Interest in "ontologies": Neuroinfromatics Working Group February 2001 meetings February 2001 meetings HBP PIs HBP PIs Neuroanatomy Ontology Workshop.

Slides:



Advertisements
Similar presentations
Ontology Assessment – Proposed Framework and Methodology.
Advertisements

The KOS spectra: a tentative typology of Knowledge Organization Systems Renato Rocha Souza Douglas Tudhope Maurício Barcellos Almeida 11 th ISKO International.
ADVANCED TERMINOLOGY SYSTEMS
The Ontology of the Radiographic Image: From RadLex to RadiO.
Using the Digital Anatomist Foundation Model: a Graphical User Interface Emily Chung Linda Shapiro, Dept. of Computer Science and Engineering University.
FMA: a domain reference ontology Comments on Cornelius Rosse’s talk Anita Burgun WG6 meeting, Rome 29 Apr- 2 May 2005.
Copyright © 2011 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Chapter 8 The Enhanced Entity- Relationship (EER) Model.
File Systems and Databases
Biological Ontologies Neocles Leontis April 20, 2005.
The Potential of the Digital Anatomist Foundational Model for “Unifying” Biomedical Ontologies Cornelius Rosse M.D., D.Sc. Structural Informatics Group.
What is an Ontology? AmphibiaTree 2006 Workshop Saturday 8:45–9:15 A. Maglia.
Session 2: Introduction to Ontology The Foundational Model of Anatomy (FMA) Ontology: Framework for Cellular and Subcellular Anatomy Onard Mejino Structural.
Challenges in Reconciling Different Views of Neuroanatomy in a Reference Ontology of Anatomy José Leonardo V. Mejino Jr., M.D., Richard F. Martin, PhD,
GI Systems and Science January 23, Points to Cover  What is spatial data modeling?  Entity definition  Topology  Spatial data models Raster.
19 April, 2017 Knowledge and image processing algorithms for real-life applications. Dr. Maria Athelogou Principal Scientist & Scientific Liaison Manager.
Semantic Web Technologies Lecture # 2 Faculty of Computer Science, IBA.
Improving Data Discovery in Metadata Repositories through Semantic Search Chad Berkley 1, Shawn Bowers 2, Matt Jones 1, Mark Schildhauer 1, Josh Madin.
How do We Teach Anatomy to the Computer? Structural Informatics Group University of Washington American Association of Clinical Anatomists 2001.
ARTIFICIAL INTELLIGENCE [INTELLIGENT AGENTS PARADIGM] Professor Janis Grundspenkis Riga Technical University Faculty of Computer Science and Information.
Developing an OWL-DL Ontology for Research and Care of Intracranial Aneurysms – Challenges and Limitations Holger Stenzhorn, Martin Boeker, Stefan Schulz,
1 Introduction to Modeling Languages Striving for Engineering Precision in Information Systems Jim Carpenter Bureau of Labor Statistics, and President,
1 CS 456 Software Engineering. 2 Contents 3 Chapter 1: Introduction.
Linking Diseases and Genes through Informatics Knowledge Bases and Ontologies Joyce A. Mitchell, Ph.D. National Library of Medicine University of Missouri.
Of 39 lecture 2: ontology - basics. of 39 ontology a branch of metaphysics relating to the nature and relations of being a particular theory about the.
INF 384 C, Spring 2009 Ontologies Knowledge representation to support computer reasoning.
Olivier Bodenreider Lister Hill National Center for Biomedical Communications Bethesda, Maryland - USA Experiences in visualizing and navigating biomedical.
School of Computing FACULTY OF ENGINEERING Developing a methodology for building small scale domain ontologies: HISO case study Ilaria Corda PhD student.
Nancy Lawler U.S. Department of Defense ISO/IEC Part 2: Classification Schemes Metadata Registries — Part 2: Classification Schemes The revision.
1 st June 2006 St. George’s University of LondonSlide 1 Using UMLS to map from a Library to a Clinical Classification: Improving the Functionality of a.
Survey of Medical Informatics CS 493 – Fall 2004 September 27, 2004.
How do We Teach Anatomy to the Computer? Structural Informatics Group University of Washington American Association of Clinical Anatomists 2001.
Confidential 111 Financial Industry Business Ontology (FIBO) [FIBO– Business Entities] Understanding the Business Conceptual Ontology For FIBO-Business.
Atlas Interoperablity I & II: progress to date, requirements gathering Session I: 8:30 – 10am Session II: 10:15 – 12pm.
American Medical Informatics Association Annual Symposium 2001 The Role of Definitions in Biomedical Concept Representation Joshua Michael, José L. V.
Semantic Data & Ontologies CMPT 455/826 - Week 5, Day 2 Sept-Dec 2009 – w5d21.
SSO: THE SYNDROMIC SURVEILLANCE ONTOLOGY Okhmatovskaia A, Chapman WW, Collier N, Espino J, Conway M, Buckeridge DL Ontology Description The SSO was developed.
Semantic web course – Computer Engineering Department – Sharif Univ. of Technology – Fall Knowledge Representation Semantic Web - Fall 2005 Computer.
Visualization-based Brain Mapping Jim Brinkley (PI) Structural Informatics Group Dept Biological Structure University of Washington, Seattle Funded by.
Using Several Ontologies for Describing Audio-Visual Documents: A Case Study in the Medical Domain Sunday 29 th of May, 2005 Antoine Isaac 1 & Raphaël.
Sharing Ontologies in the Biomedical Domain Alexa T. McCray National Library of Medicine National Institutes of Health Department of Health & Human Services.
Ontology-Based Computing Kenneth Baclawski Northeastern University and Jarg.
Christoph F. Eick University of Houston Organization 1. What are Ontologies? 2. What are they good for? 3. Ontologies and.
© 2010 Health Information Management: Concepts, Principles, and Practice Chapter 5: Data and Information Management.
Using Domain Ontologies to Improve Information Retrieval in Scientific Publications Engineering Informatics Lab at Stanford.
- EVS Overview - Biomedical Terminology and Ontology Resources Frank Hartel, Ph.D. Director, Enterprise Vocabulary Services NCI Center for Bioinformatics.
Topic Maps introduction Peter-Paul Kruijsen CTO, Morpheus software ISOC seminar, april 5 th 2005.
Knowledge Representation. Keywordsquick way for agents to locate potentially useful information Thesaurimore structured approach than keywords, arranging.
Approach to building ontologies A high-level view Chris Wroe.
Achieving Semantic Interoperability at the World Bank Designing the Information Architecture and Programmatically Processing Information Denise Bedford.
Chapter:18 ADVANCED TERMINOLOGY SYSTEMS OBJECTIVES:  Describe the need for advanced terminology system.  Identify the components of advanced terminology.
APPLICATION OF ONTOLOGIES IN CANCER NANOTECHNOLOGY RESEARCH Faculty of Engineering in Foreign Languages 1 Student: Andreea Buga Group: 1241E – FILS Coordinating.
Enable Semantic Interoperability for Decision Support and Risk Management Presented by Dr. David Li Key Contributors: Dr. Ruixin Yang and Dr. John Qu.
Presented by Kyumars Sheykh Esmaili Description Logics for Data Bases (DLHB,Chapter 16) Semantic Web Seminar.
Ontologies COMP6028 Semantic Web Technologies Dr Nicholas Gibbins
Informatics for Scientific Data Bio-informatics and Medical Informatics Week 9 Lecture notes INF 380E: Perspectives on Information.
Data Grids, Digital Libraries and Persistent Archives: An Integrated Approach to Publishing, Sharing and Archiving Data. Written By: R. Moore, A. Rajasekar,
Knowledge Representation Part I Ontology Jan Pettersen Nytun Knowledge Representation Part I, JPN, UiA1.
Semantic Graph Mining for Biomedical Network Analysis: A Case Study in Traditional Chinese Medicine Tong Yu HCLS
UNIFIED MEDICAL LANGUAGE SYSTEMS (UMLS)
The UMLS and the Semantic Web
Unit - 3 OBJECT ORIENTED DESIGN PROCESS AND AXIOMS
COMP6215 Semantic Web Technologies
NeurOn: Modeling Ontology for Neurosurgery
Towards a Computational Paradigm for Biological Structure
ece 627 intelligent web: ontology and beyond
Datamining : Refers to extracting or mining knowledge from large amounts of data Applications : Market Analysis Fraud Detection Customer Retention Production.
Architecture for ICD 11 and SNOMED CT Harmonization
Towards a Unified Ontology for Biomedical Modeling and Simulation
Building Ontologies with Protégé-2000
The Foundational Model of Anatomy
Presentation transcript:

