#  Introduction

This document is Version 3 of the Data Management Plan (DMP), presenting an
overview of data management processes agreed upon among eConfidence project’s
partners. Data management is defined in accordance with the Grant Agreement
and, in particular, with Articles 27 (Protection of results), 28 (Exploitation
of results), 29 (Dissemination of results  1  ), 31 (Access rights to results)
and 39 (Personal Data Protection)

This DMP will first establish some general principles in terms of data
management and Open Access.

Subsequently, it will be structured as proposed by the European Commission in
_H2020 Programme – Guidelines on FAIR Data Management in Horizon 2020_ 2  ,
covering the following aspects:

  * Data Summary 

  

  * FAIR data 

  

  * Allocation of resources 

  

  * Data security 

  

  * Ethical aspects 

  

  * Other issues 

  

Data management processes covered in this plan relate in particular to the
following project outputs:

  * _Consortium Agreement_ (access rights, Personal Data Protection and IPR management  3  ) 

  

  * _Deliverable 1.1 – Quality plan_ (quality control for publications) 

  

  * _Deliverable 7.2 – Dissemination plan_ (publications and scientific results) 

  

  * _Deliverable 2.4 - Report with ethical and Legal Project compliance_ (ethics and data protection) 

  

  * Exploitation activities of WP6 

  

**Review timetable**

The DMP is a “living” document outlining how the research data collected or
generated will be handled during and after the eConfidence project. The DMP is
updated over the course of the project whenever significant changes arise
(e.g. new data collected, changes in the consortium or Consortium Agreement,
revision of IPR management, revision of research protocol). Furthermore, its
development and implementation is carried out in accordance with the following
review timetable, as envisaged in the Description of Action.

**By July 2017 – Version 2 (M10)**

  * General revision of the plan during the 2  nd  partners meeting. 

  

  * Revise open access strategy and participation in ORDP, if needed (in accordance with the definition of IPR management as per _Consortium Agreement_ ). 

  

  * Data collected: specification of types and formats of data generated/collected and the expected size. 

  

  * Findability: specification of naming conventions, search keywords identifications, versioning. 

  

  * Security: definition of procedures for data storage, data recovery and transfer of sensitive data. 

  

  * _Annex 1 – Data collected and processes_

  

**By February 2018 – Version 3 (M16-17)**

  * General revision of the plan during the 3  rd  partners meeting. 

  

  * Interoperability: specification of metadata vocabularies, standards and methodologies for datasets and assessment of interoperability level. 

  

  * Ethical aspects: revision of plan and strategy upon ethical approval of intervention protocol for research 

  

**By July 2018 – Version 4 (M22-23)**

  * Accessibility: description of documentation of tools needed and/or available to access and validate the data, such as code, software, methods and protocols (in accordance with WP5 deliverables). 

  

  * Licensing: final definition. 

  

  * Resource: final definition based on collected data, analysed results and prospective publications. 

  

#  General principles for data management

##  Data collected and personal data protection

Within the eConfidence project, partners collect and process research data and
data for general project management purposes, according to their respective
internal data management procedures and in compliance with applicable
regulations.

Data collected for general purposes may include contact details of the
partners, their employees, consultants and subcontractors and contact details
of third parties (both persons and organisations) for coordination,
evaluation, communication, and dissemination and exploitation activities.

Research data are collected and processed in relation with the research pilots
(WP2, WP4 and WP5).

During the project lifetime, data are kept on computers dedicated for the
purpose and securely located within the premises of the project partners. Data
archiving, preservation, storage and access, is undertaken in accordance with
the needed ethical approval at the partner institution and the institution
where the data is captured. The data is preserved for a minimum of 10 years
(unless otherwise specified). All data susceptible of data protection are
subject to standard anonymization and stored securely (with password
protection). The costs for this is covered by the partner organization
concerned.

Detailed information on the procedures that are implemented for data
collection, storage, protection, retention and destruction are provided in
_Annex 1 – Data collected and processes_ .

Confirmation that the above mentioned processes comply with national and EU
legislation is provided by each partner and verified by the Data Controller  4
.

##  Partners’ roles

For the overall data management flow, two main roles are identified (Data
Controller and Data Processor), as defined in the Consortium Agreement.

Table 1 contains the contacts of the institutional Data Protection Officers
responsible for data management and protection of personal data within each
partners’ organisation.

