#  Executive Summary

This deliverable is D1.7 Data Management Plan of the blueSPACE project.
BlueSPACE addresses the challenges of increased capacity, scalability,
manageability, resource allocation of 5G networks by adopting a pragmatic yet
disruptive and future proof approach based on space division multiplexing in
the radio access network. BlueSPACE participates in the Open Research Data
Pilot and as a result specifies its approach to research data management in
this Data Management Plan (DMP).

The purpose of this document is to provide an initial description of the types
of data that will be generated and collected during the project and to lay out
the blueSPACE strategy for management and access regulation of this data.
Specifically, this initial version DMP describes the data management life
cycle for the datasets that have so far been identified and will be collected,
processed and/or generated by a research project. It covers:

  * the handling of research data during and after the project; 

  

  * what data will be collected, processed or generated; 

  

  * what methodology and standards will be applied; 

  

  * whether data will be shared/made open and 

  

  * how data will be curated and preserved. 

  

This document introduces the first version of the project Data Management
Plan. Following the EU’s guidelines regarding the DMP, this document may be
updated – if appropriate – during the project lifetime (in the form of
deliverables). The data management plan will cover all the data life cycle.

_Figure 1.1: Steps in the data life cycle [1]_

#  Introduction

Data management is an important component of the responsible conduct of
research. Thus, there is a need for a document to describe and define how data
will be collected, stored and preserved, managed and shared. This document,
which serves this purpose, is a Data Management Plan.

Horizon 2020 projects that are part of the Open Research Data Pilot are
required to evaluate the possibilities of making the research data accessible
via open access, following the motto “As open as possible, as closed as
necessary.” It is the aim to provide to end users free of charge online access
to project scientific information and outcomes from design and research
efforts of the consortium where deemed possible and feasible and as described
in this DMP.

Developing a DMP, the description of what data will be open access and how
these data will be shared and preserved will be introduced.

The aim of the current DMP is to describe blueSPACE’s strategy towards
research data management and to make the blueSPACE data easily:

  * Discoverable 

  

  * Intelligible 

  

  * Accessible 

  

  * Useable 

  

  * Interoperable 

  

First for the partners within the project and, second, for the wider research
community, related industries and the general public, where the latter is
deemed desirable and feasible, while maintaining the interests of the project
consortium with respect to, e.g., intellectual property (IP) protection and
commercial exploitation of project results.

The blueSPACE project participates in the Pilot on Open Research Data. The
consortium follows the principles of the concept of open science, therefore
all data produced by the project will be evaluated for the possibility to be
published under open access rules, in line with the principles described in
this document.

The blueSPACE data management plan is structured into the following sections:
section 2 discusses the structure of the DMP and basic strategy for data
management in blueSPACE, section 3 focusses on what part of the outputs of
blueSPACE can be made open access and the strategy to evaluate the latter,
section 4 discusses IPR and knowledge management related issues, while section
5 considers ethical aspects. Finally, section 7 concludes and summarizes the
blueSPACE DMP.

#  Research Data Management within blueSPACE

This section describes the structure of the blueSPACE research data management
plan (DMP) and identifies the main considerations for research data management
within blueSPACE. After introducing the general structure, it discusses the
types of data have been identified as possible outputs of blueSPACE, lays out
the basic naming conventions and metadata standards for generated data and
considers archiving, preservation and data sharing. Finally, it discusses the
intended use of the DMP within the project and across the project duration.

##  Structure of the blueSPACE DMP

The structure of DMP follows the parameters to be clarified regarding the
management of the project’s generated data. Following the template recommended
by the EC [2], the Data Management Plan (DMP) includes the following major
components, as described in Figure 2.1:

  * Data set reference and name 

  

  * Data set description 

  

  * Standards and metadata 

  

  * Data sharing 

  

  * Archiving and preservation 

  

These parameters and blueSPACE’s strategy for addressing them are discussed in
the following. It is the responsibility of each consortium partner to ensure
the data generated by the partner is treated according to the details laid out
in this DMP.

