There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

Data Mining - Concepts and Techniques.

Schema matching is a basic problem in many database application domains, such as data integration, E-business, data warehousing, and semantic query processing. In current implementations, schema matching is typically performed manually, which has significant limitations. On the other hand, previous research papers have proposed many techniques to achieve a partial automation of the match operation for specific application domains. We present a taxonomy that covers many of these existing approaches, and we describe the approaches in some detail. In particular, we distinguish between schema-level and instance-level, element-level and structure-level, and language-based and constraint-based matchers. Based on our classification we review some previous match implementations thereby indicating which part of the solution space they cover. We intend our taxonomy and review of past work to be useful when comparing different approaches to schema matching, when developing a new match algorithm, and when implementing a schema matching component.

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A survey of approaches to automatic schema matching

Ontologies tend to be found everywhere. They are viewed as the silver bullet for many applications, such as database integration, peer-to-peer systems, e-commerce, semantic web services, or social networks. However, in open or evolving systems, such as the semantic web, different parties would, in general, adopt different ontologies. Thus, merely using ontologies, like using XML, does not reduce heterogeneity: it just raises heterogeneity problems to a higher level. Euzenat and Shvaikos book is devoted to ontology matching as a solution to the semantic heterogeneity problem faced by computer systems. Ontology matching aims at finding correspondences between semantically related entities of different ontologies. These correspondences may stand for equivalence as well as other relations, such as consequence, subsumption, or disjointness, between ontology entities. Many different matching solutions have been proposed so far from various viewpoints, e.g., databases, information systems, and artificial intelligence. The second edition of Ontology Matching has been thoroughly revised and updated to reflect the most recent advances in this quickly developing area, which resulted in more than 150 pages of new content. In particular, the book includes a new chapter dedicated to the methodology for performing ontology matching. It also covers emerging topics, such as data interlinking, ontology partitioning and pruning, context-based matching, matcher tuning, alignment debugging, and user involvement in matching, to mention a few. More than 100 state-of-the-art matching systems and frameworks were reviewed. With Ontology Matching, researchers and practitioners will find a reference book that presents currently available work in a uniform framework. In particular, the work and the techniques presented in this book can be equally applied to database schema matching, catalog integration, XML schema matching and other related problems. The objectives of the book include presenting (i) the state of the art and (ii) the latest research results in ontology matching by providing a systematic and detailed account of matching techniques and matching systems from theoretical, practical and application perspectives.

Ontology Matching

A federated database system (FDBS) is a collection of cooperating database systems that are autonomous and possibly heterogeneous. In this paper, we define a reference architecture for distributed database management systems from system and schema viewpoints and show how various FDBS architectures can be developed. We then define a methodology for developing one of the popular architectures of an FDBS. Finally, we discuss critical issues related to developing and operating an FDBS.

Federated database systems for managing distributed, heterogeneous, and autonomous databases

A new indexing technique, time index, for improving the performance of certain classes of temporal queries was previously described by the author (see The 16th Conference on Very Large Databases (1990)). Three variations for implementing the time index efficiently are proposed and the performance of these three variations is compared with the performance of the original time index. Various parameters such as average lifetime of a version, average number of versions per object, block size and block clustering, and query time interval length are discussed. Simulation results show how these parameters affect the performance of the various implementation variations for the time index. >

Efficient implementation techniques for the time index

Das in der dritten und stark uberarbeiteten Auflage vorliegende Buch zahlt zu den international renommiertesten und bewahrtesten Lehrbuchern zum Thema Datenbanken. Der im Originalbuch behandelte Stoff geht weit uber den Rahmen einer einfuhrenden Vorlesung hinaus und behandelt auch fortgeschrittene Themen und Fragestellungen. Diese im Vergleich zum Original gekurzte und an die hiesige Lehre angepasste Bachelorausgabe stellt unterschiedliche Datenmodelle und Datenbanksprachen vor und behandelt die fur jeden Studenten wichtigen Grundlagen des Datenbankentwurfs.Zudem befassen sich die Autoren mit verschiedenen praxisrelevanten Aspekten des Mehrnutzerbetriebs. Alle Themenbereiche werden grundlich vertieft und so umfassend dargestellt, dass das Buch als Vorlesungsgrundlage ebenso geeignet ist wie zum spateren Nachschlagen und zum Selbststudium. Wiederholungsfragen und Ubungsaufgaben zu jedem Kapitel erleichtern die Uberprufung des Lernerfolgs. Die Losungen zu den Aufgaben und zusatzliche Kapitel der Originalubersetzung zu weiterfuhrenden Themen stehen auf der Companion Website zum Buch zur Verfugung. Hier finden Sie Downloads zu diesem Titel.

Grundlagen von Datenbanksystemen

We present GQBE, a system that presents a simple and intuitive mechanism to query large knowledge graphs. Answers to tasks such as “list university professors who have designed some programming languages and also won an award in Computer Science” are best found in knowledge graphs that record entities and their relationships. Real-world knowledge graphs are difficult to use due to their sheer size and complexity and the challenging task of writing complex structured graph queries. Toward better usability of query systems over knowledge graphs, GQBE allows users to query knowledge graphs by example entity tuples without writing complex queries. In this demo we present: 1) a detailed description of the various features and user-friendly GUI of GQBE, 2) a brief description of the system architecture, and 3) a demonstration scenario that we intend to show the audience.

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GQBE: Querying knowledge graphs by example entity tuples

Query Engines for Web-Accessible XML Data

This tutorial presents the primary constructs of the consensus temporal query language TSQL2 via a media planning scenario. Media planning is a series of decisions involved in the delivery of a promotional message via mass media. We will follow the planning of a particular advertising campaign. We introduce the scenario by identifying the marketing objective. The media plan involves placing commercials, and is recorded in a temporal database. The media plan must then be evaluated; we show how TSQL2 can be used to derive information from the stored data. We then give examples that illustrate storing and querying indeterminate information, comparing multiple versions of the media plan, accommodating changes to the schema, and vacuuming a temporal database of old data.

Ramez Elmasri

Papers

Efficient implementation techniques for the time index

Grundlagen von Datenbanksystemen

GQBE: Querying knowledge graphs by example entity tuples

Query Engines for Web-Accessible XML Data

A TSQL2 tutorial