Axel Polleres

In SPARQL queries, the combination of triple patterns is expressed by using shared variables across patterns. Based on this characterization, basic graph patterns in a SPARQL query can be partitioned into groups of acyclic pattern combinations that share exactly one variable, or star-shaped groups. We observe that the number of triples in a group is proportional to the number of individuals that play the role of the subject or the object; however, depending on the degree of participation of the subject individuals in the properties, a group could be not much larger than a class or type to which the subject or object belongs. Thus, it may be significantly more efficient to independently evaluate each of the groups, and then merge the resulting sets, than linearly joining all triples in a basic graph pattern. Based on these properties of star-shaped groups, we have developed query optimization and evaluation techniques. We have conducted an empirical analysis on the benefits of the optimization and evaluation techniques in several SPARQL query engines. We observe that our proposed techniques are able to speed up query evaluation time for join queries with star-shaped patterns by at least one order of magnitude.

Typical approaches for search and querying over structured Web Data collect (crawl) and pre-process (index) large amounts of data before allowing for query answering in a central data warehouse. This time-consuming pre-processing phase decreases the freshness of query results and only uses to a limited degree the benefits of Linked Data where structured data is accessible live and up-to-date at distributed Web resources that may change constantly. An ideal query answering system for Linked Data should return always current answers in a reasonable amount of time, even on corpora as large as the web. Query processors evaluating queries directly on the life sources require knowledge of the contents of data sources. In the current paper we develop and evaluate a probabilistic index structure for covering graph-structured content of sources adhering to Linked Data principles, provide an algorithm for answering conjunctive queries over Linked Data on the web exploiting this structure, and evaluate the system using synthetically generated queries. We find that our lightweight index structure enable more complete query results over Linked Data compared to direct lookup approaches, while keeping the overhead for additional lookups and index maintenance low.

The need for semantics preserving integration of complex data has been widely recognized in the healthcare domain. While standards such as Health Level Seven (HL7) have been developed in this direction, they have mostly been applied in limited, controlled environments, still being used incoherently across countries, organizations, or hospitals. In a more mobile and global society, data and knowledge are going to be commonly exchanged between various systems at Web scale. Specialists in this domain have increasingly argued in favor of using Semantic Web technologies for modeling healthcare data in a well formalized way. This paper provides a reality check in how far current Semantic Web standards can tackle interoperability issues arising in such systems driven by the modeling of concrete use cases on exchanging clinical data and practices. Recognizing the insufficiency of standard OWL to model our scenario, we survey theoretical approaches to extend OWL by modularity and context towards handling heterogeneity in Semantic-Web-enabled health care and life sciences (HCLS) systems. We come to the conclusion that none of these approaches addresses all of our use case heterogeneity aspects in its entirety. We finally sketch paths on how better approaches could be devised by combining several existing techniques.

This book constitutes the refereed proceedings of the Third International Conference on Web Reasoning and Rule Systems, RR 2009, held in Chantilly, VA, USA, in October 2009. The 15 revised full papers presented together with 3 invited papers were carefully reviewed and selected from 41 submissions. The papers address all current topics in Web reasoning and rule systems such as proof/deduction procedures, scalability, uncertainty, knowledge amalgamation and querying, and rules for decision support and production systems.

RDF Schema (RDFS) as a lightweight ontology language is gaining popularity and, consequently, tools for scalable RDFS inference and querying are needed. SPARQL has become recently a W3C standard for querying RDF data, but it mostly provides means for querying simple RDF graphs only, whereas querying with respect to RDFS or other entailment regimes is left outside the current specification. In this paper, we show that SPARQL faces certain unwanted ramifications when querying ontologies in conjunction with RDF datasets that comprise multiple named graphs, and we provide an extension for SPARQL that remedies these effects. Moreover, since RDFS inference has a close relationship with logic rules, we generalize our approach to select a custom ruleset for specifying inferences to be taken into account in a SPARQL query. We show that our extensions are technically feasible by providing benchmark results for RDFS querying in our prototype system , which uses Datalog coupled with a persistent Relational Database as a back-end for implementing SPARQL with dynamic rule-based inference. By employing different optimization techniques like magic set rewriting our system remains competitive with state-of-the-art RDFS querying systems.

Currently a large number of Web sites are driven by Content Management Systems (CMS) which manage textual and multimedia content but also - inherently - carry valuable information about a site's structure and content model. Exposing this structured information to the Web of Data has so far required considerable expertise in RDF and OWL modelling and additional programming effort. In this paper we tackle one of the most popular CMS: Drupal. We enable site administrators to export their site content model and data to the Web of Data without requiring extensive knowledge on Semantic Web technologies. Our modules create RDFa annotations and - optionally - a SPARQL endpoint for any Drupal site out of the box. Likewise, we add the means to map the site data to existing ontologies on the Web with a search interface to find commonly used ontology terms. We also allow a Drupal site administrator to include existing RDF data from remote SPARQL endpoints on the Web in the site. When brought together, these features allow networked RDF Drupal sites that reuse and enrich Linked Data. We finally discuss the adoption of our modules and report on a use case in the biomedical field and the current status of its deployment.

