#  Introduction

##  Objective and Scope

The objective of this deliverable is to establish a Data Management Plan (DMP)
for the CYBECO project compliant with the _Horizon 2020 FAIR Data Management
Principles_ . These principles establish that, in general terms, the project’s
research data should be findable, accessible, interoperable and reusable. The
partners will bring specific datasets towards the project, and there will be
many more data exchanges during the actual project. It is key that this data
is treated correctly, to prevent the leaking of IP or commercially sensitive
information from one of the partners by another partner.

This plan is based on the _Guidelines on FAIR Data Management in Horizon 2020_
[1] and its annex the _Horizon 2020 FAIR DMP template_ [1]. It further details
the data management contents of the _CYBECO Proposal_ [2]. The DMP is intended
to be a living document, and it will be updated with further detail as the
project progresses and when significant changes occur. Therefore, it will have
several versions and includes an update procedure.

The current report is the first version (i.e., DMP v.1), which is also
deliverable D2.2 that shall be submitted to the European Commission in the
third month of the project (M3).

##  Document Structure

The document is structured as follows:

  * Sect. 2 describes the procedure for implementing and updating the DMP. 

  

  * Sect. 3 presents the general aspects of the DMP, covering how the project as a whole would manage repositories, open access, data security and data from research with human participants. 

  

  * Sect. 4 synthesises the adherence of CYBECO datasets to the FAIR principles on making the research data findable, accessible, interoperable and reusable. It also discusses the adherence to other supporting principles, namely, resource allocation, data security and ethical aspects. The specific information for the different datasets is provided in their Dataset Record, in the annex. 

  

  * Sect. 5 provides a list with the different datasets of the project. Additionally, the data management information for each dataset is detailed in its Dataset Record (provided as annexes of this document). The current version of the DMP, the initial plan, only details one dataset: the internal repository that will centralise the project documents and most of its datasets. 

  

#  Implementation and update procedure

The DMP plan is implemented by evaluating the different datasets created by
the project regarding the FAIR principles, as well as an evaluation of the
overall data management within the project.

Specifically, the implementation of the DMP will consist of the following
steps:

  1. Creation of a _**Data Repository** _ in a private part of the CYBECO website. Unless there would be a possible conflict with confidentiality, security or commercial sensitivity, all data needed to validate the results as presented in any of the publications will be made available through an _**open research data repository** _ in the CYBECO website as soon as possible. The URL for the website is  _www.cybeco.eu_ ,  whereas the URL to access the private part is  _www.cybeco.eu/private-area/repository_ . 

  

  2. Each partner should fill a _**Dataset Record** _ for each of the datasets they create. We define a dataset as any collection of research data that is particular or special from the data management perspective. This means that data about different topics might be grouped in a dataset if no particular aspect makes its management different (e.g., confidentiality, security, intellectual property). Annex 1 provides a template of the Dataset Record. 

  

  3. Once the Dataset Record is filled, each partner should store them in the Dataset Repository alongside the actual dataset. 

  

  4. Some datasets might have specific data management policies or procedures (e.g., the experiments). If possible, each partner should upload those policies and procedures too. 

  

  5. On a regular basis, CSIC, with the support of TREK, will review these records to update the DMP accordingly and ask for additional feedback to the partners. As a minimum, the DMP should be updated in the context of the periodic evaluation/assessment of the project. If there are no other periodic reviews envisaged within the grant agreement, an update needs to be made in time for the final review at the latest. 

  

  

Additionally, the consortium will agree and specify, in the next project
meeting (second half of 2017), the following data management aspects:

  * How many years the data will be preserved after the end of the project and how the data will be curated for that long-term preservation. 

  

  * Identification of the relevant datasets that the project will generate. With special emphasis on protection (e.g., privacy and intellectual property) and public sharing (for both scientific and general usage). 

