This Thesis addresses how Semantic Web representations, in particular RDF, can enable flexible and scalable preservation, recreation, and querying of databases. An approach has been developed for selective scalable long-term archival of relational databases (RDBs) as RDF, implemented in the SAQ (Semantic Archive and Query) system. The archival of user-specified parts of an RDB is specified using an extension of SPARQL, A-SPARQL. SAQ automatically generates an RDF view of the RDB, the RD-view. The result of an archival query is RDF triples stored in: i) a data archive file containing the preserved RDB content, and ii) a schema archive file containing sufficient meta-data to reconstruct the archived database. To achieve scalable data preservation and recreation, SAQ uses special query rewriting optimizations for the archival queries. It was experimentally shown that they improve query execution and archival time compared with naïve processing. The performance of SAQ was compared with that of other systems supporting SPARQL queries to views of existing RDBs. When an archived RDB is to be recreated, the reloader module of SAQ first reads the schema archive file and executes a schema reconstruction algorithm to automatically construct the RDB schema. The thus created RDB is populated by reading the data archive and converting the read data into relational attribute values. For scalable recreation of RDF archived data we have developed the Triple Bulk Load (TBL) approach where the relational data is reconstructed by using the bulk load facility of the RDBMS. Our experiments show that the TBL approach is substantially faster than the naïve Insert Attribute Value (IAV) approach, despite the added sorting and post-processing. To view and query semi-structured Topic Maps data as RDF the prototype system TM-Viewer was implemented. A declarative RDF view of Topic Maps, the TM-view, is automatically generated by the TM-viewer using a developed conceptual schema for the Topic Maps data model. To achieve efficient query processing of SPARQL queries to the TM-view query rewrite transformations were developed and evaluated. It was shown that they significantly improve the query execution time. / eSSENCE

[pt] Bases de conhecimento são ferramentas poderosas que fornecem suporte a um amplo espectro de aplicações como, por exemplo, busca exploratória, ranqueamento e recomendação. Bases de conhecimento podem ser vistas como grafos, onde os nós representam entidades e as arestas seus relacionamentos. Atualmente, motores de busca usam bases de conhecimento para melhorar suas recomendações. No entanto, motores de busca são orientados a uma única entidade e enfrentam dificuldades ao tentar explicar porque e como duas entidades estão relacionadas, um problema conhecido como relacionamento entre entidades. Esta tese explora o uso de bases de conhecimento em formato RDF para endereçar o problema de relacionamento entre entidades, em duas direções. Em uma direção, a tese define o conceito de perfis de conectividade para pares de entidades, que são explicações concisas sobre como as entidades se relacionam. A tese introduz uma estratégia para gerar um perfil de conectividade entre um par de entidades, que combina anotações semânticas e métricas de similaridade para resumir um conjunto de caminhos entre as duas entidades. Em seguida, introduz a ferramenta DBpedia profiler, que implementa a estratégia proposta, e cuja efetividade foi medida através de experimentos com usuários. Em outra direção, considerando os desafios para explorar grandes bases de conhecimento online, a tese apresenta uma estratégia genérica de busca baseada na heurística backward, a qual prioriza alguns caminhos sobre outros. A estratégia combina medidas de similaridade e de ranqueamento, criando diferentes alternativas. Por último, a tese avalia e compara as diferentes alternativas em dois domínios, música e filmes, adotando como ground truth rankings especializados de caminhos especialmente desenvolvidos para os experimentos. / [en] Knowledge bases are a powerful tool for supporting a large spectrum of applications such as exploratory search, ranking, and recommendation. Knowledge bases can be viewed as graphs whose nodes represent entities and whose edges represent relationships. Currently, search engines take advantage of knowledge bases to improve their recommendations. However, search engines are single entity-centric and face difficulties when trying to explain why and how two entities are related, a problem known as entity relatedness. This thesis explores the use of knowledge bases in RDF format to address the entity relatedness problem, in two directions. In one direction, it defines the concept of connectivity profiles for entity pairs, which are concise explanations about how the entities are related. The thesis introduces a strategy to generate a connectivity profile for an entity pair that combines semantic annotations and similarity metrics to summarize a set of relationship paths between the given entity pair. The thesis then describes the DBpedia profiler tool, which implements the strategy for DBpedia, and whose effectiveness was evaluated through user experiments. In another direction, motivated by the challenges of exploring large online knowledge bases, the thesis introduces a generic search strategy, based on the backward search heuristic, to prioritize certain paths over others. The strategy combines similarity and ranking measures to create different alternatives. Finally, the thesis evaluates and compares the different alternatives in two domains, music and movies, based on specialized path rankings taken as ground truth.

