteristica Universalis
• More formal numbers instead of pronounceable
  characters
• eg animal2, rational3, human ? 6
• philosophy 5, philosopher -gt 30
• Calculus Ratiocinator
• calculus is binary (1679) and based on prime
  numbers
• this calculation can be performed mechanically

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Leibniz mechanical calculator

• Portable
• Inspired by Pascal, but also multiplication

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Gottfried Leibniz (1646-1716)

• Lingua Characteristica Universalis
• More formal numbers instead of pronounceable
  characters
• Eg animal2, rational3, human ? 6
• Philosophy 5, philosopher -gt 30
• Calculus Ratiocinator
• calculus is binary (1679) and based on prime
  numbers
• this calculation can be performed mechanically
• Basic assumptions
• All our ideas are compounded from a very small
  number of simple ideas, which form the alphabet
  of human thought (cf Pinker, 2008)
• Complex ideas proceed from these simple ideas by
  a uniform and symmetrical combination, analogous
  to arithmetical multiplication.

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Leibniz ontological engineering

• Methodology (De Arte Combinatoria, 1666)
• Systematic identification of all simple concepts
• Careful choice of signs (eg prime numbers)
• Rules for combination
• Reuse Wilkins top ontology as a starting point
• Knowledge representation with inference engine
  (multiplication/resolution)
• Prime numbers as signs
• Binary calculus
• (later too simple)
• Mechanical rendering was planned

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Leibniz dream

• Once the characteristic numbers of most notions
  are determined, the human race will have a new
  kind of tool, a tool that will increase the power
  of the mind much more than optical lenses helped
  our eyes, a tool that will be as far superior to
  microscopes or telescopes as reason is to vision
• from Leibniz, Philosophical Essays )

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even in service of dispute and justice
Calculemus

• "The only way to rectify our reasonings is to
  make them as tangible as those of the
  Mathematicians, so that we can find our error at
  a glance, and when there are disputes among
  persons, we can simply say Let us calculate
  calculemus, without further ado, to see who is
  right.16" (The Art of Discovery 1685, Wiener
  51, Wiener, Philip, 1951. Leibniz Selections.
  Scribner.)
• "...the plan I have had for a long time to reduce
  all human thinking to a calculation, such as we
  know it in algebra or the ars combinatoria...so
  that many arguments could be solved, the certain
  could be distinguished from the uncertain and
  even grades of probability could be measured.
  Then if two were arguing, they could say to each
  other Let us calculate (letter to Protestant
  Pietist Jacob Spener, July 1687)

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Dream or self delusion?

• Medal on calculator
• Motto
• superior to man
• Inscription
• The model of creation discovered by G.W.L
• one is enough for deriving everything from
  nothing

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publish or perish?

• Known for
• Theodicy (? Voltaire Candide)
• Invention of calculus (quarrel with Newton)
• But wrote
• 43 volumes published from 1923 on still going on
• 15,000 letters, 1000 correspondents (e-mail),
  200K pages
• Some justice two centuries later
• Russell (1900) ? inventor of formal logic
• Physics basis for relativity
• Mechanical reasoning (Turing, Wiener, AI)
• Ontologies for reasoning
• Mechanized normative (legal) reasoning
• Mechanized dispute resolution.

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However the Lingua Universalis movement is only

• A (virtual) ancestor of ontological engineering
  by hindsight
• Wilkins essay is reprinted in the 90ies (400
  100 a copy) but hardly available!
• They had an interesting indirect but practical
  effect in the devlopment thesauri
• Rogets thesaurus (1852, )
• The direct, real sources are in AI and in
  knowledge engineering

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Artificial Intelligence

• McCarty Hayes (69) Some philosophical problems
  etc.
• The frame problem
• Ontology as set of concepts to be represented
• Hayes (79) The second naive physics manifesto
• A classic, but only in printed form!
• axiomatization of common-sense
• Clusters of concepts
• Places positions, spaces objects,
• Qualities, quantities measurement
• Change, time history
• Energy, effort motion, .

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Where it really started

• Approaches to knowledge engineering (80ies-90ies)
• USA Expert systems, rapid prototyping
• EU (Common)KADS
• Separating domain knowledge from problem solving
  method
• PSM as control structure over domain level
  inferences
• Software engineering life cycle
• Specification Conceptual Modeling Language(CML)
• Design system architecture knowledge base
• Meeting ground EKAW Banff/KCAP

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Combining the two approaches

• CommonKADS
• Specifying domain knowledge ontology
• Is-a, part-of and dependency structures in CML
• USA
• Interoperability between knowledge representation
  (KR) formalisms KIF (Stanford)
• Ontologies can be formalized in KIF ? Ontolingua
• Ontologies for creating (specifications of)
  knowledge bases of knowledge systems

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Defining an ontology as

• the specification of a conceptualization
  (Gruber, 92)
• ( which applies to any model)

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Ontologies taking off on higher grounds

• Business process support
• Knowledge management
• Indexing and managing large amounts of
  information in companies and institutions
• Document management
• Expertise management
• The Semantic Web initiative
• Ontologies representing the semantics of the
  content of web pages

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Conclusions of the historical account

• Ontology has a confusing -- but also inspiring
  influence on developing ontologies
• The lingua universalis movement could have been a
  more adequate source of inspiration
• The potential roots of ontologies and
  ontological reasoning were rather in AI, in
  particular in Qualitative and Model based
  Reasoning (QR/MBR)
• They come from the Knowledge Acquisition
  community for specifying the conceptualization of
  knowledge bases