1. 1 CSIT600f: Introduction to Semantic Web Dickson K.W. Chiu PhD, SMIEEE Text: Antoniou & van Harmelen: A Semantic Web PrimerA Semantic Web Primer Ref: Ivan Herman: Tutorial on Semantic Web TechnologyTutorial on Semantic Web Technology

2. Dickson Chiu 2005CSIT600f 01-2 Towards a Semantic Web WWW is an impressive success: amount of available information (> 1 Giga-page) number of human users (> 200 Mega-user) The current Web represents information using natural language (English, Hungarian, Chinese,…) graphics, multimedia, page layout Humans can process this easily can deduce facts from partial information can create mental associations are used to various sensory information (well, sort of… people with disabilities may have serious problems on the Web with rich media!)

3. Dickson Chiu 2005CSIT600f 01-3 Need for understanding Web info Tasks often require to combine data on the Web: hotel and travel infos may come from different sites searches in different digital libraries etc. Again, humans combine these information easily even if different terminologies are used!

4. Dickson Chiu 2005CSIT600f 01-4 However… However: machines are ignorant! partial information is unusable difficult to make sense from, e.g., an image drawing analogies automatically is difficult difficult to combine information is same as ? how to combine different XML hierarchies? …

5. Dickson Chiu 2005CSIT600f 01-5 Example: Searching The best-known example… Google et al. are great, but there are too many false hits adding descriptions to resources should improve this

6. Dickson Chiu 2005CSIT600f 01-6 Where we are Today: the Syntactic Web [Hendler & Miller 02]

7. Dickson Chiu 2005CSIT600f 01-7 The Syntactic Web is … A hypermedia, a digital library A library of documents called (web pages) interconnected by a hypermedia of links A database, an application platform A common portal to applications accessible through web pages, and presenting their results as web pages A platform for multimedia BBC Radio 4 anywhere in the world! Peer-to-peer sharing (BT, edonkey, PPLive, … )PPLive A naming scheme Unique identity for those documents A place where computers do the presentation (easy) and people do the linking and interpreting (hard). Why not get computers to do more of the hard work?

8. Dickson Chiu 2005CSIT600f 01-8 Hard using the Syntactic Web … Finding the image of something Find pictures that contain red birds with blue background Complex queries involving background knowledge Find information about “ animals that use sonar but are not either bats or dolphins ” Locating information in data repositories Travel enquiries Prices of goods and services Results of human genome experiments Finding and using “ web services ” Visualise surface interactions between two proteins Delegating complex tasks to web “ agents ” Book me a holiday next weekend somewhere warm, not too far away, and where they speak French or English

9. Dickson Chiu 2005CSIT600f 01-9 What is the Problem? Consider a typical web page: Markup comprise rendering information (e.g., font size and colour) Hyper-links to related content Semantic content is accessible to humans but not (easily) to computers …

10. Dickson Chiu 2005CSIT600f 01-10 What information can we see … WWW2002 The eleventh international world wide web conference Sheraton waikiki hotel Honolulu, hawaii, USA 7-11 may 2002 1 location 5 days learn interact Registered participants coming from australia, canada, chile denmark, france, germany, ghana, hong kong, india, ireland, italy, japan, malta, new zealand, the netherlands, norway, singapore, switzerland, the united kingdom, the united states, vietnam, zaire Register now On the 7 th May Honolulu will provide the backdrop of the eleventh international world wide web conference. This prestigious event … Speakers confirmed Tim berners-lee Tim is the well known inventor of the Web, … Ian Foster Ian is the pioneer of the Grid, the next generation internet …

11. Dickson Chiu 2005CSIT600f 01-11 Information a machine may see …                          

12. Dickson Chiu 2005CSIT600f 01-12 Solution: XML markup with “ meaningful ” tags?     … How about …     Then how about …    

13. Dickson Chiu 2005CSIT600f 01-13 What Is Needed? A resource should provide information about itself also called “metadata” metadata should be in a machine processable format agents should be able to “reason” about (meta)data metadata vocabularies should be defined

14. Dickson Chiu 2005CSIT600f 01-14 What Is Needed (Technically)? To make metadata machine processable, we need: unambiguous names for resources (URIs) a common data model for expressing metadata (RDF) and ways to access the metadata on the Web common vocabularies (Ontologies) The “Semantic Web” is a metadata based infrastructure for reasoning on the Web It extends the current Web (and does not replace it)