Interest in "ontologies": Neuroinfromatics Working Group February 2001 meetings February 2001 meetings HBP PIs HBP PIs Neuroanatomy Ontology Workshop Neuroanatomy Ontology Workshop Human Brain Project

Neuroanatomy Ontology should Expectations: Neuroanatomy Ontology should "Index and retrieve neuroscience information by species for mouse, rat, macaque, human; Define several hierarchical schemes for grouping primary structures to support accessing information in bigger chunks; Specify the relation of several thousand synonyms to allow the retrieval of information in terms of different nomenclatures; Provide atlases of segmented coronal brain sections for warping of MRI and PET scans." Neuroanatomy Ontology Workshop Summary

Explaining the Brain to a Computer Cornelius Rosse M.D., D.Sc., Structural Informatics Group University of Washington Mark S. Tuttle Ph.D., Apelon Federal Services, Inc.

Goals: Why we need to explain the brain to a computer? What to explain about the brain to a computer? How to do it? How to do it? What uses will it have? Explaining the Brain to a Computer

Why to explain the Brain to a Computer? "Few researchers use existing ontologies; why do another one that no one will use?" why do another one that no one will use?" Neuroanatomy Ontology Workshop Summary ”Why do we need a standard taxonomy? May disenfranchise a substantial user community." "Neuro-ontology development is an ill-posed problem.” HBP PIs' question/comment

Why to explain the Brain to a Computer? Prototype problem: Cortical language mapping Human Brain Project grant: Structural Information Framework for Brain Mapping J.F. Brinkley PI.

