COMPSCI 732 Semantic Web Technologies Semantic Web Architecture

COMPSCI 732: Semantic Web Technologies Semantic Web Architecture Slides are based on Lecture Notes by Dieter Fensel and Federico Facca 1

Where are we? # Title 1 Introduction 2 Semantic Web Architecture 3 Resource Description Framework (RDF) 4 Web of Data 5 Generating Semantic Annotations 6 Storage and Querying 7 Web Ontology Language (OWL) 8 Rule Interchange Format (RIF) 2

Overview • • Introduction and motivation Technical solutions – – – • • Semantic Web architecture Uniform Resource Identifier e. Xtensible Markup Language (XML) XML Schema Namespaces Extensions Illustration by a large example Summary References 3

INTRODUCTION AND MOTIVATION 4

A Semantic Web Scenario From Today • Queries: – Which type of music is played by UK radio stations? – Which UK radio station is playing titles by Swedish composers? • Information to answer query is available on the Web • Web search engines analyze Web content one page at a time • The Semantic Web provides better framework to answer such queries – combines data – distributed across different sources, and – described in machine-interpretable manner 5

Steps in Answering Queries • Playlists of BBC radio shows published online in Semantic Web formats • Music groups such as “ABBA” have an identifier http: : //www. bbc. co. uk/music/artists/d 87 e 52 c 5 -bb 8 d-4 da 8 -b 9419 f 4928627 dc 8#artist • Identifier can relate music group to information at Musicbrainz – Music community portal exposing data on Semantic Web – http: //musicbrainz. org – Knows about band members (e. g. Benny Andersson) – Aligns its information with Wikipedia • Information on UK radio stations may be found in lists on Web pages – Can be translated into similar Semantic Web representation 6

Describing Things and Their Relationships • Meaning of Relationships, e. g. , band memberships explained online, too • Using collections of Ontologies available on the Web – Dublin Core (general properties of information resources) http: //dublincore. org/ – SKOS (covering taxonomic descriptions) http: //www. w 3. org/2004/02/skos/ – Specialized ontologies (covering the music domain) • Data at the BBC currently use at least nine different ontologies – http: //www. bbc. co. uk/ontologies/programmes • Availability of data in these formats enables queries to be answered – Based on a query language 7

Towards the Required Infrastructure • What infrastructure is required to implement the scenario from before? • Generic software components, Languages, Protocols • Their seamless interaction to satisfy requests • Purpose of Lecture: – Investigate Semantic Web Architecture – Analyze requirements from technical need to identify and relate data – Analyze organizational needs to maintain Semantic Web as a whole 8

Web Architecture • The Semantic Web is an evolution of the Web • Important for the fast growth and adoption of the Web are – Many people can set up Web servers easily and independently from each other – More people can create documents, put them online, and link them to each other – Even more people can browse and access any Web server to retrieve documents • Web architecture allows graceful degradation of user experience when: – Network is partially slow (World Wide Wait), while other parts still operate at full speed – Single Web servers break, because others still work – Hyperlinks are broken, because other links still lead somewhere • Separation of concerns justifies less quality outputs – Users can easily create and access documents – Distributed nature of system, without need of central coordinator, results in robustness 9

Web Architecture Principles 1. Explicit simple data representation – Common data representation hides underlying technologies (e. g. HTML) 2. Distributed system – Data sources without centralized instance controlling who owns what type of info – Distributed ownership and control can facilitate adoption and scalability – E. g. Web pages are under full control of their producers 3. Cross-referencing – Reuse of existing data and data definitions from different authorities (e. g. hyperlinks) 4. Loose coupling achieved by common language layers – – 5. Communication in standardized languages These must be easy to customize Overall communication must not be jeopardized by such specialization E. g. Coupling of Web clients/servers: HTTP for transport, HTML for Web content Ease of publishing and consumption – Easy publishing and consumption of simple data – Comprehensive publishing and consumption of complex data, e. g. : HTML simple to convey textual info; powerful browsers/content management systems 10

