1 / 13

SysML and Ontology in Biomedical Modeling

SysML and Ontology in Biomedical Modeling. Henson Graves Yvonne Bijan 30 January 2011. Outline. Our interest in ontology biomedical modeling Our initial focus Modeling objectives by ontology community Ontology modeling achievements How their OWL modeling works

fgreen
Télécharger la présentation

SysML and Ontology in Biomedical Modeling

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. SysML and Ontology in Biomedical Modeling Henson Graves Yvonne Bijan 30 January 2011

  2. Outline • Our interest in ontology biomedical modeling • Our initial focus • Modeling objectives by ontology community • Ontology modeling achievements • How their OWL modeling works • Some comparisons between SysML and OWL

  3. Our Interest In Ontology Modeling • Do the modeling principles used by Description Logic (OWL) community offer anything for MBSE? • Will these examples and the OWL models help us understand how to integrate formal reasoning with SysML? • How do biomedical examples look in SysML? • Do the modeling principles used for air vehicles and other systems work in biomedical domain?

  4. Our Initial Focus Is On Structural Modeling For Anatomy & Chemistry This kind of modeling is being actively investigated using conceptual modeling languages such as OWL

  5. Ontology Modeling Objectives • Construct a model that captures what is common to all (or at least most) human hearts • corresponds to product model, or product line • Perform general reasoning about effects of pathology and disease symptom propagation • general properties of operation • Use general case to analyze and reason about a specific heart • fault detection

  6. The Conceptual Modeling Results • Large Taxonomies of medical, biological, anatomy terms • SNOMED –reference ontology for healthcare • GALEN – reference ontology for medical terminology • Identification of primitive relations for biomedical modeling, e.g., • Instance, subclass, part, • Representation as classes and properties in OWL and other Description Logic languages • Limited amounts of reasoning

  7. A General Principle From Conceptual Modeling That Applies To Engineering Clear distinction between model and thing being modeled Model Interpretation

  8. Biomedical Often Starts With Structural Diagram (e.g., PowerPoint Engineering) … and Constructs Axioms (aka Knowledge Base, Ontology) Heart HasComponent LeftSide RightSide divisionOF MitralValve PulmonicValve TricuspidValve AorticValve hasLayer hasConnection LeftVentricle Septum RightVentricle

  9. Diagrams Are Translated To Axioms Heart Heart subclass (hasComp 1AorticVentricle) This says that a necessary condition for a heart is that it have one Aortic Ventricle hasComp AorticVentricle

  10. Axioms Do Not Fully Recognize The Distinction Between Parts and Other Connections Heart For example the arrow labeled hasLayer in the heart structure diagram is translated as LeftVentricle subclass (hasLayer some Septum) This is incorrect outside of the context of the heart. SysML would lead one to represent this as hasPart1.hasLayer1 = hasPart2.hasLayer2 Which says that the left ventricle part of the heat is connected by hasLayer1 to the same thing as the right ventricle part is connected to haspart1 RightVentricle LeftVentricle Septum Haspart2: RigntVentricle Haspart1: LeftVentricle Haslayer1 Haslayer1

  11. Our SysML BDD and IBD for the Heart

  12. There is a lot to be learned from OWL modeling, - but they don’t always get it right • Good modeling principles are critical for any approach • Sort out and define what are the necessary conditions for the model • Sort out what is a part and what is a connection, both parts and connections can be necessary conditions

  13. Future Work • We are looking at parametric constraints and state diagrams for the heart. • Our objective is to have a model that allows us to generate a 3D visualization of the heart with behavior that responds to its neural stimulation

More Related