Various ontologies and MMF Ontology Registration

Various ontologies and MMF Ontology Registration OKABE, Masao Co-editor, MMF Ontology Registration Project, ISO/IEC JTC1 SC32/WG2 Corporate Systems Department, Tokyo Electric Power Co., Inc. 2006.3.21

Introduction • Nowadays, “Ontology” is almost a buzzword and the meaning is very broad and is not so clear. • In this presentation, I will present; • my personal understanding of ontologies and • how MMF Ontology Registration* is related to my understanding of ontologies. • This topic is very challenging to me. Any comments are very welcome. * Note: • MMF Ontology Registration is a part of mulch part standards ISO/IEC 19763# # Project leader: Hajime Horiuchi (Tokyo International University, Japan) • Its current status is FCD. • Co-editors of MMF Ontology Registration are • HE Keqing (SKLSE, Wuhan university, China) • OKABE, Masao (Tokyo Electric Power Co., Inc., Japan) 東京電力・システム企画部・岡部雅夫

Outline • My personal understanding of ontologies • Various kinds of ontologies • Trustiness of ontologies • MMF Ontology Registration Appendix: What TEPCO intends to do 東京電力・システム企画部・岡部雅夫

My personal understanding of ontologies • Various kinds of ontologies • Trustiness of ontologies • MMF Ontology Registration Appendix:What TEPCO intends to do 東京電力・システム企画部・岡部雅夫

Famous definition of ontology • A famous definition is; “An ontology is a specification of a conceptualization.” by T. R. Gruber at http://www-ksl.stanford.edu/kst/what-is-an-ontology.html • This definition is very abstract, but has a very important point. • That is, “a specification of a conceptualization” 東京電力・システム企画部・岡部雅夫

A chef bakes a pancake! Thought  x  Chef  y  Pancake Bake（x, y） specification of conceptualization Referent (in UoD) Symbol A specification of a conceptualization • Using the famous “Meaning Triangle” by Ogden and Richards, a specification of a conceptualization can be explained as a image of mapping from UoD to the world of symbols based on thought. • That is, ontology is not a thing in our mind and is an explicit expression in some language (or word). 東京電力・システム企画部・岡部雅夫

Wine Ontology Tell me a appropriate wine for the dinner. I will serve a special tomato based pasta source with fresh pasta as the main course. Wine agent The recommended one is Marietta Zinfandel. Where can I buy it? Winerlibrary.com has a sale on it. Simple use case • A simple use case from 7.2 Wine Agent, 7.Usage Example, OWL Web Ontology Language Guide, http://www.w3.org/TR/owl-guide/ Wine agent needs to be able to understand Wine ontology and find a suitable answer. 東京電力・システム企画部・岡部雅夫

What is an ontology? • From this simple use case, somewhat more specific definition can be gained, that is, • An ontology is a set of descriptions of the UoD in a formal language so that a computer can understand it and share it. • Then, the question is what it means that “A computer can understand an ontology and share an ontology.” • I think there are two meanings • One is “Uniqueness of interpretation”. • almost impossible • The other is “Uniqueness of inference”. • needs to be embodied. 東京電力・システム企画部・岡部雅夫

Uniqueness of interpretation • “Uniqueness of interpretation” means that, for example, symbol “Wine” in the Wine ontology cannot be interpreted as other than wine in the UoD. • But, Semantics, Logical Entailment in KIF manual （http://logic.stanford.edu/kif/Hypertext/node13.html） • The goal of knowledge encoding is to write enough sentences so that unwanted interpretations are eliminated. Unfortunately, this is not always possible. • I do not know why it is not always possible, but practically it seems so because, first of all, to define UoD rigorously is almost impossible. • Actually, there may be an interpretation that interprets “Wine” as Japanese sake and “Winegrape” as sake-rice. 東京電力・システム企画部・岡部雅夫

Uniqueness of inference (1 of 3) • A little bit different picture of Simple use case Wine Ontology Tell me a appropriate wine for the dinner. I will serve a special tomato based pasta source with fresh pasta as the main course. MyPortal agent Wine agent The recommended one is Marietta Zinfandel. Where can I buy it? Winerlibrary.com has a sale on it. How much is it? Uhm… There are so many questions. Wine ontology is open to all. You can find the answer by yourself. 東京電力・システム企画部・岡部雅夫

