_Data not selected for publication._ This category covers raw data tagged by
the consortium as unpublished. However, these data will be screened for
quality and available upon request for potential external users.

Three listed data categories are selected in DMP with the following
objectives:

  * Ensure the public access both to the intermediate and final project results; 

  

  * Facilitate easy public search and access to publications, which are directly arising for the research funded by the European Community; 

  

  * Maximize the potential for creative reuse of research results to enhance value to all potential stakeholders; 

  

  * Avoid unnecessary duplication of research activities; 

  

  * Guarantee transparency of research process within the project framework. 

  

#  Standards and metadata

The DMP defines the data management cycle during the project life, detailing
the character of data generated in EVE individual projects and linked
metadata, as well as, exploitation, curation and preservation of these data.
The DMP concerns: Generated and Collected Data; Data Management Standards;
Data Exploitation, Sharing and Access; Data Curation and Preservation in
compliance with the following standards: ISO/IEC JTC 1/SC 32 - Data management
and interchange; ISO 9001:2008 - Quality management systems; ISO 27001:2013 -
Information Security Management Systems.

The knowledge sharing outside of the consortium will be realized through two
main instruments:

  * The consortium will define a set of documents and reports with the analysis of the project results and assets that will be available for open access on the project website. Most of the project presentations delivered on professional events will be also published on the website for free download. 

  

  * The consortium will aim at granting free-access for all the scientific publication that will be prepared during the project activities. The planned publications will be subjected to the “green” and “gold” open access model. In addition to this, presentation of program activities and relative results will be published on the consortium website. 

  

  * The publishable and analyzed raw data can be reused upon request in exchange for authorship and/or establishment of a formal collaboration. 

  

#  Quality assurance and control

The consortium has identified a number of measures related to quality
assurance and control in framework of the data management. These measures can
be summarized in three groups described below.

Measures for _quality assurance before data collection_ :

  * Definition of the standars(s) for measurements and recording prior to data collection; 

  

  * Definition of the digital format for the data to be collected; 

  

  * Specification of units of measurement; 

  

  * Definition of required metadata; 

  

  * Assignment of responsibility to a person over quality assurance for each test series; 

  

  * Design of Experiments (DoE) for each test series; 

  

  * Design a data storage system with sufficient performance; 

  

  * Design of a purpose-built database structure for data organization. 

  

Measures for _quality assurance and control during data collection and entry_
:

  * Calibration of sensors, measuring devices and other relevant instruments to check the precision, bias and scale of measurements; 

  

  * Taking multiple measurements and observations in accordance with the established DoE; 

  

  * Setting up validation rules and input masks in data entry software; 

  

  * Unambiguous labelling of variable and record names; 

  

  * Implementation of double entry rule – ensuring that two persons, performing the tests, can independently enter the data; 

  

  * Use reference mechanisms (a relational database) to minimize the number of times the data need to be entered. 

  

Measures for _quality control during data checking_ :

  * Document any modifications to the dataset to avoid duplicate error checking; 

  

  * Check the dataset for missing or irregular data entries to ensure the data completeness; 

  

  * Perform statistical summaries with checking for outliers by using graphical methods as probability and regression plots, scatterplots et al.; 

  

  * Verifying random samples of the digital data against the original data;  Data peer review both by scientific and technical criteria. 

  

#  DATA SHARING

The EVE data to be shared are subjected to three research and innovation Work
Packages of the project and focused on the following content.

##  Tyre and Ground Vehicle Modelling

  * Tyre test results on smooth and rough terrains under various real-world operating conditions on surfaces with realistic friction properties. Selected sets of test results will be made available to the broader research community to stimulate further tyre model development and correlation; 

  

  * Tyre models for longitudinal, lateral and vertical forces on smooth and rough, as well as soft and hard terrains; 

  

  * Vehicle dynamics model incl. (i) a full vehicle, multi-body dynamics model of the test vehicle developed in MSC Adams and (ii) real-time versions of the model in DSPACE ASM software. 

  

##  Active Chassis Systems

  * The vehicle model in MATLAB/Simulink software for covering tasks of real-time simulation; 

  

  * Active chassis subsystems models and validation results. The vehicle subsystems are specified in accordance to the global project tasks; 

  

  * Driving cycles and manoeuvres specification from the point of view of overall vehicle energy efficiency and safety; 

  

  * Vehicle dynamics control strategies for improvement of vehicle safety and stability. The developed control strategies will be further integrated and used for the purposes of optimal vehicle dynamics control; 

  

  * The optimal control strategy considering both energy efficiency and vehicle stability incl. controller specification. 