The Multi-Agent Logics, Languages, and Organisations Federated Workshops (MALLOW for short), in its second edition this year after the success of MALLOW’007 held in Durham (UK), is a forum for researchers interested in sharing their experiences in agents and multi-agent systems. MALLOW’009 was held at the Educatorio della Provvidenza, in Torino (Italy), from September 7th, 2009 through September 10th, 2009. This volume contains the proceedings of the five workshops, for a total of forty-seven high quality papers, which were selected by the programme committees of the workshops for presentation. Each workshop has an introductory essay, authored by the organizers, which presents the workshop.

Workshop Proceedings. This workshop was co-located with ESWC 2009.

A large number of web sites are driven by content management systems (CMS), which manage not only textual content but also structured data related to the site's topic. Exposing this information to the Web of Data has so far required considerable expertise in RDF modelling and programming. We present a plugin for the popular CMS Drupal that enables high-quality RDF output with minimal effort from site administrators. This has the potential of greatly increasing the amount and topical range of information available on the Web of Data.

In this demo we present GiaBATA, a system for storing, aggregating, and querying Semantic Web data, based on declarative logic programming technology, namely on the dlvhex system, which allows us to implement a fully SPARQL compliant semantics, and on DLVDB , which extends the DLV system with persistent storage capabilities. Compared with off-the-shelf RDF stores and SPARQL engines, we offer more flexible support for rule-based RDFS and other higher entailment regimes by enabling custom reasoning via rules, and the possibility to choose the reference ontology on a per query basis. Due to the declarative approach, GiaBATA gains the possibility to apply well-known logic-level optimization features of logic programming (LP) and deductive database systems. Moreover, our architecture allows for extensions of SPARQL by non-standard features such as aggregates, custom built-ins, or arbitrary rulesets. With the resulting system we provide a flexible toolbox that embeds Semantic Web data and ontologies in a fully declarative LP environment.

The use of RDF data published on the Web for applications is still a cumbersome and resource-intensive task due to the limited software support and the lack of standard programming paradigms to deal with everyday problems such as combination of RDF data from different sources, object identifier consolidation, ontology alignment and mediation or plain querying and processing tasks. While in a lot of other areas such tasks are supported by excellent libraries and component-oriented toolboxes of basic processing functionalities, RDF-based Web applications are still largely customized programs for a specific purpose, with little potential for reuse. This increases development costs and incurs a more error-prone development process. Speaking in software engineering terms, this means that a good standard architectural style with good support for rapid application development is still missing. In this paper we present a framework based on the classical abstraction of pipes which tries to remedy this problem and support the fast implementation of software, while preserving desirable properties such as abstraction, encapsulation, component-orientation, code re-usability and maintainability, which are common and well supported in other application areas.

Based on our recent observations at the 7th International Semantic Web Conference and some related workshops as the Social Data on The Web one [1], as well as other frequent discussion threads on the Web, trust and privacy on the Social Web remains a hot, yet unresolved topic. Indeed, while Web 2.0 helped people to easily produce data, it lead to various issues regarding how to protect and trust this data, especially when it comes to personal data. On the one hand, we are wondering how to protect our private information online, above all when this information is re-used at our disadvantage. On the other hand, information should not only be protected when being published by its owners, but tools should also help users to assess trustworthiness of third-party information online. According to our recent research works, both from a theoretical and practical point of view, we think that Semantic Web technologies can provide at least partial solutions to enable a 'trust and privacy layer' on top of the Social Web. Hence, this position paper will present our work on the topic, that is in our opinion, also particularly relevant to the mobile Web community, according to the advances of ubiquitous Social Networking with, e.g., microblogging from mobile devices.

Sensors have begun to infiltrate people's everyday lives. They can provide information about a car's condition, can enable smart buildings, and are being used in various mobile applications, to name a few. Generally, sensors provide information about various aspects of the real world. Online social networks, another emerging trend over the past six or seven years, can provide insights into the communication links and patterns between people. They have enabled novel developments in communications as well as transforming the Web from a technical infrastructure to a social platform, very much along the lines of the original Web as proposed by Tim Berners-Lee, which is now often referred to as the Social Web. In this position paper, we highlight some of the interesting research areas where sensors and social networks can fruitfully interface, from sensors providing contextual information in context-aware and personalized social applications, to using social networks as storage infrastructures for sensor information.

XSPARQL is a query language combining XQuery and SPARQL for transformations between RDF and XML. XSPARQL subsumes XQuery and most of SPARQL (excluding ASK and DESCRIBE). This document defines the XSPARQL language.

XSPARQL is a query language combining XQuery and SPARQL for transformations between RDF and XML. This document defines the semantics of XSPARQL.

XSPARQL is a query language combining XQuery and SPARQL for transformations between RDF and XML. This document provides a description of a prototype implementation of the language based on off-the-shelf XQuery and SPARQL engines. Along with a high-level description of the prototype the document presents a set of test queries and their expected output which are to be understood as illustrative help for possible other implementers.

XSPARQL is a query language combining XQuery and SPARQL for transformations between RDF and XML. This document contains an overview of XSPARQL use cases within various scenarios.

