Executive Summary

**1 EXECUTIVE SUMMARY**

This deliverable is the first version of the Data Management Plan (DMP) for
OSCCAR project. OSCCAR project participates in the H2020 Open Research Data
Pilot (ORDP) [1], which means that an open access to research data is
provided. The data management within OSCCAR project follows the data
protection and privacy issues in digital communication which are governed by
two EU directives. The 95/46/EC directive [3] protects individuals regarding
personal data (processing) and on the free movement of such data. The
2002/58/EC [4] directive specifies the requirements on data protection and
privacy in digital communications.

The deliverable follows the guidelines for F.A.I.R Data Management set by the
EC H2020 [2], to submit a first version of OSCCAR Data Management Plan (DMP)
within the first 6 months of the project. Management of datasets containing
personal information will be compliant with the General Data Protection
Regulation (GDPR) [13].

The deliverable presents how research data is collected or generated to reach
the project goals, how data is stored, made openly accessible and re-usable.
It clarifies the responsibilities for data management and presents details on
data security.

It is encouraged to make existing data available for research within OSCCAR
project. This data will be generated and colleted especially in WP1
Determination of future accident scenarios, WP2 Development of advanced
occupant protection principles and WP3 Human Body Models for assessment of new
safety systems in future vehicles which are described in detail.

The DMP is a living document and will be updated continuously, whenever
significant changes arise. However, an updated version will be available in
month 16 as deliverable “D7.4 Data Management update”.

_Keywords:_ Data Management Plan, FAIR data, Data security, Data re-use

  2. **DESCRIPTION OF WORK**

  

  

**2.1 Data Summary**

Data being further processed in the OSCCAR project will not contain personal
or commercially sensitive information. The final results, like future accident
research data from WP1 e.g, the user study and sled tests in WP2, data on
tissue and volunteer tests in WP3 and in the stakeholder group in WP6, may
contain references to practices in the OSCCAR system database, the
demonstrator evaluation and validation. These data will be processed at a high
level of abstraction, devoid of any personal or commercially-sensitive data
before sharing within the consortium and publishing.

The management of knowledge, research data, data access and intellectual
property rights are delicate issues, especially in close-to-market R&D
projects with a large number of OEMs and suppliers working closely together.
The handling with this sensitive data is regulated in the OSCCAR Consortium
Agreement [5] and Grant Agreement [9]. Some issues regarding data protection,
access and security of data have also already been part of the OSCCAR Grant
Agreement, Description of Action (DoA) [9].

For reasons of competition (competition law), detailed data on cost and sales
prices of specific components and systems WILL NOT be shared.

In Table 1 an overview is presented of the data that will be generated in the
project, the standards that will be used, how this data will be exploited
and/or shared/made accessible for verification and re-use and how this data
will be curated and preserved.  
  
<table>  
<tr>  
<th>

Generated data

</th>  
<th>

Way of exploitation of data and/or sharing/making accessible of data for
verification and re-use

</th>  
<th>

Way of curation and/or preservation of data

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

openPASS simulation software modules, configuration artefacts and simulation
results

</td>  
<td>

Develop procedures and documentation of accident scenario simulation
methodology based on openPASS; the aim is to provide the relevant software

modules in the openPASS environment, i. e. git repositories of Eclipse, so
data might be re-generated by re-using the modules.

</td>  
<td>

Deliverables describing scenarios and simulation based assessment publicly
available on the OSCCAR website; open source code and OSCCAR specific
configuration artefacts (scenario models) generated in OSCCAR committed e.g.
to

Eclipse git repositories

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

OpenSCENARIO format

descriptions

</td>  
<td>

Description of approach how to use OpenSCENARIO in the OSCCAR toolchain (link
between openPASS and CAE tools); provide examples of scenarios

</td>  
<td>

Publicly available (on the OSCCAR website) ;

Communication with XOSC project to incorporate changes/additions

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

Generated data

</td>  
<td>

Way of exploitation of data and/or sharing/making accessible of data for
verification and re-use

</td>  
<td>

Way of curation and/or preservation of data

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

Procedures for hardware testing for component and sled testing

</td>  
<td>

Convey enhanced testing procedures with respect to new components related to
future interior concepts to the international standardization community.

</td>  
<td>

Communication with standardization agencies + Publicly available on the OSCCAR
website.

