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The Concept of Metamodel on UML meta modeling A Working Model Proposed for Biological System

The Concept of Metamodel on UML meta modeling A Working Model Proposed for Biological System. Masaharu OBAYASHI Kanrikogaku, Ltd. PSE Workshop in Sapporo (2003/07/11). Revised : HL7 WGM in Atlanta (2009/09/24). Overview.

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The Concept of Metamodel on UML meta modeling A Working Model Proposed for Biological System

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  1. The Concept of Metamodel on UML meta modeling A Working Model Proposed for Biological System Masaharu OBAYASHI Kanrikogaku, Ltd. PSE Workshop in Sapporo (2003/07/11) Revised : HL7 WGM in Atlanta (2009/09/24)

  2. Overview • The UML (Unified Modeling Language) is useful to design an IT system from several viewpoints such as Enterprise, Information, Computational, Engineering, and Technology viewpoint. The UML can be extended with stereotype, tagged value, and constrains according to the target domains. Also, the concept of metamodeling is important to apply the UML to each particular domain. The metamodel is a key fundamental element to promote MDA (Model Driven Architecture) approach, especially model transformation technique. The working hypothesis for the biological (Life) system is suggested with applying the method of UML metamodeling. Keywords: UNL modeling, metamodel, MDA, Business Objects, Enterprise system, biological system

  3. Content • What is Modeling using UML? • UML Modeling Facility • MOF for Meta modeling • Tools supporting MDA • Framework for Modeling Management • Case Study for Meta Modeling • Conclusion

  4. What is Modeling using UML? • Modeling Target and Domain • MDA (Model Driven Architecture) • Modeling Type Variation • Modeling Viewpoints • Enterprise Viewpoint • Information Viewpoint • Computational Viewpoint • Engineering Viewpoint • Technology Viewpoint • Conceptual (Class) Model vs. Instance Model • Various Granularities and Abstraction levels • PIM （Platform Independent Model） vs. PSM （Platform Specific Model） • Metamodel and Domain Model

  5. RM-ODP Enterprise Viewpoint Information Viewpoint Computational Viewpoint Engineering Viewpoint Technology Viewpoint

  6. RGPS Role Enterprise Viewpoint Goal Information Viewpoint Computational Viewpoint Process Engineering Viewpoint Service Technology Viewpoint

  7. HL7RIM/V3/CDA/EHR-S/SAEAF EHR-S FM Role Enterprise Viewpoint Act CMET SAEAF: Behavior DMIM Information Viewpoint Voc Entity CDA RMIM Computational Viewpoint SAEAF: Service Engineering Viewpoint Technology Viewpoint

  8. Grammar English, Japanese, UML profile Vocabulary. Dictionary Expression, Sentence, Diagram Meta modeling Framework

  9. UML Modeling Facility • Enhancement of Modeling Facility • Extension by defining metamodel • Extension by profiling metamodel • Restriction by limiting Modeling Construct • Extension mechanism of UML • stereotype • tagged values • constraint

  10. MOF for Meta modeling • MOF（Meta Object Facility） • Interoperable metamodel • Provide Abstract Syntax as a upper model and manage memadata of governing Expression as lower Model • Metadata architecture in MOF • Information (Object) Layer (M0) • Model Layer (M1) • Meta model Layer(M2) • Meta meta model Layer(M3)

  11. Tools supporting MDA • Supported tools; • Transformation from PIM to PSM • Code generation from PSM • Code generation from PIM • Defining Model Transformation • Parameterized Model Transformation • Template for Model Transformation

  12. PIM Transformation Rule PIM-PSM Transformation Transformation Tool PSM

  13. PIM-PIM Transformation Transformation Rule PIM PIM Transformation Tool

  14. Framework for Modeling Management

  15. Meaning of Meaning [Ogden, Richards, 1923: enhanced by Obayashi ] (c) 2007 Masaharu Obayashi

  16. Graphical Notation Domain Profile Concept (Classifier) Sign Conceptualization Instances ComponentSet Component (c) 2007 Masaharu Obayashi

  17. Feature of MFI Core (1) • Modeling Artifacts to be registered • Metamodel, Model, Value sets, Vocabulary, Template, Pattern etc. • UML (domain) profile including metamodel and model • Artifacts based on OMG ODM (Part3) • Artifacts based on MOFQVT (Part4) • The other such as document, spreadsheet, XML schema etc. • Classification for components • From viewpoint of “Sign-Concept-Instances” (c) 2007 Masaharu Obayashi

  18. Feature of MFI Core (2) • Basic Metadata • Administered Item (from ISO/IEC 11179 MDR) • Selection of instance sets for a particular purpose usage • Assembly (Composition) of registered components • Plug and Play with selection • Core Framework for registering Ontology and Model Mapping (c) 2007 Masaharu Obayashi

  19. Framework of Registering (Key Idea) • Sign-Concept-Instances • Sign • designating a concept (named element) in a namespace. • namespace is a collection of signs • Concept • designated by a sign. • specified by domain knowledge. • classified by a classifier • Instances (Component Set) • a set of instances of Concept expressed by a sign. • Selection • Specific set of component for particular usage • referents designated by a sign. (c) 2007 Masaharu Obayashi