Semantic Web Requirements and Examples • Must be able to represent entities and their relationships (1) – A person, the birthday of a person, the name of a person (“Benny Andersson”) • Must be serializable in standardized manner to easily exchange data between different computing nodes (1, 2, 4) – Ease of joining information from Music. Brainz, BBC, DBPedia • Entities must be referable across borders of ownership or computing systems to allow for cross-linking of data (1, 2, 3, 4) – ABBA’s Benny Andersson becomes hard to distinguish from other Benny Anderssons • Expressive, machine-understandable data description language (1, 4, 5) – Manual inspection not scalable; refinements of basic model impossible – BBC Data involves radio stations, shows, their versions, songs and their artists • A query and manipulation language to select and aggregate data (5) – The number of Swedish composers being broadcast on a specific program • Reasoning desirable to facilitate querying (5) – Direct relationship between a program and a song using inference • • Transport of data and query and their results by agreed-upon protocols (HTTP) May involve encrypted data requests and transports (HTTPs); signature of data items to ensure authenticity of user requests and control access to resources 11

Additional Requirements • • Core requirements not yet included in language architecture Versatile means for user interaction – Broad accessibility requires viewing, searching, browsing, querying of data – While at the same time abstracting from intricacies underlying their distributed origin – On-the-fly data integration of multiple data sources: assemble information from multitude of sources without a priori knowledge about domain or structure of data – Facilitation of data production and publishing: metadata creation and migration of data must be made convenient, independent from origin of data • Provenance and Trust – Authorship and ownership get lost during data processing and aggregation – Origin, Reliability, Trustworthiness must be rethought to apply them for individual and aggregated data items, to establish faithful authentication at Semantic Web scale • Alignment of unconnected sets of data – Interlinking implies capability to suggest alignments between identifiers or concepts from different sets of data, beyond mere use of identifiers such as URI/IRIs – Such alignment may be necessary to enable a real Web of Data 12

Semantic Web Architecture • Formalized components and their relationships – What technologies make up the Semantic Web – What are the dependencies between components • Roadmap for steps of developing the Semantic Web 13

The Semantic Web architecture and its foundations TECHNICAL SOLUTION 14

Search and Query the Web I • The Web is a constantly growing network of distributed resources – – • More than 1 trillion unique URLs More than 100 billion pages More than 200 million web sites Check most updated data on: http: //news. netcraft. com/archives/web_server_survey. html User needs to be able to efficiently search resources/content over the Web – When I Google “Milan” do I find info on the city or the soccer team? • User needs to be able to perform query over largely distributed resources – When is the next performance of the rock band “U 2”, where it will be located, what are the best ways to reach the location, what are the attractions nearby… 15

Search and Query the Web II • On 2 Broker is the evolution of Ontobroker, a systems that aims at providing a solution to the problems discussed in the previous slides by adopting Semantic Technologies • On 2 Broker is a system that processes distributed information sources and that provides intelligent information retrieval, query answering • On 2 Broker relies on components of the Semantic Web Architecture [D. Fensel, S. Decker, M. Erdmann, R. Studer: Ontobroker in a Nutshell. ECDL 1998: 663664] 16

On 2 Broker: Architecture 17

On 2 Broker Components I • Query Interface – Provides a structured input that enables users to define their queries without any knowledge of the query language – Input queries are then transformed to the query language (e. g. Spar. QL) • Repository – Decouples query answering, information retrieval and reasoning – Provide support for materialization of inferred knowledge 18

On 2 Broker Components II • Crawlers and Wrappers (or Info Agent) – Extract knowledge from different distributed and heterogeneous data sources – RDFa pages and RDF repositories can be included directly – HTML and XML data sources require processing by wrappers to derive RDF data • Inference Engine – Relies on knowledge imported from the crawlers and axioms contained in the repository to support query answers – Adopts Horn logic and closed world assumption 19

On 2 Broker: Example 5. Tim Berners-Lee knows Christian Bizer and Tom Heath 1. Whom does Tim Berners -Lee know? 4. Extends KB: if “x dblp: coauthor y“ then “x foaf: knows y” if “y foaf: knows x“ then “x foaf: knows y” 2. SELECT DISTINCT ? s ? o WHERE { ? s foaf: knows ? o. } … 3. Extract RDF from: http: //www. w 3. org/P fensel. com eople/Berners-Lee/ dblp … … 20

Sem. Web Architecture: Requirements • Extensibility – Each layer should extend the previous one(s) • Support for data interchange – Using data from one source in other applications • Support for ontology description with different complexity – Including rules • • Support for data query Support for data provenance and trust evaluation see the Semantic Web Roadmap: http: //www. w 3. org/Design. Issues/Semantic. html 21