###  **Table 1 – Data Protection Officers**  
  
<table>  
<tr>  
<th>

**Organisation legal name**

</th>  
<th>

**Legal address**

</th>  
<th>

**Data Protection Officer**

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

P1 – Instituto Tecnologico de Castilla y León

</td>  
<td>

c/ Lopez Bravo 70 Burgos 09001 Spain

</td>  
<td>

Amelia García

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

P2 – EUN Partnership aisbl

</td>  
<td>

Rue de Trèves 61

B-1040 Brussels, Belgium

</td>  
<td>

John Stringer john.stringer@eun.org

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

P3 – Everis Spain SLU

</td>  
<td>

Avd. Manoteras, 52

28050 Madrid (Spain)

</td>  
<td>

Eduardo García Repiso

_Eduardo.garcia.repiso@everis.com_

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

P4 – Nurogames GmbH

</td>  
<td>

Schaafenstraße 25

50676 Cologne

</td>  
<td>

Jens Piesk

Jens.piesk@proj.nurogames.com

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

P5 – University of

Salamanca

</td>  
<td>

</td>  
<td>

D. JUAN MANUEL CORCHADO RODRÍGUEZ

Vicerrector de investigación y transferencia _vic.investigacion@usal.es_

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

P6 – FHSS Rijeka

</td>  
<td>

Sveučilišna avenija 4, HR-

51000 Rijeka, Croatia

</td>  
<td>

Rajka Kolić, rkolic@ffri.hr

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

#  Research data and Open Access

The eConfidence project is part of the H2020 Open Research Data Pilot (ORDP)
and publication of the scientific results is chosen as a mean of
dissemination. In this framework, open access is granted to publications and
research data (WP4 and WP5) and this process is carried out in line with the
_Guidelines on Open Access to Scientific Publications and Research Data in
Horizon 2020_ 5  (as outlined in the summary below)  6  .

The strategy to apply Open Access for the project’s scientific results is
revised, step by step, according to personal data protection regulations, the
results of the ethical approval process of the research protocols and the
provisions of the Consortium Agreement. If needed, it will be possible to “opt
out” from this open access strategy for specific and well-defined subsets of
data.

##  Scientific publications

Open access is applicable to different types of scientific publication related
to the research results, including its bibliographic metadata, such as:

  * journal articles 

  

  * monographs and books 

  

  * conference proceedings, abstract and presentations 

  

  * grey literature (informally published written material) 

  

Grey literature includes also reports and deliverables of the projects related
to the research, whose Dissemination level is marked as Public (WP2, WP4,
WP5).

Open access is granted as following.

  * Step 1 – Depositing machine readable electronic copy of version accepted for publication in repositories for scientific publications (before or upon publication) 

  

  * Step 2 – Providing open access to the publication via the chosen repository 

  

For access to publications, a hybrid approach is considered (both green GA and
gold OA), depending on the item and the dissemination channels that will be
available.

  * Green OA (self-archiving) – depositing the published article or the final peer-reviewed manuscript in repository of choice and ensure open access within at most 6 months (12 months for publications in the social sciences and humanities). 

  

  * Gold OA (open access publishing) – publishing directly in open access mode/journal 

  

Any publication of the scientific results also needs to comply with the
process envisaged in _D1.1 – Quality plan – Section Quality control for
publication_ and in _Consortium Agreement Section 8.3 – Dissemination_ .

##  Research data

In addition, open access is granted also to underlying research data (data
needed to validate results presented in publication) and their associated
metadata, any other data (not directly attributable to the publication and raw
data) and information on the tools needed to validate the data and, if
possible, access to these tools (code, software, protocols etc.).

Open access is granted as following.

  * Step 1 – Depositing the research data in a research data repository 

  

  * Step 2 – Enabling access and usage free of charge for any user (as far as possible) 

  

##  Other project’s outcomes

As per any other outcomes of the project, they are disseminated accordingly to
the Dissemination level indicated in the Description of Action and they are
also subjected to protection in accordance with the Consortium Agreement and
in reference to Access Rights.

#  FAIR Data management plan

##  Data summary

The Data Summary provides an overview of the purpose and the nature of data
collection and generation, and its relation to the objective of the
eConfidence project.

###  Objectives of the project and research

The eConfidence project aims to test a methodology that includes several
models, such as the Activity Theory-based Model of Serious Games (ATMSG) for
game development methodology combined with Applied Behaviour Analysis (ABA)
and Learning Analytics (LA), in order to design serious games able to promote
behavioural changes in the user.

eConfidence tests the methodology with two serious games in Spanish and
English speaking schools, to assess behavioural changes in children.

Within this research several types of data are collected.

Initially, theoretical and empirical data from previous research are collected
through literature review in order to suggest games’ scenarios and Applied
Behaviour Analysis (ABA) procedures, to determine KPIs and to select
measurement instruments.

