The emerging application-to-application paradigm allows an organization's data to be shared across applications in both intra-enterprise and inter-enterprise contexts. In order to seamlessly integrate information from disparate, heterogeneous, and multi-organizational applications and quickly adapt to new application contexts, rigid information modeling and proprietary data representation technology have proven inadequate. Conventional data integration approaches are based on database systems that represent data semantics using static structured data schemas. They cannot provide adequate facilities to satisfy the increasing need for effective and efficient application data integration from heterogeneous data sources. Applications need to be built on an information model that is standards-based, flexible, and adaptable. This research proposes a framework that adopts a semi-structured data integration approach using a data view mechanism and XML and XPath standards. A prototype of the framework is designed and implemented using a loosely-coupled mediator-agent-adapter architecture based on distributed component technology. An XML query language provides the basis for data view definition as well as query specification and transformation. A denotational semantics and an abstract syntax of the query language are defined here to provide a formal basis for implementation of query processing and logical query optimization. The mapping between the concrete XML syntax and the abstract syntax of the query language is defined to facilitate implementation of query processing. The XMark benchmark for XML databases is used to assess the functionality and performance of the prototyped implementation of the query language and system. The benchmarking result and analysis establish a base line query performance measure for the proposed data integration framework and identify the characteristics of different system implementations.

The emerging application-to-application paradigm allows an organization's data to be shared across applications in both intra-enterprise and inter-enterprise contexts. In order to seamlessly integrate information from disparate, heterogeneous, and multi-organizational applications and quickly adapt to new application contexts, rigid information modeling and proprietary data representation technology have proven inadequate. Conventional data integration approaches are based on database systems that represent data semantics using static structured data schemas. They cannot provide adequate facilities to satisfy the increasing need for effective and efficient application data integration from heterogeneous data sources. Applications need to be built on an information model that is standards-based, flexible, and adaptable. This research proposes a framework that adopts a semi-structured data integration approach using a data view mechanism and XML and XPath standards. A prototype of the framework is designed and implemented using a loosely-coupled mediator-agent-adapter architecture based on distributed component technology. An XML query language provides the basis for data view definition as well as query specification and transformation. A denotational semantics and an abstract syntax of the query language are defined here to provide a formal basis for implementation of query processing and logical query optimization. The mapping between the concrete XML syntax and the abstract syntax of the query language is defined to facilitate implementation of query processing. The XMark benchmark for XML databases is used to assess the functionality and performance of the prototyped implementation of the query language and system. The benchmarking result and analysis establish a base line query performance measure for the proposed data integration framework and identify the characteristics of different system implementations.

This text provides an architectural overview of the Enterprise Service Bus, showing how it can bring the task of integration of enterprise application and services built on J2EE, .NET, C/C++, and other legacy environments into the reach of everyday IT professionals.

This book presents fundamental concepts and technologies to tackle interoperability between information systems. It details interoperability at the data, service, and process level, and combines theoretical foundations with hands-on presentation of technologies to enable the development of sound and practical integration. Chapter 1 details general interoperability challenges and describes the structure of the book. To start with, Chapter 2 presents technologies for the exchange of data between two selected and highly relevant data formats, i.e., relational databases and XML. Next, Chapter 3 explains concepts for schema matching and mapping and data integration as well as the technological basis for implementing them based on query and transformation languages like XPath and XSLT. Chapter 4 then turns to service interoperability and explains two related technologies -- REST and GraphQL -- in detail. In Chapter 5, fundamentals for designing process orchestrations at the conceptual level are presented, focusing on how to model process orchestrations and how to verify their correctness and soundness, and showing BPMN as the de facto modeling standard. Chapter 6 then details the concepts and languages for the implementation of process orchestrations, including the presentation of execution languages for process orchestrations that are equipped with a formal semantics, e.g., Workflow Nets, the Refined Process Structure Tree, and CPEE Trees. Subsequently, Chapter 7 focuses on the growing number of distributed, loosely coupled, and often non-interoperable applications through the concepts of enterprise application integration and explains these by an implementation in CPN Tools and by two case studies. Eventually, Chapter 8 is lifting the orchestration and integration concepts and technologies to the choreography level by dealing with the interoperability between different process orchestrations. Chapter 9 concludes the book by featuring success factors for interoperability projects. It also provides a range of open research directions for interoperability such as compliance, sensor fusion, and blockchain technologies. The book is mainly intended as a textbook to be used for developing and teaching courses on interoperability and integration. To this end, it is accompanied by a Web site with additional teaching materials. It also spans a bridge from researchers to graduate students and practitioners by providing a deep understanding on practical interoperability challenges and solutions. The focus here is put on de facto standards and open-source systems and tools to enable interoperability solutions at low cost.