Semantic Web Stack 22 Adapted from http: //en. wikipedia. org/wiki/Semantic_Web_S Rules: RIF

UNICODE, URI and XML • UNICODE is the standard international character set – E. g. used to encode the data in the repository • Uniform Resource Identifiers (URIs) identify things and concepts – E. g. used to identify resources on the Web and in the repository – Be aware to distinguish between information and non-information resources – http: : //www. bbc. co. uk/music/artists/d 87 e 52 c 5 -bb 8 d-4 da 8 -b 9419 f 4928627 dc 8#artist vs. http: //dbpedia. org/resource/ABBA – Data publishers on the Semantic Web use Linked data principles: • • • Use URIs as names for things Use HTTP URIs so that people can look up those names When someone looks up a URI, provide useful information, using standards (RDF, SPARQL) Include links to other URIs, so that they can discover more things. e. Xtensible Markup Language (XML) used for data exchange – Used on the Semantic Web to exchange the description of resources – E. g. format that can be transformed into RDF and imported into the repository 23

RDF, RDFS and OWL • Resource Description Framework (RDF) – – – – is the HTML of the Semantic Web Simple way to describe resources on the Web Based on triples <subject, predicate, object> Various serializations, including one based on XML A simple ontology language (RDFS) E. g. language used to store the data in the repository More in lecture 3 • Web Ontology Language (OWL) – – – Is a more complex ontology language than RDFS Layered language based on Description Logics Overcomes some RDF(S) limitations E. g. ontology language used to define the schemas used in repository More in lecture 7 24

RDF Graph Encoding a Description of ABBA 25

RDF Serialized in RDF/XML <? xml version=“ 1. 0”> <!DOCTYPE rdf: RDF[ <!ENTITY bbca “http: //www. bbc. co. uk/music/artists/”> <!ENTITY bbci “http: //www. bbc. co. uk/music/images/artists/”> <!ENTITY mba “http: //musicbrainz. org/artist/”>]> <rdf: RDF xmlns: rdf=“http: //www. w 3. org/1999/02/22 -rdf-syntax-ns#” xmlns: owl=“http: //www. w 3. org/2002/07/owl#” xmlns: foaf=“http: //xmlns. com/foaf/0. 1/” xmlns: mo=“http: //purl. org/ontology/mo/”> <mo: Music. Artist rdf: about=“http: : //www. bbc. co. uk/music/artists/d 87 e 52 c 5 -bb 8 d-4 da 8 -b 9419 f 4928627 dc 8#artist”> <rdf: type rdf: resource=“http: //purl. org/ontology/mo/Music. Group”/> <foaf: name>ABBA</foaf: name> <foaf: homepage rdf: resource=“http: //www. abbasite. com/”/> <mo: image rdf: resource=“&bbci; 542 x 305/d 87 e 52 c 5 -bb 8 d-4 da 8 -b 941 -9 f 4928627 dc 8. jpg”> <mo: member rdf: resource=“&bbca; 042 c 35 d 3 -0756 -4804 -b 2 c 2 -be 57 a 683 efa 2#artist”> <mo: member rdf: resource=“&bbca; 2 f 031686 -3 f 01 -4 f 33 -a 4 fc-fb 3944532 efa#artist”> <mo: member rdf: resource=“&bbca; aebbb 417 -0 d 18 -4 fec-a 2 e 2 -ce 9663 d 1 fa 7 e#artist”> <mo: member rdf: resource=“&bbca; ffb 77292 -9712 -4 d 03 -94 aa-bdb 1 d 4771 d 38#artist”> <mo: musicbrainz rdf: resource=“&mba; d 87 e 52 c 5 -bb 8 d-4 da 8 -b 941 -9 f 4928627 dc 8. html”> <mo: wikipedia rdf: resource=“http: //en. wikipedia. org/wiki/ABBA”> <owl: same. As rdf: resource=“http: //dbpedia. org/resource/ABBA”> </mo: Music. Artist> </rdf: RDF> 26

