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All Participants, read and update the Draft VESPA-DMP Document !

EPN-2024-RI VA DMP contact points

EPN 2024 RI VA Science DMP pages are here


EPN 2020 RI DMP is here

To be adapted to Europlanet 2024

Need to include data from TAs + NA2


Guidelines from OU   (DMP Instructions sent to EUROPLANET2020LEADERS)

(extracted from EPN2020 coord newsletter "Europlanet Update; November 9, 2015": Europlanet2020_RI_update_09112015.pdf)

Data management plan (DMP) 

As part of WP1, we are committed to write a DMP. WP leaders will be responsible for their own DMP. The EU has provided some guidelines in the document Guidelines on Data Management in Horizon 2020. A handy tool to write a Data Management Plan that meets the Horizon 2020 policy can be found online DMP Online. One can easily sign up for the first time and then use it as a reference. 


Whatever tool we decide to use, the general questions to be addressed are:

  • Types of data that will be generated
  • Data and metadata standards
  • Policies for data access and sharing
  • Data storage and preservation of access

For example, by using the above DMP online, the following boxes need to be filled in 


Data set reference and name

Identifier for the data set to be produced. 

Data set description 

Description of the data that will be generated or collected, its origin (in case it is collected), nature and scale and to whom it could be useful, and whether it underpins a scientific publication. Information on the existence (or not) of similar data and the possibilities for integration and reuse. 

Standards and metadata 

Reference to existing suitable standards of the discipline. If these do not exist, an outline on how and what metadata will be created. 

Data sharing 

Description of how data will be shared, including access procedures, embargo periods (if any), outlines of technical mechanisms for dissemination and necessary software and other tools for enabling re-use, and definition of whether access will be widely open or restricted to specific groups. Identification of the repository where data will be stored, if already existing and identified, indicating in particular the type of repository (institutional, standard repository for the discipline, etc.).

In case the dataset cannot be shared, the reasons for this should be mentioned (e.g. ethical, rules of personal data, intellectual property, commercial, privacy-related, security-related). 

Archiving and preservation - including storage and backup 

Description of the procedures that will be put in place for long-term preservation of the data. Indication of how long the data should be preserved, what is its approximated end volume, what the associated costs are and how these are planned to be covered 


In general, the sample questions to be answered are: 

Data types, formats, standards and capture methods 

What data outputs will your research generate?

  •  outline volume, type, content, quality and format of the final dataset

Outline the metadata, documentation or other supporting material that should accompany the data for it to be interpreted correctly.

What standards and methodologies will be utilised for data collection and management? State the relationship to other data available in public repositories e.g.

  • existing data sources that will be used by the research project

  • gaps between available data and that required for the research

  • the added value that new data would provide in relation to existing data 

Access, data sharing and reuse 

What are the further intended and/or foreseeable research uses for the completed dataset(s)?

How will you make the resource accessible to potential audience(s): Where will you make the data available?

  • How will other researchers be able to access the data?

  • What is the timescale for public release of the data?

  • How will data sharing provide opportunities for coordination or collaboration? 

Short-term storage and data management 

Describe the planned quality assurance and back-up procedures [security/storage].

Specify the responsibilities for data management and curation within research teams at all participating institutions.

Define data management support. 

Deposit and long-term preservation 

Identify which of the data sets produced are considered to be of long-term value.

Outline the plans for preparing and documenting data for preservation and sharing.

Explain your archiving/preservation plan to ensure the long-term value of key datasets. 

DMP is something new in comparison with previous FP7 projects. Our PM Barbara Pizzileo will also be attending a training course about it this week so will feedback her experiences. OU will be hosting a DM meeting on 10th December, where OU’s resident expert in the field will present her experience in designing DMPs. If you wish to attend please let us know (we have already contacted some people). 

Copyrights and licenses for research data.

In Developing our DMP there are several types of copyrights and licenses for research data that we can adopt. These are Creative Commons (CC’s) but there are different types as outlined below. We propose that CC BY might be the correct solution for much of Europlanet but certain areas might come under CC BY-ND or even CC BY-NC-ND might be required to protect certain parts. It would be useful to get suggestions from you for your WP as to how you feel the data should be treated.

Attribution CC Zero

Intended to be a ‘public domain dedication’, i.e. a waiver of all rights including those of attribution.

Attribution CC BY

This license lets others distribute, remix, tweak, and build upon your work, even commercially, as long as they credit you for the original creation. This is the most accommodating of licenses offered. Recommended for maximum dissemination and use of licensed materials.

Attribution-ShareAlike CC BY-SA

This license lets others remix, tweak, and build upon your work even for commercial purposes, as long as they credit you and license their new creations under the identical terms. This license is often compared to “copyleft” free and open source software licenses. All new works based on yours will carry the same license, so any derivatives will also allow commercial use. This is the license used by Wikipedia, and is recommended for materials that would benefit from incorporating content from Wikipedia and similarly licensed projects.

Attribution-NonCommercial-ShareAlike CC BY-NC-SA

This license lets others remix, tweak, and build upon your work non-commercially, as long as they credit you and license their new creations under the identical terms.

Attribution-NonCommercial CC BY-NC

This license lets others remix, tweak, and build upon your work non-commercially, and although their new works must also acknowledge you and be non-commercial, they don’t have to license their derivative works on the same terms.

Attribution-NoDerivs CC BY-ND

This license allows for redistribution, commercial and non-commercial, as long as it is passed along unchanged and in whole, with credit to you.

Attribution-NonCommercial-NoDerivs CC BY-NC-ND

This license is the most restrictive of our six main licenses, only allowing others to download your works and share them with others as long as they credit you, but they can’t change them in any way or use them commercially. 


Links between CC and GPL ? 

http://creativecommons.org/tag/gpl

Note that CC licenses are not approved by the Open Source Initiative.





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