Semantic Web Services

Transcription

1 Semantic Web Services Web Science Dieter Fensel Ioan Toma Copyright 2008 STI INNSBRUCK

2 Where are we? # Date Title 1 5 th March Introduction 2 12 th March Web Science 3 19 th March Service Science 4 26th March Web Services (WSDL, SOAP, UDDI, XML) 5 2 nd April Web 2.0 and RESTful services 6 23 rd April WSMO 7 30 th April WSML 8 7 th May WSMX 9 14 th May OWL-S and others th May WSMO-Lite, MicroWSMO 11 4 th June SWS Use Cases th June seekda: the business point of view th June Mobile services 14 2 nd July Exam Preparation 2

3 Outline Motivation Web Science Web Evolution Web 1.0 Traditional Web Web 2.0 Web 3.0 Semantic Web What Web Science should be The computer science of the 21st century 3

4 MOTIVATION 4

5 Motivation The Web Today 5

6 Motivation [ ] As the Web has grown in complexity and the number and types of interactions that take place have ballooned, it remains the case that we know more about some complex natural phenomena (the obvious example is the human genome) than we do about this particular engineered one. A Framework for Web Science T. Berners-Lee and W. Hall and J. A. Hendler and K. O'Hara and N. Shadbolt and D. J. Weitzner Foundations and Trends in Web Science 1 (2006) A new science that studies the complex phenomena called Web is needed!! 6

7 WEB SCIENCE 7

8 Web Science definition A new science that focuses on how huge decentralized Web systems work. The Web isn t about what you can do with computers. It s people and, yes, they are connected by computers. But computer science, as the study of what happens in a computer, doesn t tell you about what happens on the Web. Tim Berners-Lee A new field of science that involves a multi-disciplinary study and inquiry for the understanding of the Web and its relationships to us Bebo White, SLAC, Stanford University Shift from how a single computer works to how huge decentralized Web systems work 8

9 Endorsements for Web Science Web science represents a pretty big next step in the evolution of information. This kind of research likely to have a lot of influence on the next generation of researchers, scientists and, most importantly, the next generation of entrepreneurs who will build new companies from this. Eric E. Schmidt, CEO Google Web science research is a prerequisite to designing and building the kinds of complex, human-oriented systems that we are after in services science. Irving Wladawsky-Berger, IBM 9

10 Web science multi-disciplinary approach 10

11 The Goals of Web Science To understand what the Web is To engineer the Web s future and providing infrastructure To ensure the Web s social benefit 11

12 Scientific method Natural Sciences such as physics, chemistry, etc. are analytic disciplines that aim to find laws that generate or explain observed phenomena Computer Science on the other hand is synthetic. It is about creating formalisms and algorithms in order to support particular desired behaviour. Web science scientific method has to be a combination of these two paradigms 12

13 What Could Scientific Theories for the Web Look Like? Some simple examples: Every page on the Web can be reached by following less than 10 links The average number of words per search query is greater than 3 Web page download times follow a lognormal distribution function (Huberman) The Web is a scale-free graph Can these statements be easily validated? Are they good theories? What constitutes good theories about the Web? 13

14 Food For Thought Electricity : 1800 Electricity Now What are the analogies for Web Science and Design? Is our understanding of the Web like that of 1800 electricity? 14

15 In the rest of this lecture Web Evolution Web Traditional Web Web 2.0 Web Semantic Web Future steps to realize Web science Large scale reasoning Rethinking Computer Science for the 21 st century 15

16 WEB 1.0 TRADITIONAL WEB 16

17 Web 1.0 More than a 2 billion users more than 50 billion pages Static WWW URI, HTML, HTTP 17

18 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. - wikipedia The Web was created around 1990 by Tim Berners-Lee working at CERN in Geneva, Switzerland. 18

19 Web 1.0 A distributed document delivery system implemented using application-level protocols on the Internet A tool for collaborative writing and community building A framework of protocols that support e-commerce A network of co-operating computers interoperating using HTTP and related protocols to form a subnet of the Internet A large, cyclical, directed graph made up of Web pages and links 19

