#  Introduction

##  Abstract

This deliverable presents the LeMO data management plan. The deliverable
outlines how the research data collected or generated will be handled during
and after the LeMO project, describes which standards and methodology for data
collection and generation will be followed, and whether and how data will be
shared. This document follows the template provided by the European Commission
in the Participant Portal  1  . The Data Management Plan will be a live
document throughout the project. This initial version will evolve during the
project according to the progress of project activities.

##  Purpose of the document

Data Management Plan is a document describing how research data from a project
are to be managed, from project start to finish. Over the course of its three
years, LeMO will produce many results to further deployment.

The Dissemination Plan confers the means of promoting those results to the
research community. The main elements of that plan are open access to
scientific publications of LeMO action. To increase the adoption of LeMO’s
results it is useful to support their reliability. One way to achieve this is
to enable the validation of the results by other researchers. This is possible
only by making available any data that accompany the technical results.

LeMO is participating in the Horizon 2020 Pilot on Open Research Data as a
formal way of making its research data available. This report complements
LeMO’s Dissemination Plan by putting forward a plan for managing the research
data. More precisely, it describes what data could be shared, any associated
metadata, how the data will be made available, and how they will be preserved.

##  Target audience

The target audience for this deliverable is:

  * Partners and Advisory & Reference Group in the LeMO project 

  

  * European Commission 

  

  * EU Parliament 

  

  * Horizon 2020 projects and related transport projects (cfr. clustering activities)  Organisations and experts involved in the LeMO case studies. 

  

  * Transport organisations both public and private 

  

#  Data Management in Horizon 2020

According to the European Commission (EC) all project proposals submitted to
"Research and Innovation actions", "Innovation actions" and “Coordination
support actions” have to include a section on research data management which
is evaluated under the criterion 'Impact'. Projects participating in the pilot
action on open access to research data have to develop a data management plan
(DMP) to specify what data will be open.  2  The DMP is **defined as** :

_“Data Management Plans (DMPs) are a key element of good data management. A
DMP describes the data management life cycle for the data to be collected,
processed and/or generated by a Horizon 2020 project. The use of a Data
Management Plan is required for projects participating in the Open Research
Data Pilot. Other projects are invited to submit a Data Management Plan if
relevant for their planned research.”_

The **purpose of a DMP** is to provide an analysis of the main elements of the
data management policy that will be used by the applicants with regard to all
the datasets that will be generated by the project.

###  Table 1 Clarification of terms  
  
<table>  
<tr>  
<th>

**Research data**

</th>  
<th>

Research data is the evidence that underpins all research conclusions (except
those which are purely theoretical) and includes data that have been
collected, observed, generated, created or obtained from commercial,
government or other sources, for subsequent analysis and synthesis to produce
original research results. These results are then used to produce research
papers and submitted for publication.

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

**Open research data**

</td>  
<td>

Openly accessible research data can typically be accessed, mined, exploited,
reproduced and disseminated, free of charge for the user.

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

**Secondary data**

</td>  
<td>

Secondary data are data that already exist, regardless of the research to be
conducted.

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

**Open access**

</td>  
<td>

Open access is understood as the principle that research data should be
accessible to relevant users, on equal terms, and at the lowest possible cost.
Access should be easy, user-friendly and, if possible, Internet-based.

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

**Metadata**

</td>  
<td>

</td>  
<td>

Metadata is data used to describe other data. It summarizes basic information
about data, which can make finding and working with instances of data easier.

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

**Research repositories**

</td>  
<td>

**data**

</td>  
<td>

Research data repositories are online archives for research data. They can be
subject based/thematic, institutional or centralised.

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

Considering privacy and data protection issues scientific research data should
be easily discoverable, accessible, assessable and intelligible, useable
beyond the original purpose for which it was collected and interoperable to
specific quality standards.

Project piloting in the Open Research Data activity, have to consider the
following aspects  3  : Regarding the digital research data generated in the
action (‘data’), the beneficiaries must deposit in a research data repository
and take measures to make it possible for third parties to access, mine,
exploit, reproduce and disseminate — free of charge for any user — the
following:

  1. the data, including associated metadata, needed to validate the results presented in scientific publications as soon as possible; 

  

  2. other data, including associated metadata, as specified and within the deadlines laid down in the data management plan. 

  

  

Projects must take measures to enable for third parties to access, mine,
exploit, reproduce and disseminate research data, thereby attach Creative
Commons License (CC-BY or CC0 tool) to the data deposited. More information on
Creative Commons Licenses can be found on the respective Web site
creativecommons.org  4  .

