Semantic Web and Services Anna Fensel 12.06.2017 & 19.06.2017

Artificial Intelligence SS 2017

Where are we?

# Title 0.1 Propositional Logic 0.2 Predicate Logic 1 Introduction 2 Reasoning 3 Search Methods 4 CommonKADS 5 Problem-Solving Methods 6 Planning 7 Software Agents 8 Rule Learning 9 Inductive Logic Programming 10 Formal Concept Analysis; Semantic Web (1st part of this slideset) 11 Neural Networks; Semantic Web Services (2nd part of this slideset) 12 Exam

1 Agenda

• Semantic Web - Data • Motivation • Development of the Web • Internet • Web 1.0 • Web 2.0 • Limitations of the current Web • Technical Solution: URI, RDF, RDFS, OWL, SPARQL • Illustration by Larger Examples: KIM Browser Plugin, Disco Hyperdata Browser • Extensions: Linked Open Data • Semantic Web – Processes • Motivation • Technical Solution: Semantic Web Services, WSMO, WSML, SEE, WSMX • Illustration by Larger Examples: SWS Challenge, Virtual Travel Agency, WSMX at work • Extensions: Mobile Services, Intelligent Cars, Intelligent Electricity Meters • Summary • References

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SEMANTIC WEB - DATA

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2 MOTIVATION

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DEVELOPMENT OF THE WEB

3 Development of the Web

1. Internet 2. Web 1.0 3. Web 2.0

INTERNET

4 Internet

• “The Internet is a global system of interconnected computer networks that use the standard Internet Protocol Suite (TCP/IP) to serve billions of users worldwide. It is a network of networks that consists of millions of private and public, academic, business, and government networks of local to global scope that are linked by a broad array of electronic and optical networking technologies.”

http://en.wikipedia.org/wiki/Internet

A brief summary of Internet evolution

Age of eCommerce Mosaic Begins WWW Internet Created 1995 Created 1993 Named 1989 and Goes TCP/IP TCP/IP Created 1984 ARPANET 1972 1969 Hypertext Invented Packet 1965 Switching First Vast Invented Computer 1964 Network Silicon Envisioned A Chip 1962 Mathematical 1958 Theory of Memex Communication Conceived 1948 1945

1945 1995

Source: http://www.isoc.org/internet/history2002_0918_Internet_History_and_Growth.ppt 10

5 WEB 1.0

Web 1.0

• “The World Wide Web ("WWW" or simply the "Web") is a system of interlinked, hypertext documents that runs over the Internet. With a Web browser, a user views Web pages that may contain text, images, and other multimedia and navigates between them using hyperlinks”. http://en.wikipedia.org/wiki/World_Wide_Web

6 Web 1.0

• Netscape – Netscape is associated with the breakthrough of the Web. – Netscape had rapidly a large user community making attractive for others to present their information on the Web.

• Google – Google is the incarnation of Web 1.0 mega grows – Google indexed already in 2008 more than 1 trillion pages [*] – Google and other similar search engines turned out that a piece of information can be faster found again on the Web than in the own bookmark list

[*] http://googleblog.blogspot.com/2008/07/we-knew-web-was-big.html

Web 1.0 principles

• The success of Web1.0 is based on three simple principles: 1. A simple and uniform addressing schema to indentify information chunks i.e. Uniform Resource Identifiers (URIs) 2. A simple and uniform representation formalism to structure information chunks allowing browsers to render them i.e. Hyper Text Markup Language (HTML) 3. A simple and uniform protocol to access information chunks i.e. Hyper Text Transfer Protocol (HTTP)

7 1. Uniform Resource Identifiers (URIs)

• Uniform Resource Identifiers (URIs) are used to name/identify resources on the Web • URIs are pointers to resources to which request methods can be applied to generate potentially different responses • Resource can reside anywhere on the Internet • Most popular form of a URI is the Uniform Resource Locator (URL)

2. Hyper-Text Markup Language (HTML)

• Hyper-Text Markup Language: – A subset of Standardized General Markup Language (SGML) – Facilitates a hyper-media environment • Documents use elements to “mark up” or identify sections of text for different purposes or display characteristics • HTML markup consists of several types of entities, including: elements, attributes, data types and character references • Markup elements are not seen by the user when page is displayed • Documents are rendered by browsers