20 WWW Components Structural Components Clients/browsers to dominant implementations Servers run on sophisticated hardware Caches many interesting implementations Internet the global infrastructure which facilitates data transfer Language and Protocol Components Uniform Resource Identifiers (URIs) Hyper Text Transfer Protocol (HTTP) Hyper Text Markup Language (HTML) 20

21 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) 21

22 Hypertext 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 22

23 HTTP Request Messages GET retrieve document specified by URL PUT store specified document under given URL HEAD retrieve info. about document specified by URL OPTIONS retrieve information about available options POST give information (eg. annotation) to the server DELETE remove document specified by URL TRACE loopback request message CONNECT for use by caches 23

24 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 Mark up elements are not seen by the user when page is displayed Documents are rendered by browsers 24

25 HTML HTML markup consists of several types of entities, including: elements, attributes, data types and character references DTD (Document Type Definition) <!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01//EN" " Element (such as document (<html> </html>), head elements (<title> </title>) Attribute: <span id='anid' class='aclass' style='color:red;' title='hypertext Markup Language'>HTML</span> Data type: CDATA, URIs, Dates, Link types, language code, color, text string, etc. Character references: for referring to rarely used characters: "水" (in hexadecimal) represents the Chinese character for water 25

26 WEB

27 Web 2.0 Web 2.0 is a notion for a row of interactive and collaborative systems of the internet 27 27

28 What is the web 2.0? Definition by O Reilly Web 1.0 Web 2.0 improvement DoubleClick Google AdSense personalized Ofoto Flickr tagging, community Britannica Online Wikipedia community, free content Webseiten blogging dialogue publishing participation CMS wikis flexibility, freedom directories tagging community taxonomy folksonomy Consumers Prosumers 28 28

29 What is the Web 2.0? - Examples Gmail Google Notebooks (Collaborative Notepad in the Web) Wikis Wikipedia Worlds biggest encyclopedia, Top 30 web site, 100 langueges Del.icio.us (Social Tagging for Bookmarks) Flickr (Photo Sharing and Tagging) Blogs, RSS, Blogger.com Programmableweb.com: 150 web-apis 29 29

30 Blogs Easy usable user interfaces to update contents Easy organization of contents Easy usage of contents Easy publishing of comments Social: collaborative (single users but strongly connected)

31 Wikis Wiki invented by Ward Cunningham Collection of HTML sites: read and edit Most famous and biggest Wiki: Wikipedia (MediaWiki) But: Also often used in Intranets (i. e. our group) Problems solved socially instead of technically Flexible structure Background algorithms + human intelligence No new technologies social: collaborative (nobody owns contents) 31 31

32 Wikis: Design Principles Open Should a page be found to be incomplete or poorly organized, any reader can edit it as they see fit. Incremental Pages can cite other pages, including pages that have not been written yet. Organic The structure and text content of the site are open to editing and evolution. Mundane A small number of (irregular) text conventions will provide access to the most useful page markup. Universal The mechanisms of editing and organizing are the same as those of writing so that any writer is automatically an editor and organizer. Overt The formatted (and printed) output will suggest the input required to reproduce it. Source:

33 Wikis: Design Principles Unified Page names will be drawn from a flat space so that no additional context is required to interpret them. Precise Pages will be titled with sufficient precision to avoid most name clashes, typically by forming noun phrases. Tolerant Interpretable (even if undesirable) behavior is preferred to error messages. Observable Activity within the site can be watched and reviewed by any other visitor to the site. Convergent Duplication can be discouraged or removed by finding and citing similar or related content. Source:

34 Social Tagging Idea: Enrich contents by user chosen keywords Replace folder based structure by a organisation using tags New: Simple user interfaces for tagging and tag based search First steps to Semantic Web? Technically: user interfaces Social: collaborative (own contents, shared tags) 34 34

