Linking Enterprise Data

Enterprise data is growing at a much faster rate than traditional technologies allow. New enterprise architectures combining existing technologies are desperately needed. This book suggests a way forward by applying new techniques of the World Wide Web to enterprise information systems. Linking Enterprise Data is an edited volume contributed by worldwide leaders in Semantic Web and Linked Data research, standards development and adoption. Linking enterprise data is the application of World Wide Web architecture principles to real-world information management issues faced by commercial, not-for-profit and government enterprises. This book is divided into four sections: Benefits of applying Linked Data principles in enterprise settings, enterprise approval and support of Linked Data projects, specific Linked Data techniques and a number of real-world success stories from early enterprise adopters. Linking Enterprise Data targets professionals working as CTOs, CIOs, enterprise architects, project managers and application developers in commercial, not-for-profit and government organizations concerned with scalability, flexibility and robustness of information management systems. Computer science graduate students and researchers focusing on enterprise information integration will also benefit.

Enterprise data is growing at a much faster rate than traditional technologies allow. New enterprise architectures combining existing technologies are desperately needed. This book suggests a way forward by applying new techniques of the World Wide Web to enterprise information systems. Linking Enterprise Data is an edited volume contributed by worldwide leaders in Semantic Web and Linked Data research, standards development and adoption. Linking enterprise data is the application of World Wide Web architecture principles to real-world information management issues faced by commercial, not-for-profit and government enterprises. This book is divided into four sections: Benefits of applying Linked Data principles in enterprise settings, enterprise approval and support of Linked Data projects, specific Linked Data techniques and a number of real-world success stories from early enterprise adopters. Linking Enterprise Data targets professionals working as CTOs, CIOs, enterprise architects, project managers and application developers in commercial, not-for-profit and government organizations concerned with scalability, flexibility and robustness of information management systems. Computer science graduate students and researchers focusing on enterprise information integration will also benefit.

Linked Data Management presents techniques for querying and managing Linked Data that is available on today's Web. The book shows how the abundance of Linked Data can serve as fertile ground for research and commercial applications.The text focuses on aspects of managing large-scale collections of Linked Data. It offers a detailed introduction to L

The two-volume set LNCS 6496 and 6497 constitutes the refereed proceedings of the 9th International Semantic Web Conference, ISWC 2010, held in Shanghai, China, during November 7-11, 2010. Part I contains 51 papers out of 578 submissions to the research track. Part II contains 18 papers out of 66 submissions to the semantic Web in-use track, 6 papers out of 26 submissions to the doctoral consortium track, and also 4 invited talks. Each submitted paper were carefully reviewed. The International Semantic Web Conferences (ISWC) constitute the major international venue where the latest research results and technical innovations on all aspects of the Semantic Web are presented. ISWC brings together researchers, practitioners, and users from the areas of artificial intelligence, databases, social networks, distributed computing, Web engineering, information systems, natural language processing, soft computing, and human computer interaction to discuss the major challenges and proposed solutions, the success stories and failures, as well the visions that can advance research and drive innovation in the Semantic Web.

This book examines the recent evolution of the concept of data as an economic and managerial phenomenon. The author first describes and discusses open data and then introduces the concept of linked data, with a focus on assets for reuse. Furthermore, he addresses the main challenges of big data. Value is identified as the main incentive for the adoption of linked data; accordingly, the next two chapters study sources of data value from a macroeconomic and micro economic perspective, respectively. This contributes to the systematization of important issues at the crossroads of enterprise data and data sharing: data ownership, personal data, and data privacy. In turn, the book reveals the role of innovation as a main vehicle for creating value by unifying big, open, and linked data. It studies the ways in which value can be created, transferred, and captured in the form of business models, before the closing chapter verifies the data unification model by combining open and linked geographical data with big data from a major telecom company.

The explosion of information technology has led to substantial growth of web-accessible linguistic data in terms of quantity, diversity and complexity. These resources become even more useful when interlinked with each other to generate network effects. The general trend of providing data online is thus accompanied by newly developing methodologies to interconnect linguistic data and metadata. This includes linguistic data collections, general-purpose knowledge bases (e.g., the DBpedia, a machine-readable edition of the Wikipedia), and repositories with specific information about languages, linguistic categories and phenomena. The Linked Data paradigm provides a framework for interoperability and access management, and thereby allows to integrate information from such a diverse set of resources. The contributions assembled in this volume illustrate the band-width of applications of the Linked Data paradigm for representative types of language resources. They cover lexical-semantic resources, annotated corpora, typological databases as well as terminology and metadata repositories. The book includes representative applications from diverse fields, ranging from academic linguistics (e.g., typology and corpus linguistics) over applied linguistics (e.g., lexicography and translation studies) to technical applications (in computational linguistics, Natural Language Processing and information technology). This volume accompanies the Workshop on Linked Data in Linguistics 2012 (LDL-2012) in Frankfurt/M., Germany, organized by the Open Linguistics Working Group (OWLG) of the Open Knowledge Foundation (OKFN). It assembles contributions of the workshop participants and, beyond this, it summarizes initial steps in the formation of a Linked Open Data cloud of linguistic resources, the Linguistic Linked Open Data cloud (LLOD).

Linking Government Data provides a practical approach to addressing common information management issues. The approaches taken are based on international standards of the World Wide Web Consortium. Linking Government Data gives both the costs and benefits of using linked data techniques with government data; describes how agencies can fulfill their missions with less cost; and recommends how intra-agency culture must change to allow public presentation of linked data. Case studies from early adopters of linked data approaches in international governments are presented in the last section of the book. Linking Government Data is designed as a professional book for those working in Semantic Web research and standards development, and for early adopters of Semantic Web standards and techniques. Enterprise architects, project managers and application developers in commercial, not-for-profit and government organizations concerned with scalability, flexibility and robustness of information management systems will also find this book valuable. Students focused on computer science and business management will also find value in this book.

This book addresses the topic of exploiting enterprise-linked data with a particular focus on knowledge construction and accessibility within enterprises. It identifies the gaps between the requirements of enterprise knowledge consumption and “standard” data consuming technologies by analysing real-world use cases, and proposes the enterprise knowledge graph to fill such gaps. It provides concrete guidelines for effectively deploying linked-data graphs within and across business organizations. It is divided into three parts, focusing on the key technologies for constructing, understanding and employing knowledge graphs. Part 1 introduces basic background information and technologies, and presents a simple architecture to elucidate the main phases and tasks required during the lifecycle of knowledge graphs. Part 2 focuses on technical aspects; it starts with state-of-the art knowledge-graph construction approaches, and then discusses exploration and exploitation techniques as well as advanced question-answering topics concerning knowledge graphs. Lastly, Part 3 demonstrates examples of successful knowledge graph applications in the media industry, healthcare and cultural heritage, and offers conclusions and future visions.