GenTree are numbers, texts, images and sounds generated by the partners during
the project and **needed to validate** the results presented in scientific
publications and other communication documents. They include metadata, i.e.
the information describing the managed research data.

This document does not concern data preexisting the GenTree project. These
data are part of the “background” contributions supplied by the GenTree
partners and are identified in the Consortium Agreement document. This
document does not concern either data originated from third party producers.
These data are managed according to the rules defined by these third parties.

With the objective of **stimulating the use and re-use of data** and to
contribute to the development of the “Open Science” strategy of the European
Union through **data sharing** , the GenTree data policy framework provides
recommendations and rules for data management and accessibility. It is based
on existing documents published in the scientific literature, such as Michener
(2015, "Ecological data sharing” Ecologial Informatics) and the guidelines
produced by the European Commission (2016, Guidelines on Data Management in
Horizon 2020).

The **general purpose** of this document is:

  1. to identify the different types of data (origin and authorship, see annex 1 for definition of terms) that will be collected during GenTree and define the different categories of users for these data during GenTree and after it is finished. 

  

  2. to provide documents and recommendations for data management and publication: 

  

  

  * a Data Management Plan template (Annex 2); 

  

  * recommendations for data sharing (Annex 3); 

  

  * data licenses adapted to specific Intellectual Properties (Annex 4); 

  

c) to provide support for the production and management of discovery metadata:
- metadata standards compliant with international requirements and
constraints; - a metadata management system.

This document only focuses on data, including output data from modeling
activities. Models and modeling platforms involved in the GenTree project are
out of its scope. Intellectual property and sharing rules related to these
components are addressed in the Consortium Agreement. Plant material and DNA
are also outside the scope of this document. Their exchange and transfer will
be addressed in a separate Material Transfer Agreement document.

#  3- Data Management Plan

All GenTree research activities that collect or generate data should provide a
Data

Management Plan (DMP). Although there is no unique rule to define at which
scale the DMP should be elaborated, it must correspond to a coherent data set
relative to their management. The H2020 DMP template (Annex 2) should be
preferably used by GenTree partners. For each data set, the following
information needs to be provided: Data set reference and name, data set
description, standards and metadata used, how data will be shared, how data
will be archived and preserved (including storage and backup).

#  4- Data sharing agreement for GenTree partners

A data sharing agreement (Annex 3) has to be signed by all GenTree partners in
order to ensure the full sharing of data among partners. Data will be
immediately accessible for all partners, without any embargo. Studies based on
specific data sets must be proposed as coresearch activities to the partner(s)
owning the intellectual property rights.

#  5- Data identification/citation

GenTree data will be stored in GnpIS  (
_https://urgi.versailles.inra.fr/Tools/GnpIS_ )  , a dedicated multispecies
integrative Information System which ensures confidential treatment, secured
archiving, browsing, visualizing and use and re-use of data. GnpIS is a
licensed information system that will be used as is, without further
development from its current state, by GenTree partners. GnpIS cannot be
installed at GenTree partner laboratories.

GenTree recommends that data sets should be identified by a DOI. GnpIS makes
it possible to generate DOI for data sets. Data and their DOI will remain
accessible to partners for a minimum of 10 years after they are stored in
GnpIS.

GenTree encourages the publication of data papers making the data produced by
GenTree accessible to the community of researchers or stakeholders interested
in the management and sustainable use of forest genetic resources in Europe.
GenTree encourages that publications using GenTree data clearly identify and
acknowledge such data and their Information System, either by citing the
relevant data papers or by linking to the proper DOI in the GenTree
Information System.

#  6- Metadata standards and tools for discovery

All GenTree datasets should be described by standardized metadata for
discovery purposes. GenTree metadata will be stored and managed using the same
dedicated Information System as for data, GnpIS  (
_https://urgi.versailles.inra.fr/Tools/GnpIS_ )  . Metadata will follow the
ISO19115/19139 standards and will be compliant with the EU INSPIRE directive.
GenTree metadata will be fully and freely accessible.

