Basics

What is Metadata?

Metadata refers to information data about research data. To ensure that published data is discoverable and comprehensible, it is essential to annotate it with additional information known as metadata.

An introduction to the topic of metadata can be found in this video:

Summarizing we can conclude that:

“Metadata plays a decisive role in the publication, finding and subsequent use of primary data. Metadata contains both administrative (researcher, location, time, etc.) and content-related information (variables, measuring instrument, coordination, etc.) on the stored data set. Especially in larger working groups, in which the staff changes over several years, it is necessary to document the data obtained so well that subsequent project members can clearly see what the data is about. If the data are stored in the repository after the project, the reuse and citability of the data increases if they are enriched with good metadata”.

University of Cologne (09.07.2023): Document Research Data

It can significantly facilitate your work in data documentation and curation, and moreover, enhance the quality of data submission when your data contributors use a tool for creating standardized metadata. This tool could, for instance, be the DataCite Metadata Generator. Using this generator, researchers can create standardized metadata for the research data they intend to submit to your FDZ. The result is an XML file containing interoperable metadata, which is handed over to you along with the data and associated documents. For later metadata updates, the file can be re-imported into the generator and edited.

This video tutorial gives an introduction to the metadata standard DataCite. It explains what DataCite is, how it is used and what tools can be helpful while using it.

Videotutorial on how to use the DataCite metadata standard. is licensed under a Creative Commons Attribution 4.0 International license. content from: DataCite

Standards for Metadata:

Some metadata is domain-specific, particularly concerning processes and content of research outcomes. For other metadata, especially bibliographic and administrative metadata, there are discipline-agnostic rules that can be identified.

Consequently, there is now a multitude of metadata standards available, which can be either generic or domain-specific in nature. These standards dictate, for example, the mandatory information that must be recorded, how research data should be described, or how metadata should be structured. Common metadata formats are for example:

1. DDI (Data Documentation Initiative): DDI is an internationally recognized standard for the documentation and description of social science data, data on human activities, and other data based on observation methods. It provides a comprehensive structure for describing datasets, variables, questionnaires, and other relevant information.
2. Dublin Core: Dublin Core is a simple and widely used metadata standard employed in various disciplines. It offers basic elements for describing resources, such as title, author, date, and keywords.
3. MARC (Machine-Readable Cataloging): MARC is a metadata format primarily used in libraries. It enables detailed descriptions of bibliographic information, such as title, author, publisher, and publication year.
4. METS (Metadata Encoding and Transmission Standard): METS is a standard for structuring and linking metadata in digital resources. It allows the integration of metadata from different sources into digital libraries or archival systems.
5. Qualitative Data Exchange Standard (QDEX): QDEX is a metadata standard specifically developed for the documentation of qualitative research data. It enables the description of interviews, transcriptions, codes, and other relevant information.

These are just a few examples, but there are many more metadata formats and standards that can be employed in the social sciences depening on the specific use case and research domain.

In addition a distinction is made between bibliographic, administrative, descriptive and process-related metadata:

• Bibliographic metadata, such as title, authors, description, or keywords, enable data and code citation and aid in discoverability and narrowing of the thematic scope.
• Administrative metadata concerning file types, locations, access rights, and licenses facilitate data management and long-term preservation.
• Content-descriptive or descriptive metadata can vary significantly depending on the discipline and provide additional information about the content and origin of the data.
• Process metadata describes the steps and actions, along with the methods and tools employed, during the generation and processing of data.

The following video from Ghent University illustrates the different types of metadata and describes the procedures used for research data description. It also mentions various metadata schemas: