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Author: Peter Christen
Publisher:
ISBN: 3030597067
Category : Computer security
Languages : en
Pages : 476
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Book Description
This book provides modern technical answers to the legal requirements of pseudonymisation as recommended by privacy legislation. It covers topics such as modern regulatory frameworks for sharing and linking sensitive information, concepts and algorithms for privacy-preserving record linkage and their computational aspects, practical considerations such as dealing with dirty and missing data, as well as privacy, risk, and performance assessment measures. Existing techniques for privacy-preserving record linkage are evaluated empirically and real-world application examples that scale to population sizes are described. The book also includes pointers to freely available software tools, benchmark data sets, and tools to generate synthetic data that can be used to test and evaluate linkage techniques. This book consists of fourteen chapters grouped into four parts, and two appendices. The first part introduces the reader to the topic of linking sensitive data, the second part covers methods and techniques to link such data, the third part discusses aspects of practical importance, and the fourth part provides an outlook of future challenges and open research problems relevant to linking sensitive databases. The appendices provide pointers and describe freely available, open-source software systems that allow the linkage of sensitive data, and provide further details about the evaluations presented. A companion Web site at https://dmm.anu.edu.au/lsdbook2020 provides additional material and Python programs used in the book. This book is mainly written for applied scientists, researchers, and advanced practitioners in governments, industry, and universities who are concerned with developing, implementing, and deploying systems and tools to share sensitive information in administrative, commercial, or medical databases. The Book describes how linkage methods work and how to evaluate their performance. It covers all the major concepts and methods and also discusses practical matters such as computational efficiency, which are critical if the methods are to be used in practice - and it does all this in a highly accessible way! David J. Hand, Imperial College, London.
Author: Peter Christen
Publisher:
ISBN: 3030597067
Category : Computer security
Languages : en
Pages : 476
Get Book Here
Book Description
This book provides modern technical answers to the legal requirements of pseudonymisation as recommended by privacy legislation. It covers topics such as modern regulatory frameworks for sharing and linking sensitive information, concepts and algorithms for privacy-preserving record linkage and their computational aspects, practical considerations such as dealing with dirty and missing data, as well as privacy, risk, and performance assessment measures. Existing techniques for privacy-preserving record linkage are evaluated empirically and real-world application examples that scale to population sizes are described. The book also includes pointers to freely available software tools, benchmark data sets, and tools to generate synthetic data that can be used to test and evaluate linkage techniques. This book consists of fourteen chapters grouped into four parts, and two appendices. The first part introduces the reader to the topic of linking sensitive data, the second part covers methods and techniques to link such data, the third part discusses aspects of practical importance, and the fourth part provides an outlook of future challenges and open research problems relevant to linking sensitive databases. The appendices provide pointers and describe freely available, open-source software systems that allow the linkage of sensitive data, and provide further details about the evaluations presented. A companion Web site at https://dmm.anu.edu.au/lsdbook2020 provides additional material and Python programs used in the book. This book is mainly written for applied scientists, researchers, and advanced practitioners in governments, industry, and universities who are concerned with developing, implementing, and deploying systems and tools to share sensitive information in administrative, commercial, or medical databases. The Book describes how linkage methods work and how to evaluate their performance. It covers all the major concepts and methods and also discusses practical matters such as computational efficiency, which are critical if the methods are to be used in practice - and it does all this in a highly accessible way! David J. Hand, Imperial College, London.
Author: Tom Heath
Publisher: Springer Nature
ISBN: 303179432X
Category : Mathematics
Languages : en
Pages : 122
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Book Description
The World Wide Web has enabled the creation of a global information space comprising linked documents. As the Web becomes ever more enmeshed with our daily lives, there is a growing desire for direct access to raw data not currently available on the Web or bound up in hypertext documents. Linked Data provides a publishing paradigm in which not only documents, but also data, can be a first class citizen of the Web, thereby enabling the extension of the Web with a global data space based on open standards - the Web of Data. In this Synthesis lecture we provide readers with a detailed technical introduction to Linked Data. We begin by outlining the basic principles of Linked Data, including coverage of relevant aspects of Web architecture. The remainder of the text is based around two main themes - the publication and consumption of Linked Data. Drawing on a practical Linked Data scenario, we provide guidance and best practices on: architectural approaches to publishing Linked Data; choosing URIs and vocabularies to identify and describe resources; deciding what data to return in a description of a resource on the Web; methods and frameworks for automated linking of data sets; and testing and debugging approaches for Linked Data deployments. We give an overview of existing Linked Data applications and then examine the architectures that are used to consume Linked Data from the Web, alongside existing tools and frameworks that enable these. Readers can expect to gain a rich technical understanding of Linked Data fundamentals, as the basis for application development, research or further study. Table of Contents: List of Figures / Introduction / Principles of Linked Data / The Web of Data / Linked Data Design Considerations / Recipes for Publishing Linked Data / Consuming Linked Data / Summary and Outlook
Author: David Wood
Publisher: Springer Science & Business Media
ISBN: 1441976655
Category : Computers
Languages : en
Pages : 318
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Book Description
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.
Author: Nigel Fielding
Publisher: SAGE Publications, Incorporated
ISBN:
Category : Reference
Languages : en
Pages : 100
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Book Description
In the light of recent theoretical and methodological advances Linking Data describes the ways in which substantive problems and research issues can be tackled effectively through the inter-relationship of quantitative and qualitative data. They also include a discussion of multi-method research which is critical of the naive assumption that using several different methods necessarily ensures the validity of research findings.