Superior temporal gyrus Cortical language mapping

Locations tested Active language site Intra-operative language sites

Supramarginal gyrus Variant gyral pattern Variant gyri

Cortical language sites Intra-operative language sites

Functional MRI language sites

Superimposed FMRI and cortical language maps

recorded with surface coordinate system of Caviness et al Incidence of cortical language sites

Montreal Average Brain All Male Patients N=15

Why to explain the Brain to a Computer? Graphical models: Document existence of probabilistic structure /function correlations Cannot reveal nature of relationships meaning of relationships Requirement: Add meaning to graphical data Symbolic Model

Why to explain the Brain to a Computer? Symbolic model to empower the computer to make inferences about the brain; to support knowledge-based applications for addressing neuroscience problems.

Goals: Why we need to explain the brain to a computer? What to explain about the brain to a computer? How to do it? How to do it? What uses will it have? Explaining the Brain to a Computer

What to explain about the brain to a computer? "What is the knowledge we need to classify?" "What levels of knowledge are to be included?" "Explicit definition of domain of neuroscience is a daunting task." HBP PIs' question/comments

What to explain about the brain to a computer? Two key strategic issues: 1. Constraints 2. Priorities

What Constraints? Subdomains in language mapping problem at UW: Neuroanatomy Richard Martin Kate Mulligan Neuroradiology Ken Maravilla Neurosurgery George Ojemann Psychology David Corina Karen Kinbar

What Constraints? Subdomains in language mapping problem at UW: Neuroanatomy Structural Informatics Richard MartinGraphical modeling Kate MulliganAndrew Poliakov, Jeff Prothero, Kevin Hinshaw Neuroradiology Symbolic modeling Ken MaravillaCornelius Rosse, Richard Martin, Jose Mejino, Linda Shapiro NeurosurgeryDatabase George OjemannRex Jakobovits PsychologyInformation System design David CorinaJim Brinkley Karen Kinbar

What Priorities? Motivation for Structural Informatics: Manifestations of health and disease may be regarded as attributes of anatomical structures; Logical and consistent representation of anatomical structure can provide the foundation for organizing other biomedical information.

What Priorities? "Any integrative approach by necessity will require a neuroanatomical basis" "Neuroanatomical ontology should provide the logical framework for organizing and locating information about the brain." organizing and locating information about the brain." Neuroanatomy Ontology Workshop Summary

What is anatomy? "Anatomy" …….. a homonym for anatomy (structure) e.g., anatomy of the frog, hand, brain anatomy (science) systematized branch of knowledge accumulated about anatomy (structure).

What is structure? "Structure" ……. a homonym for something composed of parts; (e.g., a building, a cell, a plant, brain) i.e., a material object the arrangement or interrelation of all the parts of a whole. (e.g., of a sentence, a symphony, or of society, government, or of the atom, the hand) i.e., relationships

What is structure? Structure of a material object Structure of Structure = Subobjects (parts) + Structural Relationships The components of an object and their manner of arrangement in constituting a whole.

What is anatomical structure? ”Anatomical Structure" … a homonym for a material object generated by the coordinated expression of an organism's own structural genes; the arrangement (physical interrelation) of all the parts of an anatomical structure in constituting the whole. Synonym: 'biological structure'

What Priorities? Question: What to explain first about the brain to a computer? Answer: The structure of anatomical structures that constitute the brain. Structure Brain = ({Subobject Brain }, {Structural relationship Brain })

What Priorities? Question: What to enter in the computer to explain (model) the structure of the brain? Answer: Symbols for anatomical structures of the brain. Symbols for structural relationships within the brain.

What kind of symbols? Thought “Concept” Symbol “Term” Referent Triangle of Meaning

What is a symbolic model? Symbolic model, a conceptualization of a domain of discourse represented with non-graphical symbols; in computer-processible (“understandable”) form; supports inference (reasoning).

What is a foundational model? Foundational Model is a symbolic model; declares the principles for including concepts and relationships that are implicitly assumed when knowledge of the domain is applied in different contexts; explicitly defines concepts and relationships necessary and sufficient for consistently modeling the structure of the coherent knowledge domain.

What is the Foundational Model of Anatomy (FM)? Foundational Model of Anatomy is a symbolic model of the physical organization of the human body; declares the principles for including concepts and relationships that are implicitly assumed when knowledge of anatomy is applied in different contexts; explicitly defines concepts and relationships necessary and sufficient for consistently modeling the structure of the human body.

