_1\. INTRODUCTION_

This Data Management Plan (DMP) has been prepared by mostly following the
document “Guidelines on FAIR Data Management in Horizon 2020” (Version 3.0, 26
July 2016)  1  . This final version of the DMP presents the data management
strategy in the StemForYouth (SFY) H2020 project as well as the description of
all the research data sets.

In this SWAFS project, the general goal of the project is to bring teenagers
closer to Science and Technology. Students are thus at the core of the project
and it is thus especially important to implement Responsible Research and
Innovation keys in all activities of the project. Project has to ensure that
RRI concepts will be assimilated by the students with all the significant
dimensions, as future possible researchers and responsible citizens.

For instance, through the Citizen Science projects co-created and implemented
in their schools, students themselves will collect, treat and analyse research
data. Having a comprehensive data management plan in order to allow Open
Access to Research Data is thus of vital importance, not only for the
researchers participating in the project but also to disseminate RRI best
practices to the youngest.

#  2\. DATA SUMMARY

**2.1 What is the purpose of the data collection/generation and its relation
to the objectives of the project?**

The data sets of this project have been mainly generated in WP4 (Citizen
Science at School), and WP7 (Trial and outreach activities), and assessed by
WP8 (Assessment and recommendations).

_**Citizen Science Data** _

The scientific research data collected in WP4 and WP7 are related to the
introduction of Citizen Science at School. Citizen Science experiments have
been performed through a collective research process. The young boys and girls
have participated to the governance of the research projects, design the
experiments, conduct them, and in some cases analysed the data and interpreted
the results. Experiments and their data gathering have been approved by the
Ethics Committee of the Universitat de Barcelona.

In relation to the main objective of the project -which is to bring teenagers
closer to Science and Technology-, the Citizen Science introduction at school
supports the latest research in science education, which advocates for a
reduced emphasis on memorisation of facts-based content and increased
engagement in the process of inquiry through hands-on or learning by doing
activities. It has been also demonstrated that students’ participation and
motivation is strongly increased when they participate in Citizen Science
projects, as a result of the close contact with scientists, the perception of
their ability to solve important issues for the community, and their
empowerment as true owners and disseminators of the projects results.

_**Trial and outreach activities** _

The scientific research data collected under the WP8 framework, during the
trials implementation

(Task 7.1 and Task 7.4), is related to students’ attitudes towards STEM and
their future career choice. High school students participated in Phase I and
II of the trials, by developing STEMforYouth activities generated as part of
WP6 from the following sub-courses: Mathematics, Engineering, Physics,
Chemistry, Medicine and Astronomy.

The objective was to identify students’ attitudes towards STEM as well as
their interest in STEM and their present and future career choice, before and
after the implementation of the STEMforYouth designed sub-courses. In general,
students increased their motivation for learning and their attitudes towards
STEM, stimulated by the learning methodologies employed in the sub-courses:
hands-on activities, inquiry-based learning, collaborative learning, learning
via experiments…. In addition, students, working on specific modules, such as,
Mathematics, found this subject more useful for a daily life purpose. Students
also acquired and reinforced their knowledge.

**2.2 What types and formats of data do the project generate/collect?**

_**Citizen Science Data** _

The project, in relation to Citizen Science experiments, collects **human
decision-making** data. The experiments are placed in public spaces and the
pedestrians freely decide to participate and to complete surveys and play
games using a tablet.

The experiments are divided in three parts and in each one the data generated
has different characteristics. In the first part we collect sociodemographic
data and, in some experiments through a survey, the participants' perception
about the topic of study (e.g. air quality in Games xAire or coastal
environmental pollution in Games xPalaio Faliro). In the second part we
collect properly the decision-making data by means of the social dilemmas
games, capturing the interactions between the participants when they are
interacting in the behavioural games. And finally, in the third part of the
experiments we (optionally) collect data using surveys about the topic of
study, the decisionmaking process or the participants’ experience.