8 3. Hyper-Text Transfer Protocol (HTTP)

• Protocol for client/server communication – The heart of the Web – Very simple request/response protocol • Client sends request message, server replies with response message – Provide a way to publish and retrieve HTML pages – Stateless – Relies on URI naming mechanism

WEB 2.0

9 Web 2.0

• “The term "Web 2.0" (2004–present) is commonly associated with web applications that facilitate interactive information sharing, interoperability, user-centered design, and collaboration on the World Wide Web” http://en.wikipedia.org/wiki/Web_2.0

Web 2.0

• Web 2.0 is a vaguely defined phrase referring to various topics such as social networking sites, wikis, communication tools, and folksonomies. • Tim Berners-Lee is right that all these ideas are already underlying his original web ideas, however, there are differences in emphasis that may cause a qualitative change. • With Web 1.0 technology a significant amount of software skills and investment in software was necessary to publish information. • Web 2.0 technology changed this dramatically.

10 Web 2.0 major breakthroughs

• The four major breakthroughs of Web 2.0 are: 1. Blurring the distinction between content consumers and content providers. 2. Moving from media for individuals towards media for communities. 3. Blurring the distinction between service consumers and service providers 4. Integrating human and machine computing in a new and innovative way

1. Blurring the distinction between content consumers and content providers

Wiki, Blogs, and Twiter turned the publication of text in mass phenomena, as flickr and youtube did for multimedia

11 2. Moving from a media for individuals towards a media for communities

Social web sites such as del.icio.us, facebook, FOAF, linkedin, myspace and Xing allow communities of users to smoothly interweave their information and activities

3. Blurring the distinction between service consumers and service providers

Mashups allow web users to easy integrate services in their web site that were implemented by third parties

12 4. Integrating human and machine computing in a new way

Amazon Mechanical Turk - allows to access human services through a web service interface blurring the distinction between manually and automatically provided services

LIMITATIONS OF THE CURRENT WEB

13 Limitations of the current Web

• The current Web has its limitations when it comes to: 1. finding relevant information 2. extracting relevant information 3. combining and reusing information

Limitations of the current Web Finding relevant information

• Finding information on the current Web is based on keyword search • Keyword search has a limited recall and precision due to: – Synonyms: • e.g. Searching information about “Cars” will ignore Web pages that contain the word “Automobiles” even though the information on these pages could be relevant – Homonyms: • e.g. Searching information about “Jaguar” will bring up pages containing information about both “Jaguar” (the car brand) and “Jaguar” (the animal) even though the user is interested only in one of them

14 Limitations of the current Web Finding relevant information

• Keyword search has a limited recall and precision due also to: – Spelling variants: • e.g. “organize” in American English vs. “organise” in British English – Spelling mistakes – Multiple languages • i.e. information about same topics in published on the Web on different languages (English, German, Italian,…)

• Current search engines provide no means to specify the relation between a resource and a term – e.g. sell / buy

Limitations of the current Web Extracting relevant information

• One-fit-all automatic solution for extracting information from Web pages is not possible due to different formats, different syntaxes • Even from a single Web page is difficult to extract the relevant information

Which book is about the Web?

What is the price of the book?

15 Limitations of the current Web Extracting relevant information

• Extracting information from current web sites can be done using wrappers

Wrapper WEB Structured Data, Databases, HTML pages extract XML Layout annotate Structure structure

Limitations of the current Web Extracting relevant information

• The actual extraction of information from web sites is specified using standards such as XSL Transformation (XSLT) [1] • Extracted information can be stored as structured data in XML format or databases. • However, using wrappers do not really scale because the actual extraction of information depends again on the web site format and layout

[1] http://www.w3.org/TR/xslt

16 Limitations of the current Web Combining and reusing information

• Tasks often require to combine data on the Web 1. Searching for the same information in different digital libraries 2. Information may come from different web sites and needs to be combined

Limitations of the current Web Combining and reusing information

1. Searches for the same information in different digital libraries Example: I want travel from Innsbruck to Rome.

17 Limitations of the current Web Combining and reusing information

2. Information may come from different web sites and needs to be combined Example: I want to travel from Innsbruck to Rome where I want to stay in a hotel and visit the city

How to improve the current Web?

