#  Executive summary

This document discusses the methodologies and procedures that will be followed
for sharing the research data collected by the LAW-TRAIN partners during the
execution of the project. It will provide information regarding the type of
data that will be generated, the standards used, information about how this
data will be made accessible for verification and re-use and information about
how the data will be curated and preserved.

It is important to mention that the LAW-TRAIN project involves several law-
enforcement forces and that given the nature of the project, some of the
research data generated will be confidential and therefore not shared with the
public.

This deliverable enables adherence to the Guidelines on Data Management in
Horizon 2020 provided by the European Commission.

#  Introduction

The LAW-TRAIN project is a multi-national research collaboration funded by
European Commission. The focus of this project is to develop a simulation for
training law enforcement personnel in joint interrogations, which will be
accessed from various places and used in multiple languages. Since this
project has a specific target group, namely law enforcement personnel who need
training in joint interrogations, end-users have been integrated from the
beginning. These end-users have been made partners of the project, who will
provide insights on their training routine.

LAW-TRAIN will be developed within a period of three years. Hence, different
work packages have been created in the proposal. This paper will focus on a
deliverable from WP2 – User Requirements and Specifications/Structure and API.
The objective of this WP is to create a framework through user and technical
requirements, a technical structure, an ethical manual and a data management
plan for the entire project and all following work packages, deliverables and
tasks. Therefore the developed and established settings of WP2 have to be
considered and evaluated carefully.

##  Aim of this deliverable

This deliverable aims to detail all the information regarding to the recovery,
generation, treatment and publication of research data obtained by the LAW-
TRAIN partners through the project execution and its curation during and after
the project.

In combination with this deliverable, an online version (only accessible by
project partners) of the Data Management Plan (DMP) will be generated in the
online DMPONLINE portal developed by the Digital Curation Centre (DCC). The
Digital Curation Centre (DCC) is a world-leading centre of experts in digital
information curation with a focus on building capacity, capability and skills
for research data management across the UK's higher education research
community.

##  Document updates

This document will be considered a **“live” document** as it will be updated
constantly in order to reflect the inclusion of the new generated data sets.
The DMP will be at least updated by mid-term and final review of the project,
in order to fine-tune it to the data generated and the uses identified by the
consortium since not all data or potential uses are clear from the start.

##  Tasks in this deliverable

The DMP covers all the research material generated during the whole project
execution. Nevertheless, within the work plan of LAWTRAIN project a specific
task has been foreseen to conglomerate the efforts dedicated to curate and
share the generated research data. **Task 2.5 Preparation of Ethical
Guidelines and Data Management Plan** (lead by USECON and involving IDENER as
the partner responsible for DMP and the rest of the partners as contributors)
covers the following specific issues:

  * Ethical guidelines and procedures all consortium members need to adhere to during the entire research and development and testing of the LAW-TRAIN System. These ethical guidelines will focus on related consent and confidentiality procedures of the end-users of the LAW Train system as well as the protection of any data collected. These have been published in D2.3. 

  

  * Data Management Plan (DMP) describing the data management life cycle for all datasets that will be collected, processed or generated by the research project, will be prepared. This document will outline how research data will be handled during LAW-TRAIN and after its completion, describing what data will be collected, processed or generated and following what methodology and standards, whether and how this data will be shared and/or made open, and how it will be curated and preserved; IDENER will be responsible for the creation and maintenance of the DMP. 

  

##  Scope of this deliverable

Deliverable 2.4 – Data Management Plan includes the initial version of the DMP
for the LAW-TRAIN project. This document will be updated constantly as to
include the required updates regarding the information being collected.

The scope of this deliverable is twofold: on the one side it aims to establish
specific rules and methodologies that will be followed by all partners when
generating research data and, on the other side, it will provide specific
information about such generated research data, including naming and
references, data set descriptions, list of standards and metadata used and
data sharing policies.