Each Partner shall supply GnpIS, the GenTree Information System, with its
metadata as soon as data are generated. Each Partner shall also supply the
GenTree Information System with Metadata from third parties, according to the
rules defined by such third party.

# GenTree DMP template

Templates are based on H2020 and DCC templates (
_http://www.dcc.ac.uk/resources/howguides/develop-data-plan_ )  .

The purpose of the Data Management Plan (DMP) is to provide an analysis of the
main elements of the data management policy that will be used by the
applicants with regard to all the datasets that will be generated by the
project. The DMP is not a fixed document, but evolves during the lifespan of
the project. The DMP should address the points below on a dataset by dataset
basis and should reflect the current status of reflection within the
consortium about the data that will be produced.

GenTree data should be discoverable, accessible, assessable and intelligible,
useable beyond the original purpose for which they were collected and,
finally, interoperable to specific quality standards. In GenTree, there are 3
main categories of data: site description, DNA sequences and phenotypic
traits.

For each data set, the following 5 main items should be addressed and
specified:

**1- Data set reference and name** Identifier for the data set to be produced.

##  **2- 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 re-use.

Questions to consider on data set description:

  * What data will you create? 

  

Guidance:

  * Give a brief description of the data that will be created, noting its content and coverage 

  

##  **3- 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.

Questions to consider on standards and metadata:

  * How will you capture / create the metadata? 

  

  * Can any of this information be created automatically? 

  

  * What metadata standards will you use and why? 

  

Guidance:

  * Metadata should be created to describe the data and aid discovery. Consider how you will capture this information and where it will be recorded, e.g. in a database with links to each item, in a ‘readme’ text file, in file headers etc. 

  

  * Researchers are strongly encouraged to use community standards to describe and structure data, where these are in place. The DCC offers a  catalogue of disciplinary metadata standards. 

  

##  **4- 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,
privacyrelated, security-related).

Questions to consider on methods for data sharing:

  * How will you make the data available to others? 

  

  * With whom will you share the data, and under what conditions? 

  

Guidance:

  * Consider where, how, and to whom the data should be made available. Will you share data via a data repository, handle data requests directly or use another mechanism? 

  

  * The methods used to share data will be dependent on a number of factors such as the type, size, complexity and sensitivity of data. Mention earlier examples to show a track record of effective data sharing. Questions to consider on restrictions for sharing: 

  

  * Are any restrictions on data sharing required? e.g. limits on who can use the data, when and for what purpose. 

  

  * What restrictions are needed and why? 

  

  * What action will you take to overcome or minimise restrictions? 

  

Guidance:

  * Outline any expected difficulties in data sharing, along with causes and possible measures to overcome these. Restrictions to data sharing may be due to participant confidentiality, consent agreements or IPR. Strategies to limit restrictions may include: anonymising or aggregating data; gaining participant consent for data sharing; gaining copyright permissions; and agreeing a limited embargo period. 

  

Questions to consider on data repository:

  * Where (i.e. in which repository) will the data be deposited? 

  

Guidance:

  * Most research funders recommend the use of established data repositories, community databases and related initiatives to aid data preservation, sharing and re-use. 

  

  * An international list of data repositories is available via Databib or Re3data. **5- 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.

Questions to consider on Preservation Plan:

  * What is the long-term preservation plan for the dataset? e.g. deposit in a data repository 

  

  * Will additional resources be needed to prepare data for deposit or meet charges from data repositories? 

  

Guidance:

  * Researchers should consider how datasets that have long-term value will be preserved and curated beyond the lifetime of the grant. Also outline the plans for preparing and documenting data for sharing and archiving. 

  

  * If you do not propose to use an established repository, the data management plan should demonstrate that resources and systems will be in place to enable the data to be curated effectively beyond the lifetime of the grant. 

