ontological representation of scientific laws
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Ontological representation of scientific laws
Rafał Trójczak, Piotr Kulicki, Robert Trypuz
Faculty of PhilosophyThe John Paul II Catholic University of Lublin
6th International Conference on Non-Classical LogicsŁódź 2013
Trójczak, Kulicki, Trypuz (KUL) Science Ontology Łódź 2013 1 / 21
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Ontologies within ProOptiBeef
Outline
1 Ontologies within ProOptiBeef
2 Representation of scientific laws
3 Gaining new knowledge
4 Conclusion and Future Perspective
5 Acknowledgment
Trójczak, Kulicki, Trypuz (KUL) Science Ontology Łódź 2013 2 / 21
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Ontologies within ProOptiBeef
ProOptiBeef
ProOptiBeef – Optimising beef production in Poland according tostrategy “from fork to farm”a
Project aim: to increase the level of innovation in Polish beef sectorthrough comprehensive research and development in the field of beefqualityWithin the scope of ProOptiBeef there are:
experimental taskstheoretical activities
ahttp://www.prooptibeef.pl
Trójczak, Kulicki, Trypuz (KUL) Science Ontology Łódź 2013 3 / 21
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Ontologies within ProOptiBeef
Tower of Babel
Variety of Expertsmarketing and consumerresearch, economics ofconsumption;
sensory analysis;
development of green areas;
cattle feeding and farming;
evaluation of material of animalorigin;
technology and chemistry ofmeat;
Trójczak, Kulicki, Trypuz (KUL) Science Ontology Łódź 2013 4 / 21
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Ontologies within ProOptiBeef
Ontology in ProOptiBeef
By “ontology” here we meanformal specification of domain knowledge shared by parties involved ininformation exchange.
Ontologies are intended tohelp in expressing the resultsof the project in anunambiguous way;
be used as a component of asystem for searchinginformation in a database ofscientific articles;
be used as a component inexpert system gathering theresults of the project andrevealing them to the public.
Trójczak, Kulicki, Trypuz (KUL) Science Ontology Łódź 2013 5 / 21
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Ontologies within ProOptiBeef
Ontology in ProOptiBeef
OntoBeef Library
Domain: knowledge about beef, its production and consumption.
Papers: metadata knowledge about documents and contains adescription of hundreds of scientific papers on domain.
Science: description of problems, methods, data and theses.
Trójczak, Kulicki, Trypuz (KUL) Science Ontology Łódź 2013 6 / 21
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Representation of scientific laws
Outline
1 Ontologies within ProOptiBeef
2 Representation of scientific laws
3 Gaining new knowledge
4 Conclusion and Future Perspective
5 Acknowledgment
Trójczak, Kulicki, Trypuz (KUL) Science Ontology Łódź 2013 7 / 21
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Representation of scientific laws
Definition of scientific law
Scientific law is a constant relationship between things, and more precisely,between the qualities possessed by the objects or between events in whichthe objects participatea.
aS. Krajewski, “Prawa nauki - przegląd zagadnień metodologicznych”, 1982
Trójczak, Kulicki, Trypuz (KUL) Science Ontology Łódź 2013 8 / 21
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Representation of scientific laws
Taxonomy of scientific laws
Scientific Law
Methodological Law
Qualitative Law
Quantitative Law
Objective Law
CorrelationLaw
Functional Law
Monotonic Law
Law of InclusionOrdering
Law
Trójczak, Kulicki, Trypuz (KUL) Science Ontology Łódź 2013 9 / 21
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Representation of scientific laws
DL Conventional Notation
u intersection of concepts C u D C and Dt union of concepts C t D C or D¬ complement of concept ¬C not C∀ universal restriction ∀R.C all R-successors are in C∃ existential restriction ∃R.C an R-successor exists in Cv concept inclusion C v D all C are D: concept assertion a : C a is a C: role/relation assertion (a, b) : R a is R-related to b
{. . . } concept creator {a, b} concept with elements a, b
Trójczak, Kulicki, Trypuz (KUL) Science Ontology Łódź 2013 10 / 21
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Representation of scientific laws
Examples of different laws
Example (Methodologic law)
t1: Near infra red spectroscopy can be applied for prediction ofbeef tenderness.
t1 is an instant of methodological law class:
t1 : methodological law
Each NIR spectroscopy is method (which can be used) in t1:
NIR spectroscopy v ∃ isMethodIn {t1}Each concrete beef tenderness is subject (of study) in t1:
beef tenderness v ∃ isSubjectIn {t1}
Trójczak, Kulicki, Trypuz (KUL) Science Ontology Łódź 2013 11 / 21
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Representation of scientific laws
Example (Correlation law)
t2: There exists a correlation between thermal shortening of meatunder thermal treatment and beef thermal loss.
