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Programme
- Foundations of Knowledge Representation and Reasoning
- Natural Language Processing
- Semantic Multimedia
- Social Networks
- Bioinformatics
- Web Services
Detailed Timetable
Lecture Notes
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The course material used during the Summer School appeared in the Lecture Notes in Computer Science series by Springer as LNCS 5224: see the publisher information about the volume and the online version.
Slides
-
Slides used in lectures can be downloaded from the
Repository of the European Association for Semantic Web Education
(REASE).
The query
"reasoning web school 2008"+"slides of lecture"
selects precisely the 2008 slides from among all Reasoning Web slides. - Slides of the KIWI presentation
- Slides of the MOST presentation
Course Descriptions
(1.1) Rules and Ontologies
Rules and ontologies play a key role in the Semantic Web Layer Architecture, as they are used to ascribe meaning to data on the Web, and to reason about them. While the Ontology Layer of the Semantic Web is quite developed, and the Web Ontology Language (OWL) is a W3C recommendation since a couple of years already, the Rules Layer is far less developed and active area of research; a number of initiatives and proposals have been made so far, which have quite different properties and features. In particular, the issue of having rules on top or aside ontologies in OWL is an important issue that has not been completely settled yet.
This lecture aims at presenting rule-based approaches for the Semantic Web, in view of RDF/RDFS and ontology languages for the Web, in particular OWL and its dialects. To this end, the first part of the lecture will be devoted to present and illustrate some rule-based approaches in which semantic combination with expressive ontologies does not play a major role. The second part then considers such combinations, which have been/are currently developed. The goal is that the student is, on the one hand, informed about various approaches to rules for the Semantic Web, the features they have, and their properties and relationships. On the other hand, s/he should also know about the problems that come along with having such rules, and how this problems might be overcome; furthermore, issues for research should be pointed out. The focus will be on deductive rules languages approaches with a 2-valued semantics; probabilistic, fuzzy, dynamic (event-condition-action rules, production rules) approaches, etc. will not be considered in depth.
[top of page](1.2) Concepts and Techniques for Reasoning about Uncertainty
There is currently a strong interest in using and extending AI techniques, systems, and concepts to the World Wide Web. In particular, managing uncertainty and/or vagueness is starting to play an important role in Semantic Web research.
We present the state of the art in representing and reasoning with uncertain and/or vague knowledge in the Semantic Web. Since web content and user requests are very likely to be uncertain and/or vague, there is a strong need to deal with such forms of knowledge in the Semantic Web. This need to deal with uncertainty and vagueness Semantic Web has been recognised by a large number of research efforts in this direction.
Our aim is at making attendees familiar with the concepts and techniques for representing and reasoning with uncertain and vague knowledge in current Semantic Web ontology and rule languages (and their combination), which should help the attendees to get insights on main features of the formalisms and tools proposed so far.
[top of page](2.1) Attempto Controlled English for Knowledge Representation
Attempto Controlled English (ACE) is a controlled natural language, i.e. a precisely defined, tractable subset of full English that can be automatically and unambiguously translated into first-order logic. ACE seems completely natural, but is actually a formal language, concretely it is a first-order logic language with the syntax of a subset of English. Thus ACE is human and machine understandable. As a formal language, ACE has to be learned, which -- as experience shows -- takes about two days. ACE was originally developed to specify software programs, but has since been used as a general knowledge representation language. For instance, we specified in ACE an automated teller machine, Kemmerer's library data base, Schubert's Steamroller, data base integrity constraints, Kowalski's subway regulations, and several ontologies. ACE served as natural language interface for the model generator EP Tableaux, for a FLUX agent, and for MIT's Process Handbook.
To support automatic reasoning in ACE, we have developed the Attempto Reasoner (RACE). RACE proves that one ACE text is the logical consequence of another one, and gives a justification for the proof in ACE. Furthermore, ACE has found several applications within the semantic web. We have developed translations of ACE into and from OWL 1.1 that are implemented as a plug-in for the ontology editor Protégé. The tool AceWiki combines controlled natural language with the ideas and technologies of the semantic web and with the concepts of wikis. AceRules is a forward chaining rule system that offers three different semantics.
The course will give a concise introduction into ACE and its associated tools, and offer hands-on experience with all tools.
The course is self-contained and requires only elementary linguistic knowledge
and some knowledge of first-order logic. More information can be found at
http://attempto.ifi.uzh.ch
(3.1) Semantic Multimedia Management
In this course we will deal with issues of semantics in multimedia management. Such issues involve:
- the representation of multimedia metadata using Semantic Web ontologies;
- the interpretation of multimedia objects by various means of reasoning;
- the retrieval of multimedia objects by means of low and high-level (semantic) representations of multimedia;
- the further processing of multimedia facts in order to determine provenance, certainty and other metaknowledge aspects of multimedia data.