In dieser Arbeit schlagen wir die Verwendung von materialisierten Anfragen als Indexstruktur für RDF-Daten vor. Wir streben eine Reduktion der Bearbeitungszeit durch die Minimierung der Anzahl der Vergleiche zwischen Anfrage und RDF Datenmenge an. Darüberhinaus betonen wir die Rolle von Kostenmodellen und Indizes für die Auswahl eines efizienten Ausführungsplans in Abhängigkeit vom Workload. Wir geben einen Überblick über das Problem der Auswahl von materialisierten Anfragen in relationalen Datenbanken und diskutieren ihre Anwendung zur Optimierung der Anfrageverarbeitung. Wir stellen RDFMatView als Framework für SPARQL-Anfragen vor. RDFMatView benutzt materializierte Anfragen als Indizes und enthalt Algorithmen, um geeignete Indizes fur eine gegebene Anfrage zu finden und sie in Ausführungspläne zu integrieren. Die Auswahl eines effizienten Ausführungsplan ist das zweite Thema dieser Arbeit. Wir führen drei verschiedene Kostenmodelle für die Verarbeitung von SPARQL Anfragen ein. Ein detaillierter Vergleich der Kostmodelle zeigt, dass ein auf Index-- und Prädikat--Statistiken beruhendes Modell die genauesten Informationen liefert, um einen effizienten Ausführungsplan auszuwählen. Die Evaluation zeigt, dass unsere Methode die Anfragebearbeitungszeit im Vergleich zu unoptimierten SPARQL--Anfragen um mehrere Größenordnungen reduziert. Schließlich schlagen wir eine einfache, aber effektive Strategie für das Problem der Auswahl von materialisierten Anfragen über RDF-Daten vor. Ausgehend von einem bestimmten Workload werden algorithmisch diejenigen Indizes augewählt, die die Bearbeitungszeit des gesamten Workload minimieren sollen. Dann erstellen wir auf der Basis von Anfragemustern eine Menge von Index--Kandidaten und suchen in dieser Menge Zusammenhangskomponenten. Unsere Auswertung zeigt, dass unsere Methode zur Auswahl von Indizes im Vergleich zu anderen, die größten Einsparungen in der Anfragebearbeitungszeit liefert. / In this thesis, we propose to use materialized queries as a special index structure for RDF data. We strive to reduce the query processing time by minimizing the number of comparisons between the query and the RDF dataset. We also emphasize the role of cost models in the selection of execution plans as well as index sets for a given workload. We provide an overview of the materialized view selection problem in relational databases and discuss its application for optimization of query processing. We introduce RDFMatView, a framework for answering SPARQL queries using materialized views as indexes. We provide algorithms to discover those indexes that can be used to process a given query and we develop different strategies to integrate these views in query execution plans. The selection of an efficient execution plan states the topic of our second major contribution. We introduce three different cost models designed for SPARQL query processing with materialized views. A detailed comparison of these models reveals that a model based on index and predicate statistics provides the most accurate cost estimation. We show that selecting an execution plan using this cost model yields a reduction of processing time with several orders of magnitude compared to standard SPARQL query processing. Finally, we propose a simple yet effective strategy for the materialized view selection problem applied to RDF data. Based on a given workload of SPARQL queries we provide algorithms for selecting a set of indexes that minimizes the workload processing time. We create a candidate index by retrieving all connected components from query patterns. Our evaluation shows that using the set of suggested indexes usually achieves larger runtime savings than other index sets regarding the given workload.

