How much formality do we need ? Stefan Schulz MedInfo 2007 Workshop: MedSemWeb 2007 What Semantics Do We Need for A Semantic Web for Medicine? University.

Slides:

Advertisements

Similar presentations

Charting the Potential of Description Logic for the Generation of Referring Expression SELLC, Guangzhou, Dec Yuan Ren, Kees van Deemter and Jeff.

Advertisements

Complex Occurrents in Clinical Terminologies Stefan Schulz, Kornél Markó Department of Medical Informatics, Freiburg University Hospital, Germany Boontawee.

Upper Ontology Summit Wednesday March 15 The BFO perspective Barry Smith Department of Philosophy, University at Buffalo National.

Relational statements in OWL Recipe for Failure ? OWL.

1 Institute of Medical Biometry und Medical Informatics, University Medical Center Freiburg, Germany 2 AVERBIS GmbH, Freiburg, Germany 3 Paediatric Hematology.

Anatomical boundaries and immaterial objects Stefan Schulz Department of Medical Informatics University Hospital Freiburg (Germany)

Catalina Martínez-Costa, Stefan Schulz: Ontology-based reinterpretation of the SNOMED CT context model Ontology-based reinterpretation of the SNOMED CT.

Higgs bosons, mars missions, and unicorn delusions: How to deal with terms of dubious reference in scientific ontologies Stefan Schulz a,b Mathias Brochhausen.

Schulz S, Boeker M – BioTopLite – An Upper Level Ontology for the Life Sciences – ODLS 2013 BioTopLite : An Upper Level Ontology for the Life Sciences.

A Description Logics Approach to Clinical Guidelines and Protocols Stefan Schulz Department of Med. Informatics Freiburg University Hospital Germany Udo.

SNOMED CT’s Ontological Commitment Stefan Schulz University Medical Center, Freiburg, Germany Ronald Cornet Academic Medical Center, Amsterdam, The Netherlands.

Stefan Schulz Language and Information Engineering (JULIE) Lab, Jena University, Germany Representing Natural Kinds by Spatial Inclusion and Containment.

Andrade et al. Corpus-based Error Detection in a Multilingual Medical Thesaurus HISA ltd. Biography proforma MEDINFO Lygon Street, Brunswick East.

Towards a Computational Paradigm for Biological Structure Stefan Schulz Department of Medical Informatics University Hospital Freiburg (Germany) Udo Hahn.

Ontology Notes are from:

Ontologies and the Semantic Web by Ian Horrocks presented by Thomas Packer 1.

A Probabilistic Framework for Information Integration and Retrieval on the Semantic Web by Livia Predoiu, Heiner Stuckenschmidt Institute of Computer Science,

Introduction to Protégé AmphibiaTree 2006 Workshop Sunday 8:45–9:15 J. Leopold & A. Maglia.

Description Logics. Outline Knowledge Representation Knowledge Representation Ontology Language Ontology Language Description Logics Description Logics.

Extracted from “Lmo-2 interacts with Elf-2” On the Meaning of Common Statements in Biomedical Literature Stefan Schulz Department of Medical Informatics,

Ontological Foundations for Biomedical Sciences Stefan Schulz, Kornél Markó, Udo Hahn Workshop on Ontologies and their Applications, September 28, 2004,

Reference Ontologies, Application Ontologies, Terminology Ontologies Barry Smith

Ontology-based Convergence of Medical Terminologies: SNOMED CT and ICD-11 Institute for Medical Informatics, Statistics and Documentation, Medical University.

Developing an OWL-DL Ontology for Research and Care of Intracranial Aneurysms – Challenges and Limitations Holger Stenzhorn, Martin Boeker, Stefan Schulz,

Standardization of Anatomy Parts and Wholes – From Function to Location Stefan Schulz Department of Medical Informatics University Hospital Freiburg (Germany)

The Foundational Model of Anatomy and its Ontological Commitment(s) Stefan Schulz University Medical Center, Freiburg, Germany FMA in OWL meeting November.

Stefan Schulz Medical Informatics Research Group

Alignment of the UMLS Semantic Network with BioTop Methodology and Assessment Stefan Schulz University Medical Center, Freiburg, Germany Elena Beisswanger.

The Ontology of Biological Taxa

Scalable representations of diseases in biomedical ontologies and in SNOMED CT Stefan Schulz Institute of Medical Biometry und Medical Informatics University.

OWL 2 in use. OWL 2 OWL 2 is a knowledge representation language, designed to formulate, exchange and reason with knowledge about a domain of interest.

A CompuGroup Software GmbH, Koblenz, Germany b IMBI, University Medical Center Freiburg, Germany c Semfinder AG, Kreuzlingen, Switzerland d OntoMed Research.

Value Set Resolution: Build generalizable data normalization pipeline using LexEVS infrastructure resources Explore UIMA framework for implementing semantic.

A School of Information Science, Federal University of Minas Gerais, Brazil b Medical University of Graz, Austria, c University Medical Center Freiburg,

An Introduction to Description Logics (chapter 2 of DLHB)

WHO – IHTSDO: SNOMED CT – ICD-11 coordination: Conditions vs. Situations Stefan Schulz IHTSDO conference Copenhagen, Apr 24, 2012.

Semantic web course – Computer Engineering Department – Sharif Univ. of Technology – Fall Description Logics: Logic foundation of Semantic Web Semantic.

Ontological Foundations of Biological Continuants Stefan Schulz, Udo Hahn Text Knowledge Engineering Lab University of Jena (Germany) Department of Medical.

