Semantic Web: the Story So Far - Department of Computer ...

Semantic Web The Story So Far Department Of Computer -ppt Download

  • Date:03 Aug 2020
  • Views:32
  • Downloads:0
  • Size:2.72 MB

Share Presentation : Semantic Web The Story So Far Department Of Computer

Download and Preview : Semantic Web The Story So Far Department Of Computer

Report CopyRight/DMCA Form For : Semantic Web The Story So Far Department Of Computer


Transcription:

Ontology BasedInformation SystemsIan Horrocks ian horrocks comlab ox ac uk Information Systems Group.
Oxford University Computing Laboratory What is an Ontology What is an Ontology A model of some aspect of the world What is an Ontology .
A model of some aspect of the world Introduces vocabularyrelevant to domain e g Anatomy What is an Ontology .
A model of some aspect of the world Introduces vocabularyrelevant to domain e g Anatomy Cellular biology.
What is an Ontology A model of some aspect of the world Introduces vocabularyrelevant to domain e g Anatomy.
Cellular biology Aerospace What is an Ontology A model of some aspect of the world Introduces vocabulary.
relevant to domain e g Anatomy Cellular biology Aerospace What is an Ontology .
A model of some aspect of the world Introduces vocabularyrelevant to domain e g Anatomy Cellular biology.
Aerospace Hotdogs What is an Ontology A model of some aspect of the world Introduces vocabulary.
relevant to domain Specifies meaning semantics Heart is a muscular organ thatis part of the circulatory system What is an Ontology .
A model of some aspect of the world Introduces vocabularyrelevant to domain Specifies meaning semantics Heart is a muscular organ that.
is part of the circulatory system Formalised using suitable logic The Web Ontology Language OWL Motivated by Semantic Web activityAdd meaning semantics to web content by.
annotating with terms defined in ontologies Developed by WebOnt working group Based on earlier languagesRDF OIL and DAML OIL Became a recommendation on 10 Feb 2004.
Supported by tools and infrastructure APIs e g OWL API Thea OWLink Development environments e g Prot g TopBraid Composer Reasoners Information Systems e g Pellet HermiT Quonto Based on a Description Logic SHOIN .
Description Logics DLs Fragments of first order logic designed for KR Desirable computational properties Decidable essential Low complexity desirable .
Succinct and quantifier free syntax Description Logics DLs DL Knowledge Base KB consists of two parts Ontology aka TBox axioms define terminology schema Ground facts aka ABox use the terminology data .
Why Care About Semantics Why should I care about semantics Why Care About Semantics Why should I care about semantics Well from a philosophical POV we need to specify.
the relationship between statements in the logic andthe existential phenomena they describe Why Care About Semantics Why should I care about semantics Well from a philosophical POV we need to specify.
the relationship between statements in the logic andthe existential phenomena they describe That s OK but I don t get paid for philosophy Why Care About Semantics Why should I care about semantics .
Well from a philosophical POV we need to specifythe relationship between statements in the logic andthe existential phenomena they describe That s OK but I don t get paid for philosophy From a practical POV in order to specify and.
test ontology based information systems weneed to precisely define relationships likeentailment between logical statements Why Care About Semantics In FOL we define the semantics in terms of models a model theory A model is.
supposed to be an analogue of part of the world being modeled FOL uses avery simple kind of model in which objects in the world not necessarily physicalobjects are modeled as elements of a set and relationships between objects aremodeled as sets of tuples Why Care About Semantics .
In FOL we define the semantics in terms of models a model theory A model issupposed to be an analogue of part of the world being modeled FOL uses avery simple kind of model in which objects in the world not necessarily physicalobjects are modeled as elements of a set and relationships between objects aremodeled as sets of tuples .
Note that this is exactly the same kind ofmodel as used in a database objects in theworld are modeled as values elements andrelationships as tables sets of tuples What are Ontologies Good For .
Coherent user centric view of domain Help identify and resolve disagreements Ontology based Information Systems View of data that is independent oflogical physical schema.
Queries use terms familiar to users Answers reflect knowledge data e g Patients suffering from Vascular Disease Query navigation refinement Now that should clear up a Incomplete and semi structured data few things around here.