• Increasing automatic linking among data • Increasing recall and precision in search • Increasing automation in data integration • Increasing automation in the service life cycle

• Adding semantics to data and services is the solution!

18 TECHNICAL SOLUTIONS

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Uniform Resource Identifier

• Uniform Resource Identifiers (URIs) are used to identify resources, not just things that exists on the Web, e.g. Dieter Fensel, University of Innsbruck

Taken from http://www.w3.org/TR/webarch/

19 Resource Description Framework (RDF)

• The Resource Description Framework (RDF) provides a domain independent data model

• Resource (identified by URIs) – Correspond to nodes in a graph – E.g.: http://www.w3.org/ http://example.org/#john http://www.w3.org/1999/02/22-rdf-syntax-ns#Property • Properties (identified by URIs) – Correspond to labels of edges in a graph – Binary relation between two resources – E.g.: http://www.example.org/#hasName http://www.w3.org/1999/02/22-rdf-syntax-ns#type • Literals – Concrete data values – E.g.: "John Smith", "1", "2006-03-07"

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Resource Description Framework (RDF) – Triple Data Model

• Triple data model:

– Subject: Resource or blank node – Predicate: Property – Object: Resource, literal or blank node

•Example:

• Statement (or triple) as a logical formula P(x, y), where the binary predicate P relates the object x to the object y.

• RDF offers only binary predicates (properties)

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20 Resource Description Framework (RDF) – Graph Model

• The triple data model can be represented as a graph

• Such graph is called in the Artificial Intelligence community a semantic net

• Labeled, directed graphs – Nodes: resources, literals – Labels: properties – Edges: statements ex:father-of ex:john ex:bill

ex:father-of

ex:tom

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RDF Schema (RDFS)

• RDF Schema (RDFS) is a language for capturing the semantics of a domain, for example: – In RDF: <#john, rdf:type, #Student> – What is a “#Student”?

• RDFS is a language for defining RDF types: – Define classes: • “#Student is a class” – Relationships between classes: • “#Student is a sub-class of #Person” – Properties of classes: • “#Person has a property hasName”

21 RDF Schema (RDFS)

• Classes: <#Student, rdf:type, #rdfs:Class> • Class hierarchies: <#Student, rdfs:subClassOf, #Person>

• Properties: <#hasName, rdf:type, rdf:Property> • Property hierarchies: <#hasMother, rdfs:subPropertyOf, #hasParent>

• Associating properties with classes (a): – “The property #hasName only applies to #Person” <#hasName, rdfs:domain, #Person> • Associating properties with classes (b): – “The type of the property #hasName is #xsd:string” <#hasName, rdfs:range, xsd:string>

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RDF Schema (RDFS) - Example

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22 Web Ontology Language (OWL)

• RDFS has a number of Limitations: – Only binary relations – Characteristics of Properties, e.g. inverse, transitive, symmetric – Local range restrictions, e.g. for class Person, the property hasName has range xsd:string – Complex concept descriptions, e.g. Person is defined by Man and Woman – Cardinality restrictions, e.g. a Person may have at most 1 name – Disjointness axioms, e.g. nobody can be both a Man and a Woman

• The Web Ontology Language (OWL) provides an ontology language, that is a more expressive Vocabulary Definition Language for use with RDF – Class membership – Equivalance of classes – Consistency – Classification

OWL

• OWL is layered into languages of different expressiveness – OWL Lite: Classification Hierarchies, Simple Constraints – OWL DL: Maximal expressiveness while maintaining tractability – OWL Full: Very high expressiveness, loses tractability, all syntactic freedom of RDF

• More expressive means harder to reason with

• Different Syntaxes: – RDF/XML (Recommended for Serialization) – N3 (Recommended for Human readable Fragments) – Abstract Syntax (Clear Human Readable Syntax) lite