##  Structure of the deliverable

**Section 1** provides an introduction of the project, the deliverable and the
tasks within the deliverable. It further provides the cooperating partners
detailed information concerning the structure of the deliverable. **Section
2** describes the Data Management Plan designed for the LAW-TRAIN project. It
begins by including some general information about DMP and providing some
guidelines. Then there is space to include datasheets for describing each
produced research datasets. **Section 3** provides some guidelines about how
to handle the research data during the project and also after it. **Section
4** includes information about how the archival and preservation of the
research data will be carried out. **Section 5** focuses on giving a summary
on section 1 to 4 by mentioning the most important issues. It aims to serves
as a quick sheet for project partners to follow the rules established for data
generation, treatment and curation. **Section 6** provides references to the
documents used for the generation of the current deliverable.

##  Project partners

As mentioned previously, LAW-TRAIN is a project with multi-national partners
funded and supported by the European Commission. In the three year course of
the project ten partners will participate and contribute to create the
training system simulation. Six of these ten partners are responsible for the
realization by contributing expert knowledge & methods while the remaining
four partners provide insights as LAWTRAIN’s end users.

The following parties participate as partners in LAW-TRAIN:  
  
<table>  
<tr>  
<th>

**List of Partners**

</th>  
<th>

</th>  
<th>

**Country**

</th>  
<th>

**Position**

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

**BIU**

</td>  
<td>

Bar-Ilan University

</td>  
<td>

Israel

</td>  
<td>

Partner

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

**KU**

</td>  
<td>

KU Leuven (University of Leuven)

</td>  
<td>

Belgium

</td>  
<td>

Partner

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

**INESC ID**

</td>  
<td>

Instituto de Engenharia de Sistemas e Computadores, Investigação e
Desenvolvimento em Lisboa

</td>  
<td>

Portugal

</td>  
<td>

Partner

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

**IDENER**

</td>  
<td>

Optimización orientada a la sostenibilidad S.L.

</td>  
<td>

Spain

</td>  
<td>

Partner

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

**USECON**

</td>  
<td>

USECON: the Usability Consultants

</td>  
<td>

Austria

</td>  
<td>

Partner

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

**COMPEDIA**

</td>  
<td>

Compedia

</td>  
<td>

Israel

</td>  
<td>

Partner

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

**MINTERIOR**

</td>  
<td>

Guardia Civil

</td>  
<td>

Spain

</td>  
<td>

Partner

(End-User)

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

**MINPUBSEC**

</td>  
<td>

Ministry of Public Security / Israel National Police

</td>  
<td>

Israel

</td>  
<td>

Partner

(End-User)

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

**SPFJ**

</td>  
<td>

Le Service Public Federal Justice

</td>  
<td>

Belgium

</td>  
<td>

Partner

(End-User)

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

**MJ-PJ**

</td>  
<td>

Ministério da Justiça - Polícia Judiciária

</td>  
<td>

Portugal

</td>  
<td>

Partner

(End-User)

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

_Table 1: LAW-TRAIN project's partners_

**2.7 Open Access:**

The LAW-TRAIN project has been funded under the Horizon 2020 framework’s topic
FCT-07-2014: Law enforcement capabilities topic 3: Pan European platform for
serious gaming and training. This topics is not part of the Open Data Pilot,
especially since many of its deliverables have been marked as Confidential by
the security review and by the Consortium. Nevertheless the programme
specifies the following condition:

Open access must be granted to all scientific publications resulting from
Horizon 2020 actions, and proposals must refer to measures envisaged. Where
relevant, proposals should also provide information on how the participants
will manage the research data generated and/or collected during the project,
such as details on what types of data the project will generate, whether and
how this data will be exploited or made accessible for verification and re-
use, and how it will be curated and preserved.

Open access (EC, Open Access pilot, 2013) can be defined as the practice of
providing on-line access to scientific information that is free of charge to
the end-user and that is re-usable. In the context of research and innovation,
'scientific information' can refer to (i) peer-reviewed scientific research
articles (published in scholarly journals) or (ii) research data (data
underlying publications, curated data and/or raw data).