15. Dickson Chiu 2005CSIT600f 01-15 Adding “ Semantics ” External agreement on meaning of annotations E.g., Dublin Core (http://dublincore.org/)http://dublincore.org/ Agree on the meaning of a set of annotation tags Problems with this approach Inflexible Limited number of things can be expressed Use Ontologies to specify meaning of annotations Ontologies provide a vocabulary of terms New terms can be formed by combining existing ones Meaning (semantics) of such terms is formally specified Can also specify relationships between terms in multiple ontologies

16. Dickson Chiu 2005CSIT600f 01-16 History of the Semantic Web Web was “ invented ” by Tim Berners-Lee (amongst others), a physicist working at CERN TBL ’ s original vision of the Web was much more ambitious than the reality of the existing (syntactic) Web: TBL (and others) have since been working towards realising this vision, which has become known as the Semantic Web E.g., article in May 2001 issue of Scientific American … “... a goal of the Web was that, if the interaction between person and hypertext could be so intuitive that the machine-readable information space gave an accurate representation of the state of people's thoughts, interactions, and work patterns, then machine analysis could become a very powerful management tool, seeing patterns in our work and facilitating our working together through the typical problems which beset the management of large organizations.”

17. Dickson Chiu 2005CSIT600f 01-17 Berner-Lee ’ s Architecture  Data Exchange  Semantics+reasoning  Relational Data ? ? ??? Relationship between layers is not clear OWL DL extends “DL subset” of RDF

18. Dickson Chiu 2005CSIT600f 01-18 A Spectrum of Ontology Catalog/ ID General Logical constraints Terms/ glossary Thesauri “narrower term” relation Formal is-a Frames (properties) Informal is-a Formal instance Value Restrs. Disjointness, Inverse, part- of…

19. Dickson Chiu 2005CSIT600f 01-19 Ontology in Philosophy - a philosophical discipline—a branch of philosophy that deals with the nature and the organization of reality Science of Being (Aristotle, Metaphysics, IV, 1) studies being or existence as well as the basic categories thereofbeingexistencebasic categories trying to find out what entities and what types of entities existentitiestypes of entities has strong implications for the conceptions of reality.reality Ontology: Origins and History

20. Dickson Chiu 2005CSIT600f 01-20 Ontology in Linguistics “Tank“ ReferentForm Stands for Relates to activates Concept [Ogden, Richards, 1923] ?

21. Dickson Chiu 2005CSIT600f 01-21 An ontology is an engineering artifact [Neches91]: defines basic terms and relations comprising the vocabulary of a topic area the rules for combining terms and relations to define extensions to the vocabulary “ An explicit specification of a conceptualization ” [Gruber93] Formal specification of a shared conceptualization (of a certain domain) [Borst 97]: Shared understanding of a domain of interest Formal and machine manipulable model of a domain of interest Ontology in Computer Science

22. Dickson Chiu 2005CSIT600f 01-22 Structure of an Ontology Ontologies typically have two distinct components: 1. Names for important concepts in the domain Elephant is a concept whose members are a kind of animal Herbivore is a concept whose members are exactly those animals who eat only plants or parts of plants Adult_Elephant is a concept whose members are exactly those elephants whose age is greater than 20 years 2. Background knowledge/constraints on the domain Adult_Elephants weigh at least 2,000 kg All Elephants are either African_Elephants or Indian_Elephants No individual can be both a Herbivore and a Carnivore

23. Dickson Chiu 2005CSIT600f 01-23 Ontology Elements Concepts (classes) + their hierarchy Concept properties (slots / attributes) Property restrictions (type, cardinality, domain, etc.) Relations between concepts (disjoint, equality, etc.) Instances E-R diagram / UML diagram ??? Note: “Property”  “Slot”  “Relation”  “Relationtype”  “Attribute”  Semantic link type”

24. Dickson Chiu 2005CSIT600f 01-24 A Semantic Web — First Steps Extend existing rendering markup with semantic markup Metadata annotations that describe content/function of web accessible resources Use Ontologies to provide vocabulary for annotations “ Formal specification ” is accessible to machines A prerequisite is a standard web ontology language Need to agree common syntax before we can share semantics Syntactic web based on standards such as HTTP and HTML Make web resources more accessible to automated processes

25. Dickson Chiu 2005CSIT600f 01-25 Ontology Design and Deployment Given key role of ontologies in the Semantic Web, it will be essential to provide tools and services to help users: Design and maintain high quality ontologies, e.g.: Meaningful — all named classes can have instances Correct — captured intuitions of domain experts Minimally redundant — no unintended synonyms Richly axiomatized — (sufficiently) detailed descriptions Store (large numbers) of instances of ontology classes, e.g.: Annotations from web pages Answer queries over ontology classes and instances, e.g.: Find more general/specific classes Retrieve annotations/pages matching a given description Integrate and align multiple ontologies

26. Dickson Chiu 2005CSIT600f 01-26 Steps in building an ontology 1. determine domain and scope 2. enumerate important terms 3. define classes and class hierarchies 4. define slots 5. define slot constraints (cardinality, value-type, etc.)

