Streaming the Web: Reasoning over dynamic data.

In the last few years a new research area, called stream reasoning, emerged to bridge the gap between reasoning and stream processing. While current reasoning approaches are designed to work on mainly static data, the Web is, on the other hand, extremely dynamic: information is frequently changed and updated, and new data is continuously generated from a huge number of sources, often at high rate. In other words, fresh information is constantly made available in the form of streams of new data and updates. Despite some promising investigations in the area, stream reasoning is still in its infancy, both from the perspective of models and theories development, and from the perspective of systems and tools design and implementation. The aim of this paper is threefold: (i) we identify the requirements coming from different application scenarios, and we isolate the problems they pose; (ii) we survey existing approaches and proposals in the area of stream reasoning, highlighting their strengths and limitations; (iii) we draw a research agenda to guide the future research and development of stream reasoning. In doing so, we also analyze related research fields to extract algorithms, models, techniques, and solutions that could be useful in the area of stream reasoning. © 2014 Elsevier B.V. All rights reserved

SWI-Prolog and the Web

Where Prolog is commonly seen as a component in a Web application that is either embedded or communicates using a proprietary protocol, we propose an architecture where Prolog communicates to other components in a Web application using the standard HTTP protocol. By avoiding embedding in external Web servers development and deployment become much easier. To support this architecture, in addition to the transfer protocol, we must also support parsing, representing and generating the key Web document types such as HTML, XML and RDF. This paper motivates the design decisions in the libraries and extensions to Prolog for handling Web documents and protocols. The design has been guided by the requirement to handle large documents efficiently. The described libraries support a wide range of Web applications ranging from HTML and XML documents to Semantic Web RDF processing. To appear in Theory and Practice of Logic Programming (TPLP)Comment: 31 pages, 24 figures and 2 tables. To appear in Theory and Practice of Logic Programming (TPLP

Storing and Querying Ontologies in Logic Databases

The intersection of Description Logic inspired ontology languages with Logic Programs has been recently analyzed in [GHVD03]. The resulting language, called Description Logic Programs, covers RDF Schema and a notable portion of OWL Lite. However, the proposed mapping in [GHVD03] from the corresponding OWL fragment into Logic Programs has shown scalability as well as representational de�cits within our experiments and analysis. In this paper we propose an alternative mapping resulting in lower computational complexity and more representational exibility. We also present benchmarking results for both mappings with ontologies of di�erent size and complexity

DynamiTE: Parallel Materialization of Dynamic RDF Data

One of the main advantages of using semantically annotated data is that machines can reason on it, deriving implicit knowledge from explicit information. In this context, materializing every possible implicit derivation from a given input can be computationally expensive, especially when considering large data volumes. Most of the solutions that address this problem rely on the assumption that the information is static, i.e., that it does not change, or changes very infrequently. However, the Web is extremely dynamic: online newspapers, blogs, social networks, etc., are frequently changed so that outdated information is removed and replaced with fresh data. This demands for a materialization that is not only scalable, but also reactive to changes. In this paper, we consider the problem of incremental materialization, that is, how to update the materialized derivations when new data is added or removed. To this purpose, we consider the ρdf RDFS fragment [12], and present a parallel system that implements a number of algorithms to quickly recalculate the derivation. In case new data is added, our system uses a parallel version of the well-known semi-naive evaluation of Datalog. In case of removals, we have implemented two algorithms, one based on previous theoretical work, and another one that is more efficient since it does not require a complete scan of the input. We have evaluated the performance using a prototype system called DynamiTE, which organizes the knowledge bases with a number of indices to facilitate the query process and exploits parallelism to improve the performance. The results show that our methods are indeed capable to recalculate the derivation in a short time, opening the door to reasoning on much more dynamic data than is currently possible. © 2013 Springer-Verlag

Geographica: A Benchmark for Geospatial RDF Stores

Geospatial extensions of SPARQL like GeoSPARQL and stSPARQL have recently been defined and corresponding geospatial RDF stores have been implemented. However, there is no widely used benchmark for evaluating geospatial RDF stores which takes into account recent advances to the state of the art in this area. In this paper, we develop a benchmark, called Geographica, which uses both real-world and synthetic data to test the offered functionality and the performance of some prominent geospatial RDF stores

Κατανεμημένη αποτίμηση επερωτήσεων και συλλογιστική για το μοντέλο RDF σε δίκτυα ομοτίμων κόμβων