Interoperability: the ability of a system or a product to work with other systems or products without special effort from the user is a key issue in manufacturing and industrial enterprise generally. It is fundamental to the production of goods and services quickly and at low cost at the same time as maintaining levels of quality and customisation. Composed of 40 papers of international authorship, Interoperability of Enterprise Software and Applications ranges from academic research through case studies to industrial experience of interoperability. Many of the papers have examples and illustrations calculated to deepen understanding and generate new ideas. A concise reference to the state of the art in software interoperability, Interoperability of Enterprise Software and Applications will be of great value to engineers and computer scientists working in manufacturing and other process industries and to software engineers and electronic and manufacturing engineers working in the academic environment.

A decision support system (DSS) is an information system that supports decisionmakers involved in complex decision-making processes. Modern DSSs needto exploit data that are not only numerical or symbolic, but also heterogeneouslystructured (e.g., text and multimedia data) and coming from various sources (e.g,the Web). We term such data complex data. Data warehouses are casually usedas the basis of such DSSs. They help integrate data from a variety of sourcesto support decision-making. However, the advent of complex data imposes anothervision of data warehousing including data integration, data storage and dataanalysis. Moreover, today's requirements impose integrating complex data in nearreal-time rather than with traditional snapshot and batch ETL (Extraction, Transformationand Loading). Real-time and near real-time processing requires a moreactive ETL process. Data integration tasks must react in an intelligent, i.e., activeand autonomous way, to encountered changes in the data integration environment,especially data sources.In this dissertation, we propose novel solutions for complex data integration innear real-time, actively and autonomously. We indeed provide a generic metadatabased,service-oriented and event-driven approach for integrating complex data.To address data complexity issues, our approach stores heterogeneous data into aunied format using a metadata-based approach and XML. We also tackle datadistribution and interoperability using a service-oriented approach. Moreover, toaddress near real-time requirements, our approach stores not only integrated datainto a unied repository, but also functions to integrate data on-the-y. We also apply a service-oriented approach to track relevant data changes in near real-time.Furthermore, the idea of integrating complex data actively and autonomously revolvesaround mining logged events of data integration environment. For this sake,we propose an incremental XML-based algorithm for mining association rules fromlogged events. Then, we de ne active rules upon mined data to reactivate integrationtasks.To validate our approach for managing complex data integration, we develop ahigh-level software framework, namely AX-InCoDa (Active XML-based frameworkfor Integrating Complex Data). AX-InCoDa is implemented as Web application usingopen-source tools. It exploits Web standards (e.g., XML and Web services) andActive XML to handle complexity issues and near real-time requirements. Besidewarehousing logged events into an event repository to be mined for self-managingpurposes, AX-InCoDa is enriched with active rules. AX-InCoDa's feasibility is illustratedby a healthcare case study. Finally, the performance of our incremental eventmining algorithm is experimentally demonstrated.

This book constitutes the refereed proceedings of the 9th International Conference on Extending Database Technology, EDBT 2004, held in Heraklion, Crete, Greece, in March 2004. The 42 revised full papers presented together with 2 industrial application papers, 15 software demos, and 3 invited contributions were carefully reviewed and selected from 294 submissions. The papers are organized in topical sections on distributed, mobile and peer-to-peer database systems; data mining and knowledge discovery; trustworthy database systems; innovative query processing techniques for XML data; data and information on the web; query processing techniques for spatial databases; foundations of query processing; advanced query processing and optimization; query processing techniques for data and schemas; multimedia and quality-aware systems; indexing techniques; and imprecise sequence pattern queries.