Metadata, Third Edition—eEditions PDF e-book

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Named a 2017 Choice Outstanding Academic Title

Featuring new developments driven by semantic technologies and digital data and information, with an accompanying website and supplementary learning materials, this remains the definitive primer on metadata for students, instructors, faculty, and professionals at all levels of experience.

This benchmark text is back in a new edition thoroughly updated to incorporate developments and changes in metadata and related domains. Zeng and Qin provide a solid grounding in the variety and interrelationships among different metadata types, offering a comprehensive look at the metadata schemas that exist in the world of library and information science and beyond. Readers will gain knowledge and an understanding of key topics such as

  • the fundamentals of metadata, including principles of metadata, structures of metadata vocabularies, and metadata descriptions;
  • metadata building blocks, from modeling to defining properties, from designing application profiles to implementing value vocabularies, and from specification generating to schema encoding, illustrated with new examples;
  • best practices for metadata as linked data, the new functionality brought by implementing the linked data principles, and the importance of knowledge organization systems;
  • resource metadata services, quality measurement, and interoperability approaches; 
  • research data management concepts like the FAIR principles, metadata publishing on the web and the recommendations by the W3C in 2017, related Open Science metadata standards such as Data Catalog Vocabulary (DCAT) version 2, and metadata-enabled reproducibility and replicability of research data;
  • standards used in libraries, archives, museums, and other information institutions, plus existing metadata standards’ new versions, such as the EAD 3, LIDO 1.1, MODS 3.7, DC Terms 2020 release coordinating its ISO 15396-2:2019, and’s update in responding to the pandemic; and
  • newer, trending forces that are impacting the metadata domain, including entity management, semantic enrichment for the existing metadata, mashup culture such as enhanced Wikimedia contents, knowledge graphs and related processes, semantic annotations and analysis for unstructured data, and supporting digital humanities (DH) through smart data.

A supplementary website provides additional resources, including examples, exercises, main takeaways, and editable files for educators and trainers. Examination copies are available for instructors who are interested in adopting this title for course use. This e-book is also available for libraries and individuals through aggregators and other distributors—ask your current vendor or contact us for more information.

