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

The Transmission Control Protocol.

Distributed data processing is becoming a reality. Businesses want to do it for many reasons, and they often must do it in order to stay competitive. While much of the infrastructure for distributed data processing is already there (e.g., modern network technology), a number of issues make distributed data processing still a complex undertaking: (1) distributed systems can become very large, involving thousands of heterogeneous sites including PCs and mainframe server machines; (2) the state of a distributed system changes rapidly because the load of sites varies over time and new sites are added to the system; (3) legacy systems need to be integrated—such legacy systems usually have not been designed for distributed data processing and now need to interact with other (modern) systems in a distributed environment. This paper presents the state of the art of query processing for distributed database and information systems. The paper presents the “textbook” architecture for distributed query processing and a series of techniques that are particularly useful for distributed database systems. These techniques include special join techniques, techniques to exploit intraquery paralleli sm, techniques to reduce communication costs, and techniques to exploit caching and replication of data. Furthermore, the paper discusses different kinds of distributed systems such as client-server, middleware (multitier), and heterogeneous database systems, and shows how query processing works in these systems.

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The state of the art in distributed query processing

Transactional Information Systems is the long-awaited, comprehensive work from leading scientists in the transaction processing field. Weikum and Vossen begin with a broad look at the role of transactional technology in today's economic and scientific endeavors, then delve into critical issues faced by all practitioners, presenting today's most effective techniques for controlling concurrent access by multiple clients, recovering from system failures, and coordinating distributed transactions.


The authors emphasize formal models that are easily applied across fields, that promise to remain valid as current technologies evolve, and that lend themselves to generalization and extension in the development of new classes of network-centric, functionally rich applications. This book's purpose and achievement is the presentation of the foundations of transactional systems as well as the practical aspects of the field what will help you meet today's challenges.

* Provides the most advanced coverage of the topic available anywhere--along with the database background required for you to make full use of this material.
* Explores transaction processing both generically as a broadly applicable set of information technology practices and specifically as a group of techniques for meeting the goals of your enterprise.
* Contains information essential to developers of Web-based e-Commerce functionality--and a wide range of more "traditional" applications.
* Details the algorithms underlying core transaction processing functionality.

Table of Contents

PART ONE - BACKGROUND AND MOTIVATION
Chapter 1 What Is It All About?
Chapter 2 Computational Models
PART TWO - CONCURRENCY CONTROL
Chapter 3 Concurrency Control: Notions of Correctness for the Page Model
Chapter 4 Concurrency Control Algorithms
Chapter 5 Multiversion Concurrency Control
Chapter 6 Concurrency Control on Objects: Notions of Correctness
Chapter 7 Concurrency Control Algorithms on Objects
Chapter 8 Concurrency Control on Relational Databases
Chapter 9 Concurrency Control on Search Structures
Chapter 10 Implementation and Pragmatic Issues
PART THREE - RECOVERY
Chapter 11 Transaction Recovery 
Chapter 12 Crash Recovery: Notion of Correctness
Chapter 13 Page Model Crash Recovery Algorithms
Chapter 14 Object Model Crash Recovery
Chapter 15 Special Issues of Recovery
Chapter 16 Media Recovery
Chapter 17 Application Recovery
PART FOUR - COORDINATION OF DISTRIBUTED TRANSACTIONS
Chapter 18 Distributed Concurrency Control
Chapter 19 Distributed Transaction Recovery
PART FIVE - APPLICATIONS AND FUTURE PERSPECTIVES
Chapter 20 What Is Next?

Transactional Information Systems: Theory, Algorithms, and the Practice of Concurrency Control and Recovery

We may not be able to make you love reading, but production workflow concepts and techniques will lead you to love reading starting from now. Book is the window to open the new world. The world that you want is in the better stage and level. World will always guide you to even the prestige stage of the life. You know, this is some of how reading will give you the kindness. In this case, more books you read more knowledge you know, but it can mean also the bore is full.