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

Data generated within the WP2 user study

</td>  
<td>

Generation of knowledge in respect to user opinion and input for selection of
testcases to be persued within OSCCAR

</td>  
<td>

Publication of main results

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

Biomechanical data analysis within WP3

</td>  
<td>

Development and

enhancement of HBMs

characteristics. Description and publication of implementation methods

</td>  
<td>

Validation data and methods to be published.

Respective deliverables publicly available on the

OSCCAR website

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

Simulation and assessment procedures for HBM application

</td>  
<td>

Convey adapted procedures

for virtual testing to the international standardization community.

</td>  
<td>

Communication with standardization agencies +

Publicly available on the

OSCCAR website

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

**Table 1 Overview of data generated in the project**

In the Consortium Agreement [1] signed by all partners the following aspects
regarding data management are addressed and regulated: Background, Results,
Access Rights, Publications.

####  2.1.1 Data types and formats

The type and format research data are created depending on how researchers
choose to collect and analyse data and depends on discipline-specific-
standards and customs. Ensuring long-term usability of the OSCCAR data
requires consideration of the most appropriate type and file formats.

Within research activities of OSCCAR project it is intended to use different
types and formats of data. To reach the project goals an intensive review and
coordinated analysis of past and newly available volunteer tests data will be
necessary. These data sets are from different formats and types:

  * Photos, videos, spreadsheets, mechanicals measurement data (force, displacement, trajectories etc), electromyography (EMG) measurement data (muscle activity,), For the data exchange of research results: 

  

  * Word documents, Excel documents, PowerPoint documents, pdf, documents containing simulation code, datasets 

  

For the documentation of results:

  * Deliverables (Word documents) 

  

  * Publications (pdf) Personal data: 

  

  * Contact list (internal use only) 

  

  * Personal data for user study. Dataset on empirical sample describing ergonomic aspects of user behavior in a simulated automated driving situation. The handling of the data is regulated in the information sheet, the consent informed form and the form for withdrawal of participation. No sensitive data will be collected. In the consent informed form volunteers for the study get informed about what date will be collected (e.g. audio/visual/text/survey). In the information sheet the assurance of anonymity and confidentiality is defined. Besides it details how the data collected will be used, what happens to data and results at the end of the research [14]. 

  

The following rules are followed:

  * Date will be stored under pseudonym. Data will be stored electronically and on paper. Only researchers authorized by a signed form, has access to data. The data could be accessed by any third part only in an anonymous way. 

  

  * ID – related information will be kept in separate databases from other information types in order to ensure that no personal data can be obtained without the proper authorization. 

  

  * No sensitive data will be collected. o The personal data will be stored for the duration of the project only, if collected at all. 

  

  * De-identified data will be deposited or submitted to an open source online research data repository at the end of the study. This data may be used for future research. 

  

####  2.1.2 Re-use of existing data

It is encouraged to make existing data available for research within OSCCAR
project. This data will be generated and colleted especially in WP3 Human Body
Models (HBM) for assessment of new safety systems in future vehicles. An
overview of the data in the according tasks is shown below:

  * Task 3.1.1 Existing experimental data from (CHALM; DAI and LMU) 

  

  * Task 3.1.2 Existing data: Chalmers/JARI will contribute with MRI (Magnet Resonance Imaging) data of seated volunteers. Such data will be used to further understand the position of the pelvis and adjacent inner organs. 

  

  * Task 3.1.3 Additional data on pelvis to seat interaction will be made available and will enable the use of HBMs to predict human in-crash response in future sitting positions. Existing PMHS neck response data have been identified and plans for data exchange established. 

  

  * Task 3.2.1 Project partners will provide additional volunteer data: Task 3.2.1b. These are among other parts of the OM4IS  1  (Occupant Models for Integrated Safety project) test series, the AHBM 2 (Active Human Body Model Project) test series, AHBM 3 test series and parts of the Precooni  1  data. To make this data available and to enable validation of morphed active HBMs, i.e. models made to be representative of the population diversity, additional data analysis is required. 

  

Intensive review and coordinated analysis of past and newly available
volunteer tests will be used.

  * OM4IS ½ (Improved Predictability research project) tests results/manoeuvres incl. 

  

previously unpublished female volunteer data to be made available in detail.
These are braking, lane change and combined manoeuvres.

  * Precooni (K2 research project) data & results to be made available in detail. This is a small, low-g sled test series with volunteers under laboratory conditions. 