35 Collaborative Tagging 35 35

36 Tagging: Flickr.com 36 36

37 Folksonomies Data created by tagging, knowledge structures User Tag Resource User Tag Tag Resource Resource User Tag Tag Resource Resource Mary tags with wiki wikipedia encyclopedia Bob tags with wiki web2.0 encyclopedia knowledge 37 37

38 Tag Clouds Size of Tags: count of usage Browsing replaces Searching Different meaning for different users Orientation in Information Set 38 38

39 What is the Web 2.0? Trends for Web Applications Technical Evolution Web User Interfaces become faster (AJAX) Desktop shifts to Web (GMail, Google Notebooks, AJAX) Social Evolution Collective creates additional value (Wiki, Tagging) Free contents become popular (Licenses) Attention is getting monetarized (Text-Ads) Websites with additional value by recombination (Mash-Ups, RSS) 39 39

40 SEMANTIC WEB 40

41 From Web to Semantic Web Static WWW URI, HTML, HTTP Semantic Web RDF, RDF(S), OWL 41

42 Semantic Web If the Web is about the global networking of data through URL, HTML, and HTTP the Semantic Web is about the global networking of knowledge through URI, RDF, and SPARQL This knowledge can be an annotation of Web data (this picture depicts Innsbruck) or just for knowledge s sake (Innsbruck is a city in Austria) 42

43 Semantic Web URIs are used to identify resources, not just things that exists on the Web, e.g. Sir Tim Berners-Lee RDF is used to make statements about resources in the form of triples <entity, property, value> With RDFS, resources can belong to classes (my Mercedes belongs to the class of cars) and classes can be subclasses or superclasses of other classes (vehicles are a superclass of cars, cabriolets are a subclass of cars) 43

44 Semantic Web Architecture Give URIs to concepts - Each URI identifies one concept. Share these symbols between many languages Support URI lookup 44

45 Semantic Web layer cake 45

46 URI and XML Uniform Resource Identifier (URI) is the dual of URL on Semantic Web It s purpose is to indentify resources extensible Markup Language (XML) is a markup language used to structure information Fundament of data representation on the Semantic Web Tags do not convey semantic information 46

47 RDF and OWL Resource Description Framework (RDF) is the dual of HTML in the Semantic Web Simple way to describe resources on the Web Sort of simple ontology language (RDF-S) Based on triples (subject; predicate; object) Serialization is XML based Ontology Web Language (OWL) a layered language based on DL More complex ontology language Overcome some RDF(S) limitations 47

48 SPARQL and Rule languages SPARQL Query language for RDF triples A protocol for querying RDF data over the Web Rule languages (e.g. SWRL) Extend basic predicates in ontology languages with proprietary predicates Based on different logics Description Logic Logic Programming 48

49 Semantic Web 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 49

50 Semantic Web Dereferencable URI Disco Hyperdata Browser navigating the Semantic Web as an unbound set of data sources 50

51 WEB EVOLUTION - SUMMARY 53

52 Web Evolution - summary Web 1.0 Web 2.0 Semantic Web Personal Websites Blogs Semantic Blogs: semiblog, Haystack, Semblog, Structured Blogging Content Management Systems, Britannica Online Altavista, Google Wikis, Wikipedia Google Personalised, DumbFind, Hakia Semantic Wikis: Semantic MediaWiki, SemperWiki, Platypus, dbpedia, Rhizome Semantic Search: SWSE, Swoogle, Intellidimension CiteSeer, Project Gutenberg Google Scholar, Book Search Semantic Digital Libraries: JeromeDL, BRICKS, Longwell Message Boards Community Portals Semantic Forums and Community Portals: SIOC, OpenLink DataSpaces Buddy Lists, Address Books Online Social Networks Semantic Social Networks: FOAF, PeopleAggregator Semantic Social Information Spaces: Nepomuk, Gnowsis 54