Data Management plan

Archiving and

preservation

Data sharing

Standards and

metadata

Data set

description

Data set reference

and name

_Figure 2.1 blueSPACE Data Management Plan structure_

##  Data types expected to be generated by blueSPACE

The information and data that is expected to be generated by the consortium of
the blueSPACE project includes the following four types of data:

  1. Human readable documents: project documentation, research documentation, publications etc. 

  

  

[typical office document formats, e.g., predominantly in the ‘Portable
Document Format’ (PDF)]

  2. Design documents for architecture and hardware components [design software specific formats] 

  

  3. Source code and software binaries: for implementation of functionalities, support of experimentation and simulation [plain text, binary software formats] 

  

  4. Experimental data: raw data from experiments and processed statistical data [binary raw data storage formats, e.g., ‘Hierarchical Data Format’ (h5)] 

  

  

These four data types are considered as distinct classes of data, with
different requirements towards their description and metadata, their
requirements for archiving and their potential to be shared via open access.
The following sections will consider these different types and separately
discuss them with regards to the aforementioned requirements.

##  Data Set Reference and Name

Several data types will be generated within the blueSPACE project with
different identified data sets and requirements. The data sets of all data
types however will follow a common overall naming scheme. The suggested naming
scheme is:

BlueSPACE_[Type]_[Name]_[Date]_[Partner]_[Version], where

  * [Name] is a short and characteristic name for the data 

  

  * [Type] is the type of data (code, publication, measured data etc.) 

  

  * [Date] is the date when data was produced (format: YYYYMMDD) 

  

  * [Partner] is the name of the organization associated with the dataset; specifically, in blueSPACE this can take the following values: 

    * TUE for Eindhoven University of Technology 

  

    * AIT for Athens Information Technology 

  

    * UPV for Universidad Politecnica de Valencia 

  

    * CTTC for Centre Tecnològic de Telecomunicacions de Catalunya 

  

    * UC3M for Universidad Carlos III de Madrid 

  

    * ADVA for ADVA Optical Networking SE 

  

    * THALES for THALES SA 

  

    * OPT for OPTOSCRIBE Limited 

  

    * LIONIX for Lionix International 

  

    * OP for ORANGE Poland 

  

    * ICOM for Intracom SA Telecom Solutions 

  

    * EULAMBIA for Eulambia Advanced Technologies 

  

    * NXW for Nextworks 

  

    * OTE for Hellenic Telecommunications Organisation SA 

  

  

  * [Version] is the numbering of versions of the data 

  

  * _ (underscore) is used as the separator between the fields 

  

For example, the following name of a potential data set:
_BlueSPACE_Configuration_code_20190831_AIT_v2_

would identify a data set of the type code, which issued to configure a
software element. The data set is generated on 30-08-2019 by AIT (which is
thus the owner of the data set) and the current data set is the second
version.

##  Data Set Description and Metadata Standards

A data set for the purpose of this DMP is considered to consist of one or
multiple files and associated metadata as well as a description of the data
set. A data set may combine files of multiple of the data types defined in
section 2.2. The description and metadata of the dataset serve the purpose of
identification, description and guidance for use and will at least contain the
following information, fulfilling the requirements of the DataCite [3] and
DublinCore [4] metadata schemas/standards:

  * Identifier(s): an identifier as per section 2.3 plus, optionally, additional unique identifiers (e.g., DOI 

  

[5] for publicized data sets, a deliverable number of project deliverables
etc.)

  * Creator/Author: name(s) and affiliation(s) 

  

  * Title: title of the data set 

  

  * Publisher: the entity publishing the data set 

  

  * Date: the year and month of publication, optionally the day and time of day 

  

  * Type: the dataset type, as defined in Table 2.1 

  

  * Format: the format(s) of the included data 

  

  * Description: a description of the data set, including description of its origin and intended use, as well as further description as per Table 2.1 

  

Five types of data set have been identified that are expected to be generated
within blueSPACE and are summarized with their typical included data types, a
short description, the required additional metadata as well as typical access
options in Table 2.1. Additional data set types or requirements may be added
over the course of the project as they are identified and defined.

_Table 2.1 blueSPACE data set definitions and description_  
  
<table>  
<tr>  
<th>

**Data Set Type**

</th>  
<th>

**Data**

**Types**

**(typical)**

</th>  
<th>

**Description**

</th>  
<th>

**Required information (in addition to above)**

</th>  
<th>

**Release***

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

Project Data

</td>  
<td>

(i)

</td>  
<td>

Financial and administrative data, partner information, periodic reports,
contracts etc. Typically, confidential to the consortium plus the European
Commission; certain data sets may be private to single partners or subsets of
partners.

</td>  
<td>

none

</td>  
<td>

PR, CO

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

Reports, dissemination and communication

</td>  
<td>

(i)

</td>  
<td>

Reports, deliverables, presentations, publications and communications, incl.
the project website and social media. Typically, public or where required
confidential to the consortium.

