Summer School Reasoning Web 2009

Programme

Lectures:

The timetable is available on a separate web page.

Lecture Notes:

The course material used during the Summer School appears in the Lecture Notes in Computer Science series by Springer as LNCS Volume 5689: see the publisher information about the volume and the online version.

Course Descriptions:

Description Logics

Franz Baader

This tutorial concentrates on designing and analyzing reasoning procedures for DLs. After a short introduction and a brief overview of the research of the last 20 years, it will on the one hand present approaches for reasoning in expressive DLs, which are the foundation for reasoning in OWL DL. On the other hand, it will consider tractable reasoning in the more light-weight DL EL, which is employed in bio-medical ontologies, and which is the foundation for the OWL 2 profile OWL 2 EL.

Ontologies and databases

Diego Calvanese

Both knowledge base (KB) and database (DB) systems are used to maintain information about a domain of interest and provide mechanisms to access and manipulate such information. However the assumptions that traditionally are at the basis of these two kinds of systems are fundamentally different. On the one hand, in KB systems, data is assumed to be incomplete, i.e., the open-world assumption is made, and extensional information is stored together with an ontology. The latter maintains complex relationships at the intensional level and is used at query time to infer new knowledge. On the other hand, DB systems work under the closed-world assumption and do not exploit intensional information at query time, which makes them capable of managing efficiently very large amounts of data. Various recent application domains, ranging from biological to enterprise data management, require the management of very large amounts of data and the combination of the assumptions underlying both types of systems, namely the management of very large amounts of data, as in DBs, and the presence of complex constraints in an ontology interpreted under the open-world assumption, as in KBs. Several novel challenges arise in this context and need to be addressed, such as: (i) the trade-off between the expressive power of the ontology language and the efficiency of computing answers to queries; (ii) the impedance mismatch between the abstract objects in the ontology and the values appearing in data sources; (iii) the processing of queries posed over the ontology by accessing the data stored in relational sources; (iv) the integration of multiple data sources. In this tutorial, we will analyse these issues in depth and will propose solutions based on recent research results for tractable Description Logics and in Ontology-Based Data Access. We will also allow participants to familiarise with state-of-the-art technology recently developed in this area.

Foundations of RDF Databases

Claudio Gutierrez, Marcelo Arenas, Jorge Perez

The goal of this course is to give an overview of the current state of the theory of RDF databases. In the first part of this course, we provide a formal definition of RDF that includes the features that distinguish this model from other graph data models, such as the use of blank nodes and RDFS vocabulary. In this part, we present a deductive system for RDF that is used to give a formal semantics to this data model. In the second part of this course, we move into the fundamental issue of querying RDF data. We start by considering the RDF query language SPARQL, which is a W3C Recommendation since January 2008. We provide an algebraic syntax and a compositional semantics for this language, and we study the complexity of the evaluation problem for different fragments of SPARQL. We also consider the problem of optimising the evaluation of a SPARQL query, and show that a natural fragment of this language has some good properties in this respect. We furthermore study the expressive power of SPARQL, by comparing it with some well-known query languages such as relational algebra. We conclude this course by considering the issue of querying RDF data in the presence of RDFS vocabulary and blank nodes.

Database Technologies for RDF

Souripriya Das

Efficient and scalable support for RDF/OWL data storage, loading, inferencing and querying, in conjunction with already available support for enterprise level data and operations reliability requirements, can make databases suitable to act as enterprise-level RDF/OWL repository and hence become a viable platform for building semantic applications for the enterprise environments. This tutorial outlines the requirements for supporting semantic technologies in databases including bulk load and DML, inference based on RDFS, OWL and user-defined rules, and support for SPARQL queries, discusses the design choices for handling issues that arise in implementing support for storage and operations on large scale RDF/OWL data, and in general, touches upon the practical aspects related to RDF/OWL support that become important in enterprise environments. Semantic technologies support in Oracle Database is used as a case study to illustrate with concrete examples the key requirements and design issues.

Answer Set Programming: A Primer

Thomas Eiter, Giovambattista Ianni, Thomas Krennwallner

Answer Set Programming (ASP) is a nowadays mature declarative modelling paradigm: it is based on sound theoretical foundations, features versatile, interoperable and efficient solvers, and has been applied successfully in a variety of contexts. The relationship of ASP with the Semantic Web, and in particular with the Ontology and Rule layers, arises in a variety of aspects: ASP has been proposed as the semantics of choice for defining a formalism for the Rule Layer, with proper capabilities of interacting and reasoning on top of ontologies. Likewise, it has been shown that ASP can be exploited as a middleware formalism, to which ontologies can be translated to. For solving reasoning tasks on translated ontologies, it is then possible to take advantage of existing, advanced, computing methodologies for ASP. The purpose of this lecture is to familiarise the audience with the Answer Set Programming (ASP) Paradigm in the perspective of its fruitful usage for Semantic Web applications. We introduce the attendees to the ASP basics, its modelling methodology and its principal extensions tailored for Semantic Web applications. We discuss the current impact of Answer Set Programming in the Semantic Web Area and possible future directions. Applications and examples are presented. The attendees will practice through an online interface using one of the state-of-the-art ASP solvers and some of its extensions.

Technologies for the Social Semantic Desktop

Siegfried Handschuh, Michael Sintek

The first part of the will be about the vision of the Social Semantic Desktop, which defines a user's personal information environment as a source and end-point of the Semantic Web: Knowledge workers comprehensively express their information and data with respect to their own conceptualizations. This part covers also the aspects of social semantics and meta-data creation. The second part will be about the Semantic Web languages and protocols that are used to formalize these conceptualizations and for coordinating local and global information access. Two main challenges come into focus: i) How can we cope with the heterogeneity of knowledge models and ontologies, esp. multiple knowledge modules with potentially different interpretations? ii) How can we support the tailoring of ontologies towards different needs in various exploiting applications? The lecture will present an approach that is based on named graphs for the modularization aspect and a view concept (supported by reasoning) for the tailoring of ontologies.

Logical foundations of XML and XQuery

Maarten Marx

XML is the underlying representation formalism of much web-data. Thus to reason about web-data essentially boils down to reasoning about data in XML format. In this course the students learn about languages for constraining and querying XML data. It consists of 3 parts: (1) (theory) traditional logical results ---expressivity, complexity, axiomatizations--- about the core language of XML: XPath; (2) (theory and practice) modelling data in XML and constraining it using DTD, XSchema and Relax NG; and (3) (practical) XML-ification.