DSW
DSW

Data Stewardship Wizard

Create, plan, collaborate, and bring your data management plans to life with a tool trusted by thousands of people worldwide — from data management pioneers, to international research institutes.

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Data Stewardship Wizard Application

Data Stewardship

Data stewardship focuses on tactical coordination and implementation responsible for establishing data-quality metrics and other requirements regarding good data management. The ultimate goal is to provide high-quality data that is easily accessible in a consistent manner.

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Data Stewardship

Decision Support

Building a data management plan and providing high-quality research data requires many considerations that can be overwhelming and hard to start with. In DSW, you do not have to write a lot of text. Instead, you answer understandable questions in smart questionnaires, get links to external resources, FAIR metrics indications and more. These questions can have some follow-ups based on your answers or can be connected to external resources.

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Decision Support

Collaboration

Nowadays, working in a team is crucial. DSW provides many options on how to share your project with other people. You can work together online, comment questions, and immediately see the changes made by your coworkers. You can quickly see who answered which questions, and all the changes are saved in the version history. You can then label specific versions or come back to any point in history

Collaboration

DSW in Action

Enabling Seamless Data Management Planning within PaNOSC

DSW's integration within the PaNOSC project has streamlined Data Management Planning (DMP) across various Research Infrastructures (RIs), exemplified by ESFR's creation of over 1150 DMPs with 60% auto-population. As more RIs consider making DMPs mandatory, the future holds the promise of machine-readable DMPs for enhanced data exploitation and knowledge graph development.

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The Chalmers DS Wizard Story

Chalmers University of Technology is one of the leading science and technology universities in northern Europe, with over 2,000 active researchers, coordinating around 400 new, often highly data intensive research projects yearly.

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Story of the DSW Teaching at the Clermont Auvergne University

The University of Clermont Auvergne (UCA) offers a Master's degree in Bioinformatics. One of the teaching units deals with how to handle and share public data considering best practices and FAIR principles for reproducible sciences. DSW has a friendly web interface with various DMP flavors, which makes it rapidly usable by anyone without specific background.

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Integrating DSW at IFB

The Institut Français de Bioinformatique (IFB – ELIXIR-FR) installed a DSW instance in the first half of 2021. We are in the process of creating a DMP template targeted to the French bioimagery community and we needed a user-friendly tool to help us build the structure of the DMP, experiment with it, and gather inputs and comments from the various actors.

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BioData.pt Experience

BioData.pt is the Portuguese distributed e-infrastructure for biological data and the Portuguese ELIXIR node. Its mission is to support the national scientific system through best practices in data management and state of the art data analysis.

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The ELIXIR Norway DSW Story

Norwegian funders require that research groups submit data management plans (DMPs) upon signing the contract for their research projects. Generating a DMP has been regarded by many researchers as a mere administrative burden, rather than a tool to revise their habits and support their projects.

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The SciLifeLab DSW Story

Our story started in 2018 with the development of a data management plan (DMP) template targeted at projects generating NGS data at SciLifeLab. We wanted to provide this template to a wider audience and hence needed an online resource. Through the ELIXIR network we knew about the Data Stewardship Wizard, and decided to try it out.

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Providers

How to Support Us

  • Send us a success story

    Do you use DSW in your research or is it somehow included in your workflow? We would be happy to hear and publish your success story to inspire others!

    Contact us

  • Cite our paper

    If you write a paper where you would like to refer to the Data Stewardship Wizard, we would really appreciate if you cited our DSW paper. Here we provide more details about how to cite us.

    How to cite us

  • Translate to your language

    You can easily contribute just by providing your language skills and help us translate DSW to various languages as well as maintain such translations.

    Translate DSW

  • Sponsor us

    We highly appreciate any form of feedback and support from the community. You or your organisation can support DSW development easily using GitHub Sponsors.

    Sponsor DSW @ GitHub

Acknowledgements

Releases from 3.19 up to 4.1 (see the details) were supported by ELIXIR CZ research infrastructure (MŠMT Grant No.: LM2023055).

ELIXIR CZ and MSMT logo

Releases from 2.3 up to 4.1 (see the details) were supported by Codevence Solutions.

Codevence Solutions logo

Releases from 2.4 up to 3.24 (see the details) were supported by ELIXIR-CONVERGE project (10.3030/871075).

ELIXIR-CONVERGE logo

Releases from 2.0 up to 3.18 (see the details) were supported by ELIXIR CZ research infrastructure (MŠMT Grant No.: LM2018131).

ELIXIR CZ and MSMT logo

Releases 3.5, 3.6, and 3.7 (see the details) were supported by the ENVRI-FAIR to develop the FIP wizard to generate FAIR Implementation Profiles.

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Releases 2.10, 2.11 and 2.12 (see the details) were supported by the Centre for Digital Life Norway with funding from the Research Council of Norway under grant agreement 248810.

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Releases from 1.0 up to 1.10 were developed as part of the ELIXIR Implementation Study Towards Data Stewardship in ELIXIR: Training and Portal.

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Releases before version 1.0 were created as part of the diploma theses of Vojtěch Knaisl and Jan Slifka supervised by Robert Pergl submitted at the Faculty of Information Technology, Czech Technical University in Prague.

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