The data is captured using MySQL database, the behavioural actions as well as
the survey data are shared in CSV format tables. The questions and answers of
the surveys are included in XLS file named _QuestionsAnswersSurvey_ . Each
repository has its own _README_ file with detailed information about each
field. Here is an example of the files and some of the fields that can be
found:

_Files_

  * README.txt: detailed explanation of the metadata 

  

  * QuestionsAnswersSurvey.xls: set of the surveys’ questions and answers 

  

  * session.csv: data of each game 

  

  * users.csv: data of valid users 

  

  * dictator.csv: data collected in Dictator’s Game 

  

  * snowdrift.csv: data collected in Snowdrift Game 

  

  * trust.csv: data collected in Trust Game 

  

Fields in Snowdrift Game (snowdrift.csv)

  * id: choice identifier 

  

  * user_id: user's identifier 

  

  * rival_id: rival's identifier 

  

  * rol: role (E: symmetric, A: advantage, D: disadvantage) 

  

  * choice: choice (C: Cooperate, D: Defect) 

  

  * guess: guess choice (C: Cooperate, D: Defect) 

  

  * gain: total score 

  

_**Trial and outreach activities** _

The data gathered from the Trial and Outreach Activities were mainly analysed
through a quantitative approach to collect **students’ beliefs and attitudes**
. The questionnaires were administrated to the students before and after the
implementation of the STEMforYouth activities. They freely accepted to fill
the questionnaires, being aware of they were participating in the data
collection process with a research purpose.

The questionnaires collect two types of data: sociodemographic data and
attitudes data. In particular, regarding the sociodemographic data,
questionnaires collect students’ pseudonym, age, sex, country, and future
academic and career preferences. The attitudes questions collect data
regarding:  Students’ Image of the scientist: how they see STEM
professionals, including implicit stereotypes about STEM professionals such as
the vocational nature, their reserved nature and their high intellectual
capacity.

  * Student attitudes towards STEM like enjoyment and self-concept. 

  

  * Students’ perceptions about the utility of STEM disciples, including ‘career purpose’ and ‘daily-life purpose’ dimensions. 

  

The data was collected in paper-based format or computer-based format. In the
last case, questionnaires were generated on Google Forms. This format was used
for the participant schools with a sufficient number of computers for all the
students, and suitable access to Internet. This was a minority group in a
couple of countries.

The aforementioned data have been uploaded on a XLS format. In addition, it
has included a .TXT file with general information and codes calls “README”,
and a XLS format with questions.

_Files_

  * README.txt: detailed explanation of the metadata. 

  

  * Questions.xls: set of questions included in the attitudes questionnaire. 

  

  * STEMforYouth_data.xls: data of the students’ attitudes towards STEM. 

  

Fields in the collected data (STEMforYouth_data.xls)

  * id: student’s identifier. 

  

  * Country: country where students implemented the STEMforYouth activity or activities. 

  

  * Age: student’s age. 

  

  * Gender: student’s gender (0: female and 1: male). 

  

  * Student’s answer to their academic and professional plans 

  

  * Student’s answer to the Likert scale (1: Strongly Agree, 2: Agree, 3: Somewhat Agree, 4: Somewhat Disagree; 5: Disagree; 6 Strongly Disagree). 

  

_**Do you re-use any existing data and how?** _

##  Citizen Science Data

Data from previous Citizen Science experiments on the same themes could be
used for comparison purposes, calibration or to complete the set of collected
data. These existing data from Universitat de Barcelona are already deposited
in repositories such as Dryad, GitHub and Zenodo with a CC0 1.0 license,
allowing re-use. The data gathered using citizen science experiment could also
be crossed with data from socio-economic demographics (such as average life-
expectancy, average wage, average house prices in a given neighbourhood or
region) data publicly available by public administration open repositories.

##  Trial and outreach activities data

Only data from the STEMforYouth project was analysed.

_**What is the origin of the data?** _

##  Citizen Science Data

The data are collected during Citizen Science experiments. The volunteers
freely and consciously deliver their data, which is the result of their
participation to the experiment. In addition, the experiments are thought to
solve or propose solutions relevant issues for the community based on the
evidences collectively gathered.

##  Trial and outreach activities data

The Data were collected during Trials implementation in six European
countries: Poland, Italy, Greece, Czech Republic, Slovenia and Spain. Students
freely accepted to fill the questionnaires, being conscious that they were
part of a research study. The trials were carried out to test the
attractiveness, innovativeness and usefulness of the STEMforYouth sub-courses
through their implementation in a wide variety of contexts.