Subsequently, data regarding target behaviours (safe use of internet and
bullying), key variables that affect those behaviours, as well as relevant
personal variables are collected in pre-test and post-test research phases by
using questionnaires. Also, data on in-game behaviours are collected during
the research participants’ gaming sessions and data on quality, usability and
experience with serious games are collected in post-test phase.

The purpose of collecting data in pre-test and post-test phases, as well as in
gaming sessions, is to analyse cognitive, emotional and behavioural changes
produced by the playing the games, in order to evaluate effectiveness of games
mechanics in producing changes through ABA procedures.

The final results, obtained from statistical analysis of the data, could be
useful for different stakeholders, such as game developers, educational policy
makers, educational and mental health institutions.

###  Data collected

The research data of the project are original and no existing data is being
reused for the research results.

The research data are collected through pilots in 10 schools (5 Spanish
speaking and 5 English speaking schools), through a process in three phases:
pre-test questionnaire, experimentation, post-test questionnaire. Participants
are 12-14 years old students. The description of the research protocol is
available in _D2.3 – Intervention protocol_ and the full description of the
indicators is available in _D2.2 – Dossier of measurements instruments to
apply in the pilot test._

Data collected were defined by the research partners (USAL and FHSS) for
research data (questionnaires) and by the technical partners that develop the
games, Nurogames and ITCL, for games metrics.

The data collected with the pre-test and post-test questionnaires, beside
users’ profile information (age, gender, language, parental educational and
employment status, gaming experience, and participation in prevention
programmes), focus on knowledge, behaviour, and variables derived from the
Theory of planned behaviour (TPB: attitudes, perceived behavioural control,
subjective norms and behavioural intentions) related to safe internet use and
bullying, as well as on personal variables (social skills, assertiveness,
empathy, and friendship). All TPB and personal variables are assessed by using
self-reported instruments that will be applied online.

During the gaming sessions, different behavioural indicators are recorded
(e.g. user choices in game scenarios), in order to track behaviour changes in
safe use of internet and bullying behaviour. The data collected during the
game play as metrics (participants playing the two serious games on bullying
and online safety) include most of the relevant actions in the games: their
selections, number of errors and attempts, response time, playing time by
mini-game and full game, etc. All this data are analysed in order to extract
the player evolution during the game.

This data are also analysed with Big Data in order to get gaming tends, gaming
groups etc. with supervised and unsupervised learning techniques.

Data on user satisfaction are also collected as a separate questionnaire at
the end of the experimentation phase.

####  Types of data, size and formats

Types and formats of the data generated through the research, how they were
collected and the expected size are described below.

The last column specifies which data were selected to be made openly
available, considering data protection obligations, ethical aspects and
relevance for further research.

#####  Table 2 – Datasets summary  
  
<table>  
<tr>  
<th>

**Dataset**

</th>  
<th>

**Brief description**

</th>  
<th>

**Types**

</th>  
<th>

**Formats**

</th>  
<th>

**Expected size**

</th>  
<th>

**Open data y/n**

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

Pre-test

</td>  
<td>

Knowledge, Behaviour, TPB variables, demographics

</td>  
<td>

File (data)

</td>  
<td>

Excell.xls SPSS.sav

</td>  
<td>

1,5 MB

</td>  
<td>

Yes

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

Game play

</td>  
<td>

Game metrics about playing

</td>  
<td>

TBD

</td>  
<td>

TBD

</td>  
<td>

TBD

</td>  
<td>

Yes

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

</td>  
<td>

Bullying game and Safe Use of Internet

</td>  
<td>

</td>  
<td>

</td>  
<td>

</td>  
<td>

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

Post-test

</td>  
<td>

Same variables as pre-test plus user satisfaction questions

</td>  
<td>

TBD

</td>  
<td>

Excell.xls or SPSS.sav

</td>  
<td>

1,5 MB

</td>  
<td>

Yes

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

##  FAIR Data

In general terms, research data generated in the eConfidence project are – in
as far as possible – “FAIR”, that is findable, accessible, interoperable and
re-usable.

###  Findability \- Making data findable, including provisions for metadata

Publications are provided with bibliographic metadata (in accordance with the
guidelines).

Unique and persistent identifiers are used (such as Digital Object Identifiers
- DOI  7  ), when possible also applying existing standards (such as ORCID  8
for contributor identifiers).

As per the European Commission guidelines  9  , bibliographic metadata that
identify the deposited publication are in a standard format and include the
following:

  * the terms ["European Union (EU)" & "Horizon 2020"] 

  

  * the name of the action, acronym and grant number 

  

  * the publication date, the length of the embargo period (if applicable) and a persistent identifier. 