  1. Open access to scientific publications refers to free of charge online access for any user. Legally binding definitions of “open access” and “access” in this context do not exist, but authoritative definitions of open access can be found in key political declarations on this subject. These definitions describe 'access' in the context of open access as including not only basic elements such as the right to read, download and print, but also the right to copy, distribute, search, link, crawl, and mine. 

  

  2. Open access to research data refers to the right to access and re-use digital research data under the terms and conditions set out in the Grant Agreement. Openly accessible research data can typically be accessed, mined, exploited, reproduced and disseminated free of charge for the user. 

  

  

There are two main routes towards open access to publications:

  1. Self-archiving (also referred to as 'green' open access) means that the published article or the final peer-reviewed manuscript is archived (deposited) by the author - or a representative - in an online repository before, alongside or after its publication. Repository software usually allows authors to delay access to the article (‘embargo period’). 

  

  2. Open access publishing (also referred to as 'gold' open access) means that an article is immediately provided in open access mode as published. In this model, the payment of publication costs is shifted away from readers paying via subscriptions. The business model most often encountered is based on one-off payments by authors. These costs (often referred to as Author Processing Charges, APCs) can usually be borne by the university or research institute to which the researcher is affiliated, or to the funding agency supporting the research. In other cases, the costs of open access publishing are covered by subsidies or other funding models. 

  

  

In the context of research funding, Open Access (OA) requirements in no way
imply an obligation to publish results. The decision on whether or not to
publish lies entirely with the funded organisations. Open access becomes an
issue only if publication is elected as a means of dissemination. Moreover, OA
does not interfere with the decision to exploit research results commercially,
e.g. through patenting. Indeed, the decision on whether to publish open access
must come after the more general decision on whether to publish directly or to
first seek protection. This is illustrated in the graphic representation of
open access to scientific publication and research data in the wider context
of dissemination and exploitation at the end of this section.

_Figure 1: Open Access description_

#  Data Management Plan

The following figure represents the life cycle that will be followed in the
LAW-TRAIN project for the management of the research data that will be
generated during the project.

_Figure 2: Data Management Plan life-cycle_

The project is currently in the Data Plan stage, this being the project
partners analysing what information will be generated and what would be the
conditions for sharing it. In the meantime, the public research repository
that IDENER will put at project disposition design is being carried out.

##  Global guidelines

In this section the global methodology to be used by project partners for the
research data will be sketched.

###  Data format

In the web  _http://5stardata.info_ ,  Tim Berners-Lee’s (the inventor of the
Web and Linked Data initiator) suggests a five star deployment scheme for open
data:  
  
<table>  
<tr>  
<th>

★

</th>  
<th>

make your stuff available on the Web (whatever format) under an open licence

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

★★

</td>  
<td>

make it available as structured data (e.g. Excel instead of a scan of a table)

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

★★★

</td>  
<td>

use non-proprietary formats (e.g. CSV instead of Excel)

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

★★★★

</td>  
<td>

use URIs to denote things, so that people can point at your stuff

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

★★★★★

</td>  
<td>

link your data to other data to provide context

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

In the LAW-TRAIN project, partners are encouraged to observe the above
provided rules and try (as much as possible and always considering first their
research needs) to provide their research data in a nonproprietary format and
including enough meta-data to allow the interpretation of the content and its
linking with other data sources.

###  Resource location

In addition, and in order to locate and identify more easily the generated
information, IDENER is currently analysing the different possibilities for
using a Digital Object Identifier for each of these research data. A digital
object identifier (DOI) is a unique alphanumeric string assigned by a
registration agency (the International DOI Foundation) to identify content and
provide a persistent link to its location on the Internet. The publisher
assigns a DOI when your article is published and made available
electronically.

###  Publication

The LAW-TRAIN project is not part of the Open Research Data Pilot of the
H2020. Nevertheless project partners are encouraged to follow the Open Access
method when publishing their data. In any case, partners should not publish
their results when the following conditions apply:

  * They will exploit or protect their research. 

  

  * The publication of the research data will be in violation of the security restrictions of the project. 