List of Illustrations

List of Exhibits

List of Tables



Part I   Fundamentals of Metadata

ONE    Introduction

1.1 Background

1.2 Definitions

1.3 A Brief History

1.4 Types and Functions

1.5 Standards

1.6 Principles

1.7 Examples of Metadata Descriptions

1.8 Summary

Suggested Readings



TWO   Understanding Metadata Vocabularies

2.1 Metadata Element Sets

2.1.1 Components and Structures—An Overview

2.1.2 Flat Structure Dublin Core Metadata Element Set VRA Core 3.0

2.1.3 Nested Structure VRA Core 4.0

2.2 Application Profiles

2.2.1 The Concept of Application Profile (AP)

2.2.2 Examples of APs Consisting of Elements Drawn from Other Schemas

2.2.3 Sources of Reusable Elements

2.3 Ontologies as Metadata Vocabularies

2.3.1 Background

2.3.2 Modular Structure

2.3.3 Friend of a Friend (FOAF)


2.4 RDF Vocabularies for Metadata Terms

2.4.1 An Introduction to RDF (Resource Description Framework)

2.4.2 DCMI Metadata Terms

2.4.3 Metadata Descriptions: From “Records” to “Statements”

2.5 Conclusion

Suggested Readings



THREE           Creating Metadata Descriptions

3.1 Requirements for Metadata

3.2 Basic Unit of Metadata

3.2.1 Metadata Statement, Description, and Description Set

3.2.2 Relationships between Resources

3.3 Knowing the Difference

3.4 Levels of Granularity

3.4.1 Describing Individual Items That Constitute a Collection: Item-Level Description

3.4.2 Describing the Entirety of a Collection: Collection-Level Description

3.4.3 Dataset-Level Metadata

3.4.4 Resource Decomposition

3.5 Metadata Sources

3.5.1 Manual Generation of Metadata

3.5.2 Automatic Generation of Metadata

3.5.3 Combination of Manual and Automatic Methods

3.5.4 Harvested Metadata

3.5.5 Converted Metadata

3.5.6 User-Contributed Metadata

3.6 Metadata Storage

3.6.1 Internal Storage

3.6.2 External Storage

3.7 Expressing Metadata

3.7.1 HTML Embedded in the <head> Section Embedded in the <body> Section

3.7.2 XML

3.7.3 RDF/XML and Other RDF Serialization Formats

3.8 Linkage, Wrapper, Display, and Parallel Metadata

3.8.1 Linking between Descriptions for Different Resources       

3.8.2 Wrapping

3.8.3 Encoding for Display

3.8.4 Encoding for Bilingual Metadata Statements

3.9 Combining Metadata Descriptions and Linking Resources

3.9.1 METS

3.9.2 One RDF/XML Document Containing Multiple “Resource” Descriptions

3.9.3 Aggregation

3.10 Conclusion

Suggested Readings

Advanced Readings



Part II  Metadata Vocabulary Building Blocks

FOUR  Metadata Structures and Semantics

4.1 Modeling for Metadata

4.1.1 Entity-Relationship Modeling

4.1.2 Ontological Modeling

4.1.3 Encapsulated and Modularized Approaches

4.2 Enumerating Metadata Terms

4.2.1 Communicating about the Functional Requirements

4.2.2 Identifying Desired Elements

4.3 Metadata Vocabulary/Element Set Specification

4.3.1 Basic Components

4.3.2 Presentation

4.3.3 Principles for an Element Set to Follow

4.3.4 Methodologies for Working from an Existing Element Set

4.3.5 Testing the Element Set

4.4 Value Spaces and Value Vocabularies

4.4.1 Value Spaces That Should Follow Standardized Syntax Encoding Rules

4.4.2 Value Spaces That Require Standardized Vocabulary Encoding Schemes Standardized Codes Controlled Vocabularies Name Authorities

4.4.3 Value Spaces That Require Predefined Lists of Terms Why Predefined Lists of Terms Are Needed How to Develop a Predefined List of Terms How to Handle Authority Lists for Named and Unnamed Entities

4.5 Crosswalks

4.5.1 Methods Used in Crosswalking

4.5.2 Aligning Elements with Indicators of Matching Degrees

4.6 Best Practices Guides and Other Content Guidelines

4.6.1 Best Practices Guides

4.6.2 Scheme/Vocabulary-Specific Guidelines

4.6.3 Community-Oriented Best Practices Guides

4.6.4 Data Content Standards

4.7 Conclusion

Suggested Readings



FIVE   Metadata Schemas

5.1 Background

5.2 Resource Identification

5.3 Namespaces

5.4 Schema Encoding

5.4.1 Relational Schema

5.4.2 XML Schema

5.4.3 Schema Encoding in Mixed Namespaces

5.5 Encoding Examples of Metadata Vocabularies

5.5.1 Dublin Core Schemas

5.5.2 EAD3 XML Schema

5.6 Summary

Suggested Readings



Part III            Metadata Services

SIX      Metadata Services

6.1 Metadata Services as an Infrastructure

6.2 Metadata Registries

6.2.1 Functional Requirements

6.2.2 Types

6.2.3 Essential Components

6.3 Metadata Repositories

6.3.1 Features and Approaches

6.3.2 Metadata Harvesting Model

6.3.3 Support for Multiple Description Formats in OAI-PMH

6.4 Metadata as Linked Data

6.4.1 WHAT: Linked Data Principles           

6.4.2 WHY: Understanding the Situations—Metadata in Information Silos

6.4.3 WHO: Two Roles of LAMs and Information Institutions

6.4.4 WHERE: Discovering the Factors Inhibiting LAM Data’s Linkability

6.4.5 WHEN: Taking Actions in Different Steps/Phases for Different Situations

6.4.6 HOW: Applicable Methods and Strategies Using KOS as the Connectors of Linked Datasets Enriching the Structured Data Created as “Access Points” Creating Linked Data from Semi-structured Data Creating LOD from Unstructured Data

6.4.7 Moving Forward

6.5 Ensuring Optimal Metadata Discovery and Increasing Findability

6.5.1 Metadata Retrieval

6.5.2 Metadata Exposure Methods Serving Human Users with Innovative Ideas Exposing Data to Aggregators and Search Engines Exposing Metadata via API and Web Services Providing User-Friendly SPARQL Endpoints Providing Effective, Code-Free Data Exploration and Analysis Tools