In this paper we discuss the challenges of performing reasoning on large scale RDF datasets from the Web. Using ter-Horst's pD* fragment of OWL as a base, we compose a rule-based framework for application to web data: we argue our decisions using observations of undesirable examples taken directly from the Web. We further temper our OWL fragment through consideration of authoritative sources which counter-acts an observed behaviour which we term ontology hijacking: new ontologies published on the Web re-defining the semantics of existing entities resident in other ontologies. We then present our system for performing rule-based forward-chaining reasoning which we call SAOR: Scalable Authoritative OWL Reasoner. Based upon observed characteristics of web data and reasoning in general, we design our system to scale: our system is based upon a separation of terminological data from assertional data and comprises of a lightweight in-memory index, on-disk sorts and file-scans. We evaluate our methods on a dataset in the order of a hundred million statements collected from real-world Web sources and present scale-up experiments on a dataset in the order of a billion statements collected from the Web.

Im vorliegenden Beitrag diskutieren wir Rahmenbedingungen zur Kombination, Wiederverwendung und Erweiterung bestehender RDF Vokabulare im Social Semantic Web. Hierbei konzentrieren wir uns auf das Anwendungsszenario des Auffindens und Bewerbens von Experten im Web oder Intranet. Wir präsentieren, wie RDF Vokabulare mit zunehmendem Verbreitungsgrad im Semantic Web einerseits und de facto Standardformate, die von täglich verwendeten Applikationen benutzt werden, andererseits (z.B. vCard, iCal oder Dublin Core) kombiniert werden können, um konkrete Awendungsfälle der Expertensuche und zum Management von Expertise zu lösen. Unser Fokus liegt darauf aufzuzeigen, dass für praktische Anwendungsszenarien nicht notwendigerweise neue Ontologien entwickelt werden müssen, sondern der Schlüssel vielmehr in der Integration von bestehenden, weit verbreiteten, und sich ergänzenden Formaten zu einem kohärenten Netzwerk von Ontologien liegt. Dieser Ansatz garantiert sowohl direkte Anwendbarkeit als auch niedrige Einstiegsbarrieren für Semantic Web Technologien, sowie einfache Integrierbarkeit in bestehende Applikationen. Die im Web verfügbaren und verwendeten RDF Formate decken zwar einen großen Bereich der Aspekte zur Beschreibung von Personen und Expertisen ab, zeigen aber auch signifikante Überlappungen. Bisher gibt es wenig systematische Ansätze, um diese Vokabulare zu verbinden, sei es in Form von allgemeingültigen Praktiken, die definieren, wann welches Format zu benutzen ist, oder in Form von Regeln, die Überlappungen zwischen einzelnen Formaten formalisieren. Der vorliegende Artikel analysiert, wie bestehende Formate zur Beschreibung von Personen, Organisationen und deren Expertise kombiniert und wo nötig erweitert werden können. Darüber hinaus diskutieren wir Regelsprachen zur Beschreibung von Formatüberlappungen, sowie deren praktische Verwendbarkeit zur Erstellung eines Ontologie-Netzwerks zur Beschreibung von Experten.

Workshop Proceedings. This workshop was co-located with ICLP 2008.

Logic Programming paradigms that allow for expressing preferences have drawn a lot of research interest over the last few years. Among them, the principle of ordered disjunction was developed to express totally ordered preferences for the alternatives in rule heads. In this paper we introduce an extension of this approach called Disjunctive Logic Programs with Ordered Disjunction (DLPOD) that combines ordered disjunction with common disjunction in rule heads. By this extension, we enhance the preference notions expressible with totally ordered disjunctions to partially ordered preferences. Furthermore, we show that computing optimal stable models for DLPODs still stays in Σ₂^p for head-cycle free programs and establish Σ₃^p upper bounds for the general case.

In this paper we discuss the challenges of performing reasoning on large scale RDF datasets from the Web. We discuss issues and practical solutions relating to reasoning over web data using a rule-based approach to forward-chaining; in particular, we identify the problem of ontology hijacking: new ontologies published on the Web re-defining the semantics of existing concepts resident in other ontologies. Our solution introduces consideration of authoritative sources. Our system is designed to scale, comprising file-scans and selected lightweight on-disk indices. We evaluate our methods on a dataset in the order of a hundred million statements collected from real-world Web sources.

We propose to extend the SPARQL query language to express mapping between ontologies. We use SPARQL queries as a mechanism for translating RDF data of one ontology to another. Such functionality lets users exploit instance data described in one ontology while they work with an application that’s been designed for another. An example translation of FOAF (friend-of-a-friend) files into vCards shows how to use queries to extract data from the source ontology and generate new data for the target ontology.

Workshop Proceedings. This workshop was co-located with ISWC 2008. The Semantic Web, Social Networks and other emerging technology streams promise to enable finding experts more efficiently on a Web scale across boundaries. To leverage synergies among these streams, the ExpertFinder Initiative started in 2006 with the aim of devising vocabularies, rule extensions (for e.g. FOAF and SIOC) and best practices to annotate and extract expertise-relevant information from personal and organizational web pages, blogs, wikis, conferences, publication indexes, etc. Following two previous workshops - EFW and FEWS - PICKME2008 solocited new research contributions from the Semantic Web community towards the tasks of formally representing and reusing knowledge of skills and collaborations on the Web and consequently finding people according to their expertise.

The Sindice Semantic Web index provides search capabilities over today more than 30 million documents. A scalable reasoning mechanism for real-world web data is important in order to increase the precision and recall of the Sindice index by inferring useful information (e.g. RDF Schema features, equality, property characteristic such as inverse functional properties or annotation properties from OWL). In this paper, we introduce our notion of context dependent reasoning for RDF documents published on the Web according to the linked data principle. We then illustrate an efficient methodology to perform context dependent RDFS and partial OWL inference based on a persistent TBox composed of a network of web ontologies. Finally we report preliminary evaluation results of our implementation underlying the Sindice web data index.