Τα τελευταία χρόνια υπάρχει εκθετική αύξηση του όγκου της πληροφορίας που δημοσιεύεται στο Διαδίκτυο. Καθώς όμως η πληροφορία αυτή δε συνδέεται με τη σημασιολογία της παρατηρείται δυσκολία στη διαχείρισή της και στην πρόσβαση σε αυτήν. Ο Σημασιολογικός Ιστός, λοιπόν, είναι μια ομάδα μεθόδων και τεχνολογιών που σκοπεύουν να δώσουν τη δυνατότητα στις μηχανές να κατανοήσουν τη “σημασιολογία” των πληροφοριών σχετικά με τον Παγκόσμιο Ιστό. Ο Σημασιολογικός Ιστός (Semantic Web) αποτελεί επέκταση του Παγκοσμίου Ιστού. Στο Σημασιολογικό Ιστό οι πληροφορίες εμπλουτίζονται με μεταδεδομένα, τα οποία υπακουούν σε κοινά πρότυπα και επιτρέπουν την εξαγωγή γνώσεως από την ήδη υπάρχουσα, καθώς επίσης και το συνδυασμό της υπάρχουσας πληροφορίας με στόχο την εξαγωγή συμπερασμάτων. Απώτερος στόχος του Σημασιολογικού Ιστού είναι η βελτιωμένη αναζήτηση, η εκτέλεση σύνθετων διεργασιών και η εξατομίκευση της πληροφορίας σύμφωνα με τις ανάγκες του κάθε χρήστη. Στην παρούσα διπλωματική εργασία μελετήθηκε η χρήση των τεχνολογιών του Σημασιολογικού Ιστού για τη βελτίωση της πρόσβασης σε πολιτισμικά δεδομένα. Συγκεκριμένα αρχικά έγινε εμβάθυνση στις τεχνολογίες και στις θεμελιώδεις έννοιες του Σημασιολογικού Ιστού. Παρουσιάστηκαν αναλυτικά οι βασικές γλώσσες σήμανσης: XML που επιτρέπει τη δημιουργία δομημένων εγγράφων με λεξιλόγιο καθορισμένο από το χρήστη, RDF που προσφέρει ένα μοντέλο δεδομένων για την περιγραφή πληροφοριών με τέτοιο τρόπο ώστε να είναι δυνατή η ανάγνωση και η κατανόησή τους από μηχανές. Αναφέρθηκαν, ακόμη, οι διάφοροι τρόποι σύνταξης της γλώσσας RDF καθώς και πως γίνεται αναζήτηση σε γράφους RDF με το πρωτόκολλο SPARQL. Στη συνέχεια ακολουθεί η περιγραφή της RDFS, που πρόκειται για γλώσσα περιγραφής του RDF λεξιλογίου. Έχοντας παρουσιαστεί σε προηγούμενο κεφάλαιο η έννοια της οντολογίας, γίνεται αναφορά στη σημασιολογική γλώσσα σήμανσης OWL, που χρησιμοποιείται για την έκδοση και διανομή οντολογιών στο Διαδίκτυο. Έπειτα ακολουθεί μια ανασκόπηση από επιλεγμένα έργα, ελληνικά, ευρωπαϊκά και διεθνή, των τελευταίων ετών που χρησιμοποιούν τις τεχνολογίες του Σημασιολογικού Ιστού στο τομέα του πολιτισμού και της πολιτισμικής κληρονομιάς. Τέλος στο έβδομο κεφάλαιο παρουσιάζεται μία εφαρμογή διαχείρισης αρχαιολογικών χώρων-μνημείων και μελετώνται σε βάθος οι τεχνολογίες και τα εργαλεία που χρησιμοποιήθηκαν για την υλοποίησή της. / Over the past few years there has been exponential increase of the volume of information published on the Internet. Since information is not connected to its semantics, it is difficult to manipulate and access it. Therefore, the Semantic Web consists of methods and technologies that aim to enable machines to understand information’s semantics. The Semantic Web is an extension of the World Wide Web (WWW). Specifically, information is enriched with metadata, which are subject to common standards and permit knowledge extraction from the existing one and the combination of existing information in order to infer implicit knowledge, as well. Future goals of the Semantic Web are enhanced searching, complicated processes’ execution and information personalization according to each user’s needs. This post-graduate diploma thesis researches the usage of Semantic Web technologies for the enhancement of the access to cultural data. More specifically, Semantic Web technologies and essential concepts were studied. Basic markup languages were presented analytically: XML that allows structured documents’ creation with user defined vocabulary, RDF that offers a data model for such information description that it is readable and understandable by machines. Also, various RDF syntaxes and how to search RDF graphs using SPARQL protocol were referred. Below RDFS description follows, that is a description language of RDF vocabulary. After having introduced the concept of ontology in previous chapter, the semantic markup language OWL is presented, that is used for ontology publishing and distribution on the Internet. A review of selected projects of the last years, Greek, European and international, which are characterized by the application of technologies of the Semantic Web in the sector of Culture and Cultural heritage, is presented. In the last chapter, an application that manages archaeological places- sites is presented and it is studied technologies and tools that were used for it.