Our current working groups are listed below.
Displaying 6 results.
In toxicology and pharmacology data from chemistry, biology, informatics, and human or ecosystem health science merge and toxicological metadata need to become interoperable and compliant with existing ontology-based data infrastructures of these fields.
A team from three Helmholtz programs ( Earth and Environment , Information , and Health ) will review existing metadata standards and ontologies across fields and generate an integrative, suitable ontology for the annotation of toxicological/pharmacological data and workflows from the experimental design to the data deposit in repositories.
We will establish a metadata framework for the FAIR description of exposure and experimental settings interlinked with chemical IDs and data processing workflows using ‘omics data, which will be implemented into the community-based “Galaxy” project. This will enable interoperability between disciplines to address the grand challenges of chemical pollution and human and ecosystem health.
Reflection seismic data, 2D as well as 3D, and refraction data such as active OBS data are the paramount source of information for the deep subsurface structure as they provide by far the highest resolution of any comparable geophysical technique. To this date, they have been used for a large variety of academic and commercial purposes. For many decades, reflection and refraction seismic data were the largest data sets in earth sciences, which created significant storage and archival problems. This fact and the lack of metadata standards hampers all new scientific projects that would like to use present-day and legacy data. However, GEOMAR has already initiated the implementation of the FAIR standards concerning 2D seismic data within a NFDI4Earth Pilot “German Marine Seismic Data Access” running until February 2023 in cooperation with the University of Hamburg and the University of Bremen.
Within MetaSeis, we will develop a unifying data infrastructure and prepare for future archival of reflection 3D seismic data and active OBS data from recent and future research cruises. We aim to adopt and extend existing standards and interoperable vocabularies in the seismic metadata including metadata quality and validation checks. To ensure long-term archival according to the FAIR-principles, a workflow for the integration of future and legacy data sets will be established along with best practices developed within previous projects (Mehrtens and Springer, 2019).
With this initiative, HMC will serve Germany’s marine geophysics community as represented by AGMAR of the Fachkollegium Physik der Erde of DFG but also contributes to the efforts of NFDI4Earth/DAM/DataHUB and the involved Helmholtz centres to establish a distributed infrastructure for data curation by harmonized data workflows with connections to international data repositories such as MGDS (Marine Geoscience Data System), IEDA (Interdisciplinary Earth Data Alliance), SNAP (Seismic data Network Access Point) and SeaDataNet (Pan-European Infrastructure for Ocean and Marine Data Management). International cooperation will benefit from synergy with the industrial seismic standard Open Subsurface Data Universe (OSDU) to ensure future cooperation between industry and academic research.
Capitalizing on advancements in Large Language Models (LLMs), MetaSupra aspires to expedite the process of metadata enrichment in FAIR-compliant repositories.
Specifically, MetaSupra will enhance SupraBank, a platform that provides machinereadable physicochemical parameters and metadata of intermolecular interactions in solution. By utilizing LLMs, we aim to develop data crawlers capable of extracting context-specific information from chemical literature, simplifying data acquisition, and curating FAIR repositories. This crawler software will be made accessible, inviting potential adoption by other Helmholtz centers. In addition, MetaSupra will illustrate how repositories' utility for correlation studies, machine learning, and educational purposes can be substantially amplified through the integration of quantum-chemically computed molecular parameters, positioning it as a model for other chemical repositories and moving forward with its integration into IUPAC activitie
The MetaSurf project is a comprehensive initiative aimed at transforming how data is managed, shared, and utilized in the field of surface science. It seeks to implement the FAIR (Findable, Accessible, Interoperable, and Reusable) principles across a broad spectrum of experimental and simulation data. The project's central objectives include:
-
Extension of Existing Infrastructure: Enhancing the Kadi4Mat platform by integrating advanced simulation and modeling workflows, GitLab, and JupyterLab. This extension aims to facilitate automated processing steps and streamline the data management process.
-
Development of a Public Data Repository: Establishing a centralized repository for surface science data, accessible to the global research community. This repository will serve as a hub for data exchange, fostering collaboration and accelerating scientific discovery.
-
Metadata-Driven Approach: Emphasizing the use of metadata, electronic lab notebooks, and data repositories to promote reproducibility and transparency in research. By developing tools, workflows, and templates that leverage metadata, the project intends to enable a more structured approach to data management, ensuring that data from diverse sources can be easily integrated and analyzed.
-
Community Engagement and Standardization: Working closely with the surface science community to develop standards for data exchange and processing. The project aims to cultivate a culture of data sharing and collaboration, encouraging researchers to adopt these standards in their work.
-
Innovation in Data Processing: Introducing new processing tools and techniques designed to handle the complexities of surface science data. These innovations will address the specific needs of the community, such as data visualization, analysis, and interpretation, enhancing the overall quality and impact of research in this field.
By achieving these goals, the MetaSurf project aspires to create a more cohesive, efficient, and innovative research environment in surface science, where data can be easily accessed, shared, and leveraged to drive new discoveries and advancements.
The collection and usage of sensor data are crucial in science, enabling the evaluation of experiments and validation of numerical simulations. This includes sensor maintenance metadata, e.g. calibration parameters and maintenance time windows. Enriched sensor data allows scientists to assess data accuracy, reliability, and consistence through Quality Assurance and Quality Control (QA/QC) processes. Today, maintenance metadata is often collected but not readily accessible due to its lack of digitalization. Such audit logs are commonly stored in analogue notebooks, which poses challenges regarding accessibility, efficiency, and potential transcription errors.
In MOIN4Herbie (Maintenance Ontology and audit log INtegration for Herbie), we will address the obvious lack of digitized maintenance metadata in Helmholtz’s research areas Information and Earth and Environment.
To this end, MOIN4Herbie will extend the electronic lab notebook Herbie – developed at the Hereon Institute of Metallic Biomaterials - with ontology-based forms to deliver digital records of sensor maintenance metadata for two pilot cases: For both the redeployed Boknis Eck underwater observatory and the already implemented Tesperhude Research Platform we will establish a digital workflow from scratch.
This will lead to a unified and enhanced audit of sensor maintenance metadata, and thus more efficient data recording, the empowerment of technicians to collect important metadata for scientific purpose, and last but not least improvement and facilitation of the scientific evaluation and use of sensor data.
Research software should be published in repositories that assign persistent identifiers and make metadata accessible. Metadata must be correct and rich to support the FAIR4RS principles. Their curation safeguards quality and compliance with institutional software policies. Furthermore, software metadata can be enriched with usage and development metadata for evaluation and academic reporting. Metadata curation, publication approval and evaluation processes require human interaction and should be supported by graphical user interfaces.
We create "Software CaRD" (Software Curation and Reporting Dashboard), an open source application that presents software publication metadata for curation. Preprocessed metadata from automated pipelines are made accessible in a structured graphical view, with highlighted issues and conflicts. Software CaRD also assesses metadata for compliance with configurable policies, and lets users track and visualize relevant metadata for evaluation and reporting.