#  Introduction

This Data Management Plan (DMP) has been prepared by mostly following the
recent document “Guidelines on FAIR Data Management in Horizon 2020” (Version
3.0, 26 July 2016)  1  . As stated by the mentioned guidelines, the goal of
this DMP first version is NOT to generate an extensive and definitive document
but rather to set the basis of data management in the StemForYouth (SFY) H2020
project. This document will be kept therefore alive during the evolution of
SFY project. It will be periodically updated and completed during the whole
duration of the project (see Appendix 1. Timetable for review) and the final
version delivered at the end (M30).

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.

#  Data Summary

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

The data in the project will be generated mostly in WP4 (Citizen Science at
School), WP5, WP6 and WP7. The data generated (indirectly) by WP5 will be
related largely to the Physics experiments the students will execute. Due to
its nature the data will have little scientific value, so there is no point of
making them available on the standard open data platform. Instead, this data
will be freely shared within students on the Open Content Management Platform
the project will developed – this data has value only with close relation to
the particular experiments.

The data produced by WP6 (Open Content Management Platform) and WP7 (Trail and
outreach activities) will largely concerns various system statistics, the
characteristics the students and the teachers will work with the content
(multidisciplinary courses developed) and the trial results. This data are
intended to use for scientific purposes, however this data will have value
only with connection with public deliverables and scientific papers to be
published later in the project. At the moment there is no need to closer
describe this data – the description will most likely be included in the third
version of the DMP. Later on in the documents we will focus only on the data
to be generated by WP4, as its structure and the way this data could be used
for scientific research are already known.

The scientific research data collection will be mainly associated with the
WP4, Citizen Science at School. In this WP, Citizen Science experiments will
be performed through a collective research process. The young boys and girls
will participate to the governance of the research projects, design the
experiments, conduct them and analyse the data.

In relation to the main objective of the project -which is to bring teenagers
closer to Science and Technology, Citizen Science-, the 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 the 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.

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

The project, in relation to Citizen Science experiences, will generate two
types of data:

##  HUMAN MOBILITY DATA

These data will be collected through an App installed on a mobile device
(Smartphone o Tablet). The data will consist of Timestamped GPS positions
recorded every x seconds. The XML data table will be composed by the following
fields in a simple table:

  1. id: GPS position ID 

  

  2. id_user:User ID 

  

  3. lon: Longitude 

  

  4. lat: Latitude 

  

  5. timestamp: Recorded time 

  

  6. accuracy: Accuracy provided by the user's devices 

  

  

See for example:  _http://dx.doi.org/10.5061/dryad.7sj4h_

##  HUMAN DECISION MAKING DATA

The data will consist of demographic information about the volunteers jointly
with their actions playing to original games, adapted from social dilemmas
such as for example the prisoner’s dilemma. The data will be structured in SQL
or XML (although SQL is the preferred choice) formats and here is an example
of the fields that can be found:

  1. _id: User ID_

  

  2. _num_jugador: Player ID wihin the network_

  

  3. _partida_ID: Session ID_

  

  4. _Diners_inicials: Player’s initial bucket joc clima_

  

  5. _Num_seleccions: number of total actiona for each player in joc clima_

  

  6. _Guany_final: Final payoff joc clima_

  

  7. _Rival_joc_inversor1: Opponent’s ID in joc inversor1_

  

  8. _Rival_joc_inversor2: Opponent’s ID in joc inversor2_

  

  9. _Rol_joc_inversor1: Role joc inversor1_

  

  10. _Rol_joc_inversor2: Role joc inversor2_

  

  11. _Seleccio_joc_inversor1: Strategy in joc inversor1_

  

  12. _Seleccio_joc_inversor2: Strategy in joc inversor2_

  

  13. _Seleccio_joc_premi: Strategy in Prisoner Dilemma game_

  

  14. _Guess_joc_premi: Expectation in Prisoner Dilemma Game_

  

  15. _Is_robot_joc_inversor1: Automatic computer selection in joc inversor1_

  

  16. _Is_robot_joc_inversor2: Automatic computer selection in joc inversor2_

  

  17. _Is_robot_joc_premi: Automatic computer selection in joc premi_

  

  18. _Diners_clima: Payoff joc clima_

  

  19. _Diners_inversor1: Payoff joc inversor1_

  

  20. _Diners_inversor2: Payoff joc inversor2_

  

  21. _Diners_premi: Payoff Prisoner Dilemma game_

  

  

_See for example (XML case):_ _https://doi.org/10.5281/zenodo.50429_

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

Data from previous Citizen Science experiments on the same themes will 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 will 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.

_**What is the origin of the 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 will be thought
to solve or propose solutions relevant issues for the community based on the
evidences collectively gathered.

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

Typically, for each experiment, a number of 50-200 volunteers will
participate. The size of the files is usually between 5-30 MB.

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

Each set data will 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 students involved in similar Citizen Science experiments, in the frame of StemForYouth project. It is foreseen that at least 3 schools in Barcelona, 1 in Athens and 1 in Warsaw will participate. 

  

  2. Others scientists having convergent research lines in terms of human mobility and collective decision making (in both cases, data is scarce and not generally shared). 

  

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

  

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

  

  

#  FAIR DATA

##  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 will be associated with metadata and locatable by means of a
DOI, following the previous examples (
_http://dx.doi.org/10.5061/dryad.7sj4h_ or
_https://doi.org/10.5281/zenodo.50429_ )

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

All the data names set will contain, in this order:

  1. STEMForYouth 

  

  2. The name of the school that designed the experiment 

  

  3. Name or reference of the experiment 

  

  4. Name of the place and date of the experiment 

  

  

Thus, an example of data name could thus be:

STEMForYouth_JesuïtesCasp_Gimcana_Barcelona_2017_03_05

_**Will search keywords be provided that optimize possibilities for re-use?**
_

Human mobility, Pedestrian mobility, Smart City, Human Decision Making, Social
Dilemmas, Citizen Science, STEMForYouth, Public Experiments, Collective
Experiments, Action Research, Human Behaviour, Collective Action, Geolocation,
Game Theory, Cooperation.