DL Full

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23 OWL – Example: The Wine Ontology

• An Ontology describing wine domain • One of the most widely used examples for OWL and referenced by W3C. • There is also a wine agent associated to this ontology that performs OWL queries using a web-based ontological mark-up language. That is, by combining a logical reasoner with an OWL ontology. • The agent's operation can be described in three parts: consulting the ontology, performing queries and outputting results. • Available here: http://www.w3.org/TR/owl-guide/

OWL – Example: The Wine Ontology Schema

[http://mysite.verizon.net/jflynn12/VisioOWL/VisioOWL.htm] 48

24 SPARQL – Querying RDF

•SPARQL – RDF Query language – Based on RDQL – Uses SQL-like syntax

•Example: PREFIX uni:

SELECT ?name FROM WHERE { ?s uni:name ?name. ?s rdf:type uni:lecturer }

SPARQL Queries

PREFIX uni: SELECT ?name FROM WHERE { ?s uni:name ?name. ?s rdf:type uni:lecturer }

•PREFIX – Prefix mechanism for abbreviating URIs • SELECT – Identifies the variables to be returned in the query answer – SELECT DISTINCT – SELECT REDUCED •FROM – Name of the graph to be queried – FROM NAMED • WHERE – Query pattern as a list of triple patterns • LIMIT • OFFSET • ORDER BY

25 SPARQL Example Query 1

“Return the full names of all people in the graph”

PREFIX vCard: SELECT ?fullName WHERE {?x vCard:FN ?fullName}

result: @prefix ex: . @prefix vcard: . ex:john vcard:FN "John Smith" ; fullName vcard:N [ vcard:Given "John" ; ======vcard:Family "Smith" ] ; ex:hasAge 32 ; "John Smith" ex:marriedTo :mary . ex:mary "Mary Smith" vcard:FN "Mary Smith" ; vcard:N [ vcard:Given "Mary" ; vcard:Family "Smith" ] ; ex:hasAge 29 .

SPARQL Example Query 2

“Return the relation between John and Mary”

PREFIX ex: SELECT ?p WHERE {ex:john ?p ex:mary}

@prefix ex: . result: @prefix vcard: . ex:john vcard:FN "John Smith" ; vcard:N [ vcard:Given "John" ; p vcard:Family "Smith" ] ; ex:hasAge 32 ; ======ex:marriedTo :mary . ex:mary vcard:FN "Mary Smith" ; vcard:N [ vcard:Given "Mary" ; vcard:Family "Smith" ] ; ex:hasAge 29 .

26 SPARQL Example Query 3

“Return the spouse of a person by the name of John Smith”

PREFIX vCard: PREFIX ex: SELECT ?y WHERE {?x vCard:FN "John Smith". ?x ex:marriedTo ?y} @prefix ex: . result: @prefix vcard: . ex:john vcard:FN "John Smith" ; vcard:N [ y vcard:Given "John" ; vcard:Family "Smith" ] ; ======ex:hasAge 32 ; ex:marriedTo :mary . ex:mary vcard:FN "Mary Smith" ; vcard:N [ vcard:Given "Mary" ; vcard:Family "Smith" ] ; ex:hasAge 29 .

ILLUSTRATION BY LARGER EXAMPLES

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27 Illustration 1 – KIM Browser Plugin • KIM Browser Plugin Web content is annotated using ontologies Content can be searched and browsed intelligently

Select one or more concepts from the ontology… … send the currently loaded web page to the Annotation Server

Annotated Content

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Illustration 2 – Disco Hyperdata Browser

Dereferencable Disco Hyperdata Browser URI navigating the Semantic Web as an unbound set of data sources

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28 EXTENSIONS

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Extensions: Linked Open Data

• Linked Data is a method for exposing and sharing connected data via dereferenceable URI’s on the Web – Use URIs to identify things that you expose to the Web as resources – Use HTTP URIs so that people can locate and look up (dereference) these things – Provide useful information about the resource when its URI is dereferenced – Include links to other, related URIs in the exposed data as a means of improving information discovery on the Web