RDF Serialized in Turtle @prefix rdf: owl: foaf: mo: <http: //www. w 3. org/1999/02/22 -rdf-syntax-ns#>. <http: //www. w 3. org/2002/07/owl#>. <http: //xmlns. com/foaf/0. 1/>. <http: //purl. org/ontology/mo/>. <http: : //www. bbc. co. uk/music/artists/d 87 e 52 c 5 -bb 8 d-4 da 8 -b 941 -9 f 4928627 dc 8#artist> rdf: type mo: Music. Artist, mo: Music. Group ; foaf: name “ABBA” ; foaf: homepage <http: //www. abbasite. com/> ; mo: image <http: //www. bbc. co. uk/music/images/artists/542 x 305/d 87 e 52 c 5 -bb 8 d-4 da 8 -b 941 -9 f 4928627 dc 8. jpg> ; mo: member <http: //www. bbc. co. uk/music/artists/042 c 35 d 3 -0756 -4804 -b 2 c 2 -be 57 a 683 efa 2#artist> , <http: //www. bbc. co. uk/music/artists/2 f 031686 -3 f 01 -4 f 33 -a 4 fc-fb 3944532 efa#artist> , <http: //www. bbc. co. uk/music/artists/aebbb 417 -0 d 18 -4 fec-a 2 e 2 -ce 9663 d 1 fa 7 e#artist> , <http: //www. bbc. co. uk/music/artists/ffb 77292 -9712 -4 d 03 -94 aa-bdb 1 d 4771 d 38#artist> ; mo: musicbrainz <http: //musicbrainz. org/artist/d 87 e 52 c 5 -bb 8 d-4 da 8 -b 941 -9 f 4928627 dc 8. html> ; mo: wikipedia <http: //en. wikipedia. org/wiki/ABBA> ; owl: same. As <http: //dbpedia. org/resource/ABBA>. 27

RDFS and OWL Example • Reasoning example in RDFS – – rdfs: sub. Class. Of can model class hierarchies mo: Music. Group and mo: Music. Artist specify two classes Axiom <mo: Music. Group, rdfs: sub. Class. Of, mo: Music. Artist> Stating that ABBA is an instance of type Music. Group enables reasoners to conclude that ABBA is also an instance of type Music. Artist – When query asks for all Music. Artists, then ABBA will be contained in query result, even though there is no explicit assertion of this • Reasoning example in OWL – owl: same. As can be used to specify that two resources are identical – To consolidate information about ABBA from multiple sources we can specify that http: : //www. bbc. co. uk/music/artists/d 87 e 52 c 5 -bb 8 d-4 da 8 -b 9419 f 4928627 dc 8#artist and http: //dbpedia. org/resource/ABBA are the same 28

SPARQL and Rule Languages • SPARQL – – – • Query language for RDF triples A protocol for querying RDF data over the Web E. g. language used to query the repository from the user interface Can also be used for Updates More in lecture 6 Rule languages (esp. Rule Interchange Format RIF) – W 3 C recommendation for exchanging rule sets between rule engines – Extend ontology languages with proprietary axioms – Based on different types of logics • Description Logic • Logic Programming – E. g. used to enable reasoning over data to infer new knowledge – More in lecture 8 29

SPARQL Example • SPARQL query for other music groups that members of ABBA sing in PREFIX rdf: foaf: mo: <http: //www. w 3. org/1999/02/22 -rdf-syntax-ns#> <http: //xmlns. com/foaf/0. 1/> <http: //purl. org/ontology/mo/> SELECT ? member. Name ? group. Name WHERE { <http: : //www. bbc. co. uk/music/artists/d 87 e 52 c 5 -bb 8 d-4 da 8 -b 9419 f 4928627 dc 8#artist> mo: member ? m. ? x rdf: type mo: Music. Group. ? m foaf: name ? member. Name. ? x foaf: name ? group. Name } FILTER (? group. Name <> “ABBA”) 30

SPARQL Example • SPARQL query for other music groups that members of ABBA sing in • Graphical representation of WHERE clause <http: : //www. bbc. co. uk/music/artists/d 87 e 52 c 5 -bb 8 d-4 da 8 -b 9419 f 4928627 dc 8#artist> mo: member ? m. ? x rdf: type mo: Music. Group. ? m foaf: name ? member. Name. ? x foaf: name ? group. Name 31

Two RIF rules for mapping FOAF predicates • True statements in antecedent of rule mean true statements in its conclusion if { then { } ? x foaf: first. Name ? first; foaf: surname ? last; } ? x foaf: family_name ? last; foaf: givenname ? first; foaf: name func: string-join(? first “ ” ? last) ? x foaf: name ? name } and pred: contains(? name, “ ”) } ? x foaf: first. Name func: strong-before(? name, “ ”); foaf: surname func: strong-after(? name, “ ”) 32

