Learn about the different types of metadata and their role in today's digital era. Discover the role of metadata in corporate data management.

In today's digital era, marked by a continuous influx of increasingly complex information, metadata assumes profound importance. Serving as an invisible architect, it provides structure and meaning to the rising tide of data that surrounds us.

Metadata, the eternal mysteries of the world of data, plays a crucial role in the organisation, search and understanding of information. Beyond the online world, metadata is highly relevant when working with data in any form and is essential for corporate data management and compliance with data governance and data quality policies.

In the age of Big Data, IoT and cloud computing, metadata has gained unprecedented relevance. In the midst of exponential information growth, effective metadata management emerges as a valuable resource to improve operational efficiency and facilitate strategic decision-making, thereby contributing to competitive advantage.

What is metadata?

Metadata is basically data that provides information about other data. That is, it is data about other data. Its role is to describe, contextualise, organise and provide details about other data so that it can be easily located, used, understood and managed. In journalistic terms, metadata is the "what, where, when, how and who" of data.

Metadata can contain a wide variety of information, such as the origin, structure, format, context and quality of the data. Because of the variety of aspects that metadata can address, we can classify between different types of metadata according to the information they provide, a classification that we explore below.

Etymologically, "metadata" comes from the Greek word "μετα" meaning "beyond" and the Latin word "data" which translates as "data". In other words, metadata literally means "beyond data". In this sense, the term itself tells us that metadata are not isolated entities, but information that describes and goes beyond other data sets. In computing, this idea manifests itself both in the individual analysis of metadata and in situations where a group of metadata characterises a set of data or resources.

Metadata is therefore essential in environments where large amounts of information are handled, as it facilitates the management of information and promotes its effective use.

Types of metadata

As we have already seen, there are different types of metadata that are classified according to the type of information they contain about other data.

Because in the world of information few things are black and white, there is no single classification of metadata. However, this time we will focus on the 8 types of metadata that data experts usually distinguish between.

Descriptive Metadata

Descriptive metadata is a category of metadata that provides information about the content and characteristics of data. This metadata focuses on describing what the data is, making it easier to understand, search and manage the information.

Descriptive metadata typically contains information such as:

  • Title: The title of the resource, providing a brief description of the content.
  • Author: The creator or responsible party of the data.
  • Creation Date: The date when the data was created.
  • Keywords: Terms or phrases summarizing the key topics or concepts addressed in the data.
  • Summary: A text providing an overview of the content, summarizing the main information.
  • Language: The language in which the data is written or presented.
  • File Format: The type of file format in which the data is stored (e.g., PDF, JPEG, MP3, etc.).
  • Content Type: The nature of the content, such as text, image, audio, video, etc.
  • Categories or Themes: Labels indicating the category or theme to which the data belongs.

Descriptive metadata is essential for organising and retrieving data efficiently, especially in large information sets. It facilitates indexing, searching and understanding of content, allowing users to quickly find the relevant information they are looking for.

Administrative Metadata

Administrative metadata provides information on the management and administration of the data. This metadata is essential to ensure the integrity, accessibility and proper use of the information. Within this group of metadata, a distinction is generally made between:

  • Technical administrative metadata: Technical details about the data, such as file format, size, resolution, etc.
  • Rights administrative metadata: Information about copyright and legal restrictions associated with the data.

On the other hand, administrative metadata often contains information such as:

  • File Format: Indicates the specific format in which the information is stored, such as PDF, JPEG, DOCX, etc.
  • File Size: Displays the size of the file in bytes or kilobytes.
  • Media Type: Specifies the type of media in which the information is found, whether digital, analog, printed, etc.
  • Creation Date: Indicates when the data was initially created.
  • Modification Date: Shows the most recent date when changes were made to the data.
  • Copyright and Licensing: Informs about the copyright rights associated with the data and the conditions under which they can be used.
  • Access Restrictions: Details any limitations or requirements to access the data, including security restrictions.
  • Unique Identifiers: Provides unique codes or numbers that uniquely identify the data, such as DOI (Digital Object Identifier) or ISBN (International Standard Book Number).
  • Versions: Indicates the specific version of the data, especially relevant in situations where the data may change over time.
  • Revision History: Records the changes made to the data over time, including who made the changes and when.
  • Technical Metadata: Offers technical details about the data, such as image resolution, audio bitrate, etc.

Administrative metadata is crucial for the efficient management of information resources and to ensure that data is used and shared appropriately and in accordance with established policies.

Structural Metadata

Structural metadata is a category of metadata that describes the internal organisation and relationships between the different parts of a dataset. That is, metadata for a book would provide information about the chapters of the book. 