What is the Foundational Model of Anatomy (FM)? A symbolic model of anatomy (science) represents the physical organization (structure) of biological organisms; currently limited to the human body. "Foundational" because anatomy is fundamental to all biomedical sciences; anatomical concepts encompassed by FM generalize to all biomedical domains.

where: Ao= Anatomy ontology ASA= Anatomical Structural Abstraction ATA= Anatomical Transformation Abstraction Mk= Metaknowledge (principles, rules, axioms) where: Ao= Anatomy ontology ASA= Anatomical Structural Abstraction ATA= Anatomical Transformation Abstraction Mk= Metaknowledge (principles, rules, axioms) Foundational Model of Anatomy Fm = (Ao, ASA, ATA, Mk)

ASA = (Do, Bn, Pn, SAn) (2) where: Do= Dimensional ontology Bn= Boundary network Pn= Part-of network SAn= Spatial Association network where: Do= Dimensional ontology Bn= Boundary network Pn= Part-of network SAn= Spatial Association network Fm = (Ao, ASA, ATA, Mk) (1) Anatomical Structural Abstraction Foundational Model of Anatomy

ASA = (Do, Bn, Pn, SAn) (2) where: Ln = Location On = Orientation Cn = Connectivity where: Ln = Location On = Orientation Cn = Connectivity Fm = (Ao, ASA, ATA, Mk) (1) Spatial Association Network SAn = (Ln, On, Cn) (3) Foundational Model of Anatomy

Right Ventricle Cardiac Chamber Cardiac Chamber Organ Subdivision Organ Subdivision Organ Part Anatomical Structure Anatomy Ontology -is a-

Right Ventricle Cardiac Chamber Cardiac Chamber Organ Subdivision Organ Subdivision Organ Part Anatomical Structure Anatomy Ontology -is a- Polyhedron Volume (3-D) Dimensional Ontology Dimensional Ontology

Right Ventricle Cardiac Chamber Cardiac Chamber Organ Subdivision Organ Subdivision Organ Part Anatomical Structure Anatomy Ontology -is a- Polyhedron Volume (3-D) Spatial Ontology Sternocostal Surface Sternocostal Surface Diaphragmatic Surface Diaphragmatic Surface bounded by boundary of Anatomical Feature Anatomical Feature Surface (2-D) bounded by Right Coronary Sulcus Right Coronary Sulcus Anterior Interventricular Sulcus Anterior Interventricular Sulcus Line (1-D) bounded by Coronary Sulcus Coronary Sulcus Inferior margin of heart Inferior margin of heart Apex Boundary Network -is a- Posterior IV Sulcus Posterior IV Sulcus Crux of heart Anatomical Landmark Anatomical Landmark Point (1-D) -is a-

Right Ventricle Cardiac Chamber Cardiac Chamber Organ Subdivision Organ Subdivision Organ Part Anatomical Structure Anatomy Ontology -is a- Polyhedron Volume (3-D) Spatial Ontology Sternocostal Surface Sternocostal Surface Diaphragmatic Surface Diaphragmatic Surface bounded by boundary of Anatomical Feature Anatomical Feature Surface (2-D) bounded by Right Coronary Sulcus Right Coronary Sulcus Anterior Interventricular Sulcus Anterior Interventricular Sulcus Line (1-D) bounded by Coronary Sulcus Coronary Sulcus Inferior margin of heart Inferior margin of heart Apex Boundary Network -is a- Posterior IV Sulcus Posterior IV Sulcus Crux of heart Anatomical Landmark Anatomical Landmark Point (1-D) -is a- Part-of Network Part-of Network HeartHeart super- object super- object Inflow part of RV of RV Inflow part of RV of RV Infundibulum Wall of RV Cavity of RV subobject -is a- has Cavity of infund. infund. Cavity of infund. infund. Cavity of infl.part infl.part

Right Ventricle Cardiac Chamber Cardiac Chamber Organ Subdivision Organ Subdivision Organ Part Anatomical Structure Anatomy Ontology -is a- Polyhedron Volume (3-D) Spatial Ontology Sternocostal Surface Sternocostal Surface Diaphragmatic Surface Diaphragmatic Surface bounded by boundary of Anatomical Feature Anatomical Feature Surface (2-D) bounded by Right Coronary Sulcus Right Coronary Sulcus Anterior Interventricular Sulcus Anterior Interventricular Sulcus Line (1-D) bounded by Coronary Sulcus Coronary Sulcus Inferior margin of heart Inferior margin of heart Apex Boundary Network -is a- Posterior IV Sulcus Posterior IV Sulcus Crux of heart Anatomical Landmark Anatomical Landmark Point (1-D) -is a- Part-of Network Part-of Network HeartHeart super- object super- object Inflow part of RV of RV Inflow part of RV of RV Infundibulum Wall of RV Cavity of RV subobject -is a- has Cavity of infund. infund. Cavity of infund. infund. Cavity of infl.part infl.part has adjacency adjacency anterioranteriorinferiorinferior to left Left ventricle ventricle Pericardial sac sacPericardial has adjacency adjacency DiaphragmDiaphragm inferiorinferior Spatial Association Network

Foundational Model of Anatomy Fm = (Ao, ASA, ATA, Mk) Fm BODY = {Fm ANATOMICAL_ENTITY }

Goals: Why we need to explain the brain to a computer? What to explain about the brain to a computer? How to do it? How to do it? What uses will it have? Explaining the Brain to a Computer

What about non-anatomical information? Is it an attribute of an anatomical structure? Does it need its own symbolic model? Adopt from existing sources? Integrate with anatomy model?