Με το ενδιαφέρον για τις εφαρμογές του Σημασιολογικού Ιστού να αυξάνεται ραγδαία, το μοντέλο RDF και RDFS έχει γίνει ένα από τα πιο ευρέως χρησιμοποιούμενα μοντέλα δεδομένων για την αναπαράσταση και την ενσωμάτωση δομημένης πληροφορίας στον Ιστό. Το πλήθος των διαθέσιμων πηγών πληροφορίας RDF συνεχώς αυξάνεται με αποτέλεσμα να υπάρχει μια επιτακτική ανάγκη για τη διαχείριση RDF δεδομένων. Σε αυτή τη διατριβή επικεντρωνόμαστε στην κατανεμημένη διαχείριση RDF δεδομένων σε δίκτυα ομότιμων κόμβων. Σχεδιάζουμε και υλοποιούμε το σύστημα Atlas, ένα πλήρως κατανεμημένο σύστημα για την αποθήκευση RDF και RDFS δεδομένων, την αποτίμηση και βελτιστοποίηση επερωτήσεων στη γλώσσα SPARQL και τη συλλογιστική στο μοντέλο RDFS. Το σύστημα Atlas χρησιμοποιεί κατανεμημένους πίνακες κατακερματισμού, μια δημοφιλή περίπτωση δικτύων ομότιμων κόμβων. Αρχικά, αναλύουμε κατανεμημένους αλγόριθμους για συλλογιστική RDFS χρησιμοποιώντας κατανεμημένους πίνακες κατακερματισμού. Υλοποιηούμε διάφορες παραλλαγές των αλγορίθμων προς τα εμπρός αλυσίδα εκτέλεσης και προς τα πίσω αλυσίδα εκτέλεσης καθώς και έναν αλγόριθμο που χρησιμοποιεί την τεχνική μετασχηματισμού των κανόνων σε μαγικό σύνολο. Αποδεικνύουμε θεωρητικά την ορθότητα των αλγορίθμων αυτών και προσφέρουμε μια συγκριτική μελέτη τόσο αναλυτικά όσο και πειραματικά. Παράλληλα, προτείνουμε αλγορίθμους και τεχνικές για την αποτίμηση και τη βελτιστοποίηση επερωτήσεων στη γλώσσα SPARQL για RDF δεδομένα που είναι αποθηκευμένα σε κατανεμημένους πίνακες κατακερματισμού. Οι τεχνικές βελτιστοποίησης βασίζονται σε εκτιμήσεις επιλεκτικότητας και έχουν στόχο τη μείωση του χρόνου απόκρισης της επερώτησης καθώς και της κατανάλωσης εύρους ζώνης του δικτύου. Η εκτεταμένη πειραματική αξιολόγηση των μεθόδων βελτιστοποίησης γίνεται σε μια τοπική συστάδα υπολογιστών χρησιμοποιώντας ένα ευρέως διαδεδομένο σημείο αναφοράς μετρήσεων.With the interest in Semantic Web applications rising rapidly, the Resource Description Framework (RDF) and its accompanying vocabulary description language, RDF Schema (RDFS), have become one of the most widely used data models for representing and integrating structured information in the Web. With the vast amount of available RDF data sources on the Web increasing rapidly, there is an urgent need for RDF data management. In this thesis, we focus on distributed RDF data management in peer-to-peer (P2P) networks. More specifically, we present results that advance the state-of-the-art in the research area of distributed RDF query processing and reasoning in P2P networks. We fully design and implement a P2P system, called Atlas, for the distributed query processing and reasoning of RDF and RDFS data. Atlas is built on top of distributed hash tables (DHTs), a commonly-used case of P2P networks. Initially, we study RDFS reasoning algorithms on top of DHTs. We design and develop distributed forward and backward chaining algorithms, as well as an algorithm which works in a bottom-up fashion using the magic sets transformation technique. We study theoretically the correctness of our reasoning algorithms and prove that they are sound and complete. We also provide a comparative study of our algorithms both analytically and experimentally. In the experimental part of our study, we obtain measurements in the realistic large-scale distributed environment of PlanetLab as well as in the more controlled environment of a local cluster. Moreover, we propose algorithms for SPARQL query processing and optimization over RDF(S) databases stored on top of distributed hash tables. We fully implement and evaluate a DHT-based optimizer. The goal of the optimizer is to minimize the time for answering a query as well as the bandwidth consumed during the query evaluation. The optimization algorithms use selectivity estimates to determine the chosen query plan. Our algorithms and techniques have been extensively evaluated in a local cluster

State-of-the-art on evolution and reactivity

This report starts by, in Chapter 1, outlining aspects of querying and updating resources on the Web and on the Semantic Web, including the development of query and update languages to be carried out within the Rewerse project. From this outline, it becomes clear that several existing research areas and topics are of interest for this work in Rewerse. In the remainder of this report we further present state of the art surveys in a selection of such areas and topics. More precisely: in Chapter 2 we give an overview of logics for reasoning about state change and updates; Chapter 3 is devoted to briefly describing existing update languages for the Web, and also for updating logic programs; in Chapter 4 event-condition-action rules, both in the context of active database systems and in the context of semistructured data, are surveyed; in Chapter 5 we give an overview of some relevant rule-based agents frameworks

Storage, Querying and Inferencing for Semantic Web Languages

Harmelen, F.A.H. van [Promotor