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Metadata Course
More than 2 million students worldwide

Metadata Course

Master every layer of metadata — from foundational concepts to enterprise governance and semantic web technologies. This course gives data professionals, information managers, and analysts the practical skills to design, implement, and sustain metadata programs that drive real organizational value. If your work depends on finding, trusting, and using data, this is the training you need.

Dedika for Business

What you will learn:

You will gain a solid understanding of metadata types, standards, and schemas across industries, from Dublin Core and MARC to ISO 19115 and enterprise frameworks. You’ll learn to create and capture metadata manually and with automated extraction tools, and to design controlled vocabularies, thesauri, and taxonomies that reduce ambiguity and improve retrieval. The course covers metadata quality dimensions, governance frameworks, and data stewardship roles so you can lead programs that remain accurate. You will also apply metadata in relational databases, data warehouses, and data catalogs, and explore semantic‑web technologies such as RDF, SPARQL, and Schema.org. Finally, you will craft a metadata strategy aligned with business goals and a roadmap to advance program maturity.

How you study in practice Metadata Course

How you practise Metadata Course

For companies looking to train their team

With Dedika for Business, the course includes exercises and examples tailored to your own business and the way your company needs.

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Course Content

8 Chapters • 39 LessonsDuration between 4 and 360 hours (you decide)

Chapter 1See details

Foundations of Metadata

  • Lesson 1 • Core Types of Metadata

    Covers descriptive, structural, administrative, and technical metadata types. Students map each type to practical use cases in information management.

  • Lesson 2 • Defining Metadata and Its Purpose

    Introduces the formal definition of metadata and distinguishes it from raw data. Establishes the conceptual baseline for all subsequent chapters.

  • Lesson 3 • Metadata in Information Ecosystems

    Examines how metadata functions within libraries, databases, and digital platforms. Connects metadata theory to real organizational workflows.

  • Lesson 4 • History and Evolution of Metadata

    Traces metadata practices from card catalogs to modern digital standards. Provides historical context that explains current conventions and terminology.

Chapter 2See details

Metadata Standards and Schemas

  • Lesson 1 • Business and Enterprise Metadata Schemas

    Examines schemas used in corporate data governance and asset management contexts. Students align schema elements with business data requirements.

  • Lesson 2 • Bibliographic and Library Standards

    Covers widely used bibliographic schemas for describing documents and resources. Students apply element sets to catalog sample materials accurately.

  • Lesson 3 • Geospatial and Scientific Metadata Standards

    Introduces standards for geographic and scientific datasets, emphasizing domain-specific requirements. Connects schema choice to data discovery and reuse.

  • Lesson 4 • Evaluating and Selecting Schemas

    Provides a decision framework for comparing and selecting metadata schemas. Students practice schema evaluation using real-world information scenarios.

  • Lesson 5 • Understanding Metadata Standards

    Explains what a metadata standard is and why interoperability depends on them. Frames standards as shared agreements that enable consistent data exchange.

Chapter 3See details

Metadata Creation and Capture

  • Lesson 1 • Metadata Templates and Forms

    Guides students in designing reusable metadata templates that enforce consistency. Templates are connected to schema requirements and workflow integration.

  • Lesson 2 • Batch Metadata Processing

    Introduces techniques for applying metadata to large collections efficiently. Students practice bulk operations while maintaining record accuracy.

  • Lesson 3 • Manual Metadata Entry Techniques

    Teaches structured approaches to entering metadata fields accurately by hand. Emphasizes consistency, completeness, and adherence to schema rules.

  • Lesson 4 • Automated Metadata Extraction

    Covers tools and methods that extract metadata automatically from files and systems. Students configure extraction workflows and validate output quality.

  • Lesson 5 • Metadata for Different Content Types

    Addresses unique metadata requirements for text, images, audio, video, and datasets. Students apply appropriate fields and values for each content category.

Chapter 4See details

Controlled Vocabularies and Taxonomies

  • Lesson 1 • Thesaurus Construction and Use

    Covers the structure of thesauri including broader, narrower, and related term relationships. Students build a small thesaurus from a defined subject domain.

  • Lesson 2 • Taxonomy Design and Hierarchy

    Teaches hierarchical classification principles used in organizational taxonomies. Students design a multi-level taxonomy for a realistic content collection.

  • Lesson 3 • Principles of Controlled Vocabularies

    Defines controlled vocabularies and explains their role in reducing ambiguity. Connects vocabulary control to improved search precision and recall.

  • Lesson 4 • Ontologies and Semantic Relationships

    Introduces ontologies as richer knowledge structures beyond simple hierarchies. Students distinguish ontology components and their metadata applications.