What to explain about the brain to a computer? "What is the knowledge we need to classify?" "What levels of knowledge are to be included?" "Explicit definition of domain of neuroscience is a daunting task." HBP PIs' question/comments

What to explain about the brain to a computer? Summary of strategy Constrain concept domain "Divide and conquer”; Priority: Symbolic Model of anatomical structure non-ambiguitycomprehensiveness highest level of granularity Use anatomy model as the logical foundation for other concept domains.

Goals: Why we need to explain the brain to a computer? What to explain about the brain to a computer? How to do it? How to do it? What uses will it have? Explaining the Brain to a Computer

How can the FM explain the brain to a computer? "No two anatomists agree on the precise definition of an anatomical structure” HBP PIs' question/comments Principled Modeling = Foundational Principles + Explicit Definitions

Foundational Principles Assertions that provide the basis for reasoning and action Constraint principle Definition principle Constitutive principle Organizational unit principle Structural relationship principle Representation principle Constraint principle Definition principle Constitutive principle Organizational unit principle Structural relationship principle Representation principle How can the FM explain the brain to a computer?

Explicit Definitions Purpose of FM definitions: Provide the rationale for an inheritance hierarchy in a structural context; Specify the essence of anatomical entities in terms of two sets of structural attributes: those of their genus differentiae

Principled Modeling Prototype problems: 1.How to reconcile different naming and classification conventions? 2. How to assure inheritance? 3.How to represent different and overlapping part-whole relationships? 4.How to represent different kinds of location attributes?

Principled Modeling Foundational Principles + Explicit Definitions Desiderata for definitions: Consistency with declared principles and context of modeling; State the essence of concepts in terms of their characteristics (attributes); Defining attributes should be essential characteristics shared by all members of a class; Include genus and differentiae.

HOW does FM reconcile different naming conventions? Semantic specificity Synonyms …………….. (e.g., esophagus) Homonyms …….……… (e.g., base of heart) Semantic expressivity ( e.g., unnamed entities …. parts of right ventricle)

Protégé

Semantic Specificity: synonyms

Homonym: ‘Base of heart’ Anteriorview Posteriorview Semantic Specificity: homonyms

Foundational Model Builder

Foundational Model Builder

Preferred name: Base of heart (anatomical)

Preferred name: Base of heart (clinical)

Semantic Specificity one preferred name for each anatomical entity associate synonyms with each preferred name disallow homonyms; use extensions one preferred name for each anatomical entity associate synonyms with each preferred name disallow homonyms; use extensions Assured in FM by:

Semantic Expressivity Ambiguous part-whole relationships Right ventricle

Semantic Expressivity Ambiguous part-whole relationships Infundibulum Right ventricle

Semantic Expressivity Ambiguous part-whole relationships Infundibulum Right ventricle Outflow part

Semantic Expressivity Ambiguous part-whole relationships Right ventricle Infundibulum Outflow part Right ventricle

Semantic Expressivity Ambiguous part-whole relationships Right ventricle Infundibulum Outflow part Right ventricle Inflow part

Preferred Name: Inflow part of right ventricle

UMLS

Leaf terms (concepts)

Multiple layers of meaning

Principled Modeling Prototype problems: 1.How to reconcile different naming and classification conventions? 2. How to assure inheritance? 3.How to represent different and overlapping part-whole relationships? 4.How to represent different kinds of location attributes?

HOW does FM reconcile different naming conventions? Knowledge sources Traditional hard-copy sources Textbooks, term lists Controlled Medical Terminologies (CMT)

Traditional knowledge sources: textbooks

Traditional knowledge sources: Term lists

Controlled Medical Terminologies MeSH (Medical Subject Headings) SNOMED (Systematized Nomenclature of Medicine) The Read Codes GALEN (General Architecture for Languages Encyclopedias and Nomenclatures in Medicine) NeuroNames (University of Washington) UMLS (Unified Medical Language Systems) US National Library of Medicine MeSH (Medical Subject Headings) SNOMED (Systematized Nomenclature of Medicine) The Read Codes GALEN (General Architecture for Languages Encyclopedias and Nomenclatures in Medicine) NeuroNames (University of Washington) UMLS (Unified Medical Language Systems) US National Library of Medicine

Controlled Medical Terminologies Representation of Anatomy no consistent scheme for modeling anatomy all schemes are consistent with traditional hard-copy sources contain inconsistencies Why? Context for modeling is broad; Modeling principles are not declared; Explicit definitions are not formulated.

Esophagus Leaf concept

Explicit Definitions Purpose of FM definitions: Provide the rationale for an inheritance hierarchy in a structural context; Specify the essence of anatomical entities in terms of two sets of structural attributes: those of their genus differentiae Principled Modeling

Definition Esophagus is an ‘organ with an organ cavity’, which connects the pharynx to the stomach

DefinitionDefinition Organ with organ cavity is a ‘cavitated organ’, the morphological parts of which surround a continuous cavity, which contains one or more body substances.

DefinitionDefinition Cavitated organ is an ‘organ’, the morphological parts of which surround one or more cavities, which contain one or more body substances.

DefinitionDefinition Organ is an ‘anatomical structure’,which consists of the maximal set of organ parts so connected to one another that together they constitute a self- contained unit of macroscopic anatomy, morphologically distinct from other such units.