  

  * SAFER (SAFER Consortium ) data: AHBM 2: Response corridors for vehicle kinematics, muscle activation, interactions forces, and volunteer kinematics will be provided. AHBM3: Response corridors for vehicle kinematics, muscle activation, interactions forces, seat pressure and volunteer kinematics will be provided. Analysis of female data and data for volunteers when in the driver’s seat are just to be started. 

  

  * Daimler Driving Study to be made available in detail (Unpublished volunteer test – Focus on driver: steering, braking, combined manoeuvre – male & female ) 

  

  * Published and soon to be published data from TME data to be made available in detail (owned together with IFSTAR Institute- (Institut français des sciences et technologies des transports, de l’aménagement et des reseaux) 

  

  * Existing volunteer data owned by TASS/ Siemens company will be provided. 

  

  * Analysis of PRISM (EU Project- Proposed reduction of car crash injuries through improved smart restraint development technologies project) data (standard seating posture/driver). 

  

During the course of the project, the OSCCAR team may gain access to data that
was collected before the start of the project and by an organisation that is
not a member of the consortium. In this event, the OSCCAR partner who receives
this data must ensure that there is no information contained in it, which
could be used to identify individual citizens. Further, the OSCCAR partner
must be mindful of the risks of linking this data, or conclusions resulting
from this data with data or conclusions from other data sources. Informed
consent must be obtained when acquiring preexisting data from external
sources. [9]

####  2.1.3 Origin of data

Suitable datasets to being used for validation/tuning for human body models
come from OSCCAR partners and from initiatives and projects in which the
needed data has been collected, see [7]. Data sets provided to OSCCAR will be
assessed a-priori for their suitability by the respective partner. Only
technically and legally suitable data will be used within OSCCAR.

####  2.1.4 Expected size of data

To be evaluated during the course of the project. The expected size to be
handled depends on the extent and the nature of the data that are made
available. Datasets including high resolution and or high speed video tend to
be relatively large, as are simulation datasets that include full vehicles and
HBMs in pre- and in-crash simulation. Several GBs of data can be expected for
a single set. Therefor only stripped sets will be made available.

####  2.1.5 Data utility

  * Automotive Industry 

  

  * OSCCAR consortium 

  

  * OSCCAR associated/ international research partners 

  

  * All Industry and the large research community dealing with virtual testing and or biomechanics. 

  

  * European Commission services and European Agencies 

  

  * Austrian institutions and bodies of the EU 

  

  * The general public including the broader scientific community 

  

**2.2 FAIR data**

####  2.2.1 Making data findable

With respect to the guidedlines on FAIR Data Management in Horizon 2020 [11]
research data should be “FAIR” that is findable, accessible, interoperable and
re-usable. OSCCAR project will undertake all necessary action to make its data
FAIR.

The primary responsibility for storing and making data findable lies with the
data creator. However, all data created within OSCCAR project will be stored
in one central archive – OSCCAR Projectplace [10].

####  2.2.2 Naming conventions

A structured data storage is essential for proper and secure storage of data
files and records. For any file-based storage this includes clear and
unambiguous file naming, the use of proper versioning, clear and intiuitive
folder structure.

The naming conventions within OSCCAR project are described in the Project
Handbook [8]. The following conventions are foreseen for all project documents
(presentations, meeting minutes, deliverables, reports…)

  * DATE (only if required) 

    * date of creation (format: yyyymmdd) 

  

  

  * TITLE 

    * Short description of the document, please use 7-bit ASCII characters (a..z, 0..9, _, -) only (DO NOT use special characters, e.g. “:” ) 

  

  

  * VERSION (only if required) 

    * vX-Y … use position X for a major release, and position Y for a minor release (e.g. v0-1, v0-2, v1-0, v1-1, v2-0 …) 

  

    * Avoid uploading files with version numbers in their name on Projectplace – use the versioning system instead. 

  

  

  * FILEEXTENSION 

    * according to the type of the file (docx, pdf, …) 

  

  

#####  2.2.2.1 Presentations

{DATE_}OSCCAR_TITLE{_VERSION}.FILEEXTENSION e.g.
20150623_OSCCAR_WP3_Overview_v1-0.ppt

e.g. OSCCAR_Overview.pdf

#####  2.2.2.2 Meeting minutes

DATE_OSCCAR_MoM_TITLE{_VERSION}.FILEEXTENSION e.g.
20140323_OSCCAR_MoM_CoreTeamWebex.pdf

e.g. 20140323_OSCCAR_MoM_CoreTeamWebex_v1-0.doc

#####  2.2.2.3 Deliverables

These naming conventions are relevant for the deliverable creation and
deliverable review process. The submission of deliverables to the European
Commission is exclusively handled by the co-ordinator.