• Linked Open Data is an initiative to interlink open data sources – Open: Publicly available data sets that are accessible to everyone – Interlinked: Datasets have references to one another allowing them to be used together

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29 Extensions: Linked Open Data

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Extensions: Linked Open Data - FOAF

• Friend Of A Friend (FOAF) provides a way to create machine-readable pages about: – People – The links between them – The things they do and create • Anyone can publish a FOAF file on the web about themselves and this data becomes part of the Web of Data

Dieter Fensel

• FOAF is connected to many other data sets, including – Data sets describing music and musicians (Audio Scrobbler, MusicBrainz) – Data sets describing photographs and who took them (Flickr) – Data sets describing places and their relationship (GeoNames)

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30 Extensions: Linked Open Data - GeoNames

• The GeoNames Ontology makes it possible to add geospatial semantic information to the Web of Data

• We can utilize GeoNames location within the FOAF profile

Dieter Fensel

• GeoNames is also linked to more datasets – US Census Data – Movie Database (Linked MDB) – Extracted data from Wikipedia (DBpedia)

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Extensions: Linked Open Data - DBpedia

• DBpedia is a community effort to extract structured information from Wikipedia and to make this information available on the Web

• As our FOAF profile has been linked to GeoNames, and GeoNames is linked to DBpedia, we can ask some interesting queries over the Web of Data – What is the population of the city in which Dieter Fensel lives? => 117916 people – At which elevation does Dieter Fensel live? => 574m – Who is the mayor of the city in which Dieter Fensel lives => Mag.ª Christine Oppitz-Plörer

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31 schema.org

“schema.org is a collaborative, community activity with a mission to create, maintain, and promote schemas for structured data on the Internet, on web pages, in email messages, and beyond.”

schema.org is sponsored by

http://schema.org/

schema.org – motivation

• Having structured data on the Web helps search engines to understand the information and provide richer search results • The problem is that there are too many standards and schemas for marking up different types of information on web pages • This makes is difficult for webmaster to decide on the most relevant and supported markup standards to use. • schema.org is the defacto standard supported by the major search engines providing a common support for webmasters, search engines and users: – Webmasters use one single markup for structured data supported by the major search engines – Search engines get the structured information they need to improve search results – Users get better search results and better experience on the Web

32 schema.org – schemas

• schema.org schemas includeasetofTypes each associated with a set of Properties • Types are arrange in a hierarchy • The core vocabulary consists of 642 Types, 992 Properties and 219 Enumeration values • Most commonly used types are:

schema.org – syntax

• schema.org can embedded into HTML the various formats: • RDFa • Microdata •JSON-LD

33 schema.org – simple example

Example*: Imagine you have a page about the movie Avatar—a page with a link to a movie trailer, information about the director, and so on. Your HTML code might look something like this:

Avatar

Director: James Cameron (born August 16, 1954) Science fiction html">Trailer

* http://schema.org/docs/gs.html

schema.org – simple example

Annotating the previous html code with schema.org in microdata*:

Director: James Cameron (born August 16, 1954)
Science fiction Trailer

* http://schema.org/docs/gs.html

34 schema.org – extension mechanism

• Since May 2015 schema.org offers a new extension mechanism that facilitates the creation of specialized and/or deeper vocabularies based on the core vocabulary of schema.org • There are two types of extenssions: • Review/hosted extenssions • Gets its own chunk of schema.org namespace e.g. auto.schema.org • Is maintained by the creator of the extenssion • External extenssions • Extenssions specific to third parties applications e.g. schema.pinterest.com

schema.org hotels extension

• Based on STI Accommodation Ontology http://ontologies.sti-innsbruck.at/acco/ns.html • Developed by Martin Hepp and Ioan Toma • Submitted to schema.org on 03.12.2015 • Approved as the official schema.org extension, by now

35 schema.org hotels extension

• When modeling accommodation related-information the following types are usually used: • schema:LodgingBusiness i.e. the place and local business, including subtypes schema:Hotel, schema:Hostel, schema:Resort, etc. • schema:Accomodation i.e. the relevant unit of establishment e.g. schema:HotelRoom, schema:Suite, schema:Apartment, etc. • schema:Offer to let an accommodation for a particular amount of money and for a given type of usage.

