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Combining the BIDS and ARC Directory Structures for Multimodal Research Data Organization
Combining the BIDS and ARC Directory Structures for Multimodal Research Data Organization
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Interdisciplinary collaboration and integration of large and diverse datasets are becoming increasingly important. Answering complex research questions requires combining and analysing multimodal datasets. Research data management follows the FAIR principles making data findable, accessible, interoperable, and reusable. However, there are challenges in capturing the entire research cycle and contextualizing data according, not only for the DataPLANT and NFDI4BIOIMAGE communities. To address these challenges, DataPLANT developed a data structure called Annotated Research Context (ARC). The Brain Imaging Data Structure (BIDS) originated from the neuroimaging community extended for microscopic image data. Both concepts provide standardised and file system based data storage structures for organising and sharing research data accompanied with metadata. We exemplarily compare the ARC and BIDS designs and propose structural and metadata mapping.
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URL: https://zenodo.org/records/8349563Communities:
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Template for the NFDI4Biodiversity & GfÖ Winter School
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Template for the NFDI4Biodiversity & GfÖ Winter SchoolThis publication showcases the NFDI4Biodiversity & GfÖ Winter School 2022, a transformative one-week course program designed to equip young scientists with essential Research Data Management (RDM) skills tailored for biodiversity and environmental data. Organized by the NFDI4Biodiversity consortium, the Winter School fostered data literacy and promoted sustainable research practices within the ecological and environmental science communities. The publication offers an overview of the Winter School's structure, curriculum, and highlights. Throughout the course, participants engaged in a series of expert-led lectures and hands-on practical sessions, delivered by renowned academics, data specialists, and research institutions in the biodiversity domain. These sessions covered critical aspects of RDM, encompassing data collection, curation, analysis, visualization, and long-term preservation. The curriculum extensively explored state-of-the-art software tools for data handling, including Jupyter notebook, R, Python, RightField, and OpenRefine. By providing hands-on training with these tools, the Winter School empowered participants to enhance their data management workflows and produce robust research outcomes. Targeting PhD students and Early-Career Researchers, the Winter School nurtured the next generation of scientists, equipping them with the necessary skills to navigate the challenges posed by increasingly complex and diverse ecological datasets. By sharing insights, lessons learned, and practical guidance, this publication serves as an invaluable reference and guide for organizers, educators, and researchers seeking to create impactful and inclusive training programs in research data management for biodiversity and related studies. The Winter School's legacy lies not only in the skills acquired by participants but also in the collaboration across the biodiversity and environmental science community. It exemplifies the commitment of NFDI4Biodiversity to advance data-driven research and contribute to a more sustainable and biodiverse planet
Learning Resource Type
Report
File Format
PDF
Languages
English
Media Type
Text
Publication Date
2023-08-08
License
CCBY
Size
2.7 MB
Authors
Keywords
#Data Management#Data Publication#Data annotation#Legal Aspects#NFDI#Taxonomic Harmonization
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NFDI4Biodiversity Winter School Lectures
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NFDI4Biodiversity Winter School LecturesThis Playlist collects recordings of the lectures at the NFDI4Biodiversity Winter School, that aimed on Early-Career-Researcher with a background in biodiversity and environmental science and took place in December 2022. The Winter School was a collaborative event between the Ecological Society (GfÖ) and the consortium NFDI4Biodiversity within the National Research Data Infrastructure Germany (NFDI). Various experts from the partner network (universities, data centers and research institutions) shared their widespread knowledge and trained participants in the fundamentals of Research Data Management (RDM) as well as cutting-edge technologies in handling environmental and biodiversity data across the Data Life Cycle (DLC). Topics were: Data Management and Data Literacy; Taxonomic Harmonization; Data Integration and Annotation; Legal Aspects; Data Search: Publish your Research Data
Learning Resource Type
Lecture
File Format
Unknown
Languages
English
Media Type
Video
Publication Date
2023-05-03
License
CCBY
Authors
Keywords
#Data Management#Data Publication#Data annotation#Legal Aspects#NFDI#Taxonomic Harmonization
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Improved Findability of Energy Research Software by Introducing a Metadata-based Registry
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Improved Findability of Energy Research Software by Introducing a Metadata-based RegistryNo description.
File Format
PDF
Languages
English
Media Type
Text
Publication Date
2024-01-19
License
CCBY
Size
395.1 KB
Authors
Keywords
#FAIR#Metadata#Digital Libraries#Energy Research#Interoperability#Open Source Software#Research Soft-ware#Software Reusability
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Thinking data management on different scales
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Thinking data management on different scalesPresentation given at PoL BioImage Analysis Symposium Dresden 2023
File Format
PPTX, PDF
Languages
English
Media Type
Presentation
Publication Date
2023-08-31
License
CCBY
Authors
Keywords
#FAIR#Research Data Management#I3D:bio#Microscopy
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FAIR Cookbook - Plant genomic and genetic variation data submission to EMBL-EBI databases
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FAIR Cookbook - Plant genomic and genetic variation data submission to EMBL-EBI databasesThe FAIR Cookbook is an online, open and live resource for the Life Sciences with recipes that help you to make and keep data Findable, Accessible, Interoperable and Reusable; in one word FAIR. This recipe provides guidance for submitting plant genotyping data to public repositories. It explains in a step-wise fashion which work should be done and when. Special attention should be paid to the metadata maintenance of the data that will be deposited in different repositories as part of this recipe. A prerequisite for fully understanding this recipe is a basic knowledge of the MIAPPE standard. The exact listing of the metadata fields required for a FAIRification of the genotyping data set within a VCF file is also part of this recipe with examples and explanations.
Learning Resource Type
Cookbook
File Format
MD
Languages
English
Media Type
Text
License
CCBY
Authors
Keywords
#FAIR#Repositories#BioSamples#Data Publishing#Genotyping Data#MIAPPE#Plant Phenotyping Data
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NFDI ToolTalk: One roof, several services: Bringing together all DataPLANT efforts
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NFDI ToolTalk: One roof, several services: Bringing together all DataPLANT effortsDescription Slides of the presentation given on June 08, 2022 as part of the NFDI ToolTalk series. The presentation follows up on the status reached after one and a half year into DataPLANT services discussions and developments. It will show the general concept and the already implemented services and how they could fit into either local or centralized research infrastructures. In the future these services may run on-top of future NFDI base services or integrate NFDI base service components like AAI. DataPLANT services might as well be offered to a wider community beyond fundamental plant research.
File Format
PDF
Languages
English
Media Type
Presentation
Publication Date
2022-06-08
License
CCBY
Size
1.8 MB
Authors
Keywords
#NFDI#Research Data Management#DataPLANT#nfdi4plants#Nationale Forschungsdateninfrastruktur#Open Science#RDM service infrastructure#Software Sustainability#ToolTalk
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