</td>  
<td>

\- short executive summary/abstract

</td>  
<td>

PU, CO

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

Design data

</td>  
<td>

(i), (ii)

</td>  
<td>

Software, hardware, system and network designs and related documentation.
Typically, confidential to the consortium, may be public in special cases or
private to a single partner in exceptions.

</td>  
<td>

\- intended use - design goal

</td>  
<td>

CO, PU, PR

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

Raw research data

</td>  
<td>

(i), (iii), (iv)

</td>  
<td>

Research data from simulations and experiments. May include relevant
software/core for simulation, instrumentation and/or analysis.

Typically, confidential to the consortium,

open access where possible and desirable. May be private to a single partner
in some cases

</td>  
<td>

  * intended use - data format and layout 

  

  * experimental/ simulation setup 

  

</td>  
<td>

CO, PU, PR

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

Analysed research data

</td>  
<td>

(i), (ii), (iii),

(iv)

</td>  
<td>

Processing and analysis results based on raw research data, including reports
and findings. Further includes models, statistical analysis and analytical
studies. Typically, confidential to the consortium,

open access where possible and desirable.

</td>  
<td>

\- intended use - short executive summary/abstract - relation to relevant raw
research data

</td>  
<td>

CO, PU

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

* PR: private to a consortium partner, CO: confidential within the consortium or a specified audience, PU: public 

##  Data Sharing and Preservation

The sharing and preservation of data sets generated in blueSPACE are highly
dependent on the data set type. A priori it is within the responsibility of
each consortium partner to maintain and preserve the data generated at their
side. A collaboration and sharing platform (SharePoint) has been set up to
allow collaborative creation and sharing of data sets containing predominantly
human readable documents (type (i)). The data sets deposited and created on
this sharing platform are stored and preserved by the coordinator.

Additional requirements and strategies for sharing and preservation of some
data set types or more specific groups of data sets with specific
circumstances have been agreed and are summarized in Table 2.2.

_Table 2.2 Sharing and preservation of certain data set types_  
  
<table>  
<tr>  
<th>

**Data Set Type**

</th>  
<th>

**Description**

</th>  
<th>

**Release***

</th>  
<th>

**Access**

</th>  
<th>

**Sharing**

</th>  
<th>

**Preservation**

</th>  
<th>

**Responsible**

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

Project Data

</td>  
<td>

All shared project data

</td>  
<td>

CO

</td>  
<td>

Closed

</td>  
<td>

SharePoint

</td>  
<td>

SharePoint

</td>  
<td>

Coordinator

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

Reports, dissemination and communication

</td>  
<td>

Project deliverables

</td>  
<td>

CO

</td>  
<td>

Closed

</td>  
<td>

SharePoint, EC participant portal

</td>  
<td>

EC participant portal

</td>  
<td>

Deliverable editors & coordinator (sharing), coordinator (preservation)

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

Reports, dissemination and communication

</td>  
<td>

Project deliverables

</td>  
<td>

PU

</td>  
<td>

Open

</td>  
<td>

SharePoint, EC participant portal, project website

</td>  
<td>

EC participant portal

</td>  
<td>

Deliverable editors & coordinator (sharing), coordinator (preservation)

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

Reports, dissemination and communication

</td>  
<td>

Publications

</td>  
<td>

PU

</td>  
<td>

Open

(Closed)

</td>  
<td>

Publisher, Institutional repository

</td>  
<td>

Publisher, Institutional repository

</td>  
<td>

Authors, coordinator

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

Reports, dissemination and communication

</td>  
<td>

Project reports

</td>  
<td>

PU

</td>  
<td>

Open

</td>  
<td>

Project website, social media

</td>  
<td>

\-

</td>  
<td>

Authors, coordinator

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

Reports, dissemination and communication

</td>  
<td>

Project communications

</td>  
<td>

PU

</td>  
<td>

Open

</td>  
<td>

Project website, print media, social media

</td>  
<td>

\-

</td>  
<td>

Coordinator

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

Design data

</td>  
<td>

design data in open access

</td>  
<td>

PU

</td>  
<td>

Open

</td>  
<td>

Zenodo, online sharing platforms

</td>  
<td>

Zenodo

</td>  
<td>

Authors/Creators

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

Raw research data

</td>  
<td>

open access research data

</td>  
<td>

PU

</td>  
<td>

Open

</td>  
<td>

Zenodo, online sharing platforms

</td>  
<td>

Zenodo

</td>  
<td>

Authors/Creators

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

Analysed research data

</td>  
<td>

open access research data

</td>  
<td>

PU

</td>  
<td>

Open

</td>  
<td>

Zenodo, online sharing platforms

</td>  
<td>

Zenodo

</td>  
<td>

Authors/Creators

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

* PR: private to a consortium partner, CO: confidential within the consortium or a specified audience, PU: public 

##  Use of DMP within the project

The blueSPACE project partners will use this DMP as a reference for data
management (naming, providing metadata, storing and archiving) within the
project any time new data is generated within the project. It is within each
project partner’s responsibility that data generated and handled within the
project is treated according to the provisions of this DMP. The project
partners are introduced to the DMP and its use as part of WP1 activities.
Relevant questions and concerns from partners will also be addressed within
WP1.

