10\. Embryo flushing

The data and resulting scienfic findings would also be beneficial to animal
breeders who are interested in aceiving greater efficiency in production of
cattle of specific types or sexes.

Researchers could also use the data generated from this research regarding
bovines to link to other animal models in efforts to better understand
reproduction, in particular reproductive problems.

#  2.1 Making data findable, including provisions for metadata [FAIR data]
Outline the discoverability of data (metadata provision)

The metadata is stored in Dublin Core format. All the data is captured through
measurements and sampling by the researchers of EMU. Some of the data can be
created automatically, but mainly all the data is produced bt the researchers
doing experiments and collecting data from those experiments. For the metadata
standarsd we are using appropritate sample size and correct sampling
methology.

**Outline the identifiability of data and refer to standard identification
mechanism. Do you make use of persistent and unique identifiers such as
Digital Object Identifiers?**

EMU DSpace mints (produce for the first time) DOIs via DataCite for deposited
research outputs.

**Outline naming conventions used**

All files will be named uniformly when storing them for public use, based upon
the following criteria:

No special characters such as "/ \ : * ? " < > [ ] & $ will be used in names.

Underscores (_) will be used to separate terms not spaces

Names will be 30 charcters or less in length

Names can specify the year and month of creation (YYYY-MM) at the end of the

name

Names will be descriptive of what information they contain - so that they are
understandable to someone who is unfamilar with the research.

Some information could be described in metadata including the following:

-Project or experiment name or acronym 

-Researcher name/initials 

-Date or date range of experiment 

-Type of data 

-Conditions 

-Version number of file 

-Three-letter file extension for application-specific files 

**Outline the approach towards search keyword**

Library will provide basic discovery metadata online (title, author, subjects,
keywords, department, etc.).

**Outline the approach for clear versioning**

Versions of files will only be stored and made available when relevant

Whenever possible, obsolete versions will be discarded or deleted (whilst
retaining the original 'raw' copy)

Files with multiple versions will include the letter V and the number of the
version before the date - for example V1 V2 V3, etc.

If appropriate, version control software e.g. Subversion, TortoiseSVN will be
used

**Specify standards for metadata creation (if any). If there are no standards
in your discipline describe what metadata will be created and how**

Dublin Core

#  2.2 Making data openly accessible [FAIR data]

**Specify which data will be made openly available? If some data is kept
closed provide rationale for doing so**

All metadata will made openly available via EMU Dspace. Any data that will be
kept closed will be done so either for IRP reasons or to protect
confidentiality issues.

**Specify how the data will be made available** All the data will be available
via DSpace.

**Specify what methods or software tools are needed to access the data? Is
documentation about the software needed to access the data included? Is it
possible to include the relevant software (e.g. in open source code)?**

Metadata will be available in conventional formats such as pdf files,
individual level data would be accessible using R software.

**Specify where the data and associated metadata, documentation and code are
deposited**

The data and associated metadata, documentation and code are deposited in
Estonian University of Life Sciences Library digital repository EMU DSpace.

**Specify how access will be provided in case there are any restrictions**

Data is freely accessible. Restricted data is accessible via password
protection.

#  2.3 Making data interoperable [FAIR data]

**Assess the interoperability of your data. Specify what data and metadata
vocabularies, standards or methodologies you will follow to facilitate
interoperability.**

The metadata will be created by experiments and different measurements. Some
of the information about bovines can be created automatically.

The metadata is storaged at first in the University of Life Sciences personal
server spaces and after data publication in DSpace.

Whenever possible interoperatable files, formats will be used such as ,CSV.

**Specify whether you will be using standard vocabulary for all data types
present in your data set, to allow inter-disciplinary interoperability? If
not, will you provide mapping to more commonly used ontologies?**

Whereever possible standard vocabulary will be used for data sets. No mapping
to more commonly used ontologies will be offered.

**2.4 Increase data re-use (through clarifying licenses) [FAIR data] Specify
how the data will be licenced to permit the widest reuse possible** Unless
protected via IRP, no licenses will be needed to use data.