  20. Case Study for Meta Modeling • Biological (Life) System and Meta Concept • All life phenomenon consists of cascade mechanism for information processing • Elemental Component, Ion, Base Sequence (ATGC), Amino Acid, DNA, RNA, Protein, Enzyme, Hormone, (other product material by chemical reaction), Cell, Organ tissue, Individual, Species, Symbiotic, Ecosystem, Ecological chain, Social world • Participating all of Events has time oriented causal linkages and parallel processing have been ongoing in each individual and in each cell. • Life is activated based on gene information, which is able to produce various enzymes and proteins • Base sequence (combination of ATGC) decides the behavior of Life, then it is description of model. • As human being, only about 20,000 or 30,000 of genes emerge and build 60,000,000,000,000 cells as a body to spend social activity under accurate control. • Information, which are flown and circulated through DNA, RNA, Protein and DNA, are amplified over time • Not only model but also metamodel, which is so-called “machine tool” are described .

  21. Enterprise System vs Biological System

  22. Metamodel for Biological System

  23. Metamodel for Biological System

  24. Metamodel for Biological System

  25. Biological System : Fact • ①すべては、遺伝子DNAにキーになる情報が書き込まれている。 • ②DNAの情報は、タンパク質にマッピングされて３次元構造として機能を発現する。 • ③DNA自体が、相互作用の対象として変化する。 • ④DNAの転写を制御する仕組みが存在し、それは、外部からの情報や、自身のタンパク質の連鎖生成に影響される。 • ⑤タンパク質の連鎖反応回路が、形成されている。 • ⑥生きているとは、要素情報の出し入れ（代謝）できる状態を維持していることを意味する。 • ⑦DNA単独では、生きていけない。つまり、細胞のような、要素情報が詰まった環境が必要である。 • ⑧４塩基、２０アミノ酸を３塩基対でコード化、個体あたり１０００～３００００遺伝子、可能な推定全タンパク質５×１０１０の規模。 • ⑨塩基対の異なる遺伝子のファミリ、多型が存在する。 • ⑩遺伝子上で、交配、突然変異、交差などにより遺伝子組替えが可能。 • ⑪遺伝子世界では、タンパク質世界に対して、情報の高密度の圧縮が行われている。 • ⑫種の分化や、ゲノム進化の仕組みが備わっている。大進化は、不連続である。 • ⑬個体差の存在、多様性を許す仕組みがある。 • ⑭細胞は、分裂し性質の異なる細胞に分化する。 • ⑮細胞の分化、器官、組織の形成など高度な機能を獲得。 • ⑯環境の変化に対して、安定性、頑健性（ロバスとネス）をもつ。 • ⑰環境への適用により、さまざまな形質を獲得し、多様化。 • ⑱親が生後獲得した形質は、子供へは直接的に遺伝子としては継承されない。（文化としての継承） • ⑲受精卵から個体が発生する過程には、その個体の進化の履歴が保存されている。 • ⑳生命誕生まで、すべてのイベント系列を理論的には、たどることができる。

  26. Biological System : Assumption • ①DNA、RNA、タンパク質への情報の流れは、メタな概念を用いている。 • ②メタなレベルの構造（メタモデル）が、タンパク質という共通のオブジェクトで表現されている。つまり、自己反映的な操作が行われている。 • ③自己反映的な操作で、自己の構造を変化させることが可能になっている。 • ④ある時点での、意味のあるイベントに着目し、そのイベントの状況を記録することにより、要素の状態をモデル化する。 • ⑤イベントからイベント（群）への変化は、モデル変換としてとらえる。 • ⑥モデル変換のメタモデルが、タンパク質制御の規則（定義）としてDNAに書き込まれていると考える。 • ⑦モデルとしては、DANの塩基配列のモデル層、機能タンパク質の層、器官（細胞、小器官、組織など）の層に分ける。 • ⑧実際のモデル変換は、自然界の法則にしたがって状態を変化させる。 • ⑨モデル変換が続いている間は、少なくとも部分的には生きている状態で、すべてのモデル変換が出来ない状態になった場合が、その個体の死を意味する。

  27. Enterprise Viewpoint Information Viewpoint Metamodel For Biological System Computational Viewpoint Engineering Viewpoint Technology Viewpoint

  28. Biological System Library domain profile ４ １ ２ classifier ３ ５ Genotype pattern Event Control Process Model Functional Protein Gene instances comonentSet selection component １ ２ １ ３ １ ２ ２ ３ ４ ４ ９ ６ ３ ６ ８ ５ ５ ７ ８ ７ Base Sequence Definition Model Protein Sequence Definition Model

  29. Biological System Library domain classifier Organ Cell Enzyme Body instances componentSet selection component

  30. Conclusion • UML modeling method may apply wide range of target domain. • Model transformation tool based on MDA approach is needed • Modeling for Biological System should be more elaborated using meta modeling approach • Also, organized model library is required. • Integration of other modeling methods such as analytically-described model, statistically-modeled, probabilistic model, constitutive method, is open issue.

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