Advanced topics in software engineering (Semantic web)

Semantic Clarification of the Representation of Procedures and Diseases in SNOMED CT Stefan Schulz Medical Informatics, Freiburg University Hospital (Germany)

From GENIA to BioTop – Towards a Top-Level Ontology for Biology Stefan Schulz, Elena Beisswanger, Udo Hahn, Joachim Wermter, Anand Kumar, Holger Stenzhorn.

Scalable representations of diseases in biomedical ontologies Stefan Schulz, Djamila Raufie, Martin Boeker Institute of Medical Biometry und Medical Informatics.

How to Distinguish Parthood from Location in Bio-Ontologies Stefan Schulz a,b, Philipp Daumke a, Barry Smith c,d, Udo Hahn e a Department of Medical Informatics,

Organization of the Lab Three meetings:  today: general introduction, first steps in Protégé OWL  November 19: second part of tutorial  December 3:

DL Overview Second Pass Ming Fang 06/19/2009. Outlines  Description Languages  Knowledge Representation in DL  Logical Inference in DL.

Forschungszentrum Informatik, Karlsruhe FZI Research Center for Information Science at the University of Karlsruhe Variance in e-Business Service Discovery.

Ontology Engineering Lab #5 – September 30, 2013.

TRANSITION FROM BFO 1.1 TO BFO 2.0 (OWL FORMAT) Jie Zheng Department of Genetics University of Pennsylvania May 13 th, 2013.

Pre- and Post-Coordination in Biomedical Ontologies Stefan Schulz Daniel Schober Djamila Raufie Martin Boeker Medical Informatics Research Group University.

Detection of underspecifications in SNOMED CT concept definitions using language processing 1 Federal Technical University of Paraná (UTFPR), Curitiba,

Higgs bosons, mars missions, and unicorn delusions: How to deal with terms of dubious reference in scientific ontologies Stefan Schulz a,b Mathias Brochhausen.

Charting the Potential of Description Logic for the Generation of Referring Expression SELLC, Guangzhou, Dec Yuan Ren, Kees van Deemter and Jeff.

Unintended models in OBO - OWL ontologies OWL Stefan Schulz Freiburg University Medical Center, Germany.

Using OWL 2 For Product Modeling David Leal Caesar Systems April 2009 Henson Graves Lockheed Martin Aeronautics.

Upper Ontology Summit The BFO perspective Barry Smith Department of Philosophy, University at Buffalo National Center for Ontological Research National.

International Workshop 28 Jan – 2 Feb 2011 Phoenix, AZ, USA SysML and Ontology in Biomedical Modeling Henson Graves Yvonne Bijan 30 January 2011.

Stefan Schulz Medical Informatics Research Group

Knowledge Representation Part II Description Logic & Introduction to Protégé Jan Pettersen Nytun.

Formal ontologies vs. triple based KR gap or convergence?

Semantic Web Foundations

Towards a Computational Paradigm for Biological Structure

Can SNOMED CT be harmonized with an upper-level ontology?

Text Knowledge Engineering Lab University of Jena (Germany)

Ontology authoring and assessment

Representing Natural Kinds by Spatial Inclusion and Containment

Stefan Schulz1,2, Daniel Schober1, Ilinca Tudose1, Holger Stenzhorn3

Ontological Foundations for Biomedical Sciences

Hood College Master of Science in Bioinformatics (Proposed)

Small is Again Beautiful in Description Logics

Animating the reference terminology – showing classifiers at work

Presentation transcript:

How much formality do we need ? Stefan Schulz MedInfo 2007 Workshop: MedSemWeb 2007 What Semantics Do We Need for A Semantic Web for Medicine? University Medical Center Freiburg, Medical Informatics, Freiburg, Germany

Example Using Semantic Web standards (OWL-DL) Using Biomedical Ontology standards (OBO) Terminological Inference

Classes Amino Acid Protein Aminoaciduria Proteinuria

Relations (OBO RO) hasPart / partOf (parthood in a broad sense): relates continuants hasLocation / locationOf relates continuants or occurrents with continuants transitive, reflexive, antisymmetric

Description Logic Subsumption ⊑ Equivalence ≡ Existential quantification  Conjunction ⊓ transitive roles

Axioms Protein ⊑  hasPart.AminoAcid Aminoaciduria ≡ Disorder ⊓  hasLocation.(Body ⊓  hasPart.(PortionOfUrine ⊓  hasPart.AminoAcid)) Proteinuria ≡ Disorder ⊓  hasLocation.(Body ⊓  hasPart.(PortionOfUrine ⊓  hasPart.Protein))

Inference Proteinuria ⊑ Aminoaciduria (since Proteins have Amino Acids as parts, and partOf is transitive) false! Is this error due to formal underspecification ? Is hasPart not always transitive?

Formal correctness but ontological sloppyness AminoAcid: hidden ambiguity: AminoAcidSingleMolecule AminoAcidResidue AminoAcidSingleMoleculeCollection AminoAcidSingleMoleculeCollectionLowConc AminoAcidSingleMoleculeCollectionHighConc

Corrected Axioms Aminoaciduria ≡ Disorder ⊓  hasLocation.(Body ⊓  hasPart.(PortionOfUrine ⊓  hasPart.AminoAcidSingleMoleculeCollectionHighConc)) Proteinuria ≡ Disorder ⊓  hasLocation.(Body ⊓  hasPart.(PortionOfUrine ⊓  hasPart.ProteinMoleculeCollectionHighConc))

Two sides of the same coin Formal Correctness assures consistency Ontological Correctness assures adequacy

Conclusion Even little formality must be rooted in a correct ontological foundation to prevent unintended models with inadequate inferences If we do not know exactly what we are formalizing we cannot rely on machine reasoning. In this case we should give preference to informal, thesaurus-like knowledge representations