• OSCCAR_D_DELIVERABLENUMBER.FILEEXTENSION

e.g. OSCCAR_D_6.1.doc

e.g. OSCCAR_D_6.2.pdf

####  2.2.3 Search keywords for re-use

In each deliverable keywords to describe the main content have to be included
within the Executive Summary. It is possible to search for documents on
Projectplace with a search function. All documents, files and folders in which
the searchword appears are displayed.

####  2.2.4 Version numbers

The version control for documents will be performed on Projectplace. It uses
version numbers in the format of _x_ . _y_ . Here, _x_ is the major version
and _y_ the minor version number. Once the document is checked in after
finishing the modifications, the version number is automatically updated. The
version number _within_ the document must also be updated. This has to be done
manually.

In case a new version is created by checking in a document on Projectplace, it
is required to attach a comment which describes what has changed within the
new version.

The following guidelines apply for using major and minor versions:

  * Minor version: incremented for changes to draft versions of a document (prior to release). 

  

  * Major version: incremented when a reviewed version of the document is released. A released version will always have a version of the form _x_ .0. The major version number of a draft document may also be incremented if there are very significant changes. 

  

If possible, version numbers should NOT be used in the filename. Instead, the
versioning system of Projectplace should be used. (see [8])

####  2.2.5 Metadata

Currently it is not foreseen to create new metadata within OSCCAR. In case
metadata will be needed later on, it will be outlined here what type of
metadata will be created and how.

**2.3 Open access data**

####  2.3.1 Open available data

Following the guidelines of the H2020 regulations defined for the Open
Research Data Pilot (ORDP) [1] , all data collected or produced within the
OSCCAR project consortium will be by default open. Some sensitive data may be
shared only under restrictions (e.g. within the consortium only).

To share data with the OSCCAR consortium, a repository has been set up: OSCCAR
Projectplace [10]. It provides access to project data and is also a platform
to view and share files easily. The access to data can be restricted
individually.

This repository is hosted by the project coordinator (VIF), who aims to reach
the highest level of General Data Protection Regulation (GDPR) [6] compliancy
amongst others by:

  * Applying strict policy in granting and revoking access to the data 

  

  * Logging of user identity during data access, download and upload, including version control. This enables to restore the availablity and access to the data in a timely manner in the event of a physical or technical incident 

  

Deliverables with the distribution level “Public” as well as open access
publications will be uploaded on OSCCAR Website [12] where open access is
granted for all interested parties. Other open access data will be accessible
through open access repositories.

####  2.3.2 Accessibility of data

To share data and make it accessible with OSCCAR consortium partners, a
project repository has been set-up by VIF and is available [6].As described
above public deliverables and publications will be available on OSCCAR Website
as well as in according repositories.

According to H2020 ORDP [1] open access to scientific publication is
obligatory, as well as open access to research data, where opt-outs are
possible. Beneficiaries will therefore deposit an electronic copy of the
published version or final peer-reviewed manuscript accepted for publication
in a repository for scientific publication – this ensures a long-term
preservation. After that beneficiaries mus ensure open acces to those
publication via the chosen repository. They can chose a repository but must
ensure open access for most 6 months.

As described in the ORDP research data generated in the project will be as
open as possible and as closed as necessary. Open accessible research data
will be stored in a research data repository. As far as possible measures to
enable third parties to access, mine, exploit, reproduce and disseminate (free
of charge for any user) research data will be taken [1] [17].

####  2.3.3 Deposition of data

As regulated in the ORDP beneficiaries will also provide open acces, through
the repository, to the biblographic metadata that identify the deposited
publication [1] [17]. As suggested by the EC OpenAIRE [18] / Zenodo [19] have
been chosen as such depositories.

Arrangements with the certified repository for open access data will be done
as soon as appropriate data is available.

####  2.3.4 Restrictions on use

The access to the OSCCAR repository will be provided by the project
coordinator VIF. Access is only granted to project members. Restrictions to
any folders are possible. Restrictions on use are defined in the Grant
Agreement [9] and in the Consortium Agreement [5].

Open available data (public deliverables, publications, research results) will
be available on OSCCAR Website [12] and on according depositories like
described in section 2.3.2 .

**2.3.5 Data access committee**

There is no need for a data access committee.

####  2.3.6 Conditions for access

As suggested by ORDP within OSCCAR project authors are encouraged to retain
their copyright and grant adequate licenses to publishers [1] [17].