_**What is the size of the data?** _

##  Citizen Science Data  
  
<table>  
<tr>  
<th>

**Dataset Name**

</th>  
<th>

**Size**

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

**STEMForYouth: Games xBadalona**

</td>  
<td>

_67kb_

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

**STEMForYouth: Games xViladecans**

</td>  
<td>

_87kb_

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

**STEMForYouth: Games xBarcelona**

</td>  
<td>

_72kb_

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

**STEMForYouth: Games xPalaioFaliro**

</td>  
<td>

_113kb_

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

**STEMForYouth: Games xAire**

</td>  
<td>

_186kb_

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

##  Trial and outreach activities data  
  
<table>  
<tr>  
<th>

**Dataset Name**

</th>  
<th>

</th>  
<th>

**Size**

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

**STEMForYouth: Trials and Outreach Data**

</td>  
<td>

_538kb_

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

_**To whom might it be useful ('data utility')?** _

##  Citizen Science Data

Each set data could be analysed by the students that designed the experiments
and the researchers participating in these dynamics. In addition, the Open
Data might be useful to different collectives such as:

  1. Others scientists having convergent research lines in terms of collective decision making. 

  

  2. Public institutions concerned by the social questions raised by the experiments. The data may serve as evidences to support some policies. 

  

  3. Teachers and students that will use the Citizen Science toolkit produced in the frame of StemForYouth in order to introduce Citizen Science at school. 

  

  

##  Trial and outreach activities

The data could be useful for a research purpose. It can be interesting for
different researchers, such as:

  1. Researchers whose research areas is students’ attitudes field. 

  

  2. Researchers whose research areas is academic and professional students’ plans. 

  

  

#  3\. FAIR DATA

**3.1 Making data findable, including provisions for metadata**

_**Are the data produced and/or used in the project discoverable with
metadata, identifiable and locatable by means of a standard identification
mechanism (e.g. persistent and unique identifiers such as Digital Object
Identifiers)?** _

Yes, the data are associated with metadata and locatable by means of a DOI in
both cases.

##  Citizen Science Data  
  
<table>  
<tr>  
<th>

**Dataset Name**

</th>  
<th>

**DOI**

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

**STEMForYouth: Games xBadalona**

</td>  
<td>

_10.5281/zenodo.1308963_

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

**STEMForYouth: Games xViladecans**

</td>  
<td>

_10.5281/zenodo.1308974_

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

**STEMForYouth: Games xBarcelona**

</td>  
<td>

_10.5281/zenodo.1308972_

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

**STEMForYouth: Games xPalaioFaliro**

</td>  
<td>

_10.5281/zenodo.1314180_

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

**STEMForYouth: Games xAire**

</td>  
<td>

_10.5281/zenodo.1314207_

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

##  Trial and outreach activities  
  
<table>  
<tr>  
<th>

**Dataset Name**

</th>  
<th>

**DOI**

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

**STEMForYouth: Trials and Outreach Data**

</td>  
<td>

_10.5281/zenodo.1472067_

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

_**What naming conventions do you follow?** _

##  Citizen Science Data

All the data names set will contain, in this order: STEMForYouth / Name or
reference of the experiment

##  Trial and outreach activities

A single file including STEMForYouth Data.

_**Do you provide search keywords that optimize possibilities for re-use?** _

##  Citizen Science Data

The keywords that describe our data are: Human Decision Making, Social
Dilemmas, Citizen Science, STEMForYouth, Public Experiments, Collective
Experiments, Action Research, Human Behaviour, Collective Action, Game Theory,
Cooperation.

##  Trial and outreach activities

The keywords that describe our data are: STEM, STEM education, STEMforYouth,
Attitudes, Image of Scientist, Academic plans, Career Choice, Enjoyment,
Utility, Astronomy, Engineering, Mathematics, Physics, Chemistry, Medicine.

_**Do you provide clear version numbers?** _

Yes, in both cases, the public repository provides the dataset version
following the convention of  _Semantic Versioning 2.0.0_ .

_**What metadata has been created? In case metadata standards do not exist in
your discipline, please outline what type of metadata has been created and
how.** _

In both cases, Metadata created carefully explain and describe the content and
meaning of each of the fields of the database. Each dataset repository
contains a README file with its metadata associated.

**3.2 Making data openly accessible**

_**Which data produced and/or used in the project have been made openly
available as the default? If certain datasets cannot be shared (or need to be
shared under restrictions), explain why, clearly separating legal and
contractual reasons from voluntary restrictions.** _

##  Citizen Science Data

The full data set has been available. It does not contain any personal data as
the players are using a pseudonym and the general sociodemographic data
collected, such as gender and age range, do not allow their identification.

##  Trial and outreach activities

The full data set has been also available. It does not contain any personal
data. Students employed a pseudonym and sociodemographic data collects basic
information such as gender, age and country, which do not allow the students’
identification.

