• Descriptive Metadata

  Describe the content and characteristics of digital content. They are often used in libraries, archives, and databases. Examples: title, author, summary, keywords, descriptions.

• Administrative Metadata

  Support the management and maintenance of data records. They often contain information about the origin, authenticity, and management of the data. Examples: creation date, modification date, file format, access rights, licensing information.

• Provenance Metadata

  Provide information about the origin and the creation process of the data. They are crucial for the traceability and reliability of information. Examples: source origin, editing history, responsible persons or institutions.

• Reference Metadata

  Offer a link or reference between different datasets or resources. Examples: references to related datasets, citation information.

• Technical Metadata

  Describe the technical characteristics and requirements of the data. They are particularly important for the storage and processing of digital objects. Examples: file size, file type, resolution, software and hardware requirements.

• Legal Metadata

  Concern legal aspects and terms of use of data. They are important for compliance with copyright and data protection regulations. Examples: copyright information, terms of use, privacy regulations.

• Management Metadata

  Support the management and long-term preservation of data. Examples: archiving information, data backup protocols, format migration information.

• Geospatial Metadata

  Describe the geographical aspects of data. Examples: coordinates, map data, geographic coverage areas.

The Benefits and Added Value of Metadata

Discoverability of Knowledge Resources

Metadata make it possible to find educational content and research data in a qualified manner. One no longer has to deal with the results of a full-text search but can search for and filter content specifically, according to professional, methodological, and other criteria.

Exploitation of Knowledge Resources

With metadata, it is possible not only to describe the meaning of content but also their relationships to each other. This makes them an efficient tool for a versatile delivery of educational content or research data.

Multimodal Delivery of Educational Content or Research Findings

Metadata make it possible to provide educational content and research data in a user-specific manner. One can extract them specifically and share in multiple ways, multimodally with different users or user groups, specifically related to their interests and needs.

Automated Creation, Maintenance, and Delivery of Educational Content or Research Findings

Metadata enable the automated processing of educational content and research data. For example, for automated checking, supplementing, or translating. Here, Artificial Intelligence plays an increasingly larger role. They can do a lot even with unstructured content, but they definitely cope better with content that has been enriched with metadata. And they perform optimally.