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The NFDI4Chem knowledge base provides information and recommendations to digitalise all key steps of chemical research to support scientists in their efforts to collect, store, process, analyse, publish, and reuse research data. This knowledge base is inspired by [RDMkit](https://rdmkit.elixir-europe.org/index.html) but has been tailored specifically towards Chemists as end-users.
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## Why is RDM important for chemistry?
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Research Data Management in chemistry is currently not systematically organised and individual solutions of single institutions lead to low visibility, accessibility, and usability of research results. The added value of preserving and researching scientific data in chemistry is particularly high because the significance of the data is often immortal, hence, older data can be reused for current investigations. In most cases, it is even mandatory to be able to access older data, since experimental data or complex simulation data in particular can only be regenerated with great effort.
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Research Data Management in chemistry is currently not systematically organised and individual solutions of single institutions lead to low visibility, accessibility, and usability of research results. The added value of preserving and researching scientific data in chemistry is particularly high because the significance of the data is often immortal, hence, older data can be reused for current investigations. In most cases, it is even mandatory to be able to access older data, since experimental data or complex simulation data in particular can only be regenerated with great effort.
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Main motivations for RDM in chemistry are:
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- to prevent the loss of data and ensure data security
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- to warrant long-term availability of research data
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- to warrant long-term availability of research data
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- to accelerate retrieval of data and information
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- to enhance transparency, reproducibility allow verifiability of research findings
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- to boost sustainability by saving time and resources
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The domain pages present an exemplary workflow for different chemistry disciplines along the research data life cycle. Multiple domains are illustrated in a user profile. Guidelines are provided for all digitisation steps involved and domain-specific best practices for FAIR data are given. Find out how to apply good RDM and FAIR science in the context of your own specific discipline!
The role pages focus on the motivation for role-specific requirements and answer the questions why RDM is important and how it can be implemented. Get a fast impression of all important RDM information related to your role!
The handling data section explains common problems and challenges regarding RDM. Problematic aspects of data handling are considered, starting with the creation of data management plans, data organisation and data documentation. Moreover, aspects on data storage and archiving are also covered.
To enable fully digital workflows in chemistry, the development and provision of a modular virtual laboratory environment with concepts, services and software (smartlab) is essential. Electronic lab notebooks are an important part of the smartlab, as well as integration of analytical instrumentation and data transfer to repositories.
In this category on data publishing you will find all the important information on the topic of data publishing. This includes the motivation to publish research data, paths to publish data, recommendations for research data repositories to be used, best practices and aspects of machine actionability.
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In this category on data publishing you will find all the important information on the topic of data publishing. This includes the motivation to publish research data, paths to publish data, recommendations for research data repositories to be used, best practices and aspects of machine actionability.
In scientific work, the assurance of [good research practice](https://doi.org/10.5281/zenodo.3923602) is the highest imperative.
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## Phase 4: Analysis
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In the 4th phase, as the name suggests, the focus is on the **analysis and interpretation of the data**. After analysing the data, the data should be evaluated. You should also consider **sharing the data** with colleagues in a closed and secure environment like on a project or working group level. Secure environments for sharing data are often provided by universities or federal states through Sync&share solutions. Consult your local research data team about this.
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Before sharing data, you should check whether the data is subject to **copyright protection or other protective rights**.
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In the 4th phase, as the name suggests, the focus is on the **analysis and interpretation of the data**. After analysing the data, the data should be evaluated. You should also consider **sharing the data** with colleagues in a closed and secure environment like on a project or working group level. Secure environments for sharing data are often provided by universities or federal states through Sync&share solutions. Consult your local research data team about this.
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Before sharing data, you should check whether the data is subject to **copyright protection or other protective rights**.