This metadata facilitates the understanding and navigation of the data and usually contains such information:

  • Hierarchy: Indicates the hierarchical relationship between different levels of data. For example, in a book, structural metadata might describe the relationship between chapters, sections and paragraphs.
  • Relationships: Describes the connections or relationships between different sets of data. For example, in a database, structural metadata might indicate how tables relate to each other.
  • Order: Specifies the order or sequence of the data. For example, in an ordered list of items, structural metadata would indicate the specific order.
  • Indexes: Indicates the presence of indexes or markers that facilitate efficient search and retrieval of information in a dataset.

Process Metadata

Process metadata is a type of metadata that contains detailed information on how data were created, modified or processed throughout their lifecycle. Process metadata is essential to understand the context and history of the data, as well as to ensure the reproducibility and quality of the results.

Examples of process metadata include:

  • Version History: Tracks the evolution of data over time, detailing the various versions, changes, and revisions that have taken place.
  • Creation Process: Outlines the steps and methods used to generate the data, from initial collection to final creation.
  • Transformations: Highlights any transformation or manipulation processes applied to the data, such as filters, format conversions, or aggregations.
  • Software and Tools: Lists the programs and tools utilized during data creation, manipulation, or analysis.
  • Configuration Parameters: Includes the values and settings used in data-related processes.
  • Data Sources: Identifies the original data sources and any transformations applied to them.
  • Process Stakeholders: Specifies individuals responsible for each step of the process, providing insights into authorship and contributions.
  • Processing Dates: Records the dates and timestamps associated with each stage of data processing.

This metadata is crucial to ensure transparency and reproducibility in research, data analysis and other activities related to information processing. They also facilitate the validation and verification of results, as well as the identification of possible problems or errors in the process.

Usage Metadata

Usage metadata includes information on how a dataset may be used. This metadata is useful for understanding the conditions and restrictions associated with the use of the data.

Usage metadata typically contains the following information:

  • Usage License: Specifies the terms and conditions under which the data can be used. This may include information on redistribution, modification, and legal restrictions.
  • Access Restrictions: Indicates any limitations or requirements to access the data, such as the need for special permissions, authentication, or geographical restrictions.
  • Expiration Date: In some cases, especially for datasets with a limited validity period, information is provided on the expiration or expiry date of the data.
  • Educational Use: Indicates if the data is specifically intended for educational purposes and how it can be used in academic environments.
  • Commercial Use: Provides details on restrictions or conditions related to using the data for commercial purposes.
  • Attribution: Indicates whether it is necessary to give credit to the original author or provide specific attribution when using the data.
  • Non-Commercial Use: May specify if the data is exclusively intended for non-commercial use.
  • Citation Requirements: Provides instructions on how to correctly cite the data when using it in reports, publications, or other forms of communication.

This type of metadata is essential for users to understand the limitations and permissions associated with a dataset. Usage metadata facilitates compliance with the conditions of use set by the owners or creators of the data and helps to prevent inappropriate or unauthorised use. In addition, usage metadata contributes to transparency and ethics in the use of information.

Location Metadata

Location metadata is a type of metadata that provides information about the location of other data.

Location metadata is commonly divided into two main categories: geographic metadata, which describes the spatial location of the data, and temporal metadata, which focuses on time-related information.

Geographic Metadata:

  • Geographic Coordinates: Specify the precise position on Earth's surface using coordinates, such as latitude and longitude.
  • Coordinate System: Indicates the spatial reference system used to define the coordinates, such as the Geographic Coordinate System (WGS84) or a specific projection system.
  • Altitude or Elevation: Provides information on the height or elevation of a point in relation to a reference level, such as sea level.
  • Administrative Location: Describes the location in terms of political or administrative divisions, such as country, state, province, city, etc.
  • Location Accuracy: Indicates the precision or margin of error associated with the provided geographic coordinates.
  • Observation Date and Time: Records the exact date and time when the geospatial data observation or capture was made.
  • Topographic Information: May include details about the area's topography represented in the data, such as terrain, bodies of water, and other geographical features.
  • Routes or Trajectories: In cases of tracking or movement data, metadata describing the routes or trajectories followed can be provided.

Temporary Metadata:

  • Creation Date and Time: Indicates when the data was first generated.
  • Modification Date and Time: Shows the most recent date and time when changes were made to the data.
  • Validity Dates: Specifies the period during which the data is considered valid or relevant.
  • Publication Dates: Indicates when the data was first published.
  • Time Intervals: In some cases, temporal metadata can specify relevant time intervals for interpreting the data.
  • Update Frequency: Informs about how often the geographical or temporal data is updated.

