Organising & Processing Archives

SciMesh

SciMesh provides a specification and a reference implementation for a knowledge graph schema. It is supposed to represent scientific workflows and insights. While originating in experimental research of the engineering and material sciences, its basic principle is the connection of cause and effect, which can be applied to most empiric research. Its applications range from research publication over data exchange between electronic lab notebooks to timestamping of scientific work in blockchains.

Virtual Environments in Experiments: A Prototype

How can virtual environments be used in cooperative experimental work that involves a physical test rig? In an Alex experimental setup, we have developed a prototypical solution that includes provisioning and managing virtual machines and containers tailored to specific project needs. The environments use Conda and Pip for software development and unit testing, ensuring flexibility and scalability and allowing for more efficient analysis and streamlined workflows.

Open Research Knowledge Graph (ORKG)

The Open Research Knowledge Graph (ORKG) helps researchers find, compare, and reuse scientific findings efficiently. User can organize research contributions semantically so that both humans and machines can easily understand and use them. With ORKG, you can explore knowledge across various disciplines, stay updated, and collaborate on new research. Additionally, ORKG enhances the visibility of research outputs, facilitating better discovery and innovation in the scientific community.

NFDI4Ing Maturity Model

To evaluate the implementation of research data management, maturity models are provided for individual phases, which researchers can use for self-evaluation. The models are aimed at a standardised and optimised implementation of RDM in engineering research projects.

Knowledge Base for replicable & reproducible software-based experiments

Are you an engineer in a project to (re-)program scientific code? Or are you a student in a likewise project? Or maybe you are a project/data manager looking for some inspiration and advice? Then this Knowledge Base might be just for you!

We cover multiple topics regarding the development of scientific software, e.g. Version Control and Continuous Integration.

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.

Kadi4Mat as a Service

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 – Joint Assistant for Research in Versatile Engineering Sciences

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.

HOMER – HPMC tool for Ontology-based Metadata Extraction and Re-use

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.

Data Quality Metrics Webpage

“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.

Tag: Organising & Processing