Whereas the number of services that are provided online is growing rapidly, current service discovery approaches seem to have problems fulfilling their objectives. These existing approaches are hampered by the complexity of underlying semantic service models and by the fact that they try to impose a technical vocabulary to users. This leads to what we call the service discovery gap. In this paper we envision an approach that allows users first to query or browse services using free text tags, thus providing an interface in terms of the users' vocabulary instead of the service's vocabulary. Unlike simple keyword search, we envision tag clouds associated with services themselves as semantic descriptions carrying collaborative knowledge about the service that can be clustered hierarchically, forming lightweight ``ontologies''. Besides tag-based discovery only describing the service on a global view, we envision refined tags and refined search/discovery in terms of the concepts that are common to all current semantic service description models, i.e. input, output, and operation. We argue that Service matching can be achieved, by applying tag-cloud-based service similarity on the one hand and by clustering services using case based indexing and retrieval techniques on the other hand.

The Reasoning Web summer school series is a well-established event, attracting experts from academy and industry as well as PhD students interested in foundational and applicative aspects of the Semantic Web. This volume contains the lecture notes of the fourth edition, that took place in Venice, Italy, in September 2008. This year, the school has been focussed on some important application domains where semantic web techniques proved to be particularly effective or promising in tackling application needs.

The objective of the international workshop series on cooperative information agents (CIA), since its establishment in 1997, is to provide a distinguished, interdisciplinary forum for researchers, programmers, and managers to get informed about, present, and discuss latest high quality results in research and development of agent-based intelligent and cooperative information systems, and applications for the Internet, Web and Semantic Web. Each event of the series offers regular and invited talks of excellence that are given by renown experts in the field, a selected set of system demonstrations, and honors innovative research and development of information agents by means of a best paper award, and respectively, a system innovation award. The proceedings of the series are regularly published as volumes of the Lecture Notes in Artificial Intelligence (LNAI) series of the Springer Verlag. In keeping with its tradition, this year's workshop featured a sequence of regular and invited talks of excellence given by leading researchers covering a broad area of topics of interest. In particular, CIA 2008 featured five invited and nineteen regular papers selected from thirty-eight submissions. The result of the peer-review of all contributions is included in this volume that is, as we think, again rich of interesting, inspiring, and advanced work on research and development of intelligent information agents worldwide.

Rules and ontologies play a key role in the layered architecture of the Semantic Web, as they are used to ascribe meaning to, and to reason about, data on the Web. 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 an active area of research; a number of initiatives and proposals have been made so far, but no standard as been released yet. Many implementations of rule engines are around which deal with Semantic Web data in one or another way. This article gives a comprehensive, although not exhaustive, overview of such systems, describes their supported languages, and sets them in relation with theoretical approaches for combining rules and ontologies as foreseen in the Semantic Web architecture. In the course of this, we identify desired properties and common features of rule languages and evaluate existing systems against their support. Furthermore, we review technical problems underlying the integration of rules and ontologies, and classify representative proposals for theoretical integration approaches into different categories.

Participants in current team collaborations belong to different organizations, work on multiple objectives at the same time, and frequently change locations. They use different devices and infrastructures in collaboration processes that can last from a few hours to several years. All these factors pose new challenges to the development of collaborative working environments (CWEs). Existing CWEs are unable to support emerging teams because diverse collaboration services are not well integrated or adapting to the team context. We present the inContext approach to providing a novel pervasive CWE infrastructure for emerging team forms. inContext aggregates disparate collaboration services using Web services and Semantic Web technologies and provides a platform that captures diverse dynamic aspects of team collaborations. By utilizing runtime and historical context and interaction information, adaptation techniques can be deployed to cope with the changes of emerging teams.

With currently available tools and languages, translating between an existing XML format and RDF is a tedious and error-prone task. The importance of this problem is acknowledged by the W3C GRDDL working group who faces the issue of extracting RDF data out of existing HTML or XML files, as well as by the Web service community around SAWSDL, who need to perform lowering and lifting between RDF data from a semantic client and XML messages for a Web service. However, at the moment, both these groups rely solely on XSLT transformations between RDF/XML and the respective other XML format at hand. In this paper, we propose a more natural approach for such transformations based on merging XQuery and SPARQL into the novel language XSPARQL. We demonstrate that XSPARQL provides concise and intuitive solutions for mapping between XML and RDF in either direction, addressing both the use cases of GRDDL and SAWSDL. We also provide and describe an initial implementation of an XSPARQL engine, available for user evaluation.

We introduce domain-restricted RDF (dRDF) which allows to associate an RDF graph with a fixed, finite domain that interpretations for it may range over. We show that dRDF is a real extension of RDF and discuss impacts on the complexity of entailment in dRDF. The entailment problem represents the key reasoning task for RDF and is well known to be NP-complete. Remarkably, we show that the restriction of domains in dRDF raises the complexity of entailment from NP- to Π^P₂-completeness. In order to lower complexity of entailment for both domain-restricted and unrestricted graphs, we take a closer look at the graph structure. For cases where the structure of RDF graphs is restricted via the concept of bounded treewidth, we prove that the entailment is tractable for unrestricted graphs and coNP-complete for domain-restricted graphs.

