Building Trustworthy Semantic Webs Lecture #11: Logic and Inference Rules Semantic Web Applications Dr. Bhavani Thuraisingham October 1, 2008
3/15/2018 10: 20 2 Outline of the Unit 0 What are logic and inference rules 0 Why do we need rules? 0 Example rules 0 Logic programs 0 Monotonic and Nonmonotoic rules 0 Rule Markup 0 Example Rule Markup in XML 0 Policy Specification 0 Relationship to the Inference and Privacy problems 0 Summary and Directions 0 Part II: Semantic Web Applications
3/15/2018 10: 20 3 Logic and Inference 0 First order predicate logic 0 High level language to express knowledge 0 Well understood semantics 0 Logical consequence - inference 0 Proof systems exist 0 Sound and complete 0 OWL is based on a subset of logic – descriptive logic
3/15/2018 10: 20 4 Why Rules? 0 RDF is built on XML and OWL is built on RDF 0 We can express subclass relationships in RDF; additional relationships can be expressed in OWL 0 However reasoning power is still limited in OWL 0 Therefore the need for rules and subsequently a markup language for rules so that machines can understand
3/15/2018 10: 20 5 Example Rules 0 Studies(X, Y), Lives(X, Z), Loc(Y, U), Loc(Z, U) Home. Student(X) 0 i. e. if John Studies at UTDallas and John is lives on Campbell Road and the location of Campbell Road and UTDallas are Richardson then John is a Home student 0 Note that Person (X) Man(X) or Woman(X) is not a rule in predicate logic That is if X is a person then X is either a man of a woman. This can be expressed in OWL However we can have a rule of the form Person(X) and Not Man(X) Woman(X)
3/15/2018 10: 20 6 Monotonic Rules 0 Mother(X, Y) 0 Mother(X, Y) Parent(X, Y) If Mary is the mother of John, then Mary is the parent of John Syntax: Facts and Rules Rule is of the form: B 1, B 2, ---- Bn A That is, if B 1, B 2, ---Bn hold then A holds
3/15/2018 10: 20 7 Logic Programming 0 Deductive logic programming is in general based on deduction - i. e. , Deduce data from existing data and rules - e. g. , Father of a father is a grandfather, John is the father of Peter and Peter is the father of James and therefore John is the grandfather of James 0 Inductive logic programming deduces rules from the data - e. g. , John is the father of Peter, Peter is the father of James, John is the grandfather of James, James is the father of Robert, Peter is the grandfather of Robert - From the above data, deduce that the father of a father is a grandfather 0 Popular in Europe and Japan
3/15/2018 10: 20 8 Nonmonotonic Rules 0 If we have X and NOT X, we do not treat them as inconsistent as in the case of monotonic reasoning. 0 For example, consider the example of an apartment that is acceptable to John. That is, in general John is prepared to rent an apartment unless the apartment ahs less than two bedrooms, is does not allow pets etc. This can be expressed as follows: 0 Acceptable(X) 0 Bedroom(X, Y), Y<2 NOT Acceptable(X) 0 NOT Pets(X) NOT Acceptable(X) 0 Note that there could be a contradiction. But with nonmotonic reasoning this is allowed.
3/15/2018 10: 20 9 Rule Markup 0 The various components of logic are expressed in the Rule Markup Language – Rule. ML 0 Both monotonic and nonmonotnic rules can be represented 0 Example representation of Fact P(a) - a is a parent <fact> <atom> <predicate>p</predicate> <term> <const>a</const> <term> <atom> </fact>
3/15/2018 10: 20 10 Policies in Rule. ML <fact> <atom> <predicate>p</predicate> <term> <const>a</const> <term> <atom> Level = L </fact>
3/15/2018 10: 20 11 Example Policies 0 Temporal Access Control - After 1/1/05, only doctors have access to medical records 0 Role-based Access Control - Manager has access to salary information - Project leader has access to project budgets, but he does not have access to salary information - What happens is the manager is also the project leader? 0 Positive and Negative Authorizations - John has write access to EMP - John does not have read access to DEPT - John does not have write access to Salary attribute in EMP - How are conflicts resolved?