Production workflow: concepts and techniques

The ability to notify clients of changes to their critical data has become an important feature for both data storage systems and application development frameworks. In the final chapter of this book, we summarize the state of the art in push-based data access and identify possible next steps in the development of applications and technology in the field of real-time data management.

State of the Art and Future Directions

Today, data is generated and consumed at unprecedented scale. This has lead to novel approaches for scalable data management subsumed under the term "NoSQL" database systems to handle the ever-increasing data volume and request loads. However, the heterogeneity and diversity of the numerous existing systems impede the well-informed selection of a data store appropriate for a given application context. Therefore, this article gives a top-down overview of the field: instead of contrasting the implementation specifics of individual representatives, we propose a comparative classification model that relates functional and non-functional requirements to techniques and algorithms employed in NoSQL databases. This NoSQL Toolbox allows us to derive a simple decision tree to help practitioners and researchers filter potential system candidates based on central application requirements.

NoSQL database systems: a survey and decision guidance

XML (Extensible Markup Language) is a textual markup language designed for the creation of self-describing documents which contain textual data combined with structural information describing the structure of the textual data. We introduce XCoP (XML Content Repository) as a repository which is based on an object-relational database management system (ORDBMS) and improves content management of XML documents, thereby exploiting their structural information. It allows users to reuse and process the textual portions of document contents, called fragments, which are flexibly configurable. Moreover, it enables collaborative development of documents and facilitates synchronization of fragment modification and versioning. Thus, XCoP offers comprehensive content management functionality by taking advantage of the availability of structural information.

XML content management based on object-relational database technology

Abstract With the rise of the web 2.0 and the Internet of things, it has become feasible to track all kinds of information over time, in particular fine-grained user activities and sensor data on their environment and even their biometrics. However, while efficiency remains mandatory for any application trying to cope with huge amounts of data, only part of the potential of today's Big Data repositories can be exploited using traditional batch-oriented approaches as the value of data often decays quickly and high latency becomes unacceptable in some applications. In the last couple of years, several distributed data processing systems have emerged that deviate from the batch-oriented approach and tackle data items as they arrive, thus acknowledging the growing importance of timeliness and velocity in Big Data analytics. In this article, we give an overview over the state of the art of stream processors for low-latency Big Data analytics and conduct a qualitative comparison of the most popular contenders, namely Storm and its abstraction layer Trident, Samza and Spark Streaming. We describe their respective underlying rationales, the guarantees they provide and discuss the trade-offs that come with selecting one of them for a particular task.

Real-time stream processing for Big Data

The OnTheMove 2013 event, held 9-13 September in Graz, Austria, further consolidated the importance of the series of annual conferences that was started in 2002 in Irvine, California. It then moved to Catania, Sicily in 2003, to Cyprus in 2004 and 2005, Montpellier in 2006, Vilamoura in 2007 and 2009, in 2008 to Monterrey, Mexico, to Heraklion, Crete in 2010 and 2011, and to Rome in 2012. This prime event continues to attract a diverse and relevant selection of today's research worldwide on the scientific concepts underlying new computing paradigms, which, of necessity, must be distributed, heterogeneous, and supporting an environment of resources that are autonomous and yet must meaningfully cooperate. Indeed, as such large, complex, and networked intelligent information systems become the focus and norm for computing, there continues to be an acute and even increasing need to address the implied software, system, and enterprise issues and discuss them face to face in an integrated forum that covers methodological, semantic, theoretical, and application issues as well. As we all realize, email, the Internet, and even video conferences are not by themselves optimal nor even sufficient for effective and efficient scientific exchange.

Norbert Ritter

Papers

State of the Art and Future Directions

NoSQL database systems: a survey and decision guidance

XML content management based on object-relational database technology

Real-time stream processing for Big Data

On the Move to Meaningful Internet Systems: OTM 2013 Conferences