####  2.3.7 Access management

Data on an open access depository like openAIRE manage access to the
respective data.

In Projectplace, logging of user identity during data access, download and
upload, including version control. This enables to restore the availability
and access to the data in a timely manner in the event of a physical or
technical incident.

**2.4 Data interoperability**

OSCCAR project knows that common data and metadata standards and formats are a
key aspect for data operability. Standardisation makes data discoverable and
this way promotes international and interdisciplinary access to, and use of,
research data. To ensure correct and proper use of the OSCCAR data by the
owners and re- users, the use of standardized vocabularies and ontologies is
also necessary.

Data exchange and re-use (between researchers, institutions, organisations,
countries) is provided for publications and research data in open access
repositories like claimed in ORDP.

####  2.4.1 Data and metadata vocabularies, standards or methodologies

Standardisation on data level will be performed by applying community-based
standards as used in

peer reviewed publications and conferences and ISO standards, like ESV,
Journal of Crashworthiniess, Ircobi, etc.

Standard and common vocabularies will be used in all types of data to be
published by OSCCAR. Where additional explanation is necessary, it will be
provided.

####  2.4.2 Licensing

Currently data or software licencing is foreseen to be of FOSS (free open
source software ) type to be published accordingly. (e.g. GPL v3).

####  2.4.3 Reusability of data

As soon as data and results are ready to be made available, they will be
published and / or uploaded for open access. This section will be detailed
throughout the course of the project.

**2.4.4 Useability of data by third parties after the end of the project?**

In Table 1 an overview of the data generated in the project, how this data
will be exploited and/or shared/made accessible for verification and re-use
and how this data will be curated and preserved. Project results and outputs
will be published on OSCCAR website [12] and open repositories accessible for
verification and re-use (see [9], section 2.2.4). The website will remain
online at least until five years after project end.

OSCCAR project supports the concept of FAIR data, and will work toward making
research data FAIR. The decision about long-term provision will be taken as
the data are stored: open access data (e.g. public deliverables, publications)
will be made FAIR as long as possible.

Most research data of OSCCAR project will be open access as soon as the
research has been completed and published. There are no plans to end provision
of OSCCAR data, and they will therefore be available for re-use as long as the
archives exists. The data produced in the course of OSCCAR project will be re-
usable for as long as the information they contain are relevant.

####  2.4.5 Data quality assurance processes

An initial quality control is needed at the local level and early in the
collection process. The initial control of the data, during data collection,
is the primary responsibility of the data creator/owner, who must ensure that
the data reflect the actual facts, responses, observations and events. The
consortium agreement details the publication quality control process, that is
also applied to ensure data quality.

In deliverable D8.2 [15] the data protection management system from the
coordinator VIF is described. To ensure the protection of personal data, the
data protection management system of the coordinator VIF or where required of
the data collecting partner organization will be applied.

**2.5 Allocation of resources**

####  2.5.1 Costs for making data FAIR

Costs for establishing and maintaining the OSCCAR data repository are covered
by the coordinator, VIF. While the repository will not be maintained after the
end of the project, all files stored in the repository shall be stored after
the project to meet the requirements of good scientific practice. A strategy
for storage of the files after the project is being developed and will be
included in the follow-up DMP in month 16.

Resources for long-term preservation of datasets will be ensured by its
storage in the repositories. The costs for storing data will be born locally.
The costs for making publications open access can vary from 500 to 5000 euro,
depending on the journal. This will be covered by the

company/institution of the author(s). Some funding resources are already
dedicated to this. (see other direct costs)

If eligible, and planned for, costs related to open access publication will be
covered by the H2020 Grant.

####  2.5.2 Responsibilities of data management

The project coordinator has organized a well structured data repository on
Projectplace [10].

As project coordinator VIF is responsible for:

  * Initial set-up of the data repository and upgrading when neeed 

  

  * Maintenance of the data repository: definition, creation, updating of the data repository structure, i.e.: structure of folders and subfolders, names, contents and access, upload, download rights 

  

  * Perform security assessment on a regular basis in order to guarantee the agreed security level 

  

  * Reporting and blocking any possible security threat, taking appropriate measures accordingly 

  

  * Collecting users requests for access to and download of data in the repository 

  

VIF is not responsible of the interruption of the data repository services
that are due to force majeure.

The quality control of the data, during data collection, is the primary
responsibility of the OSCCAR partners (as data providers).