  

  * The publication of the research data will be in violation of the privacy restrictions of the project. 

  

  * If the achievement of the action’s main objective would be jeopardized by making those specific parts of the research data openly accessible. 

  

In the case the partner will not publish or share their research under one of
the above conditions, justification explaining this issue should be included.

###  Confidential deliverables

The following deliverables of the project are marked as confidential:

D2.1, D2.2, D3.2, D3.3, D4.2, D4.3, D4.4, D4.7, D5.1, D5.2, D6.1, D6.2 and
D7.2

###  Ethics

The information stored in the project repository and in general all the
research conducted in the LAWTRAIN project will comply with the Ethics
Guidelines & Procedures (Deliverable D2.3).

###  Archiving and preservation

All LAW-TRAIN partners are encouraged to store their contributions and to
provide access to it. In addition to this suggestion, IDENER will provide a
research repository as described in section 5.

###  Licensing

While practice varies from discipline to discipline, there is an increasing
trend towards the planned release of research data. The need for data
licensing arises directly from such releases, so the first question to ask is
why research data should be released at all.

A significant number of research funders now require that data produced in the
course of the research they fund should be made available for other
researchers to discover, examine and build upon. Opening up the data allows
for new knowledge to be discovered through comparative studies, data mining
and so on; it also allows greater scrutiny of how research conclusions have
been reached, potentially increasing research quality. Some journals are
taking a similar stance, requiring that authors deposit their supporting data
either with the journal itself or with a recognized data repository.

There are many additional reasons why releasing data can be in a researcher’s
interests. The discipline of working up data for eventual release helps in
ensuring that a full and clear record is preserved of how the conclusions were
reached from the data, protecting the researcher from potential challenges. A
culture of openness deters fraud, encourages learning from mistakes as well as
from successes, and breaks down barriers to interdisciplinary and ‘citizen
science’ research. The availability of the data, alongside associated tools
and protocols, increases the efficiency of research by reducing both data
collection costs and the possibility of duplication. It also has the potential
to increase the impact of the research, not only academically, but also
economically and socially.

In order to license their research, partners can opt for any license they
want: Prepared licenses, Bespoke licenses, Standard Licenses, Multiple
licensing, etc. For a more extended description of licensing options please go
to  _http://www.dcc.ac.uk/resources/how-guides/license-research-data_ where
you can find a much more detailed guide.

Within the LAW-TRAIN project we will recommend the use of Creative Commons
licenses.

##  Data sets template

The following template will be followed by each partner to describe the
research data that they will generate and to provide information about its
nature, the metadata and standards used and the sharing policy. Explanations
of each of the expected fields are provided here and should be replaced by the
specific content. If some field is not yet determined TBD (To be determined)
should be put instead. If some aspect is provisional [*] should be included at
the beginning of the field.

**Data set information**

Reference of the data set using the following nomenclature:

‘LT_’PartnerShortName’_’UniqueIndex’’

**Data set reference** Where PartnerShortName is the one present in Table 1.

UniqueIndex is an incremental number (starting at 1) that will be used by each
partner to numerate theirs data subsets

Names will be done using the following nomenclature:

‘LT_’PartnerShortName’_’Type’_’Title’

Type will be one of the following options, depending on

**Data set name** the content: ‘RD’ (Research Data), ‘PM’ (Publishable

Material (e.g. papers), ‘O’ (Others).

Title will be set by the researcher to indicate in a brief way (up to 20 words
separated by underscores (‘_’) instead of spaces).

**Data set brief description (up to 100** Up to 100 words describing the main
content of the **words)** research data as well as the objective of such
research

D.O.I. Provided by your organization (if available) or by

**D.O.I. (if available)** IDENER should an agreement with a D.O.I.
registration office be accomplished

Name of your organization. Please put the short name

**Researcher – Main organization**

first(e.g. BIU – Bar-Ilan University)

**Researchers involved (include name,**

Involved researches, being the first the main one.

