A Generic Module System forWeb Rule Languages: Divide and Rule

An essential feature in practically usable programming languages is the ability to encapsulate functionality in reusable modules. Modules make large scale projects tractable by humans. For Web and Semantic Web programming, many rule-based languages, e.g. XSLT, CSS, Xcerpt, SWRL, SPARQL, and RIF Core, have evolved or are currently evolving. Rules are easy to comprehend and specify, even for non-technical users, e.g. business managers, hence easing the contributions to the Web. Unfortunately, those contributions are arguably doomed to exist in isolation as most rule languages are conceived without modularity, hence without an easy mechanism for integration and reuse. In this paper a generic module system applicable to many rule languages is presented. We demonstrate and apply our generic module system to a Datalog-like rule language, close in spirit to RIF Core. The language is gently introduced along the EU-Rent use case. Using the Reuseware Composition Framework, the module system for a concrete language can be achieved almost for free, if it adheres to the formal notions introduced in this paper

Four Lessons in Versatility or How Query Languages Adapt to the Web

Exposing not only human-centered information, but machine-processable data on the Web is one of the commonalities of recent Web trends. It has enabled a new kind of applications and businesses where the data is used in ways not foreseen by the data providers. Yet this exposition has fractured the Web into islands of data, each in different Web formats: Some providers choose XML, others RDF, again others JSON or OWL, for their data, even in similar domains. This fracturing stifles innovation as application builders have to cope not only with one Web stack (e.g., XML technology) but with several ones, each of considerable complexity. With Xcerpt we have developed a rule- and pattern based query language that aims to give shield application builders from much of this complexity: In a single query language XML and RDF data can be accessed, processed, combined, and re-published. Though the need for combined access to XML and RDF data has been recognized in previous work (including the W3C’s GRDDL), our approach differs in four main aspects: (1) We provide a single language (rather than two separate or embedded languages), thus minimizing the conceptual overhead of dealing with disparate data formats. (2) Both the declarative (logic-based) and the operational semantics are unified in that they apply for querying XML and RDF in the same way. (3) We show that the resulting query language can be implemented reusing traditional database technology, if desirable. Nevertheless, we also give a unified evaluation approach based on interval labelings of graphs that is at least as fast as existing approaches for tree-shaped XML data, yet provides linear time and space querying also for many RDF graphs. We believe that Web query languages are the right tool for declarative data access in Web applications and that Xcerpt is a significant step towards a more convenient, yet highly efficient data access in a “Web of Data”

Web and Semantic Web Query Languages

A number of techniques have been developed to facilitate powerful data retrieval on the Web and Semantic Web. Three categories of Web query languages can be distinguished, according to the format of the data they can retrieve: XML, RDF and Topic Maps. This article introduces the spectrum of languages falling into these categories and summarises their salient aspects. The languages are introduced using common sample data and query types. Key aspects of the query languages considered are stressed in a conclusion

Logic, parallelism and semantic networks : the binary predicate execution model

This thesis develops the Binary Predicate Execution Model; a distributed, massively-parallel system for semantic networks and knowledge bases that is built on a subset of first-order predicate logic. The use of logic gives the model an easily-understood programming paradigm and a well-defined semantics of execution. When expressed in binary predicates, a simple graphical interpretation can be used. All program facts are represented in an assertion graph. Each vertex is associated with a term appearing in a fact and the edges are labeled with the predicate names. Similar graphs are also associated with each rule body and the query. Finding all possible solutions corresponds to finding all possible matches between the query graph and the assertion graph. Invoking a rule corresponds to substituting the graph of its body constrained by the dependencies between its arguments. This can be implemented in a parallel, message-passing fashion where the assertion graph vertices are active processing elements which asynchronously exchange messages identifying different parts of the query that remain to be matched and containing any binding information from previous matching required to accomplish this. The model is data-driven since every message can be immediately processed without the need for any centralized control or centralized memory. By restricting how functional terms can occur, distributed data structures and remote data look-ups for unification are eliminated. Thus, the model's performance on increasingly larger problems scales-up given increasingly larger machines in most cases. Architectural support for the model is investigated and simulation results of a relatively simple software implementation are reported. This suggests performance on the order of 10^5 logical inferences per second for 256 processing elements in an n-cube configuration. Further research directions, including that of increasing efficiency, are discussed