In this demo we present a first implementation of Semantic Web Pipes, a powerful tool to build RDF-based mashups. Semantic Web pipes are defined in XML and when executed they fetch RDF graphs on the Web, operate on them, and produce an RDF output which is itself accessible via a stable URL. Humans can also use pipes directly thanks to HTML wrapping of the pipe parameters and outputs. The implementation we will demo includes an online AJAX pipe editor and execution engine. Pipes can be published and combined thus fostering collaborative editing and reuse of data mashups.

Present team members have difficulties in keeping the relations between their various, concurrent activities due to the lack of suitable tools supporting context coupling and sharing. Furthermore, collaboration services are hardly aware of related context of team members and their activities. Such awareness is required to adapt to the dynamics of collaborative teams. In this paper, we discuss the context coupling techniques provided by the inContext project. Utilizing the concept of activity-based context and Web services techniques, we can couple individual and team contexts at runtime, thus improving the context-awareness and adaptation of collaboration services such as email, shared calendars, instant messaging and document management.

Solving problems raised by heterogeneous ontologies can be achieved by matching the ontologies and processing the resulting alignments. This is typical of data mediation in which the data must be translated from one knowledge source to another. In this position paper we propose to solve the data translation problem, i.e. the processing part, using the SPARQL query language. Indeed, such a language is particularly adequate for extracting data from one ontology and, through its CONSTRUCT statement, for generating new data. We present examples of such transformations, but we also present a set of example correspondences illustrating the needs for particular representation constructs, such as aggregates, value-generating built-in functions and paths, which are missing from SPARQL. Hence, we advocate the use of two SPARQL extensions providing these missing features.

In the ongoing discussion about combining rules and Ontologies on the Semantic Web a recurring issue is how to combine first-order classical logic with nonmonotonic rule languages. Whereas several modular approaches to define a combined semantics for such hybrid knowledge bases focus mainly on decidability issues, we tackle the matter from a more general point of view. In this paper we show how Quantified Equilibrium Logic (QEL) can function as a unified framework which embraces classical logic as well as disjunctive logic programs under the (open) answer set semantics. In the proposed variant of QEL we relax the unique names assumption, which was present in earlier versions of QEL. Moreover, we show that this framework elegantly captures the existing modular approaches for hybrid knowledge bases in a unified way.

In this paper we take a view from the bottom to RDF(S) reasoning. We discuss some issues and requirements on reasoning towards effectively building Semantic Web Pipes, aggregating and patching RDF data from various distributed sources. Even if we leave out complex description logics reasoning and restrict ourselves to the RDF world, it turns out that some problems, in particular how to deal with contradicting RDF statements and patching RDF graphs, do not yet find their proper solutions within the current Semantic Web Stack. Besides theoretical solutions which involve full DL reasoning, we believe that more practical and probably more scalable solutions are conceivable one of which we discuss in this paper. Namely, we provide means to express revocations in RDF and resolve such revocations by means of a specialized RDF merge procedure. We have implemented this conflict-resolving merge procedure in the DBin 2.0 system.

In this position paper we firstly present the established notion of provenance on the Semantic Web (also referred to as named graphs or contexts), and secondly argue for the benefit of adding to the pure technical notion of provenance a social dimension to associate provenance with the originator (typically a person) of a given piece of information.

Lightweight ontologies in the form of RDF vocabularies such as SIOC, FOAF, vCard, etc. are increasingly being used and exported by ``serious'' applications recently. Such vocabularies, together with query languages like SPARQL also allow to syndicate resulting RDF data from arbitrary Web sources and open the path to finally bringing the Semantic Web to operation mode. Considering, however, that many of the promoted lightweight ontologies overlap, the lack of suitable standards to describe these overlaps in a declarative fashion becomes evident. In this paper we argue that one does not necessarily need to delve into the huge body of research on ontology mapping for a solution, but itself might - with extensions such as external functions and aggregates - serve as a basis for declaratively describing ontology mappings. We provide the semantic foundations and a path towards implementation for such a mapping language by means of a translation to Datalog with external predicates.

In this paper we take a view from the bottom to RDF(S) reasoning. We discuss some issues and requirements on reasoning towards effectively building Semantic Web Pipes, aggregating RDF data from various distributed sources. If we leave out complex description logics reasoning and restrict ourselves to the RDF world, it turns out that some problems, in particular how to deal with contradicting RDF statements, do not yet find their proper solutions within the current Semantic Web Stack. Besides theoretical solutions which involve full DL reasoning, we believe that more practical and probably more scalable solutions are conceivable one of which we discuss in this paper, namely, expressing and resolving conflicting RDF statements by means of a specialized RDF merge procedure. We implemented this conflict-resolving merge procedure in the DBin system.

Workshop Proceedings. This workshop was co-located with ISWC 2007 + ASWC 2007.

Several description frameworks to semantically describe and match services on the one hand and service requests on the other have been presented in the literature. Many of the current proposals for defining notions of match between service advertisements and requests are based on subsumption checking in more or less expressive Description Logics, thus providing boolean match functions, rather than a fine-grained, numerical degree of match. By contrast, concept similarity measures investigated in the DL literature explicitely include such a quantitative notion. In this paper we try to take a step forward in this area by means of an analysis of existing approaches from both semantic web service matching and concept similarity, and provide preliminary ideas on how to combine these two building blocks in a unified service selection framework.