  

Datasets are provided with appropriate machine-readable metadata (see
Interoperability) and keywords are provided for all type of data.

####  Search keyword

The keywords relate to the variables assessed in the research. The custom
keywords identified are: eConfidence, bullying, safe use of internet, Theory
of planned behaviour, empathy, assertiveness, social skills and friendship.

####  Naming conventions and versioning

Files are named according to their content to ease their identification with
the project. The project name is at the beginning (eConfidence_pretest;
eConfidence_post-test). The date is formatted as filename_yymmdd.

  * The name of the project: eConfidence 

  

  * Brief description of the content. i.e. Pretest 

  

  * Number of version of the file 

  

  * Date 

  

###  Accessibility – Making data openly accessible

Data and related documentation are made available depositing them in the
repository of choice (Zenodo  10  ), together with the publications, and are
accessible free of charge for any user.

Zenodo is a repository built by CERN, within the OpenAIRE project, with the
aim of supporting the EC’s Open Data policy by providing a set of tools for
funded research  11  . Zenodo provides tools to deposit publications and
related data and to link them.

Any needed restriction in access to the data is evaluated before final
publication, in accordance with ethical aspects (conducting research with
humans and children) and with protection of personal data.

####  Methods and tools

Documentation on the tools needed to access and validate the data are also
provided (including protocols and methods).

If the code/software used to analyse the results is generated by the project’s
partners under an open license and using open source tools, this code is also
made available with the data.

Methods and tools will be finalized in Version 4 of this plan (Summer 2018).

###  Interoperability - Making data interoperable

Metadata models were evaluated among the ones available in the Metadata
Standards Directory  12  .

Dublin Core standard  13  ( _Table 3 - DC Metadata Element Set_ ) was selected
to add metadata to each of the datasets identified in _Table 2 – Datasets
summary._

####  **Table 3 - DC Metadata Element Set**  
  
<table>  
<tr>  
<th>

**Term Name: contributor**

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

URI:

</td>  
<td>

_http://purl.org/dc/elements/1.1/contributor_

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

Label:

</td>  
<td>

Contributor

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

Definition:

</td>  
<td>

An entity responsible for making contributions to the resource.

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

Comment:

</td>  
<td>

Examples of a Contributor include a person, an organization, or a service.
Typically, the name of a Contributor should be used to indicate the entity.

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

**Term Name: coverage**

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

URI:

</td>  
<td>

_http://purl.org/dc/elements/1.1/coverage_

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

Label:

</td>  
<td>

Coverage

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

Definition:

</th>  
<th>

The spatial or temporal topic of the resource, the spatial applicability of
the resource, or the jurisdiction under which the resource is relevant.

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

Comment:

</td>  
<td>

Spatial topic and spatial applicability may be a named place or a location
specified by its geographic coordinates. Temporal topic may be a named period,
date, or date range. A jurisdiction may be a named administrative entity or a
geographic place to which the resource applies. Recommended best practice is
to use a controlled vocabulary such as the Thesaurus of Geographic Names
[TGN]. Where appropriate, named places or time periods can be used in
preference to numeric identifiers such as sets of coordinates or date ranges.

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

References:

</td>  
<td>

[TGN]  _http://www.getty.edu/research/tools/vocabulary/tgn/index.html_

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

**Term Name: creator**

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

URI:

</td>  
<td>

_http://purl.org/dc/elements/1.1/creator_

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

Label:

</td>  
<td>

Creator

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

Definition:

</td>  
<td>

An entity primarily responsible for making the resource.

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

Comment:

</td>  
<td>

Examples of a Creator include a person, an organization, or a service.
Typically, the name of a Creator should be used to indicate the entity.

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

**Term Name: date**

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

URI:

</td>  
<td>

_http://purl.org/dc/elements/1.1/date_

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

Label:

</td>  
<td>

Date

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

Definition:

</td>  
<td>

A point or period of time associated with an event in the lifecycle of the
resource.

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

Comment:

</td>  
<td>

Date may be used to express temporal information at any level of granularity.
Recommended best practice is to use an encoding scheme, such as the W3CDTF
profile of ISO 8601 [W3CDTF].

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

References:

</td>  
<td>

[W3CDTF]  _http://www.w3.org/TR/NOTE-datetime_

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

**Term Name: description**

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

URI:

</td>  
<td>

_http://purl.org/dc/elements/1.1/description_

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

Label:

</td>  
<td>

Description

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

Definition:

</td>  
<td>

An account of the resource.