**mail address and organization info)**

**Generation date** Date of data collection or the document generated, …
**Publication date** Date of document publication (if applicable)  
  
<table>  
<tr>  
<th>

**Te**

</th>  
<th>

**chnical description**

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

**Data set description**

</td>  
<td>

Description of the data generated or collected, its origin (in case it is
collected), nature and scale

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

**Possible applications**

</td>  
<td>

Description of whom this information could be useful and how it could be used
or integrated for reuse

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

**Usage in publication**

</td>  
<td>

Should the results of researching this data have been published, reference
(DOI, citation) to the resulting document

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

**Non previously existent data**

</td>  
<td>

Analysis report on existence of previous information that could be used in its
place. Should a new research subset of data be necessary, justification of why

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

**Data format**

</td>  
<td>

Format of the files (type of file) shared. Taking into account recommendations
of Tim Berners-Lee described in section 3.1.1 and use of open data formats
instead of commercial ones should be followed.

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

**Standards**

</td>  
<td>

CEN (European Committee for Standardisation)
_http://standards.cen.eu/index.html_ can be used to identify suitable
standards.

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

**Metadata**

</td>  
<td>

Metadata included in the research data. In a general way

CERIF - Common European Research Information Format should be used, in
addition to any specific metadata standards typical in the area of work.
Indications on adequate metadata, can be found at:
_http://www.dcc.ac.uk/resources/metadata-standards_

References to the funding under H2020 should be included in the metadata

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

**Documents naming convention**

</td>  
<td>

All files within a research data set should be included in a folder whose name
should match the data set reference. Inside the folder the names of the files
should provide clues about their content (as much as possible but without
interfering with a normal operation of the research activities).

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

</th>  
<th>

**Data Sharing**

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

**Data shared**

</td>  
<td>

Yes or no.

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

**Justification to not share**

</td>  
<td>

Should the answer to the previous question, justification of it. Reasons not
to publish it can be found in section 3.1.3.

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

**Sharing methodology**

</td>  
<td>

Sharing policies among the following options:

  * Green Open Access 

  

  * Gold Open Access 

  

  * Non-shared 

  

  * Publish in pay journal 

  

  * Other (Describe) 

  

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

**Embargo**

</td>  
<td>

Description of the embargo that will be held on the research data (i.e.
previous publication on pay magazine and later published openly) and the
period that this embargo will entail.

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

**Necessary equipment / software**

</td>  
<td>

Equipment and or software that would be required to:

  * re-create the research data (validation) 

  

  * Integrate the data in other research projects (reuse) 

  

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

**Licensing**

</td>  
<td>

Licensing (if any) for the data

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

**Archiving and preservation (including storage and backup)**

</td>  
<td>

Description of the procedures that will be put in place for long-term
preservation of the data. Indication of how long the data should be preserved,
what is its approximated end volume, what the associated costs are and how
these are planned to be covered.

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

##  Data set 1  
  
<table>  
<tr>  
<th>

</th>  
<th>

**Technical description**

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

**Data set**

**description**

</td>  
<td>

Existing closed case files that were tried by the Federal Prosecutor’s Office
in Belgium (confidential)

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

**Possible applications**

</td>  
<td>

No application

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

**Usage in**

**publication**

</td>  
<td>

[*] No publication

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

**Non previously**

**existent data**

</td>  
<td>

No previously existent available data that could replace it

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

**Data format**

</td>  
<td>

Confidential – the case files are in paper and need to be consulted at the
Federal

Prosecutor’s Office

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

**Standards**

</td>  
<td>

None

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

**Metadata**

</td>  
<td>

None

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

**Documents naming convention**

</td>  
<td>

Confidential – these files will not be made public to other consortium members

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

</th>  
<th>

**Data Sharing**

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

**Data shared**

</td>  
<td>

</td>  
<td>

No

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

**Justification not share**

</td>  
<td>

**to**

</td>  
<td>

Confidential case files, only accessible for KU Leuven consortium members

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

**Sharing methodology**

</td>  
<td>

</td>  
<td>

Non-shared

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

**Embargo**

</td>  
<td>

</td>  
<td>

No embargo

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

**Necessary equipment software**

</td>  
<td>

**/**

</td>  
<td>

No equipment or software

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

**Licensing**

</td>  
<td>

</td>  
<td>

No licensing

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

**Archiving**

</td>  
<td>

**and**

</td>  
<td>

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

**preservation (including storage and backup)**

</td>  
<td>

No preservation of the data set – only accessible for consultation at the
Federal

