Ing.grid is a scholarly-led diamond open access journal for FAIR data management in engineering sciences. It uses an open peer review process and accepts data and software submissions in addition to regular manuscripts.
A python-written metadata crawler that allows to automatically retrieve relevant research metadata from script-based workflows on HPC systems. The tool offers a flexible approach to metadata collection, as the metadata scheme can be read out from an ontology file. Through minimal user input, the crawler can be adapted to the user’s needs and easily implemented within the workflow, enabling to retrieve relevant metadata.
The Field Database Platform (FDP) prioritizes the accessibility and reusability of data, allowing researchers to interact with field datasets more effectively. By providing tools for data exploration and previewing based on operational and environmental parameters, FDP ensures users are guided in finding relevant datasets, avoiding irrelevant or redundant information. This platform enhances data reusability and promotes FAIR principles, significantly improving the research experience compared to traditional data platforms.
DataDesc is a framework that allows describing data models of software interfaces with machine-actionable metadata. The framework provides a specialized metadata schema, an exchange format and support tools for the easy collection and automated publishing of software documentation. DataDesc practically increases the FAIRness, i.e., findability, accessibility, interoperability, and the reusability of research software, as well as effectively promotes its impact on research.
The data transfer federation aims to increase mobility of data by providing a low-level service that allows asynchronous bulk transfer of large quantities of files from one storage cluster to another.
“Data Quality Metrics Webpage” is a knowledge platform offering in-depth resources on data quality, FAIR principles, and image and machine learning metrics. Built on ReadTheDocs with GitHub, it supports decentralized editing and easy updates using reStructuredText, requiring no specialized software. The platform provides, practical guidance with examples, images, and code snippets, making it accessible to users for applying data concepts, optimizing models, and enhancing understanding.
The Data Collections Explorer is an information system for the engineering community. It facilitates sharing of and searching for discipline specific repositories, archives, and databases, as well as for datasets published individually by research groups. Scientists can get a quick overview of the most important facts about services and datasets, such as access rights or usage restrictions. A SPARQL endpoint ensures programmatic access for integration with third-party services.
Coscine is a RDM platform for the active phase of research projects that enables NFDI4ING researchers to access storage space on DataStorage.nrw while guaranteeing the FAIR principles. Projects created in Coscine enable role management, metadata management, public sharing of data, referencing with PIDs and archiving of research and metadata for 10 years. In addition, project-related GitLab repositories can be integrated and external files linked. Registration takes place via your own organization (using the NFDI4ING community AAI) or ORCiD.
Betty’s (Re) Search Engine aims to solve the issue of finding research software. The engine searches for software repositories that match a given search string and then tries to find corresponding publications as well as all available metadata. This enables users to sort the repositories based on the number of citations, apply various filters and it also directly provides an impression about the research contexts in which a software has been successfully applied.
The NFDI4ING Education Platform provides essential resources for self-paced trainings in RDM tailored specifically to engineering disciplines. Driven by the needs and characteristics of the engineering domain, these trainings provide basic RDM topics adapted for engineering, including use cases and interactive quiz elements. Based on that, users can start learning and enhancing their skills in managing research data effectively, improving collaboration in their projects, and reuse research data.