DefinitionDefinition Anatomical structure is a ‘material physical anatomical entity’ which is an object generated by the coordinated expression of groups of genes; it consists of parts that are themselves anatomical structures.

Principled Modeling Prototype problems: 1.How to reconcile different naming and classification conventions? 2. How to assure inheritance? 3.How to represent different and overlapping part-whole relationships? 4.How to represent different kinds of location attributes?

Material Physical Anatomical Entity Material Physical Anatomical Entity -is a- Anatomical Structure Anatomical Structure Non-material Physical Anatomical Entity Non-material Physical Anatomical Entity

Material Physical Anatomical Entity Material Physical Anatomical Entity -is a- Anatomical Structure Anatomical Structure Non-material Physical Anatomical Entity Non-material Physical Anatomical Entity Physical Anatomical Entity Physical Anatomical Entity Conceptual Anatomical Entity Conceptual Anatomical Entity

Material Physical Anatomical Entity Material Physical Anatomical Entity -is a- Anatomical Structure Anatomical Structure Non-material Physical Anatomical Entity Non-material Physical Anatomical Entity Physical Anatomical Entity Physical Anatomical Entity Conceptual Anatomical Entity Conceptual Anatomical Entity

Material Physical Anatomical Entity Material Physical Anatomical Entity -is a- Anatomical Structure Anatomical Structure Non-material Physical Anatomical Entity Non-material Physical Anatomical Entity Physical Anatomical Entity Physical Anatomical Entity Conceptual Anatomical Entity Conceptual Anatomical Entity

Material Physical Anatomical Entity Material Physical Anatomical Entity -is a- Anatomical Structure Anatomical Structure Non-material Physical Anatomical Entity Non-material Physical Anatomical Entity Physical Anatomical Entity Physical Anatomical Entity Conceptual Anatomical Entity Conceptual Anatomical Entity Organ Part Organ Part

Material Physical Anatomical Entity Material Physical Anatomical Entity -is a- Anatomical Structure Anatomical Structure Non-material Physical Anatomical Entity Non-material Physical Anatomical Entity Physical Anatomical Entity Physical Anatomical Entity Conceptual Anatomical Entity Conceptual Anatomical Entity Organ Part Organ Part Organ Part Organ Part Tissue Organ component Organ subdivision

Anatomical Entity Physical Anatomical Entity Physical Anatomical Entity Material Physical Anatomical Entity Material Physical Anatomical Entity Organ Cell Organ Part Organ Part -is a- Anatomical Structure Anatomical Structure Body Part Body Part Non-material Physical Anatomical Entity Non-material Physical Anatomical Entity Conceptual Anatomical Entity Conceptual Anatomical Entity Human Body Human Body Organ System Organ System Tissue Organ component Organ subdivision

Anatomical Entity Physical Anatomical Entity Physical Anatomical Entity Material Physical Anatomical Entity Material Physical Anatomical Entity Organ Cell Organ Part Organ Part -is a- Anatomical Structure Anatomical Structure Body Part Body Part Non-material Physical Anatomical Entity Non-material Physical Anatomical Entity Body Substance Body Substance Conceptual Anatomical Entity Conceptual Anatomical Entity Human Body Human Body Organ System Organ System Tissue Organ component Organ subdivision

OrganOrgan Solid Organ Cavitated Organ Organ with cavitated organ part Organ with cavitated organ part Organ with organ cavity Organ with organ cavity HeartHeartEsophagusEsophagus -is a- Anatomy Ontology

Principled Modeling Fm = (Ao, ASA, ATA, Mk) Ao: taxonomic classification based on explicit definition of concepts, inheritance of definitional structural attributes; consistent with foundational principles.

Assurance of inheritance

Test What is the brain? To which Ao class would you assign the brain?

Anatomical Entity Physical Anatomical Entity Physical Anatomical Entity Material Physical Anatomical Entity Material Physical Anatomical Entity Organ Cell Organ Part Organ Part -is a- Anatomical Structure Anatomical Structure Body Part Body Part Non-material Physical Anatomical Entity Non-material Physical Anatomical Entity Body Substance Body Substance Conceptual Anatomical Entity Conceptual Anatomical Entity Human Body Human Body Organ System Organ System Tissue Organ component Organ subdivision

Organ Definition:Organ is an anatomical structure is an anatomical structure consists ofmaximal sets of organ parts consists ofmaximal sets of organ parts connected to one another constitute self-contained unit distinct from other units connected to other organs connected to other organs constitutesorgan system constitutesorgan system body part

Organ system Definition: Organ system anatomical structure is an anatomical structure members of predominantly one organ subclass; consists ofmembers of predominantly one organ subclass; interconnected by zones of continuity; interconnected by zones of continuity; connected to other organ systems constitutesthe human body

Definition of neuraxis NeuroNames: central nervous systemStedman’s: "the axial, unpaired part of the central nervous system....in contrast to the paired cerebral hemispheres" Dorland’s: an axon; central nervous system.

What is the brain?

Principled Modeling Prototype problems: 1.How to reconcile different naming and classification conventions? 2. How to assure inheritance? 3.How to represent different and overlapping part-whole relationships? 4.How to represent different kinds of location attributes?