Prosecutor’s Office

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

##  Data set 2

**Data set information**

**Data set reference**

LT_KU_2

**Data set name**

LT_KU_PM_Publication_on_literature_research_from_WP3

**Data set brief description (up to 100**

**words)**

Depending on the possibilities (since the deliverables in WP3

are confidential), KU Leuven would like to publish an article

on the best practices in joint in

terrogations or on the newly

developed methodology for joint interrogations.

**D.O.I. (if available)**

TBD

**Researcher**

**–**

**Main organization**

KU

–

KU Leuven

**Researchers involved (include name,**

**mail address and organization info)**

Prof. dr. Geert Vervaeke

Dr.

Emma Jaspaert

Ma. Ricardo Nieuwkamp

**Generation date**

TBD

**Publication date**

TBD  
  
<table>  
<tr>  
<th>

</th>  
<th>

**Technical description**

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

**Data set description**

</td>  
<td>

TBD

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

**Possible applications**

</td>  
<td>

Publication useful for police practitioners and other actors involved in
transnational police or judicial cooperation in criminal matters

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

**Usage in publication**

</td>  
<td>

TBD

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

**Non previously existent data**

</td>  
<td>

TBD

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

**Data format**

</td>  
<td>

TBD

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

**Standards**

</td>  
<td>

TBD

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

**Metadata**

</td>  
<td>

TBD

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

**Documents naming convention**

</td>  
<td>

TBD

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

**Data Sharing**  
  
<table>  
<tr>  
<th>

**Data shared**

</th>  
<th>

Yes (but not shared yet at the moment)

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

**Justification to not share**

</td>  
<td>

/

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

**Sharing methodology**

</td>  
<td>

[*] Gold Open Access (If I am correct, LAW-TRAIN has budgeted for open access?

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

**Embargo**

</td>  
<td>

TBD

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

**Necessary equipment / software**

</td>  
<td>

No equipment /software

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

**Licensing**

</td>  
<td>

No licensing

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

**Archiving and preservation**

**(including storage and backup)**

</td>  
<td>

The article will be stored on a secure server of the KU Leuven (no costs) in
addition to the common project repository

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

**3.5 Other Data Sets**

Additional datasets will be updated in the subsequent internal version of the
DMP, before M12.

#  Guidelines for handling data

##  During the LAW-TRAIN project

The LAW-TRAIN project involves cooperation with several law-enforcement forces
and therefore, some of the research data generated should be considered
security sensible. Even not having being marked as completely confidential by
the EC, some of the deliverables (and therefore some of the associated
research data) will have restricted access due to security issues.

To guarantee the security of these documents, proper guidelines for access
restriction, encryption and other measures are provided in the Project Manual
published in deliverable D1.2

Moreover, some of the research conducted in the LAW-TRAIN project involves
dealing with personal information. Guidelines as to anonymize and protect such
information have been previously defined and have been published in
Deliverable 2.3 Ethical Guidelines and procedures.

During the project and as for the deliverables and other research data, a
private online repository has been set up in USECON facilities and have been
used since the beginning of the project. This private repository has been set
using OWNCLOUD technology paying special attention to encryption and security
issues.

##  After completion of the project

Each partner will be responsible for keeping the research data available up to
three years after the completion of the LAW-TRAIN project. During this period
they will have to keep applying the security measures provided during the
project.

In addition, the research data published in IDENER’s research repository will
be maintained for a minimum of three years after the completion of the project
although the company intends to keep this information stored for a longer
period so to maximize the dissemination and re-use possibilities of the
research results. These statements not go against any requirement regarding
the privacy of the subjects researched, and the elimination of the involved
personal data will be carried out as to follow the ethical guidelines.