In general, the aim is to use European and international repositories. In
addition to this, all OSCCAR data will also be stored on OSCCAR Projectplace
[10].

The primary responsibility for back-up and recovery of the data also lies with
the OSCCAR partners, and for the data stored on Projectplace this data lies
with VIF.

  * ‘Data creation’ refers to the act of creating new data or acquiring existing data which is new to the project (for example by obtaining existing datasets for use in the project). 

  

  * If a consortium partner is the creator of data (e.g. by performing data collection or tests), the partner is responsible for properly storing, processing and sharing that data, and ensuring that it does not contain personal data before being shared in the consortium. 

  

  * If a consortium partner wishes to use information from a test, but is not the creator (e.g. by acquiring relevant datasets or relevant documentation), the partner is responsible for determining the source of the data, and assessing if the dataset contains personal or otherwise privacy- or commercial-compromising or sensitive data. If that is the case, it is the responsibility of the consortium partner to purge personal etc. data from that dataset and prepare it for further dissemination in a proper admissible form. [9] 

  

####  2.5.3 Resources for long term preservation

The OSCCAR consortium, i.e. its partners and the Executive Board, board
discusses all items related to publication of data, that also concerns details
like time, timing, place and necessary resources if applicable.

**2.6 Data security**

####  2.6.1 Provisions for data security

All shared, processed and operational data will be stored in secure
environments at the locations of consortium partners with access privileges
restricted to the relevant project partners. If (processed) data is to be
transferred from one partner to another, the transfer needs to be done
securely, for example via a secure data channel, in an encrypted mode or via
physical transfer. [9].

OSCCAR project will undertake all required efforts needed to protect the data,
products and service against unauthorized use. The primary responsibility to
take necessary measures to ensure data security lies with the partners, and
once stored on the data repository OSCCAR Projectplace [10] the security
provisions come from there.

OSCCAR project will undertake all efforts required to provide secure access to
data. Where applicable, authentification systems are used, requesting log-in
before providing access to secured data and information. Furthermore, OSCCAR
project will take measure to be compliant with the EU regulations regarding
the protection of personal data [13].

OSCCAR project promotes a culture of openness and sharing of data and will
therefore stimulate the exchange of good practices in data access and sharing
by liaising with existing European initiatives.

####  2.6.2 Repositories for long term preservation and curation

VIF provides a workspace (Projectplace) for the project users where necessary.
The Projectplace environment is hosted in Stockholm, Sweden and ISO-27001 and
SOC2/SSAE16 certified. [20]

As suggested by the EC OpenAIRE [18] and Zenodo [19] have been chosen as
depositories for open access publications.

**2.7 Ethical aspects**

###  2.7.1 Ethical or legal issues on data sharing

This section is to be covered in the context of the ethics review, ethics
section of DoA and ethic deliverables. Ethics and legal issues are covered
within the OSCCAR Grant Agreement [9] and the OSCCAR Consortium Agreement [5].
Ethics is also covered in a separate deliverable D8.2 [15], which describes
principles of handling personal data and the data protection procedure within
OSCCAR project. The aim of this deliverable was to outline a OSCCAR specific
data protection procedure. It serves to document how the data protection
requirements in OSCCAR are met. To ensure the protection of personal data, the
Data Protection Management System of the coordinator VIF will be applied. The
goals are the establishment and maintenance of the regulations from GDPR [6]
and DSG 2018 [16]; decreasing the likelihood for potential data protection
violations as well as the continuous improvement of the data security
management system (DSMS)

Subsequently, all collected personal data and the corresponding work packages
and activities are defined. It is described what personal data has been
collected and how the collected data will be managed, protected, and
preserved. No sensitive personal data, which is defined by EU GDPR [6], will
be collected or will be necessary for the project. Even though there is no
collection of sensitive personal data, the project still collects personal
data.

There are no other ethical or legal issues that can have an impact on data
sharing. Ethics and legal situation in general is constantly changing and
therefor monitored. OSCCAR project wil adapt accordingly.

###  2.7.2 Informed consent for data sharing

A questionnaire that includes consent for data sharing and long-term
preservation dealing with personal data is available in D8.1 [14]. Templates
of the informed consent/assent forms and information sheets (in language and
terms intelligible to the participants) will be kept on file and submitted on
request. (see D8.1 [14])

##  2.8 Other issues

Currently no other issues of interest are identified. During the course of
OSCCAR, additional aspects will be added here if necessary.

References