Data Integration on the (Semantic) Web with Rules and Rich Unification

For the last decade a multitude of new data formats for the World Wide Web have been developed, and a huge amount of heterogeneous semi-structured data is flourishing online. With the ever increasing number of documents on the Web, rules have been identified as the means of choice for reasoning about this data, transforming and integrating it. Query languages such as SPARQL and rule languages such as Xcerpt use compound queries that are matched or unified with semi-structured data. This notion of unification is different from the one that is known from logic programming engines in that it (i) provides constructs that allow queries to be incomplete in several ways (ii) in that variables may have different types, (iii) in that it results in sets of substitutions for the variables in the query instead of a single substitution and (iv) in that subsumption between queries is much harder to decide than in logic programming. This thesis abstracts from Xcerpt query term simulation, SPARQL graph pattern matching and XPath XML document matching, and shows that all of them can be considered as a form of rich unification. Given a set of mappings between substitution sets of different languages, this abstraction opens up the possibility for format-versatile querying, i.e. combination of queries in different formats, or transformation of one format into another format within a single rule. To show the superiority of this approach, this thesis introduces an extension of Xcerpt called Xcrdf, and describes use-cases for the combined querying and integration of RDF and XML data. With XML being the predominant Web format, and RDF the predominant Semantic Web format, Xcrdf extends Xcerpt by a set of RDF query terms and construct terms, including query primitives for RDF containers collections and reifications. Moreover, Xcrdf includes an RDF path query language called RPL that is more expressive than previously proposed polynomial-time RDF path query languages, but can still be evaluated in polynomial time combined complexity. Besides the introduction of this framework for data integration based on rich unification, this thesis extends the theoretical knowledge about Xcerpt in several ways: We show that Xcerpt simulation unification is decidable, and give complexity bounds for subsumption in several fragments of Xcerpt query terms. The proof is based on a set of subsumption monotone query term transformations, and is only feasible because of the injectivity requirement on subterms of Xcerpt queries. The proof gives rise to an algorithm for deciding Xcerpt query term simulation. Moreover, we give a semantics to locally and weakly stratified Xcerpt programs, but this semantics is applicable not only to Xcerpt, but to any rule language with rich unification, including multi-rule SPARQL programs. Finally, we show how Xcerpt grouping stratification can be reduced to Xcerpt negation stratification, thereby also introducing the notion of local grouping stratification and weak grouping stratification

Simulation and statistical model-checking of logic-based multi-agent system models