Integration of heterogeneous sources e Science E g for in silico investigations and hypothesis testing Comparing data e g on proteins to model of biological knowledge Characteristics of proteins captured in an ontology O.
Abox populated with e g data from gene sequencing experiments e Science E g for in silico investigations and hypothesis testing Comparing data e g on proteins to model of biological knowledge Characteristics of proteins captured in an ontology O.
Abox populated with e g data from gene sequencing experiments Expert compares hypotheses with query answers E g all human phosphotases are of type p1 pi Result may be e g discovery of new kinds of protein And these may be potential drug targets if unique to a pathenogen.
Result may also be discovery of errors in model Which may reflect gaps errors in existing knowledge Healthcare UK NHS has a 6 2 billion Connecting for Health IT programme Key component is Care Records Service CRS .
Live interactive patient record service accessible 24 7 Patient data distributed across local centres in 5 regional clusters and a national DB Detailed records held by local service providers Diverse applications support radiology pharmacy etc.
Applications exchange messages containing semantically rich clinicalinformation Summaries sent to national database SNOMED CT ontology provides common vocabulary for data Clinical data uses terms drawn from ontology.
Over 400 000 concepts Over 400 000 concepts Schema only no instances Language used is a well known fragment of OWL NHS version extended with 1 000s of additional classes.
OWL reasoner FaCT used to classify and check ontology Currently takes 10 minutes 180 missing subClass relationships were found e g Periocular dermatitis subClassOf Disease of face Fibrin measurement subClassOf Coagulation factor assay.
Vocabulary is extensible at point of use post coordination Users e g clinicians may add define new vocabulary Terminology service reasoner used to insert in ontology Typical new term almond allergy allergy caused by almond .
OWL reasoner FaCT used to classify new term Takes 10 ms Classified as a kind of nut allergy Clearly of crucial importance to recognise patients with allergy causedby almond as kinds of patient with nut allergy.
Columbia Presbyterian Medical Center Ontology used in analysis of results in path lab OWL reasoner used to check this ontology Several errors and omissions found that would have led to missed test results .
Result improvement in improvement in patient care Online Self Medication Advice Self medication is pervasive but can be hazardous 180 deaths in the USA in 2006 French project to provide on line advice.
Will be made available to 20 million customers of Frenchhealth insurance companies Patients have their own simple health care record SEHR Diagnosis system considers symptom descriptions SEHR Q A and self medication KB.
Uses an ontology for vocabulary and knowledge axioms about treatments contra indications side effects etc E g do not take x if patient suffers from y side effects of x may Online Self Medication Advice Self medication is pervasive but can be hazardous.
180 deaths in the USA in 2006 French project to provide on line advice Will be made available to 20 million customers of Frenchhealth insurance companies Patients have their own simple health care record SEHR .
Diagnosis system considers symptom descriptions SEHR Q A and self medication KB Uses OWL reasoner to advise on treatment and check forcontra indications side effects etc E g do not take x if patient suffers from y side effects may.
Online Self Medication Application Data taken from drug terminologies e g European Pharmaceutical Market Research Association Anatomical Therapeutic Chemical ATC Data transformed into OWL ontology.
Expert uses reasoner to check and enhance ontology OWL reasoner also used to check and enhance data Combined with induction and interaction with expert Corrected missing incorrect information on interactions contra indications allergies side effects etc .
Quality of data improved by factor of 8 Thank you for listeningAny questions Resources This talk .
http www comlab ox ac uk peopl... OWL 2 Proposed Recommendation http www w3 org 2007 OWL wiki ... A model of (some aspect of) the world Introduces vocabulary relevant to domain Specifies meaning (semantics) of terms Heart is a muscular organ that is part of the circulatory system Formalised using suitable logic The Web Ontology Language OWL Motivated by Semantic Web activity Add meaning (semantics) to web content by annotating with terms ...

Related Presentations