  • Lesson 5 • Maintaining and Updating Term Lists

    Addresses lifecycle management of vocabularies including term addition and deprecation. Students apply governance workflows to keep vocabularies current and consistent.

Chapter 5See details

Metadata Quality and Governance

  • Lesson 1 • Data Stewardship and Ownership

    Defines data stewardship roles and clarifies ownership distinctions in metadata management. Connects stewardship to day-to-day quality maintenance activities.

  • Lesson 2 • Metadata Governance Frameworks

    Introduces governance structures including roles, policies, and accountability mechanisms. Students draft a governance charter for a hypothetical metadata program.

  • Lesson 3 • Metadata Auditing Techniques

    Covers systematic methods for auditing metadata repositories to identify defects. Students conduct a structured audit using checklists and scoring rubrics.

  • Lesson 4 • Dimensions of Metadata Quality

    Defines quality dimensions such as accuracy, completeness, consistency, and timeliness. Students apply each dimension to evaluate sample metadata records.

  • Lesson 5 • Remediation and Continuous Improvement

    Provides strategies for correcting metadata defects and sustaining quality over time. Students build a remediation plan with prioritized corrective actions.

Chapter 6See details

Metadata in Data Management Systems

  • Lesson 1 • Data Lineage and Provenance

    Teaches how to document and trace data origins, transformations, and movements. Students map lineage for a sample data pipeline using standard notation.

  • Lesson 2 • Metadata APIs and Integration

    Introduces programmatic access to metadata through APIs and integration patterns. Students design a metadata exchange workflow between two systems.

  • Lesson 3 • Data Catalogs and Asset Inventories

    Covers the purpose and architecture of enterprise data catalogs for asset discovery. Students populate a catalog with business and technical metadata.

  • Lesson 4 • Metadata in Data Warehouses and Lakes

    Addresses metadata challenges specific to large-scale analytical environments. Students apply zone-based metadata strategies for data lake management.

  • Lesson 5 • Metadata in Relational Databases

    Examines how schemas, data dictionaries, and system catalogs store metadata in relational systems. Students read and interpret database metadata artifacts.

Chapter 7See details

Semantic Web and Linked Data Metadata

  • Lesson 1 • RDF and Linked Data Principles

    Covers the Resource Description Framework as the foundation for linked metadata. Students write and parse RDF triples in multiple serialization formats.

  • Lesson 2 • Schema.org and Structured Markup

    Examines Schema.org vocabularies for embedding metadata in web content. Students implement structured markup to improve search engine discoverability.

  • Lesson 3 • SPARQL for Metadata Querying

    Teaches SPARQL query language for retrieving and filtering linked metadata. Students write queries against public endpoints to extract meaningful results.

  • Lesson 4 • Semantic Web Fundamentals

    Introduces the architecture of the semantic web and the role of metadata within it. Students map the semantic web stack from URIs to reasoning layers.

  • Lesson 5 • Publishing and Consuming Linked Datasets

    Guides students through publishing a linked dataset and consuming external linked data. Connects publishing practices to open data and interoperability goals.

Chapter 8See details

Strategic Metadata Management

  • Lesson 1 • Aligning Metadata with Business Goals

    Connects metadata program objectives to measurable organizational outcomes. Students identify business drivers and translate them into metadata requirements.

  • Lesson 2 • Metadata Program Maturity Models

    Introduces maturity frameworks for assessing and advancing metadata program capability. Students score a sample organization and identify improvement priorities.

  • Lesson 3 • Building a Metadata Strategy Document

    Guides students through drafting a comprehensive metadata strategy with scope and priorities. Each component is tied to governance, quality, and technology decisions.

  • Lesson 4 • Change Management for Metadata Initiatives

    Addresses organizational resistance and adoption challenges in metadata programs. Students apply change management techniques to a metadata rollout scenario.

  • Lesson 5 • Measuring Metadata Program Success

    Defines key performance indicators and reporting mechanisms for metadata programs. Students build a dashboard framework to track program health over time.

Certification

Your valid completion certificate

This course is for you:

  • Data analysts: who need structured, reliable information to produce trustworthy insights.

  • Library and information professionals: ready to extend their cataloging expertise into digital environments.

  • Records managers: responsible for retention, classification, and compliance across large content collections.

  • Business intelligence developers: building pipelines where data discoverability and lineage matter most.

  • Career changers from research or academia: bringing domain knowledge into data management roles.

  • Content operations specialists: managing large creative or media asset libraries at scale.

What our students say

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