27. Dickson Chiu 2005CSIT600f 01-27 Step 1: Determine Domain and Scope Domain: geography Application: route planning agent Possible questions: Distance between two cities? What sort of connections exist between two cities? In which country is a city? How many borders are crossed?

28. Dickson Chiu 2005CSIT600f 01-28 Step 2: Enumerate Important Terms country city capital border connection Connection_on_land Connection_in_air Connection_on_water road railway currency

29. Dickson Chiu 2005CSIT600f 01-29 Step 3: Define Classes and Class Hierarchy

30. Dickson Chiu 2005CSIT600f 01-30 Step 4: Define Slot of Classes Step 5: Define Slot Constraints Attribute cardinality Ex: Borders_with multiple, Start_point single Attribute-value type Ex: Borders_with- Country Geographic_entity CountryCity Has_capital Capital_ofBorders_with Connection Start_point End_point Capital_city

31. Dickson Chiu 2005CSIT600f 01-31 Issues on class hierarchy - all is-a relations hold? Inst(B)  Inst(A) B A C D - check transitivity C Subclass_of(A) D Subclass_of(C) D Subclass_of(A) - avoid unexpected cycles B Subclass_of(A) A Subclass_of(B) A=B

32. Dickson Chiu 2005CSIT600f 01-32 Issues on Slots -transitive slots A.connection(B) B.connection(C) A.connection(C) -symmetric slots Ex. A borders_with B B borders_with A - inverse slots (redundant, but explicit) Country Has_capital Capital_of Capital_city

33. Dickson Chiu 2005CSIT600f 01-33 More Example: Automatic Assistant Your own personal (digital) automatic assistant knows about your preferences builds up knowledge base using your past can combine the local knowledge with remote services: hotel reservations, airline preferences dietary requirements medical conditions calendaring etc It communicates with remote information (i.e., on the Web!)

34. Dickson Chiu 2005CSIT600f 01-34 Example: Database Integration Databases are very different in structure, in content Lots of applications require managing several databases after company mergers combination of administrative data for e-Government biochemical, genetic, pharmaceutical research etc. Most of these data are now on the Web The semantics of the data(bases) should be known how this semantics is mapped on internal structures is immaterial

35. Dickson Chiu 2005CSIT600f 01-35 Example: Digital Libraries It is a bit like the search example It means catalogs on the Web librarians have known how to do that for centuries goal is to have this on the Web, World-wide extend it to multimedia data, too But it is more: software agents should also be librarians! help you in finding the right publications

36. Dickson Chiu 2005CSIT600f 01-36 Example: Semantics of Web Services Web services technology is great But if services are ubiquitous, searching issue comes up, for example: “find me the most elegant Schrödinger equation solver” what does it mean to be “elegant”? “most elegant”? mathematicians ask these questions all the time… It is necessary to characterize the service not only in terms of input and output parameters… …but also in terms of its semantics

37. Dickson Chiu 2005CSIT600f 01-37 How Simple Ontologies Help not as costly to build and potentially more importantly, many are available provide a controlled vocabulary website organization and navigation support support expectation setting (e.g. user interface) “umbrella” structures from which to extend content (e.g., UNSPSC)UNSPSC searching support sense disambiguation support (e.g., terms belong to different categories) Deborah McGuinness. Ontologies Come of Age. The Semantic Web: Why, What and How, MIT Press, 2001. (MS-Word)MS-Word

38. Dickson Chiu 2005CSIT600f 01-38 How Structured Ontologies Help more structure => more power consistency checking completion (of unspecified attributes and relations) interoperability support validation and verification testing or even encode entire test suites structured, comparative, and customized search “intelligence” in application, e.g., system configuration support

39. Dickson Chiu 2005CSIT600f 01-39 Benefits of Semantic Web Communication between people Interoperability between software agents Reuse of domain knowledge Make domain knowledge explicit Analyze domain knowledge

40. Dickson Chiu 2005CSIT600f 01-40 The Semantic Web is Not “Artificial Intelligence on the Web” although it uses elements of logic… … it is much more down-to-Earth (we will see later) it is all about properly representing and characterizing metadata of course: AI systems may use the metadata of the SW but it is a layer way above it “A purely academic research topic” SW is out of the university labs now lots of applications exist already (see examples later) big players of the industry use it (Sun, Adobe, HP, IBM,…) of course, much is still be done! Building an ontology is not a goal in itself