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HeFDI Data Talk: Chemotion - An Introduction to an Open-Source ELN for FAIR Data

Authors: Jolliffe, John;

HeFDI Data Talk: Chemotion - An Introduction to an Open-Source ELN for FAIR Data

Abstract

Electronic Lab Notebooks (ELNs) are a key prerequisite to a comprehensive documentation of research processes, the digital storage of research data, and their reuse. ELNs can be used to plan, record, store and - in combination with repositories - disclose experiments or research data. In the long run, the benefit of ELNs is the option to store and manage data in a standardized way and to enrich the data with (automatically generated) information such as metadata, identifiers and descriptors. For scientists, ELNs offer advantages such as faster research processes and a faster access to information. Selected benefits of the ELN Chemotion - an ELN that was designed for the discipline Chemistry - will be presented to show exemplarily the use of research data management tools. The ELN offers special features for chemical work and includes diverse functions that allow the use of the ELN also in other disciplines. Both, the chemistry specific as well as the generic and adaptable modules will be presented in brief. Chemotion ELN can be used in combination with the open access repository Chemotion. The disclosure of research data to the public is possible by a direct transfer of information from the ELN to the repository. The interoperable systems ELN and repository guarantee on the one hand an easy process for the disclosure of information and on the other hand the availability of comprehensive data including primary data and descriptions. The systems Chemotion ELN and Chemotion Repository are part of the strategy of the National Research Data Infrastructure for Chemistry (NFDI4Chem) in Germany. Dr. John Jolliffe from NFDI4Chem will present the strategy and measures of NFDI4Chem in brief. Important note : You can watch a recording of this HeFDI Data Talk under https://www.youtube.com/watch?v=XaF_3IjIMcI. Feel free to also check out our other event recordings there!

The HeFDI Data Talks are a bi-weekly open information and discussion event around the topic of data management in the context of science, in which relevant NFDI consortia as well as research data management services present themselves. The series discusses current topics and introduces numerous tools and services, including local and regional ones. If you have suggestions or feedback regarding topics, please feel free to contact the HeFDI office (hefdi@uni-marburg.de). If you would like to receive regular updates on our offerings and events, sign up for our newsletter .

The HeFDI Data Talks are an offer of the HeFDI Initiative (Landesinitiative HeFDI), which is funded by the Hessian Ministry of Higher Education, Research, Science and the Arts (HMWK).

Keywords

Repositorium, FAIR data, FDM, FAIR principles, Infrastruktur, metadata, Chemie, Forschungsdateninfrastruktur, Forschungsdatenmanagement, infrastructure, chemistry, FAIR-Prinzipien, repository, Elektronisches Laborbuch, electronic lab notebook, Metadaten, HeFDI Data Talk, ELB, RDM, research data management, ELN, research data infrastructure, FAIRe Daten

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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