Uniqueness of inference (2 of 3) • Then, Wine Ontology Again, Tell me a appropriate wine for the dinner. I will serve a special tomato based pasta source with fresh pasta as the main course. MyPortal agent The recommended one is St. Clement Merlot. What!!! Isn’t it Marietta Zinfandel??? Uniqueness of inference means that this kind of things never happen. 東京電力・システム企画部・岡部雅夫

Uniqueness of inference (3 of 3) • Suppose • computer A and B have the same ontology, i.e. the same set of descriptions of the universe of discourse. • Then, • From the ontology, computer A can draw all the inferences that computer B can draw from the ontology. And vice versa. • The inferences that computer A and B draw from the ontology does not contradict the inferences a human draws from the universe of discourse that the ontology describes. 東京電力・システム企画部・岡部雅夫

Requirements of a language for ontologies • Based on the definitions of ontologies above, there are two requirements of a language for ontologies • First, “Syntax” so that a computer can analyze the descriptions. • Second, “Formal semantics (or model-theoretic semantics or interpretation conditions etc.)” that specifies conditions of interpretations and procedures of inference at least sound, usually complete and preferably decidable 東京電力・システム企画部・岡部雅夫

Ontology vs. Knowledge base • So, in my formal position, there is no specific distinction between an ontology and a knowledge base. • But, intuitively, there is difference between an ontology and a knowledge base. • An ontology does not lay an emphasis on inference so much as an knowledge base does, but mainly focuses on describing the universe of discourse so far as necessary. 東京電力・システム企画部・岡部雅夫

About formal semantics • In my informal position, I accept ontologies that are described in a language that does not have its formal semantics explicitly. So, for example, a model in UML can be an ontology. • It depends on what kind of query (in a broad sense) an ontology accepts whether an ontology needs its formal semantics or not. • If an ontology accepts only usual procedural queries, something like in SQL, then it does not need its formal semantics explicitly. • If an ontology accepts more declarative queries, something like ‘Tell me the suitable wine for the pasta with tomato’, then it needs its formal semantics. 東京電力・システム企画部・岡部雅夫

Various kinds of ontologies • Based on my understanding of ontologies above, there are several axes to classify ontologies, which are not necessarily uncorrelated, in addition to “Upper ontology vs. Domain ontology”. • Heavy weight ontology vs. Light weight ontology • Ontology of the real world vs. of information systems • Ontology on the static aspect vs. on the dynamic aspect • Ontology with data-flavor vs. with program-flavor • Ontology for a computer vs. for a human 東京電力・システム企画部・岡部雅夫

Heavy weight vs. Light weight • Heavy weight ontology • A rich and formal ontology that an inference engine can derive necessary results. • Example • “Wine ontology” (and “Food ontology”) from which an agent can derive a suitable wine for a dish. • Actual “Wine ontology” at http://www.w3.org/TR/2003/PR-owl-guide-20031209/wine and “Food ontology” at http://www.w3.org/TR/2003/PR-owl-guide-20031209/food are not so rich, even though “Food ontology” has several rules on the appropriate combination of food and wine. • Ontologies based on PSL-Core and -Outercore in TC184 or FLOWS-Core in W3C • Light weight ontology • A relatively simple ontology that mainly focuses on the relations among concepts. • No explicit distinction from a taxonomy and a thesaurus. • Example: • Ontologies in RDF or Topic Maps • Traditional terminological medical ontologies such as SNOMED-III • Ontologies in MIT Process Handbook 東京電力・システム企画部・岡部雅夫

modeling for information system Real world vs. Information systems (1 of 2) • information systems (specifications) • Ontology of information systems • The real world • Ontology of the real world Note: • This issue is almost the same as whether class “employee” means an employee in the real world or the objects in the HR systems at an object-oriented analysis. UoD UoD stands for stands for specifications of conceptualizations 東京電力・システム企画部・岡部雅夫

