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General Information

What is metadata?

In simple terms, metadata is used to describe (research) data. Accordingly, metadata can be very diverse. The date of acquisition and the reason for the acquisition of research data are among the relevant metadata for researchers. In addition, it should be noted which devices were used in the laboratory, for example, and with which settings, and how the subsequent analysis was carried out (e.g., tools & software used). In many fields nowadays, it is possible for metadata to be automatically collected and stored on an instrument, so that it only needs to be linked to the associated research data. This function is very practical and, above all, saves a lot of time in everyday work.


What are the advantages of metadata?

Researchers probably think first and foremost of the additional work involved in creating and notating metadata. However, this should not discourage the creation and saving of the appropriate metadata for a research project. According to the FAIR principles, metadata offer many advantages. The findability, for example, is increased by a metadata search. Thus, other researchers can search for the metadata after reading a publication, and ask the appropriate contact person for access to the research data. Information about the accessibility of the research data should also be noted in the metadata. This will precisely regulate who is allowed to have an insight into the data and who is not. Furthermore, it can also be specified how the data is secured. Such as a password or that external persons are only given one-time access to the data via a link. The possibilities are very diverse and thanks to metadata, the processes can be described in detail. This ensures that the research data can be reused even after the main staff members have left the company. In addition, to enable easy and problem-free reusability, the metadata (as well as the research data itself) should be stored using common file formats and software.

How is metadata captured?

Metadata can be captured both digitally and analogously. Digital capture is possible, for instance, when devices directly store the set values and these can be used. This includes, for example, the settings of a camera, such as focal length, ISO value or also the exposure time. These settings are often regulated by the camera itself and are individual for each image. In order to enable reproduction and comparability of the images, it is imperative that such settings are noted. Other metadata, such as author or journal after a publication, can often also be recorded digitally. The situation is different for older research data that was documented in non-digital lab books. These must first be digitized so that they can then be easily understood and reused. What guidance does exist for capturing metadata? The first time researchers consciously deal with metadata, it can be very overwhelming. How is one supposed to know already at the beginning of a project what metadata needs to be stored? And what is relevant to the project at hand anyway? After all, not all metadata can be written down, as this would take up far too much time. Therefore, it makes sense to use so-called metadata schemas as a guide. These summarize the most important metadata for certain areas. However, this is by no means a fixed pattern. Instead, these schemas serve much more for orientation and initial classification. Subsequently, the metadata schema suitable for the project can be extended and thus individualized as desired. If researchers are just starting out on a project, it makes sense to start thinking about metadata now. In addition, it is important to pay attention to a correct vocabulary and the corresponding ontologies of the research area. This is helpful so that external parties also understand the exact content of the data and misunderstandings are avoided. In the best case, the project is rolled up from the back to the front, i.e.: What would be needed in terms of data and corresponding metadata in the event of publication so that other researchers can reproduce the experiments without additional queries? This approach can be very helpful, especially at the beginning of a project, to establish the framework for metadata creation. Of course, research is dynamic and as the project progresses, the metadata recorded can be adjusted and added to. This maintains the necessary flexibility.