6.6 Summary

Suggested Readings



SEVEN           Metadata Quality Measurement and Improvement

7.1 Quality of Metadata

7.2 Meeting the Functional Requirements

7.3 Quality Measurement with Different Granularities

7.4 Metadata Quality Measurement Indicators: CCCD

7.4.1 Completeness

7.4.2 Correctness

7.4.3 Consistency

7.4.4 Duplication Analysis

7.5 Metadata Evaluation

7.6 Enhancing Quality of Metadata

7.7 Entity-Level Quality for Reusable Metadata

7.7.1 Reusability

7.7.2 Actions for Providing Shareable and Reusable Datasets

7.8 New Challenges and Demands

7.8.1 Longevity of Metadata Vocabularies

7.8.2 Unique Identifiers

7.8.3 FAIRness Assessment for Open (Meta)data Repositories

7.9 Conclusion

Suggested Readings



EIGHT                        Achieving Interoperability

8.1 Interoperability Layers

8.2 Metadata Decisions at Different Stages of a Digital Collection Project

8.3 Achieving Interoperability at the Schema Development Stage

8.3.1 Derivation

8.3.2 Application Profiles (APs)

8.3.3 Crosswalks

8.3.4 Frameworks Europeana Data Model (EDM) International Image Interoperability Framework (IIIF)

8.3.5 Metadata Schema Registries

8.4 Achieving Interoperability at the Record Generation Stage

8.4.1 Conversion of Metadata Records

8.4.2 Data Reuse and Integration

8.5 Achieving Interoperability at the Metadata Repository Operation Stage

8.5.1 Metadata Repositories Based on the Open Archives Initiative (OAI) Protocol

8.5.2 Metadata Repositories Supporting Multiple Formats without Record Conversion

8.5.3 Aggregation and Enriched Metadata Records in a Repository

8.5.4 Element-Based and Value-Based Crosswalking Services

8.5.5 Value-Based Mapping for Cross-Database Searching

8.5.6 Value-Based Co-occurrence Mapping

8.6 Alignment Approaches Used for Linked Data

8.6.1 The Need for Alignment of Metadata Vocabularies

8.6.2 Alignment at Class Level

8.6.3 Alignment at Property Level

8.6.4 Mapping Degrees

8.7 Unifying Heterogeneous Contents in a Distributed Data Creation Environment

8.8 Conclusion

Suggested Readings



Part IV            Metadata Outlook in Research

NINE   Metadata Research Landscape

9.1 Overview

9.2 Research in Metadata Architecture

9.3 Research in Metadata Modeling

9.4 Research in Metadata Semantics

9.5 Metadata and Data-Driven X

9.6 Conclusions

Suggested Readings



Part V  Metadata Standards

TEN    Current Standards

10.1 Metadata for General Purposes

10.1.1 Dublin Core

10.1.2 MODS and the MARC Family The Reasons for MARC Transformation MARCXML Metadata Object Description Schema (MODS)

10.1.3 BIBFRAME Vocabulary

10.2 Metadata for Cultural Objects and Visual Resources

10.2.1 Introduction to CDWA

10.2.2 Important Concepts

10.2.3 Element Sets of CCO, CDWA Lite, LIDO, and VRA Core CCO (Cataloging of Cultural Objects) CDWA Lite and LIDO VRA Core Categories

10.2.4 Object ID Checklist

10.2.5 Value Vocabularies

10.3 Metadata for Research Data

10.3.1 Overview

10.3.2 Metadata Standards for Open Science Data Data Catalog Vocabulary (DCAT) DCAT Application Profiles

10.3.3 Metadata Standards for Geospatial Data

10.3.4 Metadata Standards for Biodiversity and Ecology Data

10.3.5 Metadata for Social Sciences Research Data

10.3.6 Other Developments

10.4 Metadata for Archives

10.4.1 Background

10.4.2 Finding Aid Examples

10.4.3 EAD 2002 at a Glance

10.4.4 EAC-CPF

10.4.5 EAD3

10.4.6 Related Standards

10.5 Rights Management Metadata

10.5.1 Rights Metadata Elements for User-Oriented Rights Information

10.5.2 Metadata Activities of Rights-Holder Communities DOI (Digital Object Identifier)

10.5.3 Open Digital Rights Language (ODRL)

10.6 Metadata for Publishing and Press Communications

10.6.1 ONIX (ONline Information eXchange)

10.6.2 EPUB

10.6.3 IPTC Metadata Standards

10.7 Metadata for Multimedia Objects

10.7.1 The MPEG Standards

10.7.2 MPEG-7

10.7.3 ID3v2

10.7.4 Pibcorn, the Public Broadcasting Metadata Dictionary

10.8 Preservation and Provenance Metadata

10.8.1 Digital Preservation Metadata Standards

10.8.2 OAIS Reference Model

10.8.3 Preservation Metadata: Implementation Strategies (PREMIS)

10.8.4 Preservation Metadata and Other Related Standards

10.8.5 PROV for Provenance Interchange on the Web

10.8.6 DCMI Metadata Terms for Provenance

10.9 Metadata Describing Agents

10.9.1 vCard

10.9.2 FOAF (Friend of a Friend)

10.10 Summary

Suggested Readings



Appendixes: The following appendixes are available online only.

A         Metadata Standards: Metadata Schemas, Application Profiles, and Registries

B         Value Encoding Schemes and Content Standards



About the Authors


Marcia Lei Zeng

Marcia Lei Zeng is Professor of Information Science at Kent State University in Kent, Ohio, where she teaches knowledge organization systems (KOS), metadata, Linked Data, and cultural heritage informatics. Her primary research interests include KOS, Linked Data, metadata, smart data and big data, database quality control, semantic technologies, and digital humanities. Her scholarly publications consist of more than 100 papers and six books, as well as over 200 national and international conference presentations, invited lectures, and keynote speeches. Her research projects have received funding from the National Science Foundation (NSF), Institute of Museum and Library Services (IMLS), OCLC, Ohio Board of Regents, Fulbright, and other esteemed academic and scientific foundations. Dr. Zeng has chaired or served on numerous committees, working groups, and executive boards for the International Federation of Library Associations and Institutions (IFLA), Special Libraries Association (SLA), Association of Information Science and Technology (ASIS&T), the US National Information Standards Organization (NISO), the International Organization for Standardization (ISO), Dublin Core Metadata Initiative (DCMI), International Society for Knowledge Organization (ISKO), and the World Wide Web Consortium (W3C). Dr. Zeng holds a PhD from the School of Computing and Information at the University of Pittsburgh in Pittsburgh, Pennsylvania.

Jian Qin

Jian Qin is Professor at the School of Information Studies, Syracuse University. Recipent of the 2020 LITA/OCLC Kilgour Research Award, her research interest areas include metadata, knowledge modeling and organization, ontologies, and scientific communication. Her research was funded by the Institute of Museum and Library Services, National Science Foundation, National Institute of Health/National Center for General Medical Science, Sloan Foundation/Interuniversity Consortium for Political and Social Research (ICPSR), and Online Computer Library Center (OCLC).She has published widely in scholarly journals and presented her research at national and international conferences, is the co-author of the book Metadata, and co-editor for several special journal issues on knowledge discovery in databases and knowledge representation. She has served on numerous committees in the Association of Information Science and Technology (ASIS&T), DCMI, and other professional communities and is a Distinguished Member of ASIS&T. She holds a Master of Science in Library and Information Science from Western University and a PhD from University of Illinois at Urbana-Champaign.

"Marcia Lei Zeng and Jian Qin have carefully updated the book’s contents to include materials from their analysis of job descriptions, theses, journal articles, dissertations, and proceedings related to metadata ... The text is ideal for practitioners and learners."
— Journal of Education for Library and Information Science

Praise for the second edition

"The second edition of this book represents much more than a serviceable update to the first edition, published in 2008. Zeng (Kent State Univ.) and Qin (Syracuse Univ.) have significantly revised their thinking about metadata construction, application, usability, and sustainability. As a result, the current edition of this seminal resource represents a radical and necessary shift to a richer, more comprehensive analysis of metadata and its uses ... A core reference work for all professionals and advanced students interested in the subject of metadata."
— Choice

"This is an impressive, well-written textbook for readers studying metadata. In a field that is steadily growing and changing, readers must keep abreast of the new material that appears in this edition, and not rely solely on the previous edition to inform their thinking. It is by no means an easy transition, though the authors have tried hard to include the relevant background that puts today's ideas in context. They have succeeded in making a complex subject understandable as well as anticipating future developments."
— Technicalities