Real world vs. Information systems (2 of 2) • Ontology of the real world • Example: • Wine ontology, Food ontology • Medical ontologies such as SNOMED-CT, Galen etc. • Ontology of information systems • Practically, this is very important application domain of ontologies. • Example: • Ontologies for semantics web services • Ontologies that commercial tools focus on • Ontologies by Sandpiper’s Medius • Ontologies by ILOG’s Business Rule Management System • Ontologies by FairIsaac’s Blaze Advisor • Ontologies by Ontologyworks’s Integrated Ontology Development Environment 東京電力・システム企画部・岡部雅夫

Static aspect vs. Dynamic aspect (1 of 2) • Activity diagram etc. formalized • Ontology on the dynamic aspect • Analogy to UML model • Class diagram etc. formalized • Ontology on the static aspect 東京電力・システム企画部・岡部雅夫

Static aspect vs. Dynamic aspect (2 of 2) • Ontology of the static aspect • Example: • Wine ontology, Food ontology • Medical ontologies such as SNOMED-CT, Galen etc. • Ontologies by Ontologyworks’s Integrated Ontology Development Environment • Ontology of the dynamic aspect • There are several naming. • process ontology, service ontology, task ontology… • Example: • Ontologies for semantics web services • Ontologies based on PSL-Core and –Outercore 東京電力・システム企画部・岡部雅夫

Data-flavor vs. Program-flavor • Ontology with data-flavor • Ontology that are analyzed by others • Example: • Wine ontology, Food ontology • Medical ontologies such as SNOMED-CT, Galen etc. • “ServiceProfile” of ontologies in OWL-S • Ontology with program-flavor • An ontology that itself is executed, mainly focuses on Semantic Web services • Example: • “ServiceModel” of ontologies in OWL-S 東京電力・システム企画部・岡部雅夫

For a computer vs. for a human • Ontology for a computer • According to my definition, any ontologies have to be understandable to a computer in some sense. • Example • Wine ontology, Food ontology, Ontologies in OWL-S, Ontologies in CLIF • Ontologies by Ontologyworks’s Integrated Ontology Development Environment etc. • Ontology for a human • But, practically what a computer can understand from, for example, ontologies in RDF or even in OWL is almost limited to query (i.e. SPARQL) and annotations for a human (i.e. definitions in a natural language) in these ontologies are very important. • Moreover, there are ontologies that a computer can hardly understand. • Example • Ontologies in MIT Process Handbook 東京電力・システム企画部・岡部雅夫

About “Truth” of ontologies • In an ontology or model theory, every sentence in an ontology is “true” by nature. • But in reality, it is not easy • to know whether an ontology can really be trusted, • to define (characterize fully) the existing concept so as to conform what human recognize it, • to check consistency among many ontologies. 東京電力・システム企画部・岡部雅夫

Semantic Web’s position on “trustiness” (1 of 2) • The famous story by Tim Berners-Lee • …Lucy instructed her Semantic Web agent through her handheld Web browser. The agent promptly retrieved information about Mom's prescribed treatment from the doctor's agent, looked up several lists of providers, and checked for the ones in-plan for Mom's insurance within a 20-mile radius of her home and with a rating of excellent or very good on trusted rating services… at http://www.sciam.com/article.cfm?articleID=00048144-10D2-1C70-84A9809EC588EF21 東京電力・システム企画部・岡部雅夫

Semantic Web’s position on “trustiness” (2 of2) • Semantic Web seems very optimistic on “trustiness”. • At the top of the Semantic Web stack, there is “Trust”, but it still seems to have no substance. • Semantic web people seem to believe that the knowledge on the web can be trusted because it must have been weeded out if it could not be trusted. • This is too optimistic to apply ontologies to industries. From Tim Berners-Lee's Keynote at WWW2005 http://www.w3.org/2005/Talks/0511-keynote-tbl/#[17] 東京電力・システム企画部・岡部雅夫

Objectives of MMF Ontology Registration • The objectives of MMF Ontology Registration are to support trustiness of ontologies so that ontologies can be used practically in industries. • To ensure their trustiness, standardized ontologies in each business domain should be registered in MMF Ontology Registration registry as “Reference Ontologies”. • Also ontologies localized for some application based on Reference Ontologies should registered in MMF Ontology Registration registry as “ Local Ontologies”. 東京電力・システム企画部・岡部雅夫