3/15/2018 10: 20 12 Privacy Policies 0 Privacy constraints processing - Simple Constraint: an attribute of a document is private - Content-based constraint: If document contains information about X, then it is private - Association-based Constraint: Two or more documents taken together is private; individually each document is public - Release constraint: After X is released Y becomes private 0 Augment a database system with a privacy controller for constraint processing
3/15/2018 10: 20 13 System Architecture for Access Control Pull/Query User Rule. MLAccess Policy base Push/result Rule. MFAdmin Credential base Rule. ML Data Documents Admin Tools
3/15/2018 10: 20 14 Rule. ML Data Management 0 Data is presented as Rule. ML documents 0 Query language – Logic programming based? 0 Policies in Rule. ML 0 Reasoning engine - Use the one developed for Rule. ML
3/15/2018 10: 20 15 Inference/Privacy Control Technology By UTD Interface to the Semantic Web Inference Engine/ Rules Processor Policies Ontologies Rule-based Data Management Rules Data
3/15/2018 10: 20 16 Summary and Directions 0 Rules have expressive and reasoning power 0 Handles some of the inadequacies of OWL 0 Both monotonic and nonromantic reasoning 0 Logic programming based 0 Policies specified in Rules. ML 0 Need to build an integrated system 0 Other rules: SWRL (semantic web rules language)
3/15/2018 10: 20 17 Semantic Web Applications 0 Discussion of applications - Horizontal Information Products at Elsevier - Data integration at Audi - Skill finding at Swiss Life - Think Tank Portal at Enter. Search - E-Learning - Web Services - Multimedia Collection at Scotland Yard - Online Procurement at Daimler Chrysler - Device Interoperability at Nokia 0 Common threads and challenges
3/15/2018 10: 20 18 Types of Application 0 Horizontal Information Products at Elsevier: Integration 0 Data integration at Audi: Integration 0 Skill finding at Swiss Life: Search 0 Think Tank Portal at Enter. Search: Knowledge man agent 0 E-Learning: Knowledge management 0 Web Services: Web services (for any of the other applications discussed) 0 Multimedia Collection at Scotland Yard: Searching 0 Online Procurement at Daimler Chrysler: E-Business 0 Device Interoperability at Nokia: Interoperability
3/15/2018 10: 20 19 Horizontal Information Products at Elsevier 0 Elsevier is publishing company based in Amsterdam - E. g. , publisher of Computer Standards and Interface Journal that has papers on all kinds of computer related standards 0 Currently the journals and books are grouped by topics such as say operating systems, databases, etc. (or at a higher level, Biology, Chemistry, etc. ) 0 Where do we then put the journal Computer Standards and Interfaces? 0 Need horizontal groupings also
3/15/2018 10: 20 20 Horizontal Information Products at Elsevier 0 Semantic web technologies are being used by Elsevier - RDF for document representation - RDF for ontologies - Query language based on RDF to query the documents and the ontologies - E. g. Life Science Thesaurus EMTREE - Other publishing companies are following in Elsevier’s direction
3/15/2018 10: 20 21 Data Integration at Audi 0 Integrate the data in multiple data sources to provide better customer relationship management and other services to improve profits 0 The databases are disparate and heterogeneous 0 Many current operations are carried out manually 0 Expensive and missed opportunities
3/15/2018 10: 20 22 Data Integration at Audi 0 Ontolotues are being specified to address semantic heterogeneous 0 E. g. , SLR is a type of camera; one applications calls it SLR, another application calls it Olympus-OM-10 0 When the latter application encounters the term SLR, it will query the ontology and determine that SLR is a camera 0 Details are given in Chapter 6
3/15/2018 10: 20 23 Skill Finding at Swiss Life 0 Swiss Life is an insurance company that developed a system to find all the skills in the company - E. g. , John’s skills are on data management, ontology management 0 Challenging problem as people have multiple skills for different applications 0 Need the following capabilities - Cross listing of skills - Querying skills - ----