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

Comment:

</td>  
<td>

Description may include but is not limited to: an abstract, a table of
contents, a graphical representation, or a free-text account of the resource.

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

**Term Name: format**

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

URI:

</td>  
<td>

_http://purl.org/dc/elements/1.1/format_

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

Label:

</td>  
<td>

Format

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

Definition:

</td>  
<td>

The file format, physical medium, or dimensions of the resource.

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

Comment:

</td>  
<td>

Examples of dimensions include size and duration. Recommended best practice is
to use a controlled vocabulary such as the list of Internet Media Types
[MIME].

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

References:

</td>  
<td>

[MIME]  _http://www.iana.org/assignments/media-types/_

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

**Term Name: identifier**

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

URI:

</td>  
<td>

_http://purl.org/dc/elements/1.1/identifier_

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

Label:

</td>  
<td>

Identifier

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

Definition:

</td>  
<td>

An unambiguous reference to the resource within a given context.

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

Comment:

</td>  
<td>

Recommended best practice is to identify the resource by means of a string
conforming to a formal identification system.

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

**Term Name: language**

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

URI:

</td>  
<td>

_http://purl.org/dc/elements/1.1/language_

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

Label:

</td>  
<td>

Language

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

Definition:

</td>  
<td>

A language of the resource.

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

Comment:

</td>  
<td>

Recommended best practice is to use a controlled vocabulary such as RFC 4646
[RFC4646].

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

References:

</td>  
<td>

[RFC4646]  _http://www.ietf.org/rfc/rfc4646.txt_

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

**Term Name: publisher**

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

URI:

</td>  
<td>

_http://purl.org/dc/elements/1.1/publisher_

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

Label:

</td>  
<td>

Publisher

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

Definition:

</td>  
<td>

An entity responsible for making the resource available.

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

Comment:

</td>  
<td>

Examples of a Publisher include a person, an organization, or a service.
Typically, the name of a Publisher should be used to indicate the entity.

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

**Term Name: relation**

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

URI:

</td>  
<td>

_http://purl.org/dc/elements/1.1/relation_

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

Label:

</td>  
<td>

Relation

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

Definition:

</td>  
<td>

A related resource.

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

Comment:

</td>  
<td>

Recommended best practice is to identify the related resource by means of a
string conforming to a formal identification system.

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

**Term Name: rights**

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

URI:

</td>  
<td>

_http://purl.org/dc/elements/1.1/rights_

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

Label:

</td>  
<td>

Rights

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

Definition:

</td>  
<td>

Information about rights held in and over the resource.

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

Comment:

</td>  
<td>

Typically, rights information includes a statement about various property
rights associated with the resource, including intellectual property rights.

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

**Term Name: source**

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

URI:

</td>  
<td>

_http://purl.org/dc/elements/1.1/source_

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

Label:

</td>  
<td>

Source

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

Definition:

</td>  
<td>

A related resource from which the described resource is derived.

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

Comment:

</td>  
<td>

The described resource may be derived from the related resource in whole or in
part. Recommended best practice is to identify the related resource by means
of a string conforming to a formal identification system.

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

**Term Name: subject**

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

URI:

</td>  
<td>

_http://purl.org/dc/elements/1.1/subject_

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

Label:

</td>  
<td>

Subject

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

Definition:

</td>  
<td>

The topic of the resource.

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

Comment:

</td>  
<td>

Typically, the subject will be represented using keywords, key phrases, or
classification codes. Recommended best practice is to use a controlled
vocabulary.

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

**Term Name: title**

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

URI:

</td>  
<td>

_http://purl.org/dc/elements/1.1/title_

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

Label:

</td>  
<td>

Title

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

Definition:

</td>  
<td>

A name given to the resource.

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

Comment:

</td>  
<td>

Typically, a Title will be a name by which the resource is formally known.

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

**Term Name: type**

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

URI:

</td>  
<td>

_http://purl.org/dc/elements/1.1/type_

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

Label:

</td>  
<td>

Type

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

Definition:

</td>  
<td>

The nature or genre of the resource.

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

Comment:

</td>  
<td>

Recommended best practice is to use a controlled vocabulary such as the DCMI
Type Vocabulary [DCMITYPE]. To describe the file format, physical medium, or
dimensions of the resource, use the Format element.

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

References:

</td>  
<td>

[DCMITYPE]  _http://dublincore.org/documents/dcmi-type-vocabulary/_

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

If relevant, additional metadata will be defined, for datasets specific to the
project, in accordance with the existing standards. In this case, the option
to provide a mapping to existing ontologies will be assessed during the
evaluation phase (WP5) in summer 2018.