  

Questions to consider on Resourcing:

  * What additional resources are needed to deliver your plan? 

  

  * Is additional specialist expertise (or training for existing staff) required? 

  

  * Do you have sufficient storage and equipment or do you need to cost in more? 

  

  * Will charges be applied by data repositories? 

  

  * Have you costed in time and effort to prepare the data for sharing / preservation? 

  

Guidance:

  * Carefully consider any resources needed to deliver the plan. Where dedicated resources are needed, these should be outlined and justified. Outline any relevant technical expertise, support and training that is likely to be required and how it will be acquired. Provide details and justification for any hardware or software which will be purchased or additional storage and backup costs that may be charged by IT services. 

  

  * Funding should be included to cover any charges applied by data repositories, for example to handle data of exceptional size or complexity. Also remember to cost in time and effort to prepare data for deposit and ensure it is adequately documented to enable re-use. If you are not depositing in a data repository, ensure you have appropriate resources and systems in place to share and preserve the data. 

  

  * See UKDS guidance on costing data management. 

  

# GenTree Data Sharing Agreement

**1\. Conditions for supplying Data and Metadata to the GenTree Information
System 1.1 Data and Metadata coming from Parties of the GenTree Project**

##  a) Data and Metadata defined as Background

  * Each Party shall supply the GenTree Information System with its Data and Metadata as soon as possible, if these Data and Metadata are needed for carrying out the activities of the research project, unless these Data or Metadata have been excluded or limited in the Consortium Agreement. 

  

  * The Parties will provide a citation (acknowledgement) reference for each Data set included as a Metadata into the GenTree Information System 

  

##  b) Data and Metadata (Foreground) produced by the Parties

  * Each Party shall supply the GenTree Information System with its Data and Metadata as soon as they are generated if these Data and Metadata are needed for carrying out the activities of the research project. 

  

  * The Parties will provide a citation (acknowledgement) reference of each Data set provided into the GenTree Information System 

  

###  1.2 Data and Metadata coming from third Parties

 The Parties shall supply the GenTree Information System with Data and
Metadata from third parties, according to the rules defined by each such third
party.

###  2 Access policy to Data and Metadata during, outside and after the
GenTree Project

####  2.1 Access to Metadata

 Public access to the Metadata will be given once these are entered into the
GenTree Information System.

**2.2 Access to Data**

##  a) Access to Data defined as Background

  * Access to Data defined as Background will be given to the GenTree partners as needed for the implementation of their research activities and projects in compliance with the Consortium Agreement. 

  

  * Access to Data defined as Background will be given to the scientific community upon prior authorisation given by the Party who owns the data or rights pertaining to such data 

  

##  b) Access to Data defined as Foreground

  * Access to Data defined as Foreground obtained within the GenTree Project, will be given to the GenTree partners once they are entered into the GenTree Information System, and to the public, after a maximum delay of 18 (eighteen) months after the end of GenTree. 

  

  * Parties who own the Data will endeavour to shorten this period of 18 (eighteen) months. The period of 18 (eighteen) months can be extended through a decision of the GenTree ExCom, after prior consultation of the owner the Data. 

  

###  3 Publication/communication

####  3.1 Metadata public release

 Metadata shall be released to the Public as soon as possible. Any
publication or communication of Data and/or Metadata shall be made according
to the provisions of article 8.4 (Dissemination) of the Consortium Agreement.

####  3.2 Referencing and acknowledgement

  * Any publication of the results obtained within the GenTree project must reference the project as follows: “This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 676876”. 

  

  * Any publication of results obtained that use Data and/or Metadata shared within the GenTree Information System, must reference the Data and/or Metadata owner, the citation reference of the dataset (whenever provided in the metadata) and the project. 

  

  * Any publication of a synthesis of Data and/or Metadata shared in the GenTree information system, including for dissemination or training, must reference the Data and/or Metadata owner, the citation reference of the datasets (whenever provided in the metadata) and the project.