schema.org hotels extension Model

schema:Product schema:Place schema:Organization

schema:containedInPlace schema:Accommodation schema:LodgingBusiness schema:Price schema:containsPlace Specification

schema:Apartment schema:CampingSite schema:Hostel schema:CampingPitch schema:House schema:Hotel schema:Motel schema:Room schema:Resort schema:HotelRoom

schema:MeetingRoom schema:priceSpecification schema:Offer schema:Rate schema:Suite schema:PropertyValue schema:Thing schema:QualitativeValue schema:Accomodation schema:BedDetails schema:BedType Feature

Existing types and properties in schema.org New types and properties subType relationship 72

36 schema.org hotels extension Model

• All actual accommodations are subtypes of schema:Place and of schema:Product • All types of lodging businesses are subtypes of schema:Place and of schema:LocalBusiness • schema:containsPlace and schema:containedInPlace to link between an accommodation and the lodging business • schema:makesOffer and schema:offeredBy to link between the lodging business and its offer • schema:offers and schema:itemOffered to link between an accommodation and the offer

schema.org hotels extension New Types

• Includes 13 new types:

• Accommodation • AccommodationFeature • Apartment • BedDetails • BedType • CampingSite • CampingPitch • House • HotelRoom • MeetingRoom • Resort • Room • Suite

37 schema.org hotels extension New Properties

• Includes 18 new properties: • accommodationSize • availabilityTimes • bed • feature • gated • includedFeature • numberOfBeds • numberOfRooms • occupancy • occupancyAdults • occupancyMinors • optionalFeature • petsAllowed • permittedUsage • roomNumber • smokingAllowed • starRating • typeOfBed 75

schema.org hotels extension Minimal Example

Hotel Rotes Wildschwein

A beautifully located family hotel right in the heart of the alps. Watch the sun rise over the scenic Inn valley while enjoying your morning coffee.

Tiergartenstrasse 200 6020 Innsbruck Tyrol, Austria

Phone: +43 512 8000‐0 Star rating: ***** Room rates: €65 ‐ €155

38 SEMANTIC WEB - PROCESSES

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MOTIVATION

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39 Motivation

http://www.sti-innsbruck.at/results/movies/dip-promotion-video

Motivation

• The Web is moving from static data to dynamic functionality – Web services: a piece of software available over the Internet, using standardized XML messaging systems – Mashups: The compounding of two or more pieces of web functionality to create powerful web applications

40 Motivation

Limitations of the current Web Processes

• Web services and mashups are limited by their syntactic nature

• As the amount of services on the Web increases it will be harder to find Web services in order to use them in mashups

• The current amount of human effort required to build applications is not sustainable at a Web scale

41 What is needed?

• Formal, machine processable descriptions of processes on the Web that allows easy integration, configuration and reuse • Semantic support for finding, composing and executing these processes and all the other related tasks

Solution: Combine Semantics and Web processes/services that enables the automation of many of the currently human intensive tasks around Web processes/services

TECHNICAL SOLUTIONS

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42 Semantic Web Services

• Brings the benefits of Semantics to the executable part of the Web – Ontologies as data model – Unambiguous definition of service functionality and external interface

• Reduce human effort in integrating services in SOA – Many tasks in the process of using Web services can be automated

• Improve dynamism – New services available for use as they appear – Service Producers and Consumers don’t need to know of each others existence

• Improve stability – Service interfaces are not tightly integrated so even less impact from changes – Services can be easily replaced if they are no longer available – Failover possibilities are limited only by the number of available services

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Semantic Web Services

• Semantic Web Services are a layer on top of existing Web service technologies and do not aim to replace them

• Provide a formal description of services, while still being compliant with existing and emerging technologies

• Distinguish between a Web service (computational entity) and a service (value provided by invocation)

• Make Web services easier to: –Find – Compare – Compose – Invoke

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43 Technical Overview

Conceptual Model for SWS

Formal Language for WSMO

Execution Environment Ontology & Rule Language For SWS for the Semantic Web

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WSMO – Design Principles

Web Service versus Service

Strict Decoupling Ontology-Based of Modeling Elements WSMO Centrality of Ontological Role Mediation Separation