53 Web Evolution - summary Traditional Web (Web1.0) Normal User: browsing Communication style: one-direction communication (e.g. reading a book) Data: web data (string and syntactic format) Data contributor: webmaster or experienced user How to add data: compose HTML pages Social Web (Web2.0) Normal User: browsing + publishing and organizing web data Communication style: human-human (sharing) Data: web data + tags Data contributor: normal user revolution! How to add data: tagging Semantic Web Normal User: interacting (human-machine) Communication style: human machine Data: web data + tags + metadata (in SW Language) Data contributor: normal user, machine How to add data: machine generate or user publish 55

54 WHAT WEB SCIENCE SHOULD BE 56

55 Web principles In the context of the traditional Web (Web 1.0) a set of principles were proposed: Web resource are identified by URI (Universal Resource Identifier) Namespaces should be used to denote consistent information spaces Make use of HTML, XML and other W3C Web technology recommendations, as well as the decentralization of resources 57

56 Web semantics = Semantic Web The traditional Web represents information using natural language (English, German, Italian, ) 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 58

57 Web semantics = Semantic Web 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 automatically is <foo:creator> same as <bar:author>? how to combine different XML hierarchies? 59

58 Semantic Web Semantic Web is about applying semantics to the tradition Web, Web 1.0 Some of the benefits of Semantic Web: More precise queries Smarter apps with less work Share & link data between apps Information has machine-processable and machine-understandable semantics 60

59 Limitations of applying semantics to traditional Web The principal limits of describing large, heterogeneous, and distributed systems The principal limits of self representation and self reflection Necessitates incompleteness and incorrectness of semantic descriptions. 61

60 Limitations of applying semantics to traditional Web The principal limits of describing large, heterogeneous, and distributed systems 62

61 Limitations of applying semantics to traditional Web The principal limits of self representation and self reflection 63

62 Limitations of applying semantics to traditional Web The principal limits of self representation and self reflection The mission of STI International is to establish Semantics as a core pillar of modern computer engineering. It is supposed to be the leading international think tank in this field. The mission of STI International is to establish Semantics as a core pillar of modern computer engineering. establish It supposed to be the leading international think tank in this field. The mission of STI International is to Semantics as a core pillar of modern computer engineering. It is supposed to be the leading international think tank in this field. 64

63 Limitations of applying semantics to traditional Web The principal limits of self representation and self reflection Meta Layer (encodes heuristics, i.e. strategic knowledge) Introspection Reflection Object Layer (encodes possible complete reasoning knowledge for the problem) 65

64 Limitations of applying semantics to traditional Web The meta layer should apply heuristics that may help Speed up the overall reasoning process. Increase its flexibility. Therefore, it needs to be incomplete in various aspects and resemble important aspects of our consciousness. Introspection Reflection Unbounded rationality, constrained rationality, limited rationality. 66

65 Limitations of applying semantics to traditional Web Description of data by metadata or programs by metaprograms Always larger (even infinitely large) or always an approximation 67

66 Data look-up on the Web In a large, distributed, and heterogeneous environment, classical ACID guarantees of the database world no longer scale in any sense. Even a simple read operation in an environment such as the Web, a peer-to-peer storage network, a set of distributed repositories, or a space, cannot guarantee completeness in the sense of assuming that if data was not returned, then it was not there. Similarly, a write can also not guarantee a consistent state that it is immediately replicated to all the storage facilities at once. 68

67 Information retrieval on the Web Modern information retrieval applies the same principles In information retrieval, the notion of completeness (recall) becomes more and more meaningless in the context of Web scale information infrastructures. It is very unlikely that a user requests all the information relevant to a certain topic that exists on a worldwide scale, since this could easily go far beyond the amount of information processing he or she is investing in achieving a certain goal. Therefore, instead of investigating the full space of precision and recall, information retrieval is starting to focus more around improving precision and proper ranking of results. 69