This metadata is crucial for the interpretation and analysis of information according to its geographical and temporal context. They are also fundamental for interoperability and data exchange between different systems and applications.

Social metadata captures information about the social interactions and relationships associated with a dataset or content. This metadata provides social context and can include details about participation, feedback and social influence.

Examples of social metadata include:

  • Comments and Annotations: Information regarding user comments and annotations related to the content.
  • Likes and Favorites: The number of times the content has been marked as "Like" or favorited by users.
  • Social Media Shares: Indicates how many times the content has been shared on social media platforms and provides links to those shares.
  • Followers or Subscribers: The amount of users following or subscribed to the content creator.
  • Ratings and Reviews: Numeric evaluations or comments provided by users to express their opinion on the content.
  • Viewing History: Information on how many times the content has been viewed or accessed by other users.
  • Social Tags: Keywords or tags that users assign to the content to describe or socially categorize it.
  • Engagement in Discussions: Indicates user participation in discussions or debates related to the content.

This type of data is particularly relevant for online platforms, social networks and online communities where social interaction is critical. They provide valuable information on the popularity, reception and influence of content within an online community, which can be useful for understanding trends, assessing content quality and encouraging engagement.

Security Metadata:

Security metadata is a type of metadata that contains details on aspects related to security and data protection. This metadata is crucial to ensure the confidentiality, integrity and availability of information.

Examples of security metadata include:

  • Access Levels: Indicates who has permission to access the data and what type of access is granted to them (read, write, delete, etc.).
  • Roles and Responsibilities: Describes the specific roles of users and their responsibilities in relation to data security.
  • Geographical Access Restrictions: Specifies limitations on where the data can be accessed from, such as geographical constraints or network restrictions.
  • Digital Signatures: Provides information on digital signatures used to verify the authenticity and integrity of the data.
  • Audit Trail: Details information on security events, including who accessed the data, when, and what actions were taken.
  • Encryption: Indicates whether the data is encrypted and, if so, what algorithms and keys are used.
  • Retention Period: Specifies the duration for which data must be retained before being deleted or archived.
  • Password Policies: Informs about the policies established for password creation and management, including complexity, expiration, etc.
  • Sensitivity Levels: Classifies data based on its sensitivity level, helping to determine the necessary security controls.
  • Access Controls: Describes the mechanisms and controls used to regulate access to data, such as multi-factor authentication, role-based access control, etc.

This metadata is essential to ensure that data is handled securely and complies with privacy and security requirements. It facilitates the implementation and monitoring of security policies, as well as the identification and response to potential security threats or breaches.

The role of metadata in data management

Metadata plays a critical role in an organisation's data management. It facilitates efficient search, enables interpretation and understanding of data, aids in version management and change control, and plays a crucial role in security and compliance.

Metadata is also essential to data governance policies within an organisation, as it acts as informative labels that are vital for data owners to understand, manage and use data effectively.

By providing detailed context about data, metadata improves the efficiency of data-driven decision making, ensures quality and enables more effective management of information throughout its lifecycle.

Efficient Discovery and Search: Metadata enables users to swiftly identify and locate specific datasets. By providing details on content, structure, and data location, it streamlines the search process, enhancing accessibility and information utility.

Interpretation and Understanding: Offering context on data nature, origin, and significance, metadata is essential for users to grasp data quality, relevance for a specific purpose, and proper interpretation.

Version Management and Change Control: Version and change metadata provide a detailed history of data modifications. This is crucial for version management, ensuring data integrity, and allowing precise tracking of alterations over time.

Security and Regulatory Compliance: Security metadata offers vital information on data access, implemented security controls, and associated restrictions. This is essential for data security assurance and compliance with regulatory and legal requirements.

Performance Optimization: Including technical details like file format, database structure, and other technical aspects, metadata contributes to performance optimization by facilitating the selection of appropriate tools and processes for efficient data manipulation and processing.

Ultimately, metadata enriches data management by improving the visibility, interpretation and reliability of information. It facilitates informed decision-making, ensures data integrity and contributes to more effective information management in the organisational environment.



Metadata plays a crucial role in an organization's data management, providing context, enhancing search efficiency, improving data interpretation and understanding, and ensuring security and regulatory compliance. Furthermore, metadata facilitates version control and change management, optimizes performance, and contributes to more effective information handling. Recognizing the significance of metadata in data-driven decision-making and enhancing efficiency in the organizational environment is essential.

Posted by Núria Emilio