Description versus Implementation

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44 WSMO – Conceptual Model

Objectives that a client wants to achieve by using Web Services

Formally specified Semantic description terminology used of Web Services by all other • Capability (functional) components • Interfaces (usage)

Connectors between components with mediation facilities for handling heterogeneities

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WSML – Language Family

WSML ‐ Full

WSML ‐ Rule with WSML ‐ DL f without

Expressivity WSML ‐ Flight

WSML ‐ Core

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45 Semantic Execution Environment

Semantic Execution Environment

vertical broker

Discovery Ranking Selection

Composition Data Mediation Process Mediation

Process Lifting &

Monitoring Execution Lowering

base

Reasoning Storage

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Semantic Execution Environment - WSMX Data Data and Communication Protocols Adapters Adapter 1 Adapter System Interface System Adapter 2 Adapter ... Adapter n

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46 ILLUSTRATION BY LARGER EXAMPLES

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Receives a customer id Illustration 1: SWS Challenge and returns a full customer description

id Purchase Order

cid

openOrder Purchase Order Confirmation addItem*

closeOrder

Blue Company can only send POs and • Blue companyreceive has PO discovered Moon company on the Web Confirmations • Blue company wishes to communicate with MoonAllows thecompany opening of a PO, the specification of the items to be purchased and the • Broker required to resolve data and process interoperabilityclosing of the POissues

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47 Illustration 2: Virtual Travel Agency

Rail Services

Flight Services

Hotel Services

Car Hire Services

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Illustration 3: WSMX At Work Data Data and Communication Protocols Adapters Adapter 1 Adapter System Interface System Adapter 2 Adapter ... Adapter n

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48 EXTENSIONS

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Extensions: Mobile Services

49 Extensions: Mobile Services

• Extending the mobile and sensors networks with Semantic technologies, Semantic Web will enable: – Interoperability at the level of sensors data and protocols – More precise search for mobile capabilities and sensors with desired capability

From: http://www.opengeospatial.org/projects/groups/sensorweb 99

SCHEMA.ORG ACTIONS

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50 What is schema.org actions?

• schema.org is about providing vocabularies for describing entities such as people, places, restaurants, hotels, etc. • The Web is not just about static descriptions of entities, but also about taking actions on these entities. • schema.org actions is a vocabulary that enable websites to describe actions they enable and how these actions can be invoked. • Some example of actions that can be described using schema.org actions vocabulary: • Make a reservation • Watch a movie • Comment on a post

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schema:Action overview

• Main type of schema.org actions is schema:Action • Before the introduction of schema.org actions, this type was used to describe past actions • With the introduction of schema.org schema:Action is used to features the capability to perform an action in the future, as well as the definition of how that capability can be exercised. •Anaction is performed by a direct agent and indirect participants upon a direct object. • An action optionally happens at a location with the help of an inanimate instrument. • The execution of the action may produce a result.

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51 schema:Action example in JSON-LD

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schema.org actions vocabulary (cont’d)

• schema:actionStatus • Indicates the current disposition of the schema:Action. • Enumeration members include: potential, active, and completed • schema:potentialAction • Indicates a potential Action, which describes an idealized action in which this thing would play an 'object' role. • Describes the "prototype" of an action that can be taken on that Thing. { "@context": "http://schema.org", "@type": "Movie", "name": "Footloose", "potentialAction": { "@type": "WatchAction" } } 104

52 schema.org actions vocabulary (cont’d)

• schema:target • Potential actions are materialized via execution against the target schema:EntryPoint of an schema:Action • I/O constaints • Additional information is often required from a user or client in order to formulate a complete request. To facilitate this process we need the ability to describe within a potential action how to construct these inputs

{ "@context": "http://schema.org", "@type": "WebSite", "name": "Example.com", "potentialAction": { "@type": "SearchAction", "target": "http://example.com/search?q={q}", "query-input": "required maxlength=100 name=q" } }