Author: Sören Auer
Publisher: Springer
ISBN: 3319098462
Category : Computers
Languages : en
Pages : 218
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Book Description
Linked Open Data (LOD) is a pragmatic approach for realizing the Semantic Web vision of making the Web a global, distributed, semantics-based information system. This book presents an overview on the results of the research project “LOD2 -- Creating Knowledge out of Interlinked Data”. LOD2 is a large-scale integrating project co-funded by the European Commission within the FP7 Information and Communication Technologies Work Program. Commencing in September 2010, this 4-year project comprised leading Linked Open Data research groups, companies, and service providers from across 11 European countries and South Korea. The aim of this project was to advance the state-of-the-art in research and development in four key areas relevant for Linked Data, namely 1. RDF data management; 2. the extraction, creation, and enrichment of structured RDF data; 3. the interlinking and fusion of Linked Data from different sources and 4. the authoring, exploration and visualization of Linked Data.
Author: Seth van Hooland
Publisher: Facet Publishing
ISBN: 1856049647
Category : Language Arts & Disciplines
Languages : en
Pages : 273
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Book Description
This highly practical handbook teaches you how to unlock the value of your existing metadata through cleaning, reconciliation, enrichment and linking and how to streamline the process of new metadata creation. Libraries, archives and museums are facing up to the challenge of providing access to fast growing collections whilst managing cuts to budgets. Key to this is the creation, linking and publishing of good quality metadata as Linked Data that will allow their collections to be discovered, accessed and disseminated in a sustainable manner. This highly practical handbook teaches you how to unlock the value of your existing metadata through cleaning, reconciliation, enrichment and linking and how to streamline the process of new metadata creation. Metadata experts Seth van Hooland and Ruben Verborgh introduce the key concepts of metadata standards and Linked Data and how they can be practically applied to existing metadata, giving readers the tools and understanding to achieve maximum results with limited resources. Readers will learn how to critically assess and use (semi-)automated methods of managing metadata through hands-on exercises within the book and on the accompanying website. Each chapter is built around a case study from institutions around the world, demonstrating how freely available tools are being successfully used in different metadata contexts. This handbook delivers the necessary conceptual and practical understanding to empower practitioners to make the right decisions when making their organisations resources accessible on the Web. Key topics include: - The value of metadata Metadata creation – architecture, data models and standards - Metadata cleaning - Metadata reconciliation - Metadata enrichment through Linked Data and named-entity recognition - Importing and exporting metadata - Ensuring a sustainable publishing model. Readership: This will be an invaluable guide for metadata practitioners and researchers within all cultural heritage contexts, from library cataloguers and archivists to museum curatorial staff. It will also be of interest to students and academics within information science and digital humanities fields. IT managers with responsibility for information systems, as well as strategy heads and budget holders, at cultural heritage organisations, will find this a valuable decision-making aid.
Author: David Wood
Publisher: Springer Science & Business Media
ISBN: 1461417678
Category : Computers
Languages : en
Pages : 248
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Book Description
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.
Author: Jeff Z. Pan
Publisher: Springer
ISBN: 3319456547
Category : Computers
Languages : en
Pages : 281
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Book Description
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.
Author: Deepak P
Publisher: Springer
ISBN: 3030018725
Category : Technology & Engineering
Languages : en
Pages : 343
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Book Description
This book highlights research in linking and mining data from across varied data sources. The authors focus on recent advances in this burgeoning field of multi-source data fusion, with an emphasis on exploratory and unsupervised data analysis, an area of increasing significance with the pace of growth of data vastly outpacing any chance of labeling them manually. The book looks at the underlying algorithms and technologies that facilitate the area within big data analytics, it covers their applications across domains such as smarter transportation, social media, fake news detection and enterprise search among others. This book enables readers to understand a spectrum of advances in this emerging area, and it will hopefully empower them to leverage and develop methods in multi-source data fusion and analytics with applications to a variety of scenarios. Includes advances on unsupervised, semi-supervised and supervised approaches to heterogeneous data linkage and fusion; Covers use cases of analytics over multi-view and heterogeneous data from across a variety of domains such as fake news, smarter transportation and social media, among others; Provides a high-level overview of advances in this emerging field and empowers the reader to explore novel applications and methodologies that would enrich the field.
Author: Philipp Cimiano
Publisher: Springer Nature
ISBN: 3030302253
Category : Computers
Languages : en
Pages : 286
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Book Description
This is the first monograph on the emerging area of linguistic linked data. Presenting a combination of background information on linguistic linked data and concrete implementation advice, it introduces and discusses the main benefits of applying linked data (LD) principles to the representation and publication of linguistic resources, arguing that LD does not look at a single resource in isolation but seeks to create a large network of resources that can be used together and uniformly, and so making more of the single resource. The book describes how the LD principles can be applied to modelling language resources. The first part provides the foundation for understanding the remainder of the book, introducing the data models, ontology and query languages used as the basis of the Semantic Web and LD and offering a more detailed overview of the Linguistic Linked Data Cloud. The second part of the book focuses on modelling language resources using LD principles, describing how to model lexical resources using Ontolex-lemon, the lexicon model for ontologies, and how to annotate and address elements of text represented in RDF. It also demonstrates how to model annotations, and how to capture the metadata of language resources. Further, it includes a chapter on representing linguistic categories. In the third part of the book, the authors describe how language resources can be transformed into LD and how links can be inferred and added to the data to increase connectivity and linking between different datasets. They also discuss using LD resources for natural language processing. The last part describes concrete applications of the technologies: representing and linking multilingual wordnets, applications in digital humanities and the discovery of language resources. Given its scope, the book is relevant for researchers and graduate students interested in topics at the crossroads of natural language processing / computational linguistics and the Semantic Web / linked data. It appeals to Semantic Web experts who are not proficient in applying the Semantic Web and LD principles to linguistic data, as well as to computational linguists who are used to working with lexical and linguistic resources wanting to learn about a new paradigm for modelling, publishing and exploiting linguistic resources.