_**Note that in multi-beneficiary projects it is also possible for specific
beneficiaries to keep their data closed if relevant provisions are made in the
consortium agreement and are in line with the reasons for opting out.** _

The data sets generated through the Citizen Science experiments and the Trial
and outreach activities will be all made openly available.

Citizen Science Data associated to Citizen Science pilot experiments (Games
xViladecans/Barcelona/Viladecans) are already open. The Citizen Science Data
associated with the Citizen Science pilots replication (Games xPalaio Faliro
and Games xAire) will be openly available later on June 2019, when the
associated research paper will be ready to be submitted for peerreview
publication.

Data from trials and outreach activities will be openly available in a maximum
of 30 months (30th of April of 2021). This is because we are aiming to produce
research papers during this time, and publishing them on journals or books. If
this research work and the research instruments employed and designed by Jose
M. Diego-Mantecón are published before the expected time (30 months), data may
be opened earlier.

_**How will the data be made accessible (e.g. by deposition in a
repository)?** _

For the Citizen Science Data, the data are deposited in Zenodo using standard
CSV files for data tables.

For the trials and outreach activities, the data are deposited in Zenodo using
standard XLS files for data tables.

_**What methods or software tools are needed to access the data?** _

No specific software is necessary to access the data.

_**Is documentation about the software needed to access the data included?** _

No.

_**Is it possible to include the relevant software (e.g. in open source
code)?** _

Not applicable.

_**Where are the data and associated metadata, documentation and code
deposited? Preference should be given to certified repositories which support
open access where possible.** _

##  Citizen Science Data

The data are deposited in Zenodo (OpenAire/CERN repository) and the code
associated with the games platform in Github, traditionally associated with
the Open Source movement.

##  Trials and outreach activities

The data is deposited in Zenodo (OpenAire/CERN repository).

_**Have you explored appropriate arrangements with the identified
repository?** _

Yes.

_**If there are restrictions on use, how will access be provided?** _

Citizen Science Data and Trials and outreach activities data will be open and
free Access. The only restriction would be time; some data are already open
and some others will be open after 8 months (30  th  June 2019) or 30 months
(30  th  April 2021). This is the time expected for the research work, and
papers publication, as described in earlier sections in this document.

_**Is there a need for a data access committee?** _

No.

_**Are there well described conditions for access (i.e. a machine readable
license)?** _

Yes.

_**How will the identity of the person accessing the data be ascertained?** _

We are able to use the protocols from Zenodo and GitHub (OpenSource and
OpenData) although it will be generally difficult to identify the person.

**3.3 Making data interoperable**

_**Are the data produced in the project interoperable, that is allowing data
exchange and re-use between researchers, institutions, organisations,
countries, etc. (i.e. adhering to standards for formats, as much as possible
compliant with available (open) software applications, and in particular
facilitating re-combinations with different datasets from different
origins)?** _

##  Citizen Science Data

The data produced in the project follow the standard format of behavioural
data obtained through social dilemmas. This way the results can be easily
compared with any sets of existing data.

##  Trials and outreach activities data

The data gathered during the trials and outreach activities collect students’
attitudes towards STEM and their career plans. This data could be of interest
to others and related to other studies in similar contexts.

_**What data and metadata vocabularies, standards or methodologies will you
follow to make your data interoperable?** _

##  Citizen Science Data

The data and metadata produced in the project use the standard vocabulary (see
2.2) used in the field of social dilemmas, which are well documented in a
variety of scientific articles. Similarly, the use of social dilemmas to
investigate human behaviour is a well established methodology and number of
similar data sets can be found.

##  Trials and outreach activities data

The data produced in the project use the standard vocabulary used in the field
of student attitudes and beliefs, well documented in a variety of scientific
articles.

_**Will you be using standard vocabularies for all data types present in your
data set, to allow inter-disciplinary interoperability?** _

Yes. It is also intended to be fully comprehensive by students participating
in the project, but also the scientific community.

_**In case it is unavoidable that you use uncommon or generate project
specific ontologies or vocabularies, will you provide mappings to more
commonly used ontologies?** _

Yes.

**3.4 Increase data re-use (through clarifying licenses)**

_**How will the data be licensed to permit the widest re-use possible?** _

All the data will have a Creative Commons License: CC BY-SA 4.0.

( _https://creativecommons.org/licenses/by-sa/4.0/_ )

_**When will the data be made available for re-use? If an embargo is sought to
give time to publish or seek patents, specify why and how long this will
apply, bearing in mind that research data should be made available as soon as
possible.** _

##  Citizen Science Data

The data related with the Citizen Science pilots experiments are already
available. The data related with the Citizen Science pilots replication will
be made available as soon as the corresponding research papers will be
published and in any case not later than 30  th  of June of 2019.