The DMP will not only be a static reference, but is intended as a dynamic,
living and developing guideline, continuously adapted to reflect the data
types and data sets generated. It will thus be updated from its creation to
the end of blueSPACE project whenever required.

#  FAIR data

BlueSPACE Consortium follows the principle of FAIR data and so this section of
the Data Management Plan describes how blueSPACE ensures its data is findable,
accessible, interoperable and reusable. This applies to, first, the partners
within the project and, second, for the wider research community, related
industries and the general public, where the latter is deemed desirable and
feasible, while maintaining the interests of the project consortium with
respect to, e.g., intellectual property (IP) protection and commercial
exploitation of project results.

##  Making data findable and openly accessible

In order to make blueSPACE data findable, standard dataset names and full
metadata and descriptions will be provided as it is described in section 2.
The use of a standardized metadata set allows full indexing and easy search
for available data sets. Additionally, search keywords and clear version
numbers will be provided to optimize possibilities for re-use.

blueSPACE data sets will be evaluated if open access is desirable and can be
provided. Where such evaluation is positive, data sets will be made available
online via research data sharing platforms, with Zenodo [6] identified as the
primary option. In addition to the standard metadata, Zenodo includes
assignment of a DOI [5], sophisticated versioning and licensing/access
control.

##  Data Sharing

Data sharing in blueSPACE comes in multiple fashions. First, human readable
data that is generated through the project and released to public access will
be shared through project website. This website permits the users and research
collaborators to have easy and convenient access to the project communications
and documentation and together with the project social media activities serves
as main instrument for outreach beyond the research community.

Second, all data sets of the reports, dissemination and communication, design
data, raw research data and analyzed research data types will be evaluated if
open access is desirable and can be provided. Where such access can be
provided it will be provided via online research data sharing platforms as
discussed in the previous section.

The consortium aims for most of the project data to be made openly accessible.
However, sharing and the provision of open access is contingent on that it is
deemed desirable and feasible, while maintaining the interests of the project
consortium with respect to, e.g., intellectual property (IP) protection and
commercial exploitation of project results. If data sets are produced which
according to this evaluation cannot be shared, the reasons will be documented
and these data sets will be preserved by the generating partner in a
repository with limited access.

##  Archiving and Preservation

The archiving and preservation of project data is mainly the responsibility of
the consortium partner generating the data, as described in section 2.5. For
data made publicly accessible, different provisions are made within the
consortium.

Data that is made publicly accessible via the project website and social media
is considered to be of relevance only in the short and medium term and will be
maintained by the respective platforms for a few years beyond the project
duration.

Data sets that are scientific publications are archived for open access by the
publishing consortium partner(s) in their respective institutional
repositories or similar; these also serve for preservation for the time beyond
the project duration. Additionally, the publisher, i.e., engineering or
academic society or publishing house, will deposit the publications in their
respective libraries where perpetual online availability is guaranteed.

Research data made publicly available will be deposited on online sharing and
depositing platforms, where storage duration and availability is governed by
the service description of the respective platform. In particular, Zenodo [6]
has been identified as the default sharing platform for any data sets made
publicly available and guarantees storage for at least 20 years,  1  which for
the majority of the research data sets generated in blueSPACE is considered
more than sufficient.

Finally, the main project outcomes and research results contained in the
public project deliverables will be archived by the European Commission via
the participant portal and associated systems.

##  Making data interoperable

It is blueSPACE’s aim to make its data interoperable to the maximum degree
possible without impacting the execution of work and research within the
consortium and where possible within reasonable effort. In order to make data
exchange possible, standard formats, vocabularies and document structures will
be applied. Additionally, metadata will be defined as per standards of
DataCite [3]. DataCite is a digital research data metadata standard, developed
with the purpose of accurate and consistent identification of datasets [3].

