Kadi4Mat Software Ecosystem
The software ecosystem of Kadi4Mat includes different tools and libraries that are built around and on top of Kadi4Mat, the generic and open source virtual research environment.
The software ecosystem of Kadi4Mat includes different tools and libraries that are built around and on top of Kadi4Mat, the generic and open source virtual research environment.
Kadi4Mat is a generic and open source virtual research environment, which can be hosted as a web-based service. The instances hosted at KIT can be leveraged to enhance (meta)data management and integration in the engineering community working in academia, research institutions, or industry.
Jarves provides guidance in RDM by ordering the RDM activities based on their occurrence in the engineering research process. Taking into account the specific RDM requirements of a research project, e.g. requirements of funding organisations or institutional boundaries, a decision support system provides information on the next steps and available tools. Alongside, matching trainings for the current step are provided. Furthermore, Jarves offers a broad connectivity to other services, allowing for seamless (meta)data exchange.
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.
GitLab is an open-source-software to host and manage own Git-repositories. Besides the main task of the code-management other functions like a simple issue-tracking-system, a wiki and also an option to review codes are covered. With this GitLab supports the developer, who increase the quality of the developed program codes.
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.