Logics, Proof and Trust • Security and Encryption – HTTPs provides data integrity and confidentiality when transmitting data and queries – Digital signing of RDF graphs provides authenticity and non-repudiation • Unifying logic – Bring together the various ontology and rule languages – Connect unlinked data to provide more meaning to data, and drive data integration – E. g. identity management and alignment via http: //sameas. org • Proof – Explanation of inference results, data provenance • Trust – – • Trust that the system performs correctly Trust that the system can explain what it is doing Network of trust for data sources and services Technology and user interface Many open problems, topics for future research 33

Foundations Rules: RIF 34

More than a-z, A-Z UNICODE 35

CHARACTER SETS • ASCII – 7 bit, 128 characters (a-z, A-Z, 0 -9, punctuation) • Extension code pages – 128 chars (ß, Ä, ñ, ø, Š, etc. ) – Different systems, many different code pages – ISO Latin 1, CP 1252 – Western languages – ISO Latin 2, CP 1250 – East Europe (197 = Å) (197 = Ĺ) • Code page is an interpretation, not a property of text – Swedish programmer would have to write ä aÄiÜ='Ön'; ü instead of { a[i]='n'; } • Thus if we do not interpret correctly the code page, the result visualized will not be the expected one 36

UNICODE: an unambiguous code • We need a solution that can be unambiguously interpreted, i. e. whether a code corresponds to a single character and vice versa • That’s why UNICODE was created! $Å Ĺ Æ ή U+0024 U+00 C 5 U+0139 U+00 C 6 U+03 AE ♥⅝ﻙ Ж� U+0643 U+215 D U+2665 U+0416 U+0 E 0 D 37

UNICODE • ISO standard – About 100, 000 characters, space for 1, 000 – Unique code points from U-0000 through U-FFFF to U-10 FFFF – Well-defined process for adding characters • When dealing with any text, simply use UNICODE – Character code charts: http: //www. unicode. org/charts/ • See also: – http: //www. tbray. org/talks/rubyconf 2006. pdf – http: //tbray. org/ongoing/When/200 x/2003/04/06/Unicode 38

How to identify things on the Web URI: UNIFORM RESOURCE IDENTIFIERS 39

Identifier, Resource, Representation Taken from http: //www. w 3. org/TR/webarch/ 40

URI, URN, URL • A Uniform Resource Identifier (URI) is a string of characters used to identify a name or a resource on the Internet • • A URI can be a URL or a URN A Uniform Resource Name (URN) defines an item's identity – the URN urn: isbn: 0 -395 -36341 -1 is a URI that specifies the identifier system, i. e. International Standard Book Number (ISBN), as well as the unique reference within that system and allows one to talk about a book, but doesn't suggest where and how to obtain an actual copy of it • A Uniform Resource Locator (URL) provides a method for finding it – the URL http: //www. auckland. ac. nz identifies a resource (Uo. A's home page) and implies that a representation of that resource (such as the home page's current HTML code, as encoded characters) is obtainable via HTTP from a network host named www. auckland. ac. nz 41

URI Syntax • Examples – – • http: //www. ietf. org/rfc 3986. txt mailto: John. Doe@example. com news: comp. infosystems. www. servers. unix telnet: //melvyl. ucop. edu/ URI Syntax – – – scheme: [//authority] [/path] [? query] [#fragid] The scheme distinguishes different kinds of URIs Authority normally identifies a server Path normally identifies a directory and a file Query adds extra parameters Fragment ID identifies a secondary resource 42

URI Syntax cont’d • Reserved characters (like /: ? #@$&+* ) • Many allowed characters • Rest percent-encoded by UTF-8 – http: //google. com/search? q=technikerstra%C 3%9 Fe • IRI – Internationalized Resource Identifier – Allows whole UNICODE – Specifies transformation into URI – mostly UTF-8 encoding 43