Workshop Proceedings. This workshop was co-located with ICLP 2007.

This paper describes the dlvhex SPARQL plugin, a query processor for the upcoming Semantic Web query language standard by W3C. We report on the implementation of this languages using dlvhex, a flexible plugin system on top of the DLV solver. This work advances our earlier translation based on the semantics by Perez et al. towards an engine which is fully compliant to the official SPARQL specification. As it turns out, the differences between these two definitions of SPARQL, which might seem moderate at first glance, need some extra machinery. We also briefly report the status of implementation, and extensions currently being implemented, such as handling of aggregates, nested CONSTRUCT queries in the spirit of networked RDF graphs, or partially support of RDFS entailment. For such extensions a tight integration of SPARQL query processing and Answer-Set Programming, the underlying logic programming formalism of our engine, turns out to be particularly useful, as the resulting programs can actually involve unstratified negation.

Rules play an increasingly important role in a variety of Semantic Web applications as well as in traditional IT systems. As a universal medium for publishing information, the Web is envisioned to become the place for publishing, distributing, and exchanging rule-based knowledge. Realizing the importance and the promise of this vision, the W3C has created the Rule Interchange Format Working Group (RIF WG) and chartered it to develop an interchange format for rules in alignment with the existing standards in the Semantic Web architecture stack. However, creating a generally accepted interchange format is by no means a trivial task. First, there are different understandings of what a ``rule'' is. Researchers and practitioners distinguish between deduction rules, normative rules, production rules, reactive rules, etc. Second, even within the same category of rules, systems use different (often incompatible) semantics and syntaxes. Third, existing Semantic Web standards, such as RDF and OWL, show incompatibilities with many kinds of rule languages at a conceptual level. This article discusses the role that different kinds of rule languages and systems play on the Web, illustrates the problems and opportunities in exchanging rules through a standardized format, and provides a snapshot of the current work of the W3C RIF WG.

The SIOC (Semantically-Interlinked Online Communities) Core Ontology provides the main concepts and properties required to describe information from online communities (e.g., message boards, wikis, weblogs, etc.) on the Semantic Web. This document contains a detailed description of the SIOC Core Ontology.

In the ongoing discussion about combining rules and Ontologies on the Semantic Web a recurring issue is how to combine first-order classical logic with nonmonotonic rule languages. Whereas several modular approaches to define a combined semantics for such hybrid knowledge bases focus mainly on decidability issues, we tackle the matter from a more general point of view. In this paper we show how Quantified Equilibrium Logic (QEL) can function as a unified framework which embraces classical logic as well as disjunctive logic programs under the (open) answer set semantics. In the proposed variant of QEL we relax the unique names assumption, which was present in earlier versions of QEL. Moreover, we show that this framework elegantly captures the existing modular approaches for hybrid knowledge bases in a unified way.

This paper presents a framework for the reuse and extension of existing, established vocabularies in the Semantic Web. Driven by the primary application of expert finding, we will explore the reuse of vocabularies that have attracted a considerable user community already (FOAF, SIOC, etc.) or are derived from de facto standards used in tools or industrial practice (such as vCard, iCal and Dublin Core). This focus guarantees direct applicability and low entry barriers, unlike when devising a new ontology from scratch. The Web is already populated with several vocabularies which complement each other (but also have considerable overlap) in that they cover a wide range of necessary features to adequately describe the expert finding domain. Little effort has been made so far to identify and compare existing approaches, and to devise best practices on how to use and extend various vocabularies conjointly. It is the goal of the recently started ExpertFinder initiative to fill this gap. In this paper we present the ExpertFinder framework for reuse and extension of existing vocabularies in the Semantic Web. We provide a practical analysis of overlaps and options for combined use and extensions of several existing vocabularies, as well as a proposal for applying rules and other enabling technologies to the expert finding task.

Tutorial at the 4th European Semantic Web Conference (ESWC2007)

This position paper raises some issues regarding the output of solvers for Answer Set Programming and discusses experiences made in several different settings. The first set of issues was raised in the context of the first ASP system competition, which led to a first suggestion for a standardised yet miniature output format. We then turn to experiences made in related fields, like Satisfiability Checking, and finally adopt an application point of view by investigating interface issues both with simple tools and in the context of the Semantic Web and query answering.

Workshop Proceedings. This workshop was co-located with LPNMR 2007.

As the data and ontology layers of the Semantic Web stack have achieved a certain level of maturity in standard recommendations such as RDF and OWL, the current focus lies on two related aspects. On the one hand, the definition of a suitable query language for RDF, SPARQL, is close to recommendation status within the W3C. The establishment of the rules layer on top of the existing stack on the other hand marks the next step to be taken, where languages with their roots in Logic Programming and Deductive Databases are receiving considerable attention. The purpose of this paper is threefold. First, we discuss the formal semantics of SPARQL extending recent results in several ways. Second, we provide translations from SPARQL to Datalog with negation as failure. Third, we propose some useful and easy to implement extensions of SPARQL, based on this translation. As it turns out, the combination serves for direct implementations of SPARQL on top of existing rules engines as well as a basis for more general rules and query languages on top of RDF.