#  Archiving and preservation

All the research data generated during the project will be centralized and
stored in a research repository provided by IDENER, which is currently under
development. This research repository will comply will the following policies:

  * Data will be stored in a secure way, avoiding unauthorized access or modification to it. 

  

  * Data will be backed up on a regular and frequent basis. Specifically, incremental backups will take place at least weekly and usually on a daily basis. 

  

  * Two backups will be generated. The first one will be stored in the IDENER online servers and the second one will be stored locally in IDENER main office. 

  

  * IDENER’s IT department will be responsible for the backup of data stored on such systems. 

  

  * On submission of a paper, the raw data must be submitted to IDENER’s IT department for archiving and the data set description should be included following the template of section 3. It may include: 

    * Information about the paper (title, journal, authors, etc.) 

  

    * The raw data (if access can be granted) o An index to the data files if required o A description of the structure of the data files 

  

    * Explanation of how to reproduce the experiments that lead to such results, if applicable 

  

  

  * IDENER will securely (encrypted) store archived data for the required period of time and will make it available as defined in this document and complying with the sharing policy of each data subset. 

  

  * The data will be stored on Linux systems that will be kept up to date with security patches and updates. These systems will require a passwords to access them. Redundancy systems such as hard disks on RAID configuration will be used to prevent against the failure of a single system. 

  

  * The backups systems will comply with the same security and redundancy issues as the main repository. 

  

  * The total currently reserved space for project research data is fixed at 3TB. Upon necessity of expanding this value, the systems will be upgraded to satisfy such requirement. 

  

  * Steps will be followed as to publish IDENER’s research repository in the re2data.org index 

  

The information stored in the project repository will comply with the Ethics
Guidelines & Procedures (Deliverable D2.3 of the project). In addition any
personal information held by the project will be:

  * Processed fairly and lawfully 

  

  * Processed for one or more specified and lawful purposes, and not further processed in any way that is incompatible with the original purpose 

  

  * Adequate, relevant and not excessive 

  

  * Accurate and, when necessary, kept up to date 

  

  * Kept for no longer than is necessary for the purpose for which it is being used 

  

  * Processed in line with the rights of individuals 

  

  * Kept secure with appropriate technical and organizational measures taken to protect the information. 

  

  * Not transferred outside the European Economic Area unless there is adequate protection for the personal information being transferred. 

  

**5.1 Associated infrastructure and costs:**

In order to comply with the abovementioned policies IDENER is designing an
architecture including new services and equipment to complement their current
infrastructure.

Three different data servers will be used. A and B will be located in OVH’s
dedicated servers (using two different European data centres) and C will be
located in IDENER’s main office.

Estimated costs as for the implementation of this infrastructure as well as
the execution of the DMP is foreseen at around 6.000 € within the duration of
the project. It includes rental services of the abovementioned data servers
and the acquisition of equipment and software for IDENER offices. Arrangements
to try to include other costs as registration fees for D.O.I.s are being
scheduled.

#  Summary

This document represents the Data Management Plan that will be followed during
the LAW-TRAIN project to manage the generated research data and results. In
addition to this deliverable an online version of the DMP will be generated
using the DMPONLINE portal developed by the Digital Curation Centre (DCC).
This document will be updated constantly as to reflect the identification of
new data sets and the changes of any of the already included ones.

The LAW-TRAIN project is not part of the Horizon 2020 Open Data Pilot
initiative. Nevertheless partners are encouraged to follow some of the
guidelines of such initiative. Specifically, partners should try to publish
their results (e.g. peer-reviewed papers) and the associated research data
following the Open Access practice.

Tables to be filled by each partner are provided to describe the different
research data sets to be generated during the project. These tables include
all the key information to be defined from naming and referencing to licensing
issues.

Details about the policies that will be applied by IDENER to set up a research
data repository that will be used by project partners to store and publish
their research information is provided. Moreover an estimation of the
associated costs is provided.