URI Schemes Scheme Description • Schemes partition the URI space into subspaces • Schemes can add or clarify properties of resources – Ownership (how authorities are formed) – Persistence (how stable the URIs should be) – Protocol (default access protocol) RFC file Host-specific file names [1738] ftp File Transfer Protocol [1738] http Hypertext Transfer Protocol [2616] https Hypertext Transfer Protocol Secure [2818] Instant Messaging [3860] internet message access protocol [5092] ipp Internet Printing Protocol [3510] iris Internet Registry Information Service [3981] ldap Lightweight Directory Access Protocol [4516] Electronic mail address [2368] message identifier [2392] im imap mailto mid From http: //www. iana. org/assignments/uri-schemes. html 44

How to exchange structured data on the Web XML: EXTENSIBLE MARKUP LANGUAGE 45

EXTENSIBLE MARKUP LANGUAGE • Language for creating languages – “Meta-language” – XHTML is a language: HTML expressed in XML • W 3 C Recommendation (standard) – XML is, for the information industry, what the container is for international shipping – For structured and semistructured data • Main plus: wide support, interoperability – Platform-independent • Applying new tools to old data 46

STRUCTURE OF XML DOCUMENTS • Elements, attributes, content • One root element in document • Characters, child elements in content 47

XML ELEMENT • Syntax <name>contents</name> – <name> is called the opening tag – </name> is called the closing tag • Examples <gender>Female</gender> <story>Once upon a time there was…. </story> • Element names case-sensitive 48

ATTRIBUTES TO XML ELEMENTS • Name/value pairs, part of element contents • Syntax <name attribute_name="attribute_value">contents</name> • Values surrounded by single or double quotes • Example <temperature unit="F">64</temperature> <swearword language='fr'>con</swearword> 49

EMPTY ELEMENTS • Empty element: <name></name> • This can be shortened: <name/> • Empty elements may have attributes • Example <grade value='A'/> 50

COMMENTS • May occur anywhere in element contents or outside the root element • Start with <!- • End with --> • May not contain a double hyphen • Comments cannot be nested • Example: <element>content <!-- a comment, will be ignored in processing --> </element> <!-- comment outside the root element --> 51

NESTING ELEMENTS • Elements may contain other (child) elements – The containing element is the parent element • Elements must be properly nested • Example with improper nesting: <b>bold <i>bold-italic</b> italic? </i> • The above is not XML (not well-formed) 52

SPECIAL CHARACTERS IN XML • < and > are obviously reserved in content – Written as < and > • Same for ' and " in attribute values – Written as &apos; and " • Now & is also reserved – Written as & • Any character: ß or ß ß – Decimal or hexa-decimal unicode point • Elements and attributes whose name starts with “xml” are also special 53

USES OF XML • Document mark-up – XHTML – HTML is a language, so it can be expressed in XML • Exchanged data – – Scalable vector graphics – SVG E-commerce – eb. XML Messaging in general – SOAP And many more standards • Internal data – Databases – Configuration files • Etc. 54

WHY XML? • For semistructured data: – Loose but constrained structure – Unspecified content length • For structured data: – – Table(s) or similar rows Well-defined structure, data types Good interoperability But: requirements for quick access, processing 55

XML PARSERS • Document Object Model (DOM) builder – Creates an object model of XML document, tree-traversal API – In-memory representation, random access – DOM complex, simpler JDOM etc. • Simple API for XML parsing (SAX) – – Views XML as stream of events el_start("date"), attribute("day", "10"), el_end("date") Content reported as callback to methods on handler object of design DOM builder can use SAX • Pull parsers – Intermediate parsed results can be accessed as local variables – St. AX (JAVA), XMLReader (PHP), System. XMLReader (. NET) 56

How to distinguish categories of resources NAMESPACES 57

The Problem • Documents use different vocabularies – Example 1: CD music collection – Example 2: online order transaction • Merging multiple documents together – Name collisions can occur • Example 1: albums have a <name> • Example 2: customers have a <name> – How do you differentiate between the two? 58

The Solution: Namespaces! • What is a namespace? – A syntactic way to differentiate similar names in an XML document • Binding namespaces – Uses Uniform Resource Identifier (URI) • e. g. “http: //example. com/NS” – Can bind to a named or “default” prefix 59

Namespace Binding Syntax • Use “xmlns” attribute – Named prefix • <a: foo xmlns: a=‘http: //example. com/NS’/> – Default prefix • <foo xmlns=‘http: //example. com/NS’/> • Element and attribute names are “qualified” – URI, local part (or “local name”) pair • e. g. { “http: //example. com/NS” , “foo” } 60