Web Services have added a new level of functionality to the current Web, making the first step to achieve seamless integration of distributed components. Nevertheless, current Web Service technologies only address the syntactical aspects of a Web Service and, therefore, only provide a set of rigid services that cannot adapt to a changing environment without human intervention. The human programmer has to be kept in the loop and scalability as well as economy of Web Services are limited. The description of Web Services in a machine-understandable fashion is expected to have a great impact in areas of e-Commerce and Enterprise Application Integration, as it can enable dynamic and scalable cooperation between different systems and organisations. These great potential benefits have led to the establishment of an important research activity, both in industry and in academia, which aims at realising Semantic Web Services. This chapter outlines aspects of the description of semantic Web Services.

This position paper on expert finding presents a conceptual framework for the reuse and interlinking of existing, well-established vocabularies in the Semantic Web. Such a framework can be used to connect people with people, based on joint or complementing interests (e.g. the need to develop specific new or existing skills for upcoming projects). Driven by a requirement to find experts using the profiles of people in social networks and using the content they create in online communities, we are exploring the usage of vocabularies in these domains that have already gained considerable momentum and that have suitable concepts for this application area. We will present the relevant properties of the FOAF ontology for matching people and their skills in social networks, then detail the SIOC project and methods for identifying relevant discussion topics/individuals, and finally we will outline a combinatory scenario that will allow people to find individuals with the desired expertise in a particular domain of interest.

In the context of the Semantic Web, several approaches to the combination of ontologies, given in terms of theories of classical first-order logic, and rule bases have been proposed. They either cast rules into classical logic or limit the interaction between rules and ontologies. Autoepistemic logic (AEL) is an attractive formalism which allows to overcome these limitations, by serving as a uniform host language to embed ontologies and nonmonotonic logic programs into it. For the latter, so far only the propositional setting has been considered. In this paper, we present several embeddings of normal and disjunctive non-ground logic programs under the stable-model semantics into first-order AEL, and compare them in combination with classical theories, with respect to stable expansions and autoepistemic consequences. Our results reveal differences and correspondences of the embeddings and provide a useful guidance in the choice of a particular embedding for knowledge combination.

In the ongoing discussion about rule extensions for Ontology languages on the Semantic Web a recurring issue is how to combine first-order classical logic with nonmonotonic rule languages. Whereas several modular approaches to define a combined semantics for such hybrid knowledge bases focus mainly on decidability issues, we tackle the matter from a more general point of view. In this paper we show how Quantified Equilibrium Logic (QEL) can function as a unified framework that embraces classical logic as well as disjunctive logic programs under the (open) answer set semantics. In the proposed variant of QEL we relax the unique names assumption from earlier versions. Moreover, we show that this framework elegantly captures several modular approaches to nonmonotonic semantics for hybrid knowledge bases.

As the data and ontology layers of the Semantic Web stack have achieved a certain level of maturity in standard recommendations such as RDF and OWL, the current focus lies on two related aspects. On the one hand, the definition of a suitable query language for RDF, SPARQL, has just reached candidate recommendation status within the W3C. The establishment of the rules layer on top of the existing stack on the other hand marks the next step to be tackled, where especially languages with their roots in Logic Programming and Deductive Databases are receiving considerable attention. In this work we try to bridge the gap between these two efforts by providing translations between SPARQL and Datalog extended with negation and external built-in predicates. It appears that such a combination serves both as an underpinning for a more general rules and query language on top of RDF and SPARQL as well as for direct implementations of SPARQL on top of existing rules engines. Our prototype implementation is based on the datalog engine DLV. As it turns out, features of the language of this system can be fruitfully combined with SPARQL.

For realizing the Semantic Web vision, extensive work is underway for getting the layers of its conceived architecture ready. Given that the Ontology Layer has reached a certain level of maturity with W3C recommendations such as RDF and the OWL Web Ontology Language, current interest focuses on the Rules Layer and its integration with the Ontology Layer. Several proposals have been made for solving this problem, which does not have a straightforward solution due to various obstacles. One of them is the fact that evaluation principles like the closed-world assumption, which is common in rule languages, are usually not adopted in ontologies. Furthermore, naively adding rules to ontologies raises undecidability issues. In this paper, after giving a brief overview about the current state of the Semantic-Web stack and its components, we will discuss nonmonotonic logic programs under the answer-set semantics as a possible formalism of choice for realizing the Rules Layer. We will briefly discuss open issues in combining rules and ontologies, and survey some existing proposals to facilitate reasoning with rules and ontologies. We will then focus on description-logic programs (or dl-programs, for short), which realize a transparent integration of rules and ontologies supported by existing reasoning engines, based on the answer-set semantics. We will further discuss a generalization of dl-programs, viz. HEX-programs, which offer access to different ontologies as well as higher-order language constructs.

Workshop Proceedings. This workshop was co-located with ICLP 2006.

In the context of current efforts around Semantic-Web languages, the combination of classical theories in classical first-order logic (and in particular of ontologies in various description logics) with rule languages rooted in logic programming is receiving considerable attention. Existing approaches such as SWRL, dl-programs, and DL+log, differ significantly in the way ontologies interact with (nonmonotonic) rules bases. In this paper, we identify fundamental representational issues which need to be addressed by such combinations and formulate a number of formal principles which help to characterize and classify existing and possible future approaches to the combination of rules and classical theories. We use the formal principles to explicate the underlying assumptions of current approaches. Finally, we propose a number of settings, based on our analysis of the representational issues and the fundamental principles underlying current approaches.