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## Phase 5: Disclosure/ Publication
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During this exchange and the associated reflections on the data, you should think about archiving and using the data in scientific publications. If you are not aware of any **criteria for archiving** and no criteria are specified in your working group or institute, decision-making guides such as the [“5 steps to decide what data to keep”](https://www.dcc.ac.uk/guidance/how-guides/five-steps-decide-what-data-keep)outlined by the DCC can help. Based on the established criteria, it is determined which of the collected raw data should be archived and which should be deliberately deleted.
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During this exchange and the associated reflections on the data, you should think about archiving and using the data in scientific publications. If you are not aware of any **criteria for archiving** and no criteria are specified in your working group or institute, decision-making guides such as the [“5 steps to decide what data to keep”](https://www.dcc.ac.uk/guidance/how-guides/five-steps-decide-what-data-keep) outlined by the DCC can help. Based on the established criteria, it is determined which of the collected raw data should be archived and which should be deliberately deleted.
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In addition to the criteria, the migration of the data into **suitable [formats](/docs/format_standards) and onto suitable media** is important for archiving the data. In this step, the data should again be enriched with metadata so that it can be understood in the future without further knowledge about the data.
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In addition to archiving, the [publication](/docs/data_publishing) of the data plays a special role. Many research funders expect the data to be published if there are no special reasons not to do so, such as a non-disclosure agreement or the inclusion of personal data. A **chemistry-specific or chemistry-related [repository](/docs/repositories)** such as the [Chemotion Repository](https://www.chemotion-repository.net/), [NOMAD](https://nomad-lab.eu/services/repo-arch), or [MassBank](https://massbank.eu/MassBank/)is recommended for the publication of data. An overview of repositories can be found, for example, at [re3data.org](https://www.re3data.org/) or [fairsharing.org](https://fairsharing.org/). re3data.org allows you to filter repositories according to certain criteria such as the assignment of a persistent identifier or access.
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In addition to archiving, the [publication](/docs/data_publishing) of the data plays a special role. Many research funders expect the data to be published if there are no special reasons not to do so, such as a non-disclosure agreement or the inclusion of personal data. A **chemistry-specific or chemistry-related [repository](/docs/repositories)** such as the [Chemotion Repository](https://www.chemotion-repository.net/), [NOMAD](https://nomad-lab.eu/services/repo-arch), or [MassBank](https://massbank.eu/MassBank/) is recommended for the publication of data. An overview of repositories can be found, for example, at [re3data.org](https://www.re3data.org/) or [fairsharing.org](https://fairsharing.org/). re3data.org allows you to filter repositories according to certain criteria such as the assignment of a persistent identifier or access.
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Data publishing often takes place at certain milestones, for example, in combination with a text publication or at the end of a project. The **final version of the data management plan** is also required at the end of a project.
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## Phase 6: Re-use
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In order to return these data to the cycle, it is important that these data are described in detail with metadata, that proper documentation has been carried out in the form of a DMP, and that the data are citable.
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What is the potential of your data?
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What is the potential of your data?
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## Sources and further information
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-[Review of data management lifecycle models](https://researchportal.bath.ac.uk/en/publications/review-of-data-management-lifecycle-models)
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-[DCC: 5 steps to decide what data to keep](https://www.dcc.ac.uk/guidance/how-guides/)
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- German: [Überblick zum Management von Forschungsdaten (FDM I) = Research Data Management - An Overview](https://doi.org/10.18154/RWTH-2019-06489)
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- German: [Forschungsdaten.info: Informieren und Planen](https://www.forschungsdaten.info/themen/informieren-und-planen/datenlebenszyklus/)
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- German: [Forschungsdaten.info: Informieren und Planen](https://www.forschungsdaten.info/themen/informieren-und-planen/datenlebenszyklus/)
Looking for information on managing research data in chemistry? Choose your chemical domain and find discipline-specific help on research data management.
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- data producing methods (including a table with recommendations on interoperable open file formats)
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- data analysis
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- publication of research data
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Click on a button below to get started with your chemical domain. The domain-specific profiles will be continuously updated based on new developments and feedback.
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