Example Document I • Namespace binding <? xml version=‘ 1. 0’ encoding=‘UTF-8’? > <order> <item code=‘BK 123’> <name>Care and Feeding of Wombats</name> <desc xmlns: html=‘http: //www. w 3. org/1999/xhtml’> The <html: b>best</html: b> book ever written! </desc> </item> </order> 61

Example Document II • Namespace scope <? xml version=‘ 1. 0’ encoding=‘UTF-8’? > <order> <item code=‘BK 123’> <name>Care and Feeding of Wombats</name> <desc xmlns: html=‘http: //www. w 3. org/1999/xhtml’> The <html: b>best</html: b> book ever written! </desc> </item> </order> 62

Example Document III • Bound elements <? xml version=‘ 1. 0’ encoding=‘UTF-8’? > <order> <item code=‘BK 123’> <name>Care and Feeding of Wombats</name> <desc xmlns: html=‘http: //www. w 3. org/1999/xhtml’> The <html: b>best</html: b> book ever written! </desc> </item> </order> 63

How to define XML document structures XML SCHEMA 64

What is it? • A grammar definition language – More expressive than Document Type Definitions (DTDs) • Uses XML syntax – Defined by W 3 C • Primary features – Datatypes • e. g. integer, float, date, etc… – More powerful content models • e. g. namespace-aware, type derivation, etc… 65

XML Schema Types • Simple types – Basic datatypes – Can be used for attributes and element text – Extendable • Complex types – Defines structure of elements – Extendable • Types can be named or “anonymous” 66

Simple Types • DTD datatypes – Strings, ID/IDREF, NMTOKEN, etc… • Numbers – Integer, long, float, double, etc… • Other – Binary (base 64, hex) – QName, URI, date/time – etc… 67

Deriving Simple Types • Apply facets – Specify enumerated values – Add restrictions to data – Restrict lexical space • Allowed length, pattern, etc… – Restrict value space • Minimum/maximum values, etc… • Extend by list or union 68

A Simple Type Example • Integer with value (1234, 5678] <xsd: simple. Type name=‘My. Integer’> <xsd: restriction base=‘xsd: integer’> <xsd: min. Exclusive value=‘ 1234’/> <xsd: max. Inclusive value=‘ 5678’/> </xsd: restriction> </xsd: simple. Type> 69

A Simple Type Example II • Validating integer with value (1234, 5678] <data xsi: type='My. Integer'></data> <data xsi: type='My. Integer'>Andy</data> <data xsi: type='My. Integer'>-32</data> <data xsi: type='My. Integer'>1233</data> <data xsi: type='My. Integer'>1234</data> <data xsi: type='My. Integer'>1235</data> <data xsi: type='My. Integer'>5678</data> <data xsi: type='My. Integer'>5679</data> INVALID INVALID 70

Complex Types • Element content models – Simple – Mixed • Unlike DTDs, elements in mixed content can be ordered – Sequences and choices • Can contain nested sequences and choices – All • All elements required but order is not important 71

A Complex Type Example I • Mixed content that allows <b>, <i>, and <u> <xsd: complex. Type name=‘Rich. Text’ mixed=‘true’> <xsd: choice min. Occurs=‘ 0’ max. Occurs=‘unbounded’> <xsd: element name=‘b’ type=‘Rich. Text’/> <xsd: element name=‘i’ type=‘Rich. Text’/> <xsd: element name=‘u’ type=‘Rich. Text’/> </xsd: choice> </xsd: complex. Type> 72

A Complex Type Example II • Validation of Rich. Text <content xsi: type='Rich. Text'></content> <content xsi: type='Rich. Text'>Andy</content> <content xsi: type='Rich. Text'>XML is <i>awesome</i>. </content> <content xsi: type='Rich. Text'><B>bold</B></content> INVALID <content xsi: type='Rich. Text'><foo/></content> INVALID 73

EXTENSIONS 74

BUILDING ON THE FOUNDATIONS • RDF for semantic data – Graphs of linked data – Semantic Web • Any XML or HTML can support translation to RDF – GRDDL: a pointer to a transformation – RDFa: RDF in XHTML – Makes existing data part of the Semantic Web • XML has encryption and digital signature – Necessary technologies for data provenance, trust 75