68 Reasoning on the Web What holds for a simple data look-up holds in an even stronger sense for reasoning on Web scale. The notion of 100% completeness and correctness as usually assumed in logic-based reasoning does not even make sense anymore since the underlying fact base is changing faster than any reasoning process can process it. Therefore, we have to develop a notion of usability of inferred results and relate them with the resources that are requested for it. 70

69 Reasoning on the Web Semantic Web precision (soundness) Logic IR recall (completeness) 71

70 LarKC LarKC The Large Knowledge Collider An open source, modular, and distributed platform for inference on the Web that makes use of new reasoning techniques A plug-in architecture that supports cooperation between distributed, heterogeneous, cooperating modules enabling research into new and different reasoning techniques 72

71 WEB SCIENCE THE COMPUTER SCIENCE OF THE 21 st CENTURY 73

72 Web Science The Computer Science of the 21st Century With the Web we have an open, heterogeneous, distributed, and fast changing computing environment. Therefore we need computing to be understood as A goal driven approach where the solution process is only partially determined and actually decided during runtime, based on available data and services. A heuristic approach that gives up on absolute notion of completeness and correctness in order to gain scalability. The times of 100% complete and correct solutions are gone. 74

73 Web Science The Computer Science of the 21st Century The Need for Trade-offs: In all areas one has to define the trade-off between the guarantees one provides in terms of service level agreements. Completeness and correctness are just examples of some very strong guarantees and what this requires in terms of assumptions, and computational complexity Different heuristic problem solving approaches are just different combinations of these three factors. 75

74 Web Science The Computer Science of the 21st Century Service level agreements (or goals) define what has to be provided as result of solving a problem. Do we request an optimal solution, a semi-optimal solution, or just any solution? 76

75 Web Science The Computer Science of the 21st Century Assumptions describe the generality of the problem solving approach: Assuming that there is only one solution allows stopping the search for an optimum immediately after a solution has been found. Instead of a global optimization method, a much simpler heuristic search method can be used in this case, which would still deliver a global optimum. Computational complexity (scalability) or the resources that are required to fill the gap between the assumptions and the goals. 77

76 Web Science The Computer Science of the 21st Century Computer science in the 20th century was about perfect solutions in closed domains and applications. Web science, the new computer science of the 21st century, will be about approximate solutions and frameworks that capture the relationships of partial solutions and requirements in terms of computational costs, i.e., the proper balance of their ratio. 78

77 Web Science The Computer Science of the 21st Century This shift is comparable to the transition in physics, from classical physics to relativity theory and quantum mechanics,...where the notion of absolute space and time is replaced by relativistic notions and the principle limits of precision. the more precisely we know about the location of a particle in space, the less we know about its movement in time and vice versa.???? 79

78 References Web Science Research Initiative T. Berners-Lee, W. Hall, J. Hendler, N. Shadbolt, D. Weitzner (2006): Creating a science of the Web. T. Berners-Lee, W. Hall, J. Hendler, K. O Hara, N. Shadbolt, D. Weitzner (2006): A Framework for Web Science. N. Shadbolt. Web Science Research Initiative Seminar November D. Fensel, Dieter F. van Harmelen. Unifying Reasoning and Search to Web Scale, IEEE Internet Computing, 11(2), 2007 D. Fensel, D. Wolf: The Scientific Role of Computer Science in the 21st Century. In Proceedings of the third International Workshop on Philosophy and Informatics (WSPI 2006), Saarbruecken, Germany, May 3-4,

79 Next lecture # Date Title 1 5 th March Introduction 2 12 th March Service Science 3 19 th March Web Science 4 26 th March Web Services (WSDL. SOAP, UDDI, XML) 5 2 nd April Web 2.0 services/ restful services 6 23 rd April WSMO 7 30 th April WSML 8 7 th May WSMX 9 14 th May OWL-S and others th May SA-WSDL, WSMO-Lite, MicroWSMO 11 4 th June SWS are good for what th June seekda: the business point of view th June Mobile services 14 2 nd July Exam 81

80 Questions? 82