###  Data re-use and licensing

As per data quality assurance processes, in order to assess the good quality
of the data retrieved, these guidelines are followed. Once the datasets are
downloaded from the Xtend platform in the Excel format, they are transformed
into .sav format (SPSS) and basic quality assurance measures are taken. After
datasets from different schools are merged, it is assured that all the
variables line up in their proper columns. If omission are found, in order not
to lose results on the entire scale, the missing values are substituted with
means. Basic statistical analysis is then performed to check for any outliers
or impossible answers, checked against expected scale ranges. Several
variables have to be recoded or transformed, so a clear coding system was
developed. Transformation is conducted separately by two research teams (USAL
and FHSS), and data are compared in order to ensure no mistakes are made
during transformation.

Publications and underlined data are made available at the end of the
evaluation phase, once all data are collected and analysed (Summer 2018). All
the data indicated in section 4.1.2 as Open Data will be made available for
re-use after the end of the project. The licences for publications and related
data will be defined in Version 4 of this plan, based on the final data, in
order to verify compliance with personal data protection regulations and the
ethical approval process results. Creative Commons is the chosen licensing
system, and the license for each item will be selected using the EUDAT license
wizard tool  14  .

##  Allocation of resources

In Horizon 2020, costs related to open access to research data are eligible
for reimbursement during the duration of the project, under the conditions
defined in the Grant Agreement (Article 6). The project uses this option for
publications, while related data will be deposited in open repositories, free
of charge.

Human resources required to implement this plan are considered in the relevant
partners’ staff budget, according to their tasks in the project’s activities
(ITCL, EUN, Everis, FHSS, USAL).

Roles and responsibilities for data management within the project are
described in sections _General principles for data management_ and _Annex 1 –
Data collected and processes – summary_ .

##  Data security

The key procedure for data security of the eConfidence project are outlined in
the document _D2.4 – Report with ethical and Legal Project compliance_ and
summarized in the following.

###  Data collection

The collection of research data is carried out entirely through the Xtend
platform  15  (an educational platform made available by the Data Controller,
EVERIS): pre-test questionnaire, game play and post-test questionnaire.

Each participant accesses the platform through an individual account (username
and password), created by EVERIS and provided directly to the research
coordinator of each school through password protected files. The research
coordinator provides the students involved in the research with their
credentials ensuring confidentiality.

####  Anonymization Process

Data Results in the platform are not associated with user’s identity.

The name of the research participant appears on the consent forms, of which
one digital copy is kept by everis. All data in the platform is anonymized by
assigning an anonymized user to each student. Algorithm of anonymization is
only known by Data Manager Controller to maintain the anonymity of the
results.

Information of the association between platform user and student of each
centre/school is transmitted to each coordinator of the school in Excel format
and with the specific data of the school. The Excel sheet is secured through
256-bit AES (Advanced Encryption Security) codification and password. Password
is sent to the centre’s research coordinator through SMS, not to use the same
communication channel as for the Excel sheet. Student’s data and platform’s
users’ conversion of the centre are stored by the school following the legal
requirements of the country and are to be destroyed at the end of the project.

All data collected during the study through the platform is associated to the
platform user. That means that reports, results, internal communications and
external publications do not contain any personal data of the students.

###  Data maintenance and storage

####  Data access in Xtend platform

Research and research-related personal data collected are stored only in Xtend
systems. Personal Data is only accessible by Data Controller.

Access is restricted to each participant, under their fictional pseudo-
identity, and to the members of the Data Controller organisation and
eConfidence research team.

Each access to the research data is properly logged with the information of
the authorized user who requests access to the data.

Access is managed using cost-effective state of the art information security
techniques: i.e. mutual authentication of the experimental prototype and its
authorized users, restricted access for each user to functionality required to
fulfil their project role, and encryption of all messages passing between the
users and the experimental prototype.

In Xtend, three roles had been defined and had been associated to eConfidence
profiles. **Table 4 - Xtend platform roles**  
  
<table>  
<tr>  
<th>

**e-confidence Profile**

</th>  
<th>

**Xtend role**

</th>  
<th>

**Groups inside the role**

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

Student

</td>  
<td>

Student

</td>  
<td>

2 groups: control and experimental

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

Research Coordinator

</td>  
<td>

Coordinator

</td>  
<td>

2 groups: school and school group

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

Data Manager

</td>  
<td>

Administrator

</td>  
<td>

No group

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

Functionalities and access defined for each role are explained in the table
below.