WEB OF LINKED DATA 76

RDF TEASER • Resource Description Framework – Metadata: about Web resources – But also any other data • Graphs of resources interlinked with properties Rafael Nadal Shakira plays knows sings Tennis Shakira Waka waka • Ontology languages for data schemas – Various properties: knows, plays, sings – Classes of resources: Person, Athlete, Singer, Sport, Song • SPARQL for querying the data 77

The Semantic Web architecture in practice ILLUSTRATION BY A LARGER EXAMPLE 78

Semantic Conference • All the data about the conference is part of the Semantic Web – – Date, location Organizers, peer-review committees Articles (papers), their authors Detailed program schedule • Each Semantic Web architecture layer plays a role • ISWC is annotating conference data using Semantic Web technologies – http: //data. semanticweb. org/conference/iswc/2011/html – Currently available data regards only papers and authors – This could be extended to support features discussed above 79

Foundation Layers • UNICODE – All participants' names should be in UNICODE because they are international: Denny Vrandečić, Diego Meroño, François Maué – Same for paper titles: "α-decay and β-decay of heavy atoms" • URI: All important things must have identifiers, for example: – Conference: http: //data. semanticweb. org/conference/iswc/2011 – Participant: http: //data. semanticweb. org/person/piero-bonatti – Participant's affiliation: http: //data. semanticweb. org/organization/talis-informationlimited – Paper: http: //data. semanticweb. org/conference/iswc/2011/paper/tutorial/7 80

Data Layers • XML – The HTML pages should be in XHTML – The RDF data (below) should be in RDF/XML – News feed should be in Atom (an XML format) • RDF – The conference dataset, and any useful subsets, should be published in RDF for download; for example: • http: //data. semanticweb. org/conference/iswc/2011/rdf 81

Ontologies, Query • RDFS, OWL – – • The conference would use various vocabularies and ontologies, such as: FOAF (Friend of a friend) for talking about the attendees and authors/presenters Dublin Core for paper metadata Calendar ontology for the program SPARQL – The conference server should have a public SPARQL endpoint that can be used for queries over the conference data – http: //data. semanticweb. org/snorql/ 82

Browsing ISWC Data http: //data. semanticweb. org/person/tom-heath/html 83

Querying ISWC Data http: //data. semanticweb. org/snorql/ 84

That’s almost all for today… SUMMARY 85

Things to Keep in Mind • Semantic Web builds on the Web • For any text, use UNICODE, probably UTF-8 • URIs can identify anything – Not only documents on the Web • XML helps with data exchange, interoperability • XML languages are distinguished with namespaces 86

References • Mandatory: – http: //www. w 3. org/TR/webarch/ – http: //www. w 3. org/Design. Issues/Architecture. html • Further reading: – – – – http: //www. w 3. org/Provider/Style/URI http: //www. ietf. org/rfc 3986. txt http: //www. unicode. org/charts/ http: //www. tbray. org/talks/rubyconf 2006. pdf http: //tbray. org/ongoing/When/200 x/2003/04/06/Unicode http: //www. w 3. org/TR/xml/ http: //www. w 3. org/TR/xml-names/ http: //www. w 3. org/TR/xmlschema-1/ – Fensel et al. , On 2 broker: Semantic-Based Access to Information Sources at the WWW – Fensel et al. : Ontobroker in a Nutshell – http: //www. ics. uci. edu/~fielding/pubs/dissertation/top. htm – http: //www. w 3. org/Design. Issues/Semantic. html 87

References • Wikipedia links: • • • http: //en. wikipedia. org/wiki/Semantic_Web_Stack http: //en. wikipedia. org/wiki/URI http: //en. wikipedia. org/wiki/Unicode http: //en. wikipedia. org/wiki/XML_Namespaces http: //en. wikipedia. org/wiki/Resource_Description_Framework http: //en. wikipedia. org/wiki/RDF_Schema http: //en. wikipedia. org/wiki/Web_Ontology_Language http: //en. wikipedia. org/wiki/SPARQL http: //en. wikipedia. org/wiki/Rule_Interchange_Format 88

Next Lecture # Title 1 Introduction 2 Semantic Web Architecture 3 Resource Description Framework (RDF) 4 Web of Data 5 Generating Semantic Annotations 6 Storage and Querying 7 Web Ontology Language (OWL) 8 Rule Interchange Format (RIF) 89

Questions? 90 90