  

#  Summary of the Data Management Plan

The DMP details the following aspects: datasets, standards and metadata, data
sharing, identification of repositories, long-term preservation and associated
costs. The project datasets will be kept in a repository in a private part of
the CYBECO website (hereafter the CYBECO Repository), which will allow for all
data to be identifiable, but also include information about whether this data
is commercially sensitive and so on to allow for proper sharing of the
information amongst the partners and the public at large. This central
repository will ensure long-term preservation of the data, and will also be
secured using relevant methods for access protection and backup.

The main reference for the DMP are the _Guidelines on FAIR Data Management in
Horizon 2020_ [1] and its annex the _Horizon 2020 FAIR DMP template_ [1].
These provide a sufficient high-level procedure for data management.

However, the approach of the plan is bottom-up: each dataset will be evaluated
and prepared based on its security, privacy, technical and dissemination
needs. Those datasets without critical aspects will follow the H2020’s FAIR
guidelines. However, some datasets would have additional specific data
management procedures. Two of these specificities are privacy and ethical
aspects. Datasets generated from research with human participants will follow
stringent procedures as specified in Sect. 3.2. Another factor that makes more
convenient an individual data management procedure is that each domain has
different publication or metadata standards or procedures. Thus, for
maximising the access and utility of our public datasets, it is important to
follow these domain-specific procedures.

##  Open access to research data

Unless there would be a possible conflict with confidentiality, security or
commercial sensitivity, all data needed to validate the results as presented
in any of the publications will be made available through an open research
data repository in the CYBECO website as soon as possible. Likewise, other
elements, such as software tools or equipment, will also be provided in the
same repository.

Any sensitive data may be masked and made anonymous to protect the sensitivity
of data, while still allowing this to be used by other projects in the future.
Such sensitive data could also fall under an embargo period, the length of
which will be determined by the potential commercial development based on this
data, such as e.g. IP protection.

Some data may not be made available at all to the public due to its
commercially sensitive or security nature, to ensure that the project delivers
long-term profitable development for the commercial partners. The same applies
to IP brought into and developed during the project. If during the project
certain IP would restrict the intended availability of some of the outputs,
then a sample code approach will be used to overcome this problem. Such sample
code, as e.g. also used in the standardisation of the MPEG format, allows for
a functional model to be presented, while the freely available code would not
contain all possible optimisations. Hence, commercially and security sensitive
information can be retained and secured accordingly while the open source
tools would still be functional.

Following the dissemination plan of CYBECO (D8.1), datasets associated with
scientific publications are especially relevant. Peer-reviewed scientific
publication must be made openly available and free of charge, online, for any
user. Therefore, datasets and tools needed for make the paper reproducible
will be provided.

##  Data management of research with human participants

As declared in the ethical self-assessment, we shall perform research with
human participants, specifically with volunteers for social and human sciences
research and that personal data collection/processing will be involved. These
activities will be performed by DEVSTAT and UNN, which have experience in
performing this type of research with the highest ethical standards. Their
research protocols will fully comply with the principles of the _Declaration
of Helsinki (1989)_ , the _Universal Declaration of Human Rights (UNESCO,
1948)_ and the _Agreement for the Human Rights Protection in Biology and
Biomedicine (Oviedo, 1997)_ , and the CYBECO charter of ethics for experiments
[2].

###  Behavioural economic studies

Several considerations will be made to minimise confidentiality issues with
the participants in the behavioural economics studies. First, the amount of
personal information required will be limited to the absolute minimum. Second,
personal information will be collected without unique identifiers attached to
the data, or known to the researcher. Although consent forms will include the
participant name, these personal identifiers will not be linked to the
recorded data. Third, each participant data will be associated with an
alphanumeric code to remain anonymous in all stages of the research protocol.
The identifying list will be stored in a safe and separate area from the study
data.

Security measures for storage and handling of subject data will be carefully
considered: experimental data will be originally recorded in a computer
without Internet access and with restricted access to researchers involved in
the project. Access passwords are necessary to log in the experimental
computerised setup. Participant recordings will be removed from the computer
when the experiment has finished with each participant to increment the
security of this data set.