Ontologies for MMF Ontology Registration • What kind of ontologies should be registered in MMF Ontology Registration registry? • Any kinds of ontologies, including the onespresentedin “2. Various kinds of ontologies”, should be able to registered in MMF Ontology Registration registry as Reference or Local Ontologies, so far as they are useful. • Therefore, MMF Ontology Registration has to have very generic structure that can be applied to almost any kinds of ontologies. 東京電力・システム企画部・岡部雅夫

An ontology consists of sentences. e.g. Example_Ontology consists of • Buyerhas.Creditrating(Tony) • Buyer(Tony) • Creditrating(Credit-A) • A sentence consists of symbols. e.g. Buyerhas.Creditrating(Tony) consists of • Buyer • has • logical symbols  ,  ,  (and variables ) Ontology Sentence • Creditrating • Tony Symbol Common basic structure of ontology • A very simplified but common three granularity level structure is; 東京電力・システム企画部・岡部雅夫

MMF Ontology Registration structure(1) • MMF Ontology Registration consists of Ontology, Ontology Component, Ontology Atomic Construct that correspond to • ontology, sentence, symbol * respectively and that have • administrative information ** of its correspondent • structural information of this level • a reference(URI) to its correspondent, for further semantics, if necessary Note * : Logical symbols such as  ,  ,  and variables are ignored. **: inherited from Administered Item of ISO/IEC 11179-3 MDR , such as registration authority, creation date etc. 東京電力・システム企画部・岡部雅夫

Actual ontology MMF Ontology Registration • e.g. Administrative information etc. corresponding to • Example_Ontology • e.g. Administrative information etc. corresponding to each of • Buyerhas.Creditrating(Tony) • Buyer(Tony) • Creditrating(Credit-A) • e.g. Administrative information etc. corresponding to of each • Buyer • has Ontology +administrative info. Ontology reference consistOf Ontology Component +administrative info Sentence reference use Ontology Atomic Construct +administrative info Symbol reference • Creditrating • Tony MMF Ontology Registration structure(2) • MMF Ontology Registration mainly relies on OMG ODM for actual ontologies. 東京電力・システム企画部・岡部雅夫

Reference and Local Ontologies • Reference Ontology • Standardized ontology in each business domain • Trustworthy to others • A reference ontology is composed by sentences only in reference ontologies. • A sentence in a reference ontology uses symbols only in reference ontologies • Local ontology • Localized ontology for some application system based on Reference Ontologies • It is its user’s responsibility to trust this ontology or not. • A local ontology is composed by sentences both in this local ontology and other reference ontology. • A sentence in a local ontology uses a symbols in this local ontology and other reference ontologies. 東京電力・システム企画部・岡部雅夫

Reference Ontology Local Ontology sameAs Local Ontology Component Reference Ontology Component 0:1 0:* sameAs Local Ontology Atomic Construct Reference Ontology Atomic Construct 0:1 0:* Core portion of MMF Ontology Registration metamodel 東京電力・システム企画部・岡部雅夫

Appendix: What TEPCO intends to do (1 of 2) • TEPCO (Tokyo Electric Power Co.,Inc) • is one of the largest private electric power utility companies and • operates and maintains many facilities, including nuclear power stations, fusel fuel power stations, hydro power stations, sub-stations etc. • faces the time when its skilled engineers are retiring. • So, it is important to maintain and improve the engineering know-how systematically. 東京電力・システム企画部・岡部雅夫

Appendix: What TEPCO intends to do (2 of 2) • TEPCO is now trying to establish ontologies that support the operations and maintenances of our facilities. • The ontologies TEPCO intends to establish are • on the real worlds, • mainly on the dynamic aspect, • with data-flavor, • mainly for a human and partially for a computer, • hopefully heavy-weight, so that a computer can check invalid operations and maintenance procedures. 東京電力・システム企画部・岡部雅夫

Thank you for your attention. • Any comments are very welcome to okabe.masao<at>tepco.co.jp 東京電力・システム企画部・岡部雅夫

Various ontologies and MMF Ontology Registration