AIMS – Applying Interoperable Metadata Standards

 

Accurate and comprehensible documentation using metadata is crucial for the long-term findability and interpretability of research data. This applies both to the active use of the data during the research process and afterwards, when the data has already been archived. Metadata refers to all additional information (e.g. information on data format or publication) that is necessary for the interpretation of research data. Research data are (digital) data (e.g. audiovisual recordings, survey data) that are created during a research process or are its result. It is therefore particularly important in terms of findability that metadata follow documented standards that are tailored to specific requirements, such as the type of data or the scientific discipline - in this project mechanical engineering. In addition to suitable standards, scientists also need appropriate tools, methods and an infrastructure that supports the creation and use of metadata.

At present, however, these requirements are only met for a very limited number of scientific disciplines. For most disciplines, including mechanical engineering, no adequate metadata standards are available. For engineering, the collections of metadata standards maintained by the RDA Metadata Standards Directory Working Group and the Digital Curation Centre list only five standards, none of which are specific to engineering. In addition, the management of research data in the field of mechanical engineering is usually based on simple file systems and relies on the manual organisation of directories, files and metadata. As a result, metadata is created only on a case-by-case basis and is often stored inconsistently and untraceably.

The research project AIMS therefore pursues two main goals. The first is to create an environment that will enable scientists to create, exchange and reuse metadata standards that meet the specific needs of their discipline. This goal is integrated into the creation of interoperable standards for discipline-specific metadata and is considered a priority goal for successful research data management and is an important requirement at both federal and European level. The second goal is to develop tools and workflows that can be used for the effortless creation of standardized metadata.