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SUMMARY

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53 Summary

• The Semantic Web provides a mechanism for – Representing knowledge on the Web – Annotating data on the Web – Annotating services on the Web

• Everything is identified by a URI • RDF to assert relations between resources • RDFS and OWL to make statements about types • SPARQL to query RDF data • WSMO as a conceptual model • WSML for describing services at different levels of expressivity • WSMX as a Semantic Execution Environment for bringing requesters and providers together

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REFERENCES

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54 References

• Mandatory reading: – T. Berners-Lee, J. Hendler, O. Lassila. The Semantic Web, Scientific American, 2001. – Dieter Fensel, Holger Lausen, Axel Polleres, Jos de Bruijn, Michael Stollberg, Dumitru Roman, John Domingue, Enabling Semantic Web Services: The Web Service Modeling Ontology, Springer-Verlag, 2007 • Further reading: – Dieter Fensel, Mick Kerrigan, Michal Zaremba (Eds.), Implementing Semantic Web Services: The SESA Framework. Springer-Verlag, 2008. – Jos de Bruijn, Dieter Fensel, Mick Kerrigan, Uwe Keller, Holger Lausen, and James Scicluna: Modeling Semantic Web Services, Springer-Verlag, 2008 – D. Fensel. Ontologies: A Silver Bullet for Knowledge Management and Electronic Commerce, 2nd Edition, Springer 2003. – G. Antoniou and F. van Harmelen. A Semantic Web Primer, (2nd edition), The MIT Press 2008. – H. Stuckenschmidt and F. van Harmelen. Information Sharing on the Semantic Web, Springer 2004. – T. Berners-Lee. Weaving the Web, HarperCollins 2000 – T.R. Gruber, Toward principles for the design of ontologies used or knowledge sharing? , Int. J. Hum.-Comput. Stud., vol. 43, no. 5-6,1995

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References

– David Martin, et al., OWL-S: Semantic Markup for Web Services, W3C Member Submission 22 November 2004, http://www.w3.org/Submission/OWL-S. – Joel Farrell and Holger Lausen, Semantic Annotations for WSDL and XML Schema, W3C Recommendation 28 August 2007, http://www.w3.org/TR/sawsdl – Rama Akkiraju et al., Web Service Semantics - WSDL-S, W3C Member Submission 7 November 2005, http://www.w3.org/Submission/WSDL-S – Steve Battle et al., Semantic Web Services Framework (SWSF), W3C Member Submission 9 September 2005, http://www.w3.org/Submission/SWSF – Semantic Web Primer: http://www.ics.forth.gr/isl/swprimer/ – RDF Primer: http://www.w3.org/TR/REC-rdf-syntax/ – RDF Schema: http://www.w3.org/TR/rdf-schema/ – OWL Guide: http://www.w3.org/TR/owl-guide/ – RDF SPARQL Protocol: http://www.w3.org/TR/rdf-sparql-protocol/ – Linked Open Data: http://linkeddata.org/ – Linked Open Data Tutorial: http://www4.wiwiss.fu-berlin.de/bizer/pub/LinkedDataTutorial/ –WSMO: http://www.wsmo.org/TR/d2/ –WSML: http://www.wsmo.org/TR/d16/d16.1/ –WSMO/WSML Tutorials: http://wiki.sti2.at/index.php?title=WSMT_Tutorials

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55 References

• Wikipedia links: – URI: http://en.wikipedia.org/wiki/URI – RDF; http://en.wikipedia.org/wiki/Resource_Description_Framework – RDFS: http://en.wikipedia.org/wiki/RDFS –SPARQL: http://en.wikipedia.org/wiki/SPARQL –WSMO: http://en.wikipedia.org/wiki/WSMO –WSML: http://en.wikipedia.org/wiki/Web_Services_Modeling_Language

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http://www.sti-innsbruck.at/results/movies/serviceweb-30-future-internet

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56 Next Lecture

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Questions?

Email: [email protected] Web: http://bit.ly/2mwtf1h Twitter: @alphaverda Facebook: https://www.facebook.com/STIInnsbruck/

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Semantic Web and Services Anna Fensel 12.06.2017 & 19.06.2017

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