#  Use of Data in the Research Process

To enable the reuse of research data, the data must be processed after they
are generated. The value chain for digital research data is divided into four
main steps:

Secondary

data

Data

collection

Processing &

analysis

Storage &

publishing

Long

\-

term

management

Access to data

& metadata

The first step is the collection or creation of data, where the data are kept
in a workspace. It is best practice to employ accepted documentation standards
now at this stage, as it will simplify subsequent efforts relating to long-
term storage and publication.

In the second step, the data are quality assured. This is a process for
determining whether the raw data are to be preserved. Analysis of the quality-
assured data is also carried out during this phase.

The third step is preparing the data for long-term archiving and publication.
This involves discipline-specific documentation and coding of data (metadata)
describing i.e. who is responsible for the data, what the data contain, what
has been done with the data, who can use them for which purpose. These
metadata will make it possible for other researchers to find and reuse the
data. Relevant information about the data will be indexed in search
engines/catalogues when the data are transferred to a data repository. As the
data are stored in a data repository, the data set is assigned an identifier
which follows the data set throughout its lifetime. The data are now
accessible to other researchers.

When the data are stored in a repository they are preserved for the future.
This usually entails a storage period of minimum five years or more. Moreover,
data deposited in long-term storage must be altered to new technologies and
formats to ensure that they remain findable, available, interoperable and
reusable in the future.

#  FAIR Data

The international FAIR Principles have been formulated as a set of guidelines
for the reuse of research data. The acronym FAIR stands for findable,
accessible, interoperable and reusable.  5  Research data must be of quality
that makes them accessible, findable and reusable.

##  Making data findable, including provisions for metadata

Data will be stored at the coordinator's (Western Norway Research Institute)
_Dropbox_ repository and will be kept for 5 years after the end of the
project. Where requested, data will be kept for 2 more years.

A naming convention will include a concise description of contents, the host
institution collecting the data and the month of publication.

Version numbering will only be an issue if a participant requests withdrawal
of their data in which case a version number will be added to the filename.

No specific standards or metadata have been identified for the time being for
the proposed datasets.

The real names of participants will NOT be distributed.

Data will be shared only in relation to publications (deliverables and
papers). As such, the publication will serve as the main piece of metadata for
the shared data. When this is not seen as being adequate for the comprehension
of the raw data, a report will be shared along with the data explaining their
meaning and methods of acquisition.

##  Making data openly accessible

Where possible data will be made available subject to Ethics and participant
agreement. However, the personally-identifiable nature of the data collected
within LeMO means that in most instances it would be difficult to release
collected data. Where data is made available we will do so using the Western
Norway Research Institute’s Dropbox.

Prior to release, a requesting party will need to contact the Project
Coordinator describing their intended use of a dataset. The Project
Coordinator will send a terms and conditions document for them to sign and
return. Upon return, the dataset will be released. Documentation will be
included with the release of the data.

##  Increase data re-use through clarifying licenses

Due to the sensitive nature of the data they will only be available on
application and their use will be restricted to the research use of the
licensee and colleagues on a need-to-know basis. This non-commercial licence
is renewable after 2 years, data may not be copied or distributed and must be
referenced if used in publications. These arrangements will be formalised in a
User Access Management licence which describes in detail the permitted use of
the data.

##  Interoperability

The concept interoperable demands that both data and metadata must be machine-
readable and that a consistent terminology is used.

#  Other Issues

##  Allocation of resources

Data will be stored at the Western Norway Research Institute's Dropbox
repository and will be kept for 5 years after the end of the project. Where
requested, data will be kept for 2 more years.

##  Data security

Data is managed and supported by a team of big data researchers at the Western
Norway Research Institute and subject to the institute’s data security
measures and backup policies.

Transfer of data is via a Zip process of distribution.

Encryption of sensitive data using shared-key methods.

Password distributed separately.

##  Ethical aspects

All our work is subject to ethical approval (locally, via an Ethics Committee
Chair and the EC REA). Prior to data collection related to case studies
participants will agree to the terms and conditions outlined in a Participant
Information and Consent Form. An ethical approach will be adopted and
maintained throughout the case studies process. The responsible partners will
assure that the EU standards regarding ethics and Data Management are
fulfilled. Each partner will proceed with the survey according to the
provisions of the national legislation that are adjusted according to the
respective EU Directives for Data Management and ethics.

##  Datasets

To be added when relevant.