To further ensure interoperability and reusability of the research data,
blueSPACE has defined a number of additional, data set type dependent,
metadata and descriptive elements to be included for the respective data sets,
as shown in Table 2.1. These will aid interoperability and, combined with the
use of research best practices for data generation and research conception,
will ensure data sets generated within blueSPACE contain all required
information for exploitation by third party researchers.

#  IPR and Knowledge Management

##  IPR management

All project partners have Intellectual Property Rights (IPR) on their
technologies and data. Since the partners economically rely on their IPR, the
consortium is committed to allow protection of the relevant data and consult
with involved partners before publishing or making publicly accessible and
data sets.

The Consortium Agreement (CA) includes all the information and rules that
project partners take under consideration in order to define the important
points necessary to obtain the best possible management (financial conditions,
IPR, planning) of intellectual property. IPR will be managed in line with a
principle of equality of all the partners towards the foreground knowledge and
in full compliance with the general European Commission policies regarding:

  * Ownership, 

  

  * exploitation rights and 

  

  * confidentiality. 

  

In general, outcomes, innovative ideas, concepts and solutions where
protection by patent application is not sought by the partners and which are
not regarded trade secrets will be made public after agreement between the
partners, to allow others to benefit from these results and exploit them. The
CA is used as a reference for all IPR cases.

The Consortium Agreement provides rules for handling confidentiality and IPR
to the benefit of the consortium and its partners. All the project
documentation will be stored electronically in the project’s collaborative
environment which is maintained by the coordinator. Classified documents will
be handled according to the respective rules with regard to classification,
numbering, locked storage and distribution limitations. The policy, that will
govern the IPR management in the scope of blueSPACE, is driven by the
principles described in the CA.

#  Ethical aspects

The blueSPACE project consortium confirms that its actions that were mentioned
in the above chapters are respecting the ethical approach to the use cases and
pilots, conforming the regulations of the user informed consent and privacy
policies and regulations of the EU. The consortium will, where applicable, act
according to the:

  * General Data Protection Regulation 2016/679 (Protection of personal data) 

  

  * Opinion 23/05/2000 of the European Group on Ethics in Science and New Technologies concerning ‘Citizens Rights and New Technologies: A European Challenge’ and specifically those relating to: 

    * ICT (Protection of privacy and protection against personal intrusion) 

  

    * Ethics of responsibility (Right to information security) 

  

    * Article 15 (Freedom of expression and research and data protection) 

  

  

The project will ensure that the consortium agreement (or addendums thereof)
is constructed to enable such assurances to be formally made and adhered to by
consortium partners.

In addition, with respect to General Data Protection Regulation 2016/679
(Protection of personal of data), individual work packages will be
specifically requested to ensure that any models, specifications, procedures
or products also enable the project end users to be compliant with this
regulation.

BlueSPACE partners also will abide by professional and research ethical best
practices and comply with the Charter of Fundamental Rights of the European
Union [7].

#  Conclusion

This Data Management Plan provides an overview of the data that blueSPACE will
produce together with related challenges and constraints that need to be taken
into consideration. The methods described in this report allows the procedures
and infrastructures to be implemented by blueSPACE to efficiently manage the
data that will be produced. Most project partners will be owners or/and
producers of data, which implies specific responsibilities, as described in
this report. The blueSPACE Consortium will put strong emphasis on data
management with specific attention on IPR rules, regulations and good
practices.

_Table 6.1 blueSPACE data management summary_  
  
<table>  
<tr>  
<th>

**Data Management Plan**

</th>  
<th>

**blueSPACE DMP**

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

Data Set Reference and Name

</td>  
<td>

BlueSPACE_[Name]_[Type]_[Date]_[Partner]_[Version]

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

Data Set Description

</td>  
<td>

  * The nature of the data set 

  

  * The scale of the data set 

  

  * To whom could the data set be useful 

  

  * Whether the data set underpins a scientific publication 

  

  * Information on the existence (or not) of similar data sets. 

  

  * Possibilities for integration with other data sets and reuse 

  

  * Relation to other datasets 

  

  * Conditions for (re-)use 

  

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

Standards and Metadata

</td>  
<td>

Following recognized metadata standards, namely:

  * DataCite metadata standard [3] 

  

  * Dublin core [4] 

  

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

Data Sharing

</td>  
<td>

Data type specific (includes: blueSPACE, EC, and 5G PPP websites and
repositories, consortium partner institutional repositories, publisher
databases, research data sharing platforms)

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

Archiving and Preservation

</td>  
<td>

Same as for data sharing where suitable for archiving, especially: consortium
institutional, EC and 5G PPP repositories, publisher databases and Zenodo

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