**Specify when the data will be made available for re-use. If applicable,
specify why and for what period a data embargo is needed**

The data will be made available after articles have been published in peer-
reviewed journals.

As the time to publish or seek patents may vary greatly, no precise time
period can be stated.

**Specify whether the data produced and/or used in the project is useable by
third parties, in particular after the end of the project? If the re-use of
some data is restricted, explain why**

Restrictions to data sharing may be due to participant confidentiality,
consent agreements or IPR. Restrictions are required until the data is
published. After that all the data can be used by third parties. Restrictions
are needed in order to be published in peer-reviewed journals. Limited embrago
period until data is published.

**Describe data quality assurance processes**

The consistency and quality of data collection will be controlled and
documented with repeated samples or measurements, standardised data capture,
data entry validation, peer-review of data or representation with controlled
vocabularies.

**Specify the length of time for which the data will remain re-usable**

In perpetuity

#  Allocation of resources

**Estimate the costs for making your data FAIR. Describe how you intend to
cover these costs**

Free of charge.

**Clearly identify responsibilities for data management in your project**

Data Management is handled by researchers during collection and by staff of
the EMU

Library during curation and preservation

**Describe costs and potential value of long term preservation** Its
librarians voluntary job.

#  Data security

**Address data recovery as well as secure storage and transfer of sensitive
data**

EMU DSpace is maintained and operated by Estonian University of Life Sciences
Library. All data files are stored in Estonian University of Life Sciences
storage service in two independent copies. Preservation and back-ups of the
data are ensured by the EMU DSpace preservation policies: daily backups,
security updates, tightly controlled administrative access. Sensitive data is
available only for SEARMET group members via login.

#  Ethical aspects

**To be covered in the context of the ethics review, ethics section of DoA and
ethics deliverables. Include references and related technical aspects if not
covered by the former**

No research involving human participants is done. All the researchers have
given consent for data preservation and sharing. For animal experiments there
are licenses obtained from the local ethics committee in accordance with the
EU guidelines. These licences are preserved in EMU DSpace.

Sensitive data will be securely stored at EMU DSpace.

#  Other

**Refer to other national/funder/sectorial/departmental procedures for data
management that you are using (if any)**

N/A

SEARMET Deliverable #2.3  
  
<table>  
<tr>  
<th>

</th>  
<th>

**H2020-TWINN-2015** **Grant Agreement no**

This project is funded under the **EUROPEAN COMMISSION** in the

Framework Programme for Research and Innovation (2014-2020).

</th> </tr>  
<tr>  
<td>

Call:

</td>  
<td>

Work programme **H2020** under **“Spreading Excellence and Widening
Participation”, call: H2020-TWINN-2015: Twinning** (Coordination and Support
Action).

</td> </tr>  
<tr>  
<td>

Project full title:

</td>  
<td>

Scientific Excellence in Animal Reproductive Medicine and Embryo Technology

</td> </tr>  
<tr>  
<td>

Project acronym:

</td>  
<td>

SEARMET

</td> </tr>  
<tr>  
<td>

Work Package (WP):

</td>  
<td>

2

</td> </tr>  
<tr>  
<td>

Deliverable (D):

</td>  
<td>

2.3

</td> </tr>  
<tr>  
<td>

Due date of deliverable:

</td>  
<td>

20

</td>  
<td>

</td> </tr>  
<tr>  
<td>

Author(s):

</td>  
<td>

Ülle Jaakma

</td> </tr>  
<tr>  
<td>

Contributor(s):

</td>  
<td>

</td> </tr>  
<tr>  
<td>

Start date of project:

</td>  
<td>

1 January 2016

</td>  
<td>

Duration: 36 Months

</td> </tr> </table>  
<table>  
<tr>  
<th>

**Dissemination Level**

</th>  
<th>

</th> </tr>  
<tr>  
<td>

**PU**

</td>  
<td>

Public

</td>  
<td>

_PU_

</td> </tr>  
<tr>  
<td>

**CO**

</td>  
<td>

Confidential, only for members of the consortium (including the Agency
Services)

</td>  
<td>

</td> </tr> </table>

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