#  Introduction

The data management plan (DMP) is a living document and will be updated over
the course of the project whenever significant changes arise, such as new data
or changes in consortium policies. The DMP will be updated in month 24 and
month 36, and for the final review in month 48\. The DMP will be written
according to the ‘H2020 templates: Data management plan v1.0

– 13.10.2016’

#  Data Summary

In order to facilitate the data collection, document sharing and
collaboration, the University of Nottingham's file will make use of a
combination of Microsoft SharePoint and a Git based repository service, figure
1.

The latter is managed internally by the George Green Institute for
Electromagnetics Research (GGIEMR) and the former is supplied as part of a
long-term business contract with Microsoft. This combination will guarantee
availability and data integrity throughout and beyond the span of the project.

Both services will be available to all project partners either by direct login
to the service, a private (to that individual) hyperlink or a public
hyperlink. Privileges to read, edit or contribute to the data and/or documents
can be controlled via each approach.

**Figure 1.** Data management and sharing services available at The George
Green Institute, University of Nottingham.

##  Expected Data Formats

The anticipated experimental and simulation work will encompass large range of
different model description, experimental setup data, experimental measurement
data and documentation. The data stored will therefore need able to reflect
the multitude of sources. In order to give an accessible and coherent
representation of the data all project partners will concentrate on a few, but
very common data formats where possible, namely:

  1. Measurement data, an ASCII based touchstone format, file ending .sp2. These files are directly written by measurement instrumentation and can be read by a multitude of software. 

  

  2. Numerical data stored in MATLAB compatible (binary format for large data sets) or comma separated variable (.csv) formats (for smaller data sets). The corresponding files should be accompanied by scripts that allow for the reading and visualisation of the data, or by an explicit description on how to read the data using other applications. 

  

  3. The data collected will, in the main, originate through experimental measurement. The data sets collected can range from a number of kilobytes (KB) through to many gigabytes (GB) in size 

  

  4. Documentation should be provided as editable MS Word files i.e. .docx. Final versions of documents for dissemination should also be stored as .pdf. 

  

  5. Simulation results arising from using commercial software should be made available along with the complete simulation packages’s ‘project’ files used to generate the result(s). 

  

  

#  FAIR data

##  Making data findable, including provisions for metadata

To facilitate the usage and re-use of the stored date, all stored data will be
accompanied by a text-based description of the data i.e. its source and format
and how the data can be interacted with. The precise detail of the data format
should be contained with a folder containing the data and named using a
convention that readily identifies the source Institution and ESR.

Measurement datasets originating from electronic instruments usually will
usually themselves contain metadata describing the state of the instrument
during data acquisition. Therefore, metadata, in a human readable format will
be held external to the data they describe. The metadata will follow the
principles of the Dublin Core Schema and for each of the datasets stored the
following metadata elements will be provided, table 6.1:  
  
<table>  
<tr>  
<th>

**Metadata Element**

</th>  
<th>

**Use**

</th>  
<th>

**Example value**

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

**Title**

</td>  
<td>

Name of dataset

</td>  
<td>

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

**Subject**

</td>  
<td>

Specific research topic

</td>  
<td>

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

**Description**

</td>  
<td>

Description of dataset

</td>  
<td>

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

**Creator**

</td>  
<td>

Primary person responsible for collecting dataset

</td>  
<td>

Typically the ESR

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

**Publisher**

</td>  
<td>

Parent Institution of Creator

</td>  
<td>

e.g. University of Nottingham

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

**Contributor**

</td>  
<td>

Other(s) involved in creating dataset

</td>  
<td>

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

**Date**

</td>  
<td>

Date of creation

</td>  
<td>

YYYY-MM-DD

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

**Type**

</td>  
<td>

Nature of the dataset

</td>  
<td>

e.g. vector network analyser

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

**Format**

</td>  
<td>

Format of the dataset and/or file identifier

</td>  
<td>

Touchstone, .sp2

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

**Language**

</td>  
<td>

Language of the dataset

</td>  
<td>

Use ISO Code 639-1 Code e.g. for English: en

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

**Relation**

</td>  
<td>

Any related resources

</td>  
<td>

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

**Rights**

</td>  
<td>

Any rights related to the dataset

</td>  
<td>

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

**Table 6.1:** Table metadata elements applicable to SCENT datasets.

The main entrance point for all the data will be via the following link:
_https://uniofnottm.sharepoint.com/sites/SCENT_ to which all members of the
project will have access.

The longevity of the data storage is ensured by a contract between University
of Nottingham and Microsoft for their content management solution
“Sharepoint”. The administrative accounts are spread out over several
permanent members of staff at UN to ensure responsiveness and availability.

##  Making data openly accessible

The Horizon 2020 strategic priority of Open Science (OS) will be completely
respected by all participants. OS describes the on-going evolution of doing
and organising science, as enabled by digital technologies and driven by
globalisation of the scientific community. OS aimed at promoting diversity in
science and opening it to the general public, in order to better address the
societal challenges and ensure that science becomes more responsive both to
socioeconomic demands and to those of European citizens. OS also provides
significant new opportunities for researchers to disseminate, share, explore
and collaborate with other researchers. OS aims at improving and maximizing
access to and re-use of research data generated by funded projects. Results
should be findable, accessible, interoperable and reusable (FAIR). Therefore
SCENT will deposit and take measures to make it possible for third parties to
access, mine, exploit, reproduce and disseminate - free of charge for any user
– data resulting as well as results from the funded project.

##  Making data interoperable

  * Data will be stored in formats as outlined in section 1.1 to allow the re-use of any data as appropriate. 

  

  * Research data management plans will ensure that research data are available for access and reuse where required by Horizon 2020 terms and conditions or where otherwise appropriate and under appropriate safeguards. 

  

  * ESRs are responsible for deciding, subject to legal, ethical and commercial constraints, which data sets are to be released to meet their obligations. Data shall be released for access and reuse as soon as practicable after research activity is completed and results published. 

  

##  Increase data re-use (through clarifying licences)

  * The privacy and other legitimate interests of the subjects of research data must be protected. 

  

  * Research data of future historical interest, and all research data that represent records of the project’s partner Institutions, including data that substantiate research findings, will be offered and assessed for deposit and retention in an appropriate national or international data service or domain repository, or a University repository. 

  

  * Exclusive rights to reuse or publish research data should not be handed over to commercial publishers or agents without retaining the rights to make the data openly available for re-use, unless this is a condition of funding. 

  

#  Allocation of resources

Data storage will be managed internally by the George Green Institute for
Electromagnetics

Research (GGIEMR) and the former is supplied as part of a long-term business
contract with Microsoft. This combination will guarantee availability and data
integrity throughout and beyond the span of the project. There are no
additional costs to the project.

#  Data security

All data is subject to local backup and backup provision through the cloud
based services maintained at the University of Nottingham. All data stored on
University Microsoft Cloud based services is encrypted and therefore secure.
Data is accessible through modern web browsers over the secure Hypertext
Transfer Protocol Secure (https).

#  Ethical aspects

No ethical aspects for the data are expected. Research data will be managed to
the highest standards throughout the research data lifecycle as part of the
University’s commitment to research excellence.

#  Conclusion

To reflect the dynamic nature of the generation of data and its associated
type, this is a living document and will be updated at 12 monthly intervals to
include a summary of data stored.