Embedding semantics within research metadata serves to standardize, refine and contextualize it, thereby improving interoperability between data sources and promoting the FAIR principles. Within the Helmholtz Association, we are committed to evaluating existing semantic resources and established practices and to developing guidelines for their handling and use in the field of earth and...
In agrosystem science, the transition to a FAIR (Findable, Accessible, Interoperable, Reusable) data future is essential for fostering innovation and collaboration. While technical developments provide the necessary infrastructure, the true challenge lies in changing ingrained habits and cultural practices. To address this, the FAIRagro initiative has developed a participation concept aimed at...
The rapid evolution of research software necessitates efficient and accurate metadata management to ensure software discoverability, reproducibility, and overall project quality. However, manually curating metadata can be time-consuming and prone to errors. This poster presents two innovative tools designed to streamline and improve metadata management: fair-python-cookiecutter and...
Enriching data with metadata is a key concept for the data output of scientific
research to be FAIR. Data processing software and custom code often do not
support the annotation with metadata out-of-the-box or the usage process does
not mandate it. This confronts data creators and maintainers with challenges
to annotate their data. From a Human Machine Interface (HMI)...
Research data management (RDM) is an important aspect of modern scientific research, which is heavily relying on interconnected data sets and corresponding metadata. For modeling and integrating these interconnections and metadata, the Resource Description Framework (RDF) has often been proposed as a standard, since it has been in use by search engines and knowledge management systems for...
In our increasingly digital and interconnected world, the integration of Persistent Identifiers (PIDs) in metadata are essential for machine-readable and -understandable metadata as also described in the FAIR Guiding Principles for research data management. PIDs provide unique, permanent and machine-readable references to various types of digital objects, including publications, datasets,...
Software is important research output. Therefore, funding agencies are interested in the value that a software contributes to the overall results of a funded project. The Helmholtz Association is working towards a system to evaluate data and software publications. The "Task Group Helmholtz Quality Indicators for Data and Software Publications" has already published a vision paper about how...
The Sample Environment Communication Protocol (SECoP) provides a generalized way for controlling measurement equipment – with a special focus on sample environment (SE) equipment [1,2]. In addition, SECoP holds the possibility to transport SE metadata in a well-defined way.
SECoP is designed to be
- simple to use,
- inclusive concerning different control systems and control philosophies...