  

##  Cooperative Test Technologies

  * Documentation to the test platform for integration of the brake, active suspension and tyre pressure control systems; 

  

  * Documentation to the test vehicle demonstrator; 

  

  * Results of the successive testing of vehicle models, controllers and integrated chassis control system on the integrated test platform developed; 

  

  * Results of vehicle tests to quantify the ride and handling of the test vehicle with different control strategies. 

  

#  ARCHIVING AND PRESERVATION

The EVE online database will provide wide access to shared electronic research
and technical material of the participating institutions and will follow in
general the concept of the Horizon 2020 pilot on Open Research Data. In
addition to this, the consortium has decided to include ZENODO, Figure 1, as
data repository for the sharing and dissemination of the research assets.
ZENODO targets high quality data in engineering sciences and uses the DOI
format to sort and preserve the data themselves. A detailed description of the
chosen data repository is given in the next section.

**_Figure 1 - Graphic interface of ZENODO web portal_ **

#  DATA REPOSITORY

The EVE consortium has defined that the project results and assets will be
made available on the project web portal for wide international audience in
order to share the acquired knowledge outside of the consortium. As more and
more funders and journals adopt data policies that require researchers to
deposit research data in a data repository, the question over where to store
this data and how to choose a repository becomes more and more important.
ZENODO enables researchers, scientists, EU projects and institutions to
display and share multidisciplinary research results. In particular, ZENODO
provides with: easy sharing of small research results in a wide variety of
formats including text, spreadsheets, audio, video, and images across all
fields of science; display of the research results and credits by making the
research results citable and by integrating them to funding agencies like the
European Commission; easy access and reuse of shared research results.

Here follows an example of data sharing through ZENODO in accordance with the
dissemination requirements of the project. As an example, the uploading
procedure of a publication from ResearchGate personal web portal will be
described.
through ZENODO repository_

The research data is here represented by a journal paper from Figure 2\. Once
the document is selected, it can be uploaded on the ZENODO personal web portal
by going to the UPLOAD section, Figure 3. Hence, it is possible to specify a
large amount of information for each uploaded data: here a brief list of the
most important information required for the fair data storage and
identification is reported.

_**Figure 3 - ZENODO interface for data uploading. Focus on the compulsory
details for the fair data preservation** _

Individual members can share any type of data linked to the project, such as
Articles and

Conference Papers. First of all, the type of data to upload can be specified
in the field “Type of File”. With reference to the example, the option
Publication – Journal Paper is selected. In addition to this, among the main
characteristics of ZENODO repository, there is the possibility to preserve the
data by means of the DOI codification. In the “Digital Object Identifier”
field it is either possible to assign a new DOI, automatically generated by
ZENODO, or to use the original code in order to allow the other users to
easily and unambiguously cite the uploaded file. Moreover, the latter choice
avoids the useless multiplication of the same data: in this view, the file is
generated once and then stored.

With reference to Figure 4, further important information is required, such
as: the title of the shared article or conference paper; the name of the
Authors linked to the document; a description of the uploaded data. Moreover,
to guarantee an easy consulting and research of the shared data, it is
possible to enrich the submitted documents with the keywords. Thereafter, in
the “Community” section, the name of the EVE community wherein the data is
aimed at being shared must be specified. At last, the Grant financing the
research activity can be also included in the form.
details for the fair data preservation_

In conclusion, the consortium has decided to include ZENODO as data repository
for the sharing and dissemination of the research assets in addition to the
EVE web portal. Above, just the most important information required for the
data sharing on ZENODO repository have been illustrated. Mainly four reasons
brought the consortium to this choice:

  1. ZENODO targets high quality data, such as publications and associated metadata and uses the DOI format to sort and preserve the data themselves; 

  

  2. the database restriction level can be set among open, closed and restricted; 

  

  3. it concerns the engineering sciences in general; 

  

  4. it has the European Commission Horizon 2020 among the participating institutions. 

  

  

Hence, ZENODO complies the requirements of the Horizon 2020 pilot on Open
Research Data providing wide access to shared electronic research and
technical material of the participating institutions.