#####  Table 5 - Xtend platform functionalities  
  
<table>  
<tr>  
<th>

Student

</th>  
<th>

access to own questionnaire

</th>  
<th>

Complete and send the completed

</th>  
<th>

To run the game

</th>  
<th>

To see all students of his/her

</th>  
<th>

</th>  
<th>

</th>  
<th>

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

</td>  
<td>

</td>  
<td>

questionnaire

</td>  
<td>

</td>  
<td>

group

</td>  
<td>

</td>  
<td>

</td>  
<td>

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

Coordinator

</td>  
<td>

access to own questionnaire

</td>  
<td>

Complete and send the completed questionnaire

</td>  
<td>

To run the game

</td>  
<td>

To see all students of his/her group

</td>  
<td>

To see all Xtend

profiles of his/her group

</td>  
<td>

To send message

to all

students of his/her group

</td>  
<td>

To change his/her password

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

Administrator

</td>  
<td>

All Xtend functionality

</td>  
<td>

</td>  
<td>

</td>  
<td>

</td>  
<td>

</td>  
<td>

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

####  Process of backups of Xtend platform

Xtend platform is hosted on Amazon Web Services (AWS) infrastructure and
follow an automated procedure for daily backups of data managed. A daily
backup is programmed for all the instances of the platform using the AES-256
encryption algorithm. Daily backups have a retention period of 30 days.

A second data storage backup is programming once a month but with a retention
period of 5 years.

##  Ethical aspects

The ethical aspects of the research generating the scientific data of the
project are covered in the following deliverables, also taking into
consideration the European Commission Ethics Summary Report for the project.

  * _D2.3 – Intervention protocol_

  

  * _D2.4 – Report with ethical and Legal Project compliance_

  

As mentioned, these aspects are taken into consideration in the selection of
data to be made available for re-use (section 4.1.2) and for the security
procedures (section 4.5).

###  Consent

Expressed written consent is collected for all participants (students 12-14
years old) and their parents, before the pre-test phase. Participants and
parents were also provided with Information sheets.

The request for consent makes clear that:

  * anonymized or process data could be used in future studies as well as for publication purposes 

  

  * personal privacy and data protection is guaranteed during these activities 

  

  * data from the tests (anonymized) may be reused by other researchers after the eConfidence project, for validation process or for new research. 

  

The full process to manage the consent is outlined in D2.4.

Since the name of the parent/guardian as well as their respective child(ren)
constitute personal data, the consent forms are handled as follows:

  * A digital copy of the consent form is made and kept on a secure computer at the Data Controller’s premises; only the data controller has access to these copies. 

  

  * The hardcopy is destroyed. 

  

  * An arbitrary index is assigned to each participant. 

  

The correspondence between the arbitrary index and the softcopy consent forms
is held in a suitably encrypted table held on a secure computer at the Data
Controller’s premises. This table also contains a cross-reference to the data
processor(s) for the data associated the indexes in the table. Any datasets
(video, audio etc.) is associated with the index generated. Only the Data
Controller has access to the correspondence between consent form and indexes.

##  Other issues

Table 6 contains other relevant national, sectorial and institutional
references and procedures for data management.

###  **Table 6 – Other references for data management**  
  
<table>  
<tr>  
<th>

**Organisation**

</th>  
<th>

**National regulations**

</th>  
<th>

**Other references**

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

P1 – Instituto

Tecnologico de

Castilla y León

</td>  
<td>

Organic Law 15/1999 fron 13th of

December for personal data protections

</td>  
<td>

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

P2 – EUN

Partnership aisbl

</td>  
<td>

GDPR/Privacy Act 8th December 1992 – protection of privacy in relation to the
processing of personal data

</td>  
<td>

Belgian Data Protection Authority

(commission@privacy commission.be)

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

P5 – University of

Salamanca

</td>  
<td>

</td>  
<td>

Comité de Bioética of the Univ. of Salamanca

https://evaluaproyectos.usal.es/main_pa ge.php

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

P6 – FHSS RIJEKA

</td>  
<td>

The Law on Protection of Personal Data (Republic of Croatia, Official Gazzete
no.