t2 : correlation law
thermal shortening v ∃ isParameterIn {t2}
beef thermal loss v ∃ isParameterIn {t2}
Trójczak, Kulicki, Trypuz (KUL) Science Ontology Łódź 2013 12 / 21
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Representation of scientific laws
Example (Functional law)
t3: Beef slaughtering season has influence on beef fat acids profile.
t3 : functional law
beef slaughtering season v ∃ isIndependentParameterIn {t3}
beef fat acids profile v ∃ isDependentParameterIn {t3}
Example (Monotonic law)
t4: Beef tenderness improves with longer aging time.
t4 : monotonic law
beef aging time v ∃ isIndependentParameterIn {t4}
beef tenderness v ∃ isDependentParameterIn {t4}
(t4, positive) : hasMonotonicTypeRel
Trójczak, Kulicki, Trypuz (KUL) Science Ontology Łódź 2013 13 / 21
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Representation of scientific laws
Example (Inclusion law)
t5: Bovine serum albumin is the main beef allergen.
t5 : inclusive law
bovine serum albumin v ∃ isInstantOfSubclassIn {t5}
beef allergen v ∃ isInstantOfSuperclassIn {t5}
Trójczak, Kulicki, Trypuz (KUL) Science Ontology Łódź 2013 14 / 21
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Representation of scientific laws
Example (Ordering law)
t6: Addition of antioxidant to ground beef improves its oxidativestability.
t6 : ordering law
ground beef v ∃ isContextIn {t6}
oxidative stability v ∃ isQualityIn {t6}
antioxidant v ∃ isDifferentiationFactorIn {t6}
(t6, positive) : hasMonotonicTypeRel
Trójczak, Kulicki, Trypuz (KUL) Science Ontology Łódź 2013 15 / 21
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Gaining new knowledge
Outline
1 Ontologies within ProOptiBeef
2 Representation of scientific laws
3 Gaining new knowledge
4 Conclusion and Future Perspective
5 Acknowledgment
Trójczak, Kulicki, Trypuz (KUL) Science Ontology Łódź 2013 16 / 21
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Gaining new knowledge
Gaining new knowledge
OWL-API-poweredapplication to deduce newscientific laws
Obtaining new knowledgefrom ontology:
transitivity offunctional laws;“reverse inheritance”
Trójczak, Kulicki, Trypuz (KUL) Science Ontology Łódź 2013 17 / 21
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Gaining new knowledge
Gaining new knowledge
OWL-API-poweredapplication to deduce newscientific laws
Obtaining new knowledgefrom ontology:
transitivity offunctional laws;“reverse inheritance”
Trójczak, Kulicki, Trypuz (KUL) Science Ontology Łódź 2013 17 / 21
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Gaining new knowledge
Gaining new knowledge
OWL-API-poweredapplication to deduce newscientific laws
Obtaining new knowledgefrom ontology:
transitivity offunctional laws;“reverse inheritance”
law 1
law 2
law 3
D
D
I
I
D
I
Functional Laws in Science Ontology
Q1
Q2
Q3
Trójczak, Kulicki, Trypuz (KUL) Science Ontology Łódź 2013 17 / 21
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Gaining new knowledge
Gaining new knowledge
OWL-API-poweredapplication to deduce newscientific laws
Obtaining new knowledgefrom ontology:
transitivity offunctional laws;“reverse inheritance”
C1
C2 C3 law 2law 1
C1
C2 C3 law 2law 1
law 1 law 2
Before reasoning
After reasoning
Trójczak, Kulicki, Trypuz (KUL) Science Ontology Łódź 2013 17 / 21
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Conclusion and Future Perspective
Outline
1 Ontologies within ProOptiBeef
2 Representation of scientific laws
3 Gaining new knowledge
4 Conclusion and Future Perspective
5 Acknowledgment
Trójczak, Kulicki, Trypuz (KUL) Science Ontology Łódź 2013 18 / 21
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Conclusion and Future Perspective
Conclusion and Future Perspective
We presented:
an ontology of scientific laws;
its implementation in JAVA application;
simple reasoning methods for obtaining a new knowledge from theone explicitly written in the ontology.
Future Perspectives:
ontology – evaluation, verification and testing;
implementation new reasoning methods;
interface for inputting a new data to Science.
Trójczak, Kulicki, Trypuz (KUL) Science Ontology Łódź 2013 19 / 21
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Acknowledgment
Outline
1 Ontologies within ProOptiBeef
2 Representation of scientific laws
3 Gaining new knowledge
4 Conclusion and Future Perspective
5 Acknowledgment
Trójczak, Kulicki, Trypuz (KUL) Science Ontology Łódź 2013 20 / 21
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Acknowledgment
Acknowledgment
Research was realised within the Project no. WND-POIG.01.03.01-00-204/09Optimising of Beef Production in Poland According to “from Fork to Farm”Strategy co-financed by the European Regional Development Fund under theInnovative Economy Operational Programme 2007 – 2013.
Trójczak, Kulicki, Trypuz (KUL) Science Ontology Łódź 2013 21 / 21