Attributed Part-Whole Relationships

Shared parts Tracheobronchial tree Lungs

Shared parts (Cranial Nerves: Wilson-Pauwels et al.) Oculomotor Nerve

Shared parts

Anatomical/Arbitrary Parts (Netter’s Atlas of Human Anatomy)

Anatomical/Arbitrary Parts Cerebral vasculature of P54

Anatomical/Arbitrary Parts M1 M2 M3

Anatomical/Arbitrary Parts

Granularity of parts Anterior viewPosterior view Esophagus

Granularity of parts

(Alberts et al.: Molecular Biology of the Cell) Nuclear pore complex

ASA = (Do, Bn, Pn, SAn) (2) where: Do= Dimensional ontology Bn= Boundary network Pn= Part-of network SAn= Spatial Association network where: Do= Dimensional ontology Bn= Boundary network Pn= Part-of network SAn= Spatial Association network Fm = (Ao, ASA, ATA, Mk) (1) Anatomical Structural Abstraction Foundational Model of Anatomy

What is a cerebral sulcus a part of? Test

Anatomical Entity Physical Anatomical Entity Physical Anatomical Entity Material Physical Anatomical Entity Material Physical Anatomical Entity Organ Cell Organ Part Organ Part -is a- Anatomical Structure Anatomical Structure Body Part Body Part Non-material Physical Anatomical Entity Non-material Physical Anatomical Entity Body Substance Body Substance Conceptual Anatomical Entity Conceptual Anatomical Entity Human Body Human Body Organ System Organ System Tissue Organ component Organ subdivision

What is a cerebral sulcus a part of?

Principled Modeling Prototype problems: 1.How to reconcile different naming and classification conventions? 2. How to assure inheritance? 3.How to represent different and overlapping part-whole relationships? 4.How to represent different kinds of location attributes?

How to represent different location relationships? "Location, location, location; surface coordinates, scanner coordinates, Talairach coordinates, etc.; not standard, not universally accepted. Multiple forms of location definition need to be supported." HBP PIs' question/comment

ASA = (Do, Bn, Pn, SAn) (2) where: Ln = Location On = Orientation Cn = Connectivity where: Ln = Location On = Orientation Cn = Connectivity Fm = (Ao, ASA, ATA, Mk) (1) Spatial Association Network SAn = (Ln, On, Cn) (3) How to represent different location relationships?

How

How

How

How to represent different location relationships? Adjacency Anterior viewPosterior view Esophagus

T2-3 T8

Anterior Posterior How to represent different location relationships? Coordinates How

How How Anterior Posterior Right lateral Right lateral Left lateral Left lateral

How to represent different location relationships? Adjacency How Pericardial sac Pericardial sac

Anterior Posterior How to represent different location relationships? Coordinates How Right lateral Right lateral Left lateral Left lateral Right AnteriorLeft Anterior Right PosteriorLeft Posterior Right Antero- lateral Right Postero- lateral Left Postero- lateral Left Antero- lateral

T2-3 T8

How to represent different location relationships? Adjacency How

Principled Modeling Prototype problems: 1.How to reconcile different naming and classification conventions? 2. How to assure inheritance? 3.How to represent different and overlapping part-whole relationships? 4.How to represent different kinds of location attributes?

Goals: Why we need to explain the brain to a computer? What to explain about the brain to a computer? How to do it? How to do it? What uses will it have? Explaining the Brain to a Computer

ASA = (Do, Bn, Pn, SAn) (2) Ln = (Cnmt, Adj, QCrd) (4) Fm = (Ao, ASA, ATA, Mk) (1) Principled Modeling SAn = (Ln, On, Cn) (3) How can the FM explain the brain to a computer?

How Challenges for modeling neuroanatomy Superimposed FMRI and cortical language maps

How can the FM explain the brain to a computer? Challenges for modeling neuroanatomy Independent symbolic model for brain? Integrate with nervous system; Neuroanatomy model? Concept of Foundational Model valid for brain? Integrate with Foundational Model of whole body? Reuse available terminologies NeuroNames?

How can the FM explain the brain to a computer? Challenges for modeling neuroanatomy How to represent Individual variations in brain anatomy Classes of variants Anatomy of individuals Multiple species Selected species Vertebrate anatomy FM

Goals: Why we need to explain the brain to a computer? What to explain about the brain to a computer? How to do it? How to do it? What uses will it have? Explaining the Brain to a Computer

What uses will symbolic brain model have? Evaluation Validity of knowledge representations scheme consistency,comprehensiveness,expressivity How much anatomy does the computer know? How can we test it? Knowledge-based applications

Symbolic Information Image Repository 2-D Images 2-D Images 2-D Annotations 2-D Annotations 3-D Model 3-D Model 3-D Image Volumes 3-D Image Volumes Metadata Foundational Model Foundational Model

Symbolic Information Image Repository Protégé Annotator Brain Mapper Brain Mapper 2-D Images 2-D Images 2-D Annotations 2-D Annotations 3-D Model 3-D Model 3-D Image Volumes 3-D Image Volumes Metadata Foundational Model Foundational Model Authoring Programs