This thesis presents SALMA (Simulation and Analysis of Logic-Based Multi- Agent Models), a new approach for simulation and statistical model checking of multi-agent system models. Statistical model checking is a relatively new branch of model-based approximative verification methods that help to overcome the well-known scalability problems of exact model checking. In contrast to existing solutions, SALMA specifies the mechanisms of the simulated system by means of logical axioms based upon the well-established situation calculus. Leveraging the resulting first-order logic structure of the system model, the simulation is coupled with a statistical model-checker that uses a first-order variant of time-bounded linear temporal logic (LTL) for describing properties. This is combined with a procedural and process-based language for describing agent behavior. Together, these parts create a very expressive framework for modeling and verification that allows direct fine-grained reasoning about the agents’ interaction with each other and with their (physical) environment. SALMA extends the classical situation calculus and linear temporal logic (LTL) with means to address the specific requirements of multi-agent simulation models. In particular, cyber-physical domains are considered where the agents interact with their physical environment. Among other things, the thesis describes a generic situation calculus axiomatization that encompasses sensing and information transfer in multi agent systems, for instance sensor measurements or inter-agent messages. The proposed model explicitly accounts for real-time constraints and stochastic effects that are inevitable in cyber-physical systems. In order to make SALMA’s statistical model checking facilities usable also for more complex problems, a mechanism for the efficient on-the-fly evaluation of first-order LTL properties was developed. In particular, the presented algorithm uses an interval-based representation of the formula evaluation state together with several other optimization techniques to avoid unnecessary computation. Altogether, the goal of this thesis was to create an approach for simulation and statistical model checking of multi-agent systems that builds upon well-proven logical and statistical foundations, but at the same time takes a pragmatic software engineering perspective that considers factors like usability, scalability, and extensibility. In fact, experience gained during several small to mid-sized experiments that are presented in this thesis suggest that the SALMA approach seems to be able to live up to these expectations.In dieser Dissertation wird SALMA (Simulation and Analysis of Logic-Based Multi-Agent Models) vorgestellt, ein im Rahmen dieser Arbeit entwickelter Ansatz für die Simulation und die statistische Modellprüfung (Model Checking) von Multiagentensystemen. Der Begriff „Statistisches Model Checking” beschreibt modellbasierte approximative Verifikationsmethoden, die insbesondere dazu eingesetzt werden können, um den unvermeidlichen Skalierbarkeitsproblemen von exakten Methoden zu entgehen. Im Gegensatz zu bisherigen Ansätzen werden in SALMA die Mechanismen des simulierten Systems mithilfe logischer Axiome beschrieben, die auf dem etablierten Situationskalkül aufbauen. Die dadurch entstehende prädikatenlogische Struktur des Systemmodells wird ausgenutzt um ein Model Checking Modul zu integrieren, das seinerseits eine prädikatenlogische Variante der linearen temporalen Logik (LTL) verwendet. In Kombination mit einer prozeduralen und prozessorientierten Sprache für die Beschreibung von Agentenverhalten entsteht eine ausdrucksstarke und flexible Plattform für die Modellierung und Verifikation von Multiagentensystemen. Sie ermöglicht eine direkte und feingranulare Beschreibung der Interaktionen sowohl zwischen Agenten als auch von Agenten mit ihrer (physischen) Umgebung. SALMA erweitert den klassischen Situationskalkül und die lineare temporale Logik (LTL) um Elemente und Konzepte, die auf die spezifischen Anforderungen bei der Simulation und Modellierung von Multiagentensystemen ausgelegt sind. Insbesondere werden cyber-physische Systeme (CPS) unterstützt, in denen Agenten mit ihrer physischen Umgebung interagieren. Unter anderem wird eine generische, auf dem Situationskalkül basierende, Axiomatisierung von Prozessen beschrieben, in denen Informationen innerhalb von Multiagentensystemen transferiert werden – beispielsweise in Form von Sensor- Messwerten oder Netzwerkpaketen. Dabei werden ausdrücklich die unvermeidbaren stochastischen Effekte und Echtzeitanforderungen in cyber-physischen Systemen berücksichtigt. Um statistisches Model Checking mit SALMA auch für komplexere Problemstellungen zu ermöglichen, wurde ein Mechanismus für die effiziente Auswertung von prädikatenlogischen LTL-Formeln entwickelt. Insbesondere beinhaltet der vorgestellte Algorithmus eine Intervall-basierte Repräsentation des Auswertungszustands, sowie einige andere Optimierungsansätze zur Vermeidung von unnötigen Berechnungsschritten. Insgesamt war es das Ziel dieser Dissertation, eine Lösung für Simulation und statistisches Model Checking zu schaffen, die einerseits auf fundierten logischen und statistischen Grundlagen aufbaut, auf der anderen Seite jedoch auch pragmatischen Gesichtspunkten wie Benutzbarkeit oder Erweiterbarkeit genügt. Tatsächlich legen erste Ergebnisse und Erfahrungen aus mehreren kleinen bis mittelgroßen Experimenten nahe, dass SALMA diesen Zielen gerecht wird