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Guides

In deciding where to store your data, you may have a number of choices about who will look after it. The choice may be straightforward if you have an established data management facility in your domain or institution, or even within your research group or department. When data preservation standards or norms exist in your discipline, these should be followed. Your research funder may recommend a data centre or self-deposit archive. In order of preference:

  1. Use an external data archive or repository already established for your research domain to preserve the data according to recognised standards in your discipline.
  2. If available, use an institutional research data repository, or your research group’s established data management facilities.
  3. Use a cost-free data repository such as Zenodo.
  4. Search for other data repositories here: re3data.org. On top of specific research disciplines you can filter on access categories, data usage licenses, trustworthy data repositories (with a certificate or explicitly adhering to archival standards) and whether a repository gives the data a persistent identifier.

res3data categories

Remember – you don’t need to keep everything! Work with your library to help you determine which data you need to retain for validation and/or reuse.

When choosing a repository it is important to consider factors such as whether the repository:

  • Gives your submitted dataset a persistent and unique identifier. This is essential for sustainable citations – both for data and publications – and to make sure that research outputs in disparate repositories can be linked back to particular researchers and grants.
  • Provides a landing page for each dataset, with metadata that helps others find it, tell what it is, relate it to publications, and cite it. This makes your research more visible and stimulates reuse of the data.
  • Helps you to track how the data has been used by providing access and download statistics.
    Responds to community needs and is preferably certified as a ‘trustworthy data repository’, with an explicit ambition to keep the data available in the long term.
  • Matches your particular data needs (e.g. formats accepted; access, back-up and recovery, and sustainability of the service). Most of this information should be contained within the data repository’s policy pages.
  • Offers clear terms and conditions that meet legal requirements (e.g. for data protection) and allow reuse without unnecessary licensing conditions.
  • Provides guidance on how to cite the data that has been deposited.
  • Charges for its services.

Your institution may offer Research Data Management support to help you deal with these issues and get the most out of the investment put into your research. This could involve:

  • Registering datasets with the institution’s Data Catalogue to help make the research more visible. National registry services are also being established to harvest institutional data catalogue records to make the data visible at a national level.
  • Depositing the dataset with an institutional repository to maintain a long-term record of its safekeeping and, if it is publicly available, the access and download statistics.
  • Providing advice on rich metadata and other documentation, to help make the data both discoverable and understandable.
    Selecting an appropriate licence for using your data – also when you make them available Open Access.

The Guidelines on FAIR Data Management in Horizon 2020 (v3, July 2016) describe what a Data Management Plan should cover. Based on the Guidelines the Digital Curation Centre has included a DMP template in its DMPonline platform. You can write, export and update the DMP.

In addition, the Digital Curation Centre has linked its own guidance to several elements of the templates, which extends the EC guidance in the Guidelines. All guidance is located on the right-hand side of the web page.

Additional Support materials

Taking ARGOS as default DMP tool, which offers DMP templates that match the demands and suggestions of the Guidelines on Data Management in Horizon 2020, it is recommended to refer it the Principal Researcher.

A DMP in Argos consists of key information about the research, such as purpose, objectives and researchers involved, but also about documentation of research datasets, namely Datasets that highlight the steps followed and the means used across data management activities.

  1. Sign up to ARGOS
  2. Select Start new DMP > Start Wizard
  3. Fill in the following fields:
    1. Title of DMP*
    2. Description
      (Briefly describe the context and purpose of the DMP)
    3. Language
      (Select the language of your DMP)
    4. Visibility
      (Choose how the DMP is displayed in Argos: Restricted or Public)
    5. Researchers
      (Add the names of people that have produced, processed, analysed the data described in the DMP)
    6. Organizations
      (Add the name(s) of the organization(s) contributing to the creation and revision of the DMP)
    7. Funding organizations*
      (Select European Commission from the list)
    8. Grants*
      (Find the grant of your research or add new)
    9. Project
      (This field is to be completed only for projects where multiple grants apply)
    10. License
      (Assign a license to your DMP by selecting the most appropriate from the list)
    11. Dataset info*
      (Select a template to describe your datasets: H2020)
  4. Select Save & Add Dataset

* Required field

Once you select Save & Add Dataset, you have successfully created your DMP and will be transferred to the Dataset editor.

Datasets are documented following pre-defined templates which set the content of dataset descriptions. In Argos, a DMP can contain as many dataset descriptions as the datasets it documents.

A DMP in ARGOS can be saved anytime. It can also be shared and it can be downloaded/exported in various formats (in machine readable (.xml) and machine-actionable (.json) formats). A user guide is avaible in the portal at https://argos.openaire.eu/user-guide.

argos logo newARGOS is a OpenAIRE service that simplifies the management, validation, monitoring and maintenance of Data Management Plans. It allows actors (researchers, managers, supervisors etc) to create actionable DMPs that may be freely exchanged among infrastructures for carrying out specific aspects of the Data management process in accordance with the intentions and commitment of Data owners.

 

 

Projects participating in the Horizon 2020 Open Research Data Pilot will be required to develop several versions of a Data Management Plan (DMP), in which they will specify what data will be kept for the longer term.

Other projects are invited to submit a Data Management Plan if it is relevant for their planned research.

The first version of the DMP is expected to be delivered within the first 6 months of the project. More elaborated versions of the DMP can be delivered at later stages of the project.

The DMP should be updated as a minimum in time with the periodic evaluation/assessment of the project. If there are no other periodic reviews foreseen within the grant agreement, then such an update needs to be made in time for the final review at the latest. Furthermore, the consortium can define a timetable for review in the DMP itself.

New versions of the DMP should be created whenever important changes to the project occur due to inclusion of new data sets, changes in consortium policies or external factors.