Symbolic Information Image Repository Protégé Annotator Brain Mapper Brain Mapper 2-D Images 2-D Images 2-D Annotations 2-D Annotations 3-D Model 3-D Model 3-D Image Volumes 3-D Image Volumes Metadata Foundational Model Foundational Model Authoring Programs Internet

Symbolic Information Image Repository Protégé Annotator Brain Mapper Brain Mapper 2-D Images 2-D Images 2-D Annotations 2-D Annotations 3-D Model 3-D Model 3-D Image Volumes 3-D Image Volumes Metadata Foundational Model Foundational Model Knowledge Server Knowledge Server Image Server Image Server Data Server Data Server Graphics Server Graphics Server Authoring Programs Internet

Symbolic Information Image Repository Protégé Annotator Brain Mapper Brain Mapper DA Atlases DA Atlases Tutor Consultant 2-D Images 2-D Images 2-D Annotations 2-D Annotations 3-D Model 3-D Model 3-D Image Volumes 3-D Image Volumes Metadata Foundational Model Foundational Model Knowledge Server Knowledge Server Image Server Image Server Data Server Data Server Graphics Server Graphics Server End User Interfaces Authoring Programs Internet

Symbolic Information Image Repository Protégé Annotator Brain Mapper Brain Mapper DA Atlases DA Atlases Tutor Consultant 2-D Images 2-D Images 2-D Annotations 2-D Annotations 3-D Model 3-D Model 3-D Image Volumes 3-D Image Volumes Metadata Foundational Model Foundational Model Metaknowledge Knowledge Server Knowledge Server Image Server Image Server Data Server Data Server Graphics Server Graphics Server DIGITAL ANATOMIST End User Interfaces Authoring Programs Internet

End User Interfaces DIGITAL ANATOMIST Knowledge Server Knowledge Server Image Server Image Server Data Server Data Server Graphics Server Graphics Server Symbolic KB Image Repository Anatomy Education Anatomy Education Brain Map Visualizer Brain Map Visualizer Radiation Oncology Radiation Oncology 2-D Images 2-D Images 2-D Annotations 2-D Annotations 3-D Model 3-D Model 3-D Image Volumes 3-D Image Volumes Clinical Info Foundational Model Foundational Model Metaknowledge Authoring Programs Clinical Applications

Conclusions What is a …. ? OntologyTaxonomy Symbolic Model Knowledge Base

Conclusions What is an ontology ? a theory about the nature of the kinds of things that exist; an academic pursuit that studies such theories; a conceptualization of a domain; a document or file that formally defines relationships among terms; an explicit formal specification of terms and the relations among them; a taxonomy plus a set of inference rules.

Conclusions What is Ao of FM ? taxonomic classification based on explicit definition of concepts, inheritance of definitional structural attributes; consistent with foundational principles. What is a taxonomy ? a document or file that defines classes of objects and relations among them.

Conclusions What is a symbolic model ? a conceptualization of a domain of discourse represented with non-graphical symbols; in computer-processible (“understandable”) form; support inference (reasoning).

Conclusions What is a foundational model ? is a symbolic model; declares the principles for including concepts and relationships that are implicitly assumed when knowledge of the domain is applied in different contexts; explicitly defines concepts and relationships necessary and sufficient for consistently modeling the structure of the coherent knowledge domain.

Conclusions What is a knowledge base ? an ontology together with sets of instances of its classes; an integration of several symbolic models that conceptualize the domains pertinent to a set of problems.

Conclusions Expectations Expectations (Neuroanatomy Ontology Workshop Summary) "Index and retrieve neuroscience information by species for mouse, rat, macaque, human; Define several hierarchical schemes for grouping primary structures to support accessing information in bigger chunks; Specify the relation of several thousand synonyms to allow the retrieval of information in terms of different nomenclatures; Provide atlases of segmented coronal brain sections for warping of MRI and PET scans."

Conclusions Traditional knowledge sources do not meet the needs of knowledge modeling in the information age; Need next-generation knowledge sources Neuro-anatomy FM Neuro-anatomy FM should be a resource for the development of knowledge-based applications Neuro-anatomy FM should be a resource for the development of knowledge-based applications

Conclusions Importance of and opportunity for modeling deep knowledge in a constrained domain; Collaboration between Domain experts basic and clinical neuroscientists Knowledge modelers; The future of biomedical concept representation prerequisite for knowledge-based applications enhancement of CMTs HBP's trend-setting initiative

Foundational Principles Constraint Principle The abstraction should model physical organization of the human body physical organization of the human body from an anatomical viewpoint from an anatomical viewpoint Physical anatomical entities generated by coordinated gene expression generated by coordinated gene expression

Foundational Principles Constitutive Principle: Anatomical Structures Anatomical Structures constituted by anatomical structures largest: organism smallest: macromolecule Anatomical Spatial Entities constituted by anatomical spatial entities of same dimension

Foundational Principles Organizational Unit Principle: Organ is the unit of macroscopic anatomy; Organ is the unit of macroscopic anatomy; Subclasses of Anatomical Structure Subclasses of Anatomical Structure constitute organs constitute organs constituted by organs constituted by organs