3/15/2018 10: 20 24 Skill Finding at Swiss Life 0 Ontologies are being developed to specify the skills and query languages to query the ontologies 0 E. g. <owl: Class rdf: ID = “Publishing”> <rdfs: sub. Class. Of rdf: resource = ‘#Skills”/> </owl: Class> <owl: Class rdf: ID = “Skills”> - --- </owl: Class>
3/15/2018 10: 20 25 Think Tank Portal at Enter. Search 0 Enter. Search is a consortium of corporations in Europe that provide IT for the energy companies 0 Similar to MCC in Austin TX 0 Enter. Serach Portal currently describes the various research projects, papers etc. 0 XML representation is used for describing the web content 0 Need to represent semantics so that the corporations can get answers to useful questions of the form - “where do I put my computing resources to solve a problem? ”
3/15/2018 10: 20 26 Think Tank Portal at Enter. Search 0 Semantic web technologies are being utilized – in particular ontoogies are developed for the following - Hardware - Software - Communications - E-Commerce - Agents - Market/Auction - Resource Allocation - ----
3/15/2018 10: 20 27 E-Learning 0 With the Internet and the web, we now have on-line universities, course offerings, tutoring etc. 0 Students should have the choice for selecting various courses in the order they want, provide they take the prerequisites 0 Semantic web technologies enable flexible access as well as integration of various data sources and processes to enable learning 0 Ontologies are being developed for learning applications - E. g. , Contents of the courses - Description of the courses etc.
3/15/2018 10: 20 28 Web Services 0 Web services can be utilized by any of the other applications discussed in this unit (e. g. , Elsevier, Audi etc. ) 0 We services are invoked to carry out functions on the web including find locations, search for documents etc. 0 Simple services and compound services 0 Three components to the service - Service profile: Description of the service – what it does - Serviced model: how it does it - Service groundings: protocol for invoking the service
3/15/2018 10: 20 29 Web Services 0 DAML and DAML-S developed by the DARPA community combined with the European community developing OIL focused on , languages for web services - Semantic of the web services (e. g. , reasoning about the services, why certain actions are taken etc. ) - DAML+OIL 0 W 3 C community started with DAML+OIL for ontology specifications and developed OWL 0 E. g. , <profile: Service. Provider rdf ID = “Sportsnews”> - ---- </profile: Service. Provider>
3/15/2018 10: 20 30 Multimedia Collection Indexing at Scotland Yard 0 Scotland Yard uses a database to keep track of the antiques that are stolen 0 While sophisticated indexing techniques have been developed, there is a problem with semantics 0 E. g. , Red cushioned chair could also be described as Queen Anne chair 0 Ontologies for describing semantics 0 Need more details of the project
3/15/2018 10: 20 31 On-line Procurement at Daimler Chrysler 0 Daimler Chrysler interacts with numerous suppliers to develop a product 0 Standards developed by Rosetta. Net for E-Business are being used for interoperability - XML syntax, no semantics of the product descriptions are available 0 Ontologies for describing the various product descriptions including the semantics are the long term goal for seamless integration of the supply chain operation 0 Need more details of the project
3/15/2018 10: 20 32 Device Interoperability at Nokia 0 Nokia’s objective is to integrate multiple devices (cell phone, PDA, cars, laptop etc) to provide a pervasive computing environment 0 Objects is to locate the various services and understand the different devices and their functions - Need to describe the various services - Current technology provides syntactic descriptions 0 Semantic web technologies, through ontologies enable the understanding the devices and reasons about their functions 0 Need more details of the project
3/15/2018 10: 20 33 Common Threads and Challenges 0 Common Threads - Building Ontologies for Semantics - XML for Syntax 0 Challenges - Scalability, Resolvability - Security policy specification, Securing the documents and ontologies - Developing applications for secure semantic web technologies - Automated tools for ontology management = Creating, maintaining, evolving and querying ontologies
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