###  Psychology-led studies

Similar considerations will be in place for the psychology-led studies, which
adheres, in addition, to the ethical code of practice as laid down by the
_British Psychological Society_ . Although the stored interview data may hold
information unique to particular participants and so strict consent protocols
will be devised around the storage and use of this data and the right to
withdraw. Participants will be free to withdraw from the experiment at any
time. It will be made clear that participation is voluntary, and that deciding
to quit from the study is affecting only the amount of payment, but a minimum
wage is guaranteed at the end of the first session.

##  Data management security

Information will be handled as confidentially as possible in accordance to
applicable national regulations on data protection, to the _Directive
95/46/EC_ of the European Parliament and of the Council of 24 October 1995 on
the protection of individuals with regard to the processing of personal data
and on the free movement of such data (OJ 23 November 1995, No L. 281 pp.
0031-0050) and to the _Directive 2001/20/EC_ of the European Parliament and of
the Council of 4 April 2001 on the approximation of the laws.

Because of its very own nature, security is a key issue within CYBECO. As
stated, the Executive Board of the Project will act as well as Security
Scrutiny Committee, identifying issues that should remain at confidential
level. In particular, some details in connection with the experiments and the
product will remain at such level for security reasons, as stated in the work
plan. Besides, the CSIC team includes a specialist in data protection, J.A.
Rubio, who will take care of data protection issues.

#  Adherence to the FAIR principles

This section synthesizes the adherence of the CYBECO datasets to the FAIR
principles on making the research data findable, accessible, interoperable and
reusable. The specific information for the different datasets is provided in
their Dataset Record, in the annexes.

This section will evolve as the CYBECO project grows.

##  Making data findable

  * CYBECO will create a repository for the project partners and an open research data repository for the public. 

  

  * Datasets and documents will contain version numbers, metadata and keywords for identification. Internally, following the structure of the project organisation. The public available datasets will, additionally, use identifiers such as DOI and metadata that facilitates a clear identification and citation by external users. 

  

##  Making data openly accessible

  * All data needed to validate the results of CYBECO will be made openly available unless there would be a possible conflict with confidentiality, security or commercial or intellectual property aspects. 

  

  * Sensitive datasets may be masked, made anonymous, or presented as a sample to protect the sensitivity of data, while still allowing this to be used by the public. 

  

##  Making data interoperable

• The public available datasets will follow standardized formats that
facilitate their interoperability and reusability. First, by using highly
interoperable formats such as .sql, .csv, or .xml. Second, by producing “tidy
data” [3] so that the datasets are easy to edit and visualize.

##  Making data reusable

• Sensitive data may fall under an embargo period for determining whether and
how this data will be made public.

##  Additional aspects of data management

###  Resource allocation

  * Long-term preservation of the CYBECO website and, thus, the repositories. 

  

  * Preservation of back-ups of the datasets. 

  

###  Data security

  * Datasets in the CYBECO repository will include information about whether the data is sensitive and the type of sensitive information (e.g., personal data, intellectual property, commercial). 

  

  * Website hosted in European servers. 

  

  * Use of secure methods for access and backups of the CYBECO repositories. 

  

  * The CSIC team includes a specialist in data protection, J.A. Rubio, who will take care of data protection issues. 

  

###  Ethical aspects

  * Following the ethical self-assessment, we have declared that we shall perform research with human participants and, thus, personal data collection and processing. 

  

  * The data management of research with human participants will be performed by DEVSTAT and UNN, which have experience in performing this type of research with the highest ethical standards. Further details of the data management of this research is provided in Sect. 3.2. 

  

#  Datasets

The initial DMP identifies one special dataset: the internal repository.
During the life of the project this list will grow to include other datasets.
Each of the dataset is further detailed in its correspondent annex.