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

Yes, see naming conventions. In addition, the raw data and the treated data
will be provided.

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

Metadata created will carefully explain and describe the meaning of each of
the fields of the database. Additionally, there will be a lab notebook made by
students and the results of surveys. These files will be related to assessment
and performance of students and this needs to be discussed with all partners
with similar needs or similar outcomes (December 2016).

##  Making data openly accessible

_**Which data produced and/or used in the project will be 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.** _

Personal data will not be available (being in an independent file). Rest of
the data and specifically produced data code will remain open. Some of the
activities in the classroom will however encourage the use of open source
platforms.

_**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 generated through the Citizen Science experiment will all be made
openly available except from personal data (those socio-demographic data that
might help to identify a single individual or those mobility data that can
make possible to retrieve personal data such as home address). In the latter
case, data will be properly randomized to avoid any re-identification process.

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

The data will be deposited simultaneously in Zenodo and Github using standard
files for data tables (e.g. SQL or XML).

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

In general, no software is necessary to access the data. In case this were
necessary, the appropriate open source software will be also provided.

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

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

Yes, in GitHub. A specific space in GitHub will be created in order to include
the software used in SFY.

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

Yes. Zenodo (OpenAire/CERN repository) and Github, traditionally associated
with the Open Source movement.

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

_**If there are restrictions on use, how will access be provided?** _ Access
is free and open in both cases.

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

##  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)?** _ Yes. Recombination with different datasets is also considered
specially related to neighbourhood open access data such as welfare or life-
expectancy or geolocated urban elements. Open software applications will be
used by students such as Carto (https://carto.com) and Plot.Ly
(https://plot.ly), which are indeed available to process data and elaborate
new data with online tools. A good, alternative to make open data available is
to include data together with an R package and programs in GitHub that they
are able to dive into the open data. R has become very popular in big data
analysis. R has also a large user community, so on open R package may be an
efficient way to disseminate the WP4 (and other project statistic) results
amongst the research community. Finally, data processed can be downloaded as
well and placed in a public repository as Zenodo. Codes been used might not
always be available. The availability of codes to run specific digital
platforms will be discussed with partners and if relevant, included in the
next revised version of this DMP.

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

Vocabularies being used will have three main origins: Education, Social
Sciences when experimenting with human subjects and Cartography and
Geolocation. Statistics, probability and Movement Ecology are possible
additional vocabulary. To be discussed with all partners when dealing with
Assessment. In the case of Zenodo repository, all metadata is stored
internally in MARC. Metadata is exported in several standard formats such as
MARCXML, Dublin Core, and DataCite Metadata Schema according to OpenAIRE
Guidelines. For textual items, English is preferred but all languages are
accepted.

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

Yes. It will also intend to be fully comprehensive by students participating
in the project.

_**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.

##  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 CC0 1.0 license.

_**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.** _

The data will be made available shortly, from six months to twelve months
after the realization of the experiments. In addition, data will be delivered
to volunteers almost immediately through userfriendly interfaces.

_**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. No
restriction.

_**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?** _

Yes. The data quality will be assessed by the researchers of Universitat de
Barcelona that will help conducting the Citizen Science experiments. The
documentation attached to each database will include 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.

#  ALLOCATION OF RESOURCES

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

In the case of UB, no cost associated for the deposit in repositories
(although they have a size limit), 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.) and while another copy
with personal data is stored an in-house UB server.

_**How will these 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).** _ Not applicable unless more space
than the one offered for free in the repositories in the repository. However,
based on the current plan, this case is unlikely. Hard disk will be funded by
the EU project and with the UB budget in the case of the Citizen Science
experiments.

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

Ignasi Labastida, Head of the Research Unit at the CRAI of the UB.

_**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)** _

In case we exceed the quota, the cost in GitHub is 6.43 Euros per month and
per user (see  _https://github.com/pricing_ )  . There is an unlimited use in
Zenodo but the size constraint is 2GB per file. Higher file quotas in Zenodo
can be requested. Zenodo general policies can be consulted here
_https://zenodo.org/policies_ .

#  DATA SECURITY

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

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

_**Is the data safely stored in certified repositories for long term
preservation and curation?** _ Yes, Zenodo repository provide this
certification https://zenodo.org/policies

#  ETHICAL ASPECTS

_**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).** _

Before making the data available, all possible references allowing identifying
the volunteers will be taken out of the data set. All volunteers will sign an
informed consent. All the Citizen Science experiments will pass through the
Ethics Committee of Universitat de Barcelona and the rest of the partners
should perform identical protocols. The data collection of the Spanish Citizen
Science experiments will follow the rules of the LOPD (Ley Orgánica de
Protección de Datos de Carácter Personal, Organic Law for Personal Data
Protection) and equivalent process will be followed for experiments done in
Poland and Greece.

_**Is informed consent for data sharing and long term preservation included in
questionnaires dealing with personal data?** _ We will not share personal
data.

#  OTHER ISSUES

_**Do you make use of other national/funder/sectorial/departmental procedures
for data management? If yes, which ones?** _ None.

#  APPENDIXES

_**1\. Timetable for review** _

M6: Submission of DMP first version (DMP version 1, D9.2)

M8: Introduction to Open Data and DMP (Second Project Meeting)

M12: First review of DMP (DMP version 2)

M24: Second review of DMP (DMP version 3)

M30: Final DMP (DMP version 4, D9.6)