The Web Service Modeling Language (WSML) is a language for the specification of different aspects of Semantic Web Services. It provides a formal language for the Web Service Modeling Ontology WSMO which is based on well-known logical formalisms, specifying one coherent language framework for the description of Semantic Web Services, starting from the intersection of Datalog and the Description Logic SHIQ. This core language is extended in the directions of Description Logics and Logic Programming in a principled manner with strict layering. WSML distinguishes between conceptual and logical modeling in order to facilitate users who are not familiar with formal logic, while not restricting the expressive power of the language for the expert user. IRIs play a central role in WSML as identifiers. Furthermore, WSML defines XML and RDF serializations for inter-operation over the Semantic Web.

Knowledge representation formalisms used on the Semantic Web adhere to a strict open world assumption. Therefore, nonmonotonic reasoning techniques are often viewed with scepticism. Especially negation as failure, which intuitively adopts a closed world view, is often claimed to be unsuitable for the Web where knowledge is notoriously incomplete. Nonetheless, it was suggested in the ongoing discussions around rules extensions for languages like RDF(S) or OWL to allow at least restricted forms of negation as failure, as long as negation has an explicitly defined, finite scope. Yet clear definitions of such scoped negation as well as formal semantics thereof are missing. We propose logic programs with contexts and scoped negation and discuss two possible semantics with desirable properties. We also argue that this class of logic programs can be viewed as a rule extension to a subset of RDF(S).

Tutorial at the 3rd European Semantic Web Conference (ESWC2006)

In diesem Kapitel werden Anwendungsgebiete und Ansätze für die semantische Beschreibung von Web Services behandelt. Bestehende Web Service Technologien leisten einen entscheidenden Beitrag zur Entwicklung verteilter Anwendungen dadurch, dass weithin akzeptierte Standards vorliegen, die die Kommunikation zwischen Anwendungen bestimmen und womit deren Kombination zu komplexeren Einheiten erm öglicht wird. Automatisierter Mechanismen zum Auffinden geeigneter Web Services und deren Komposition dagegen werden von bestehenden Technologien in vergleichsweise geringem Mas unterstützt. Ähnlich wie bei der Annotation statischer Daten im Semantic Web setzen Forschung und Industrie grosse Hoffnungen in die semantischen Beschreibung von Web Services zur weitgehenden Automatisierung dieser Aufgaben.

The Semantic Web community is currently dominated by knowledge representation formalisms adhering to a strict open world assumption. Nonmonotonic reasoning formalisms are viewed with partial scepticism and it is often argued that nonmonotonic reasoning techniques which adopt a closed world assumption are invalid in an open environment such as the Web where knowledge is notoriously incomplete. Nonetheless, in the ongoing discussion about rule extensions for Semantic Web Languages like RDF(S) or OWL several proposals have been made to partly break with this view and to allow a restricted form of negation as failure. Recently, the term scoped negation emerged in discussions around this topic, yet a clear definition about the meaning of scope and scoped negation and a formal semantics are still missing. In this paper we provide preliminary results towards these missing definitions and define two possible semantics for logic programs with contextually scoped negation, which we propose as an extension of RDFS.

The goal of this book is to provide an insight into and an understanding of the problems faced by Web services and service-oriented architectures, as well as the promises and solutions of the Semantic Web. We focus particularly on the Web Service Modeling Ontology (WSMO), which provides a comprehensive conceptual framework for the fruitful combination of Semantic Web technologies and Web services. With the present book we want to give an overall understanding of the WSMO framework and show how it can be applied to the problems of service-oriented architectures. It is not a ready-to-install user manual for Semantic Web services that is provided with this book, but rather an in-depth introduction. While many of the related technologies and standards are still under development we nevertheless think it is not too early for such a book: it is important to create an awareness of this technology and think about it today rather than tomorrow. The technology might not be at an industrial strength maturity yet, but the problems are already.

Answer set programming (ASP) with disjunction offers a powerful tool for declaratively representing and solving hard problems. Many NP-complete problems can be encoded in the answer set semantics of logic programs in a very concise and intuitive way, where the encoding reflects the typical guess and check nature of NP problems: The property is encoded in a way such that polynomial size certificates for it correspond to stable models of a program. However, the problem-solving capacity of full disjunctive logic programs (DLPs) is beyond NP, and captures a class of problems at the second level of the polynomial hierarchy. While these problems also have a clear guess and check structure, finding an encoding in a DLP reflecting this structure may sometimes be a non-obvious task, in particular if the check itself is a coNP-complete problem; usually, such problems are solved by interleaving separate guess and check programs, where the check is expressed by inconsistency of the check program. In this paper, we present general transformations of head-cycle free (extended) disjunctive logic programs into stratified and positive (extended) disjunctive logic programs based on meta-interpretation techniques. The answer sets of the original and the transformed program are in simple correspondence, and, moreover, inconsistency of the original program is indicated by a designated answer set of the transformed program. Our transformations facilitate the integration of separate guess and check programs, which are often easy to obtain, automatically into a single disjunctive logic program. Our results complement recent results on meta-interpretation in ASP, and extend methods and techniques for a declarative guess and check problem solving paradigm through ASP.

Workshop Proceedings. This workshop was co-located with ICSOC 2005.