103/03, 118/06, 41/08, 130/11, 106/12)

</td>  
<td>

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

Annex 1

–

Data collected and

process

es

–

summary  
  
<table>  
<tr>  
<th>

**Organisation**

</th>  
<th>

**Dataset name**

</th>  
<th>

**Description**

</th>  
<th>

**Type**

</th>  
<th>

**Format**

</th>  
<th>

**Collection process**

</th>  
<th>

**Owner**

</th>  
<th>

**Storage**

</th>  
<th>

**Access/**

**Privacy level**

</th>  
<th>

**Backup**

</th>  
<th>

**Destruction at the of end of the project**

</th>  
<th>

**Retention in years**

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

P1 - ITCL

</td>  
<td>

Anonymized test

about aesthetic line

</td>  
<td>

survey containing several questions about gaming preferences, aesthetic lines,
colour palettes and game narrative to Target group

</td>  
<td>

Project data

</td>  
<td>

pdf

</td>  
<td>

Physical forms with digitisation

</td>  
<td>

ITCL

</td>  
<td>

ITCL local repository

</td>  
<td>

ITCL staff

</td>  
<td>

No backup

</td>  
<td>

NO

</td>  
<td>

5 (for

management and auditing requirements)

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

P1 - ITCL

</td>  
<td>

Anonymized test about Beta version of

School of Empathy

</td>  
<td>

survey containing several questions about the first beta version of School of
empathy to Target group

</td>  
<td>

Project data

</td>  
<td>

pdf

</td>  
<td>

Physical forms with digitisation

</td>  
<td>

ITCL

</td>  
<td>

ITCL local repository

</td>  
<td>

ITCL staff

</td>  
<td>

No backup

</td>  
<td>

NO

</td>  
<td>

5 (for

management and auditing requirements)

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

P2 – EUN

</td>  
<td>

Call for schools

</td>  
<td>

Organisation, contact persons, applications and selection process data, to
manage the selection and agreement with schools

</td>  
<td>

Organisat ion and personal data

</td>  
<td>

.xls

</td>  
<td>

Through application form

</td>  
<td>

</td>  
<td>

EUN NAS

(server)

</td>  
<td>

EUN Staff and experts

</td>  
<td>

Once

</td>  
<td>

No

</td>  
<td>

5 (for

management and auditing requirements)

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

P3 – EVERIS SPAIN SL

</td>  
<td>

Experts list

</td>  
<td>

List of experts related to econfidence project.

</td>  
<td>

Public data

</td>  
<td>

Pdf

</td>  
<td>

In public web

</td>  
<td>

everis

</td>  
<td>

Everis client database

</td>  
<td>

everis workers

</td>  
<td>

No

</td>  
<td>

No

</td>  
<td>

Indefinitely

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

P3 – EVERIS SPAIN SL

</td>  
<td>

Consent forms in digital format

</td>  
<td>

Form consent of students and parents for econfidence use.

</td>  
<td>

Personal data

</td>  
<td>

Pdf

</td>  
<td>

Physical form with digitisation

</td>  
<td>

Everis

</td>  
<td>

everis local repository

</td>  
<td>

256-bit AES &

Password protected/

Only Data Controller

</td>  
<td>

No backup

</td>  
<td>

No

</td>  
<td>

TBD

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

P3 – EVERIS SPAIN SL

</td>  
<td>

File with the association between student and Xtend User – digital format

</td>  
<td>

Excel sheet with the association between Xtend platform user with the student
data

</td>  
<td>

Personal and project data

</td>  
<td>

xls

</td>  
<td>

List form

</td>  
<td>

everis

</td>  
<td>

everis local repository

</td>  
<td>

256-bit AES &

Password protected/ Only Data Controller

</td>  
<td>

No backup

</td>  
<td>

Yes

</td>  
<td>

0

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

P3 – EVERIS SPAIN SL

</td>  
<td>

Platform Users

</td>  
<td>

Users of Xtend platform with association with the profile which define
accesses to data

</td>  
<td>

Project data

</td>  
<td>

In platform Database

</td>  
<td>

Database

list

</td>  
<td>

everis

</td>  
<td>

Xtend platform

</td>  
<td>

Password protected. Only Data Manager

</td>  
<td>

Xtend platfor m

</td>  
<td>

No

</td>  
<td>

5 _(for_

_management and auditing requirements)_

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

P3 – EVERIS SPAIN SL

</td>  
<td>

Results and reports of using platform (questionnaire and games)

</td>  
<td>

Research and personal data about the use of Xtend platform

</td>  
<td>

Results data

</td>  
<td>

In platform Database

</td>  
<td>

Database information or reports in Xtend platform

</td>  
<td>

everis

</td>  
<td>

Xtend platform

</td>  
<td>

Xtend users considering profiles

</td>  
<td>

Xtend platfor m

</td>  
<td>

No

</td>  
<td>

5 _(for_

_management and auditing requirements)_

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

This project has received funding from the European Union's Horizon 2020
research and innovation programme under grant agreement - No 732420

This communication reflects only the author's view. It does not represents the
view of the European Commission and the EC is not responsible for any use that
may be made of the information it contains.

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