(4.1) Applications of Semantic Web Methodologies and Techniques to Social Networks and Social Media Sites
John G. Breslin, Stefan Decker
Social networking sites such as
MySpace, Facebook and orkut and
content-sharing sites (that also offer social networking functionality)
including Flickr, last.fm and del.icio.us
have captured
the attention of millions of users as well as billions of dollars in
investment and acquisition. As more social networking services (SNSs)
form around the connections between people and their objects of
interest, and as these "object-centered networks" grow bigger and more
diverse, more intuitive methods are needed for representing and
navigating the content items in these networks: both within and across
social networking sites. Also, to better enable user access to
multiple sites, interoperability among SNSs is required in terms of
both the content objects and the person-to-person networks expressed
on each site. This requires representation mechanisms to interconnect
people and objects on the Web in an interoperable, extensible way.
The Semantic Web provide such representation mechanisms: it links people and objects to record and represent the heterogeneous ties that bind us to each other. By using agreed-upon Semantic Web formats to describe people, content objects, and the connections that bind them together, SNSs can interoperate by appealing to some common semantics. Developers are already using Semantic Web technologies to augment the ways in which they create, reuse, and link content on social networking and media sites.
In this course, we will give an overview of various social networking and social media applications, list some of their strengths and limitations, and describe some applications of Semantic Web technology to address issues with social media sites and to enhance the current "Web 2.0" platform with semantics. We will demonstrate how the Semantic Web can serve as a useful platform for linking and for performing operations on diverse person- and object-related data gathered from heterogeneous social networking sites, and show that in the other direction, social media sites can themselves serve as rich data sources for Semantic Web applications.
[top of page](4.2) The KIWI Project, a Showcase for Semantic Wikis and for Writing FP7 Project Applications
The project KIWI is concerned with knowledge management in Semantic Wikis and funded by the European Commission under the Project Number 211932 in the EU Seventh Framework Programme (FP7).
The first part of the talk will give an overview of the project KIWI and its objectives, namely to investigate how knowledge management in highly dynamic environments can be supported using Semantic Wiki technologies, and how Semantic Wikis can be improved to satisfy the requirements of knowledge management.
The second part of the talk is intended to share experience and offer insight into the process of submitting applications in the framework of FP7 Call 3. The KIWI project will be used to exemplify what -- in the author's opinion and experience -- are "success factors" in a successful project proposal.
[top of page](5.1) Applications of Semantic Web Methodologies and Techniques to Biology and Bioinformatics
Paolo Romano, Andrea Splendiani
Semantic Web technologies are extremely appealing for biomedical researchers since they promise to solve many of the daily problems they face while accessing and integrating biological information that is distributed over the Internet and managed by using tools which are extremely heterogeneous and largely not compatible. Otherwise, the complexity of biomedical information and its heterogeneity, together with the need of keeping current production services steadily up and running, make the transition from current semantic-less to future semantic-aware services a huge problem.
Up to now, little has been made for supporting semantic integration. What we need are shared definitions of knowledge domains, i.e. ontologies, association of biological concepts to existing data, metadata information describing information sources and search tools able to make the best use of this additional information. The definition of ontologies and their application to software and database tools may be seen as a first, needed attempt to organize the information, overcoming heterogeneity of data structures. But the problem of associating the information sources and the huge amount of data with concepts defined in these ontologies is a big one. The addition of semantic contents in current databases would give an essential contribution to the best integration of distributed biological information.
The development of metadata for biological information, on the basis of Semantic Web standards, and its definition for all information sources can also be seen as a promising approach for a semantic based integration of biological information. Text mining is of a fundamental importance since literature still is the most relevant information source in biomedical research. Moreover, it is the most clear example of an unstructured information source whose content should be integrated with structured data in order to be fully exploited.
In this paper, authors start by presenting the main characteristics of biomedical information and of related information services that make adoption of semantic web technologies both desirable and complex at the same time. They then present the tools and the applications that have been developed so far, including biomedical ontologies, RDF/OWL data stores, query systems and semantic-aware tools and browsers. Finally, they present current community efforts, such as the activity of W3C interest group, and the perspectives that can be sought for short- and mid-term developments in the field.
The course only requires basic knowledge of semantic web tools: RDF, OWL, SPARQL, GRDDL, Semantic Web Services. Basic knowledge of biological and medical data models is an advantage but is not necessary.
[top of page](6.1) Semantic Web Services
Web services allow encapsulating an organization's functionality with an appropriate interface and advertising it in the Web. In many cases, Web services can be utilized in an isolated form, but their full potential is achieved through their composition to form Web processes. There is a growing consensus that Web services alone will not be sufficient to develop valuable processes due the degree of heterogeneity, autonomy, and distribution of the Web. Several researchers agree that it is essential for Web services to be machine understandable in order to support all the phases of the lifecycle of Web processes. One solution to create Semantic Web services is by mapping concepts in a Web service description to ontological concepts. Using this approach, users can explicitly define the semantics of a Web service for a given domain. Different approaches to specifying Semantic Web services have been proposed. Examples include OWL-S, WSMO, SWSO and SAWSDL. Using these specifications, the Semantic Web services deployed will allow the annotation, advertisement, discovery, selection, composition, and execution of inter-organization business logic, making the Internet become a global common platform where organizations and individuals communicate among each other to carry out various commercial activities and to provide value-added services.
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