##  Trials and outreach activities data

Data will be open in a maximum of 30 months (not later than the 30  th  of
April 2021). This is because we are aiming to produce research papers during
this time, and publishing them on journals or books. If this research work and
the research instruments employed and designed by Jose M. Diego-Mantecón are
published before the expected time (30 months), data may be opened earlier.

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

Yes, the data can be used by third parties under a Creative Commons License:
CC BY-SA 4.0.

_**How long is it intended that the data remains re-usable?** _

Always. In the Zenodo repository, items will be retained for the lifetime of
the repository. This is currently the lifetime of the host laboratory CERN,
which currently has an experimental programme defined for the next 20 years at
least. In all case, a DOI and a perma-link will be provided.

_**Are data quality assurance processes described?** _

##  Citizen Science Data

Yes. The data quality is assessed by the researchers of Universitat de
Barcelona that helped conducting the Citizen Science experiments. The
documentation attached to each database is including a discussion about data
quality. Scientific papers using the data will also validate the data quality.
Zenodo and GitHub only guarantee a minimal quality process. For instance, all
data files are stored along with a MD5 checksum of the file content. Files are
regularly checked against their checksums to assure that file content remains
constant.

##  Trials and outreach activities data

Yes. The data quality is assessed by the researchers of University of
Cantabria that designed the attitudes questionnaire. In particular, the
questionnaire employed is an amended version of DiegoMantecón’s (2012) student
mathematics-related beliefs instrument, and has been designed under his
anthropological model. Diego-Mantecón’s model seeks to validate results on
cross-cultural projects by considering key factors affecting human behaviour
and therefore human performance in any discipline or subject.

#  4\. ALLOCATION OF RESOURCES

**4.1. What are the costs for making data FAIR in your project?**

Citizen Science Data and Trials and outreach activities data, no cost
associated for the deposit in repositories as all the processes described are
free of charge. In addition, an offline copy of all data sets will be saved in
hard disk funded by the EU project (300-600 euros approx.).

**4.2. How will these costs be covered?**

Note that costs related to open access to research data are eligible as part
of the Horizon 2020 grant (if compliant with the Grant Agreement conditions).

Hard disks will be funded by the EU project in the case of the Citizen Science
experiments and Trials and outreach activities data.

**4.3. Who will be responsible for data management in your project?**

Julián Vicens, researcher of OpenSystems, Universitat de Barcelona.

**4.4. Are the resources for long term preservation discussed (costs and
potential value, who decides and how what data will be kept and for how
long)**

Long term preservation is already guaranteed in Zenodo and Github _._

#  5\. DATA SECURITY

**5.1 What provisions are in place for data security (including data recovery
as well as secure storage and transfer of sensitive data)?**

The data are stored in an in-house UB server. In addition, a copy is done in
an external disc. Data files and metadata in Zenodo are backed up nightly and
replicated into multiple copies in the online system.

**5.2 Is the data safely stored in certified repositories for long term
preservation and curation?**

Yes, Zenodo repository provide this certification
_https://zenodo.org/policies_

#  6\. ETHICAL ASPECTS

**6.1. Are there any ethical or legal issues that can have an impact on data
sharing?**

_These can also be discussed in the context of the ethics review. If relevant,
include references to ethics deliverables and ethics chapter in the
Description of the Action (DoA)._

_**Citizen Science Data** _

The Citizen Science experiments passed through the Ethics Committee of
Universitat de Barcelona. The data collection does not include any personal
data according to the Spanish LOPD (Ley Orgánica de Protección de Datos de
Carácter Personal, Organic Law for Personal Data Protection) or equivalent
laws of Poland and Greece.

_**Trials and outreach activities Data** _

The trials implementation passed through the Ethics Committee of Universidad
de Cantabria. The data collection does not include any personal data according
to the Spanish LOPD (Ley Orgánica de Protección de Datos de Carácter Personal,
Organic Law for Personal Data Protection) or equivalent laws of Poland,
Greece, Slovenia, Czech Republic and Italy.

**6.2. Is informed consent for data sharing and long term preservation
included in questionnaires dealing with personal data?**

We do not share personal data.

#  7\. OTHER ISSUES

**7.1. Do you make use of other national/funder/sectorial/departmental
procedures for data management? If yes, which ones?**

None.