#  Executive Summary

The **SERENA** project participates in the ORDP. As such, the current document
describes the initial version of its Data Management Plan as this was
developed through the first period M01-M06 of the project.

The deliverable outlines the handling of research data that will be generated
during and after the lifetime of **SERENA** . The possible ways of archiving
and management of the data through available web-based platforms will be
investigated. Furthermore, online databases for storing research data have
been examined and the most suitable was selected to be used both by the
consortium partners as well as from interested people/organizations from
outside the project.  
  
<table>  
<tr>  
<th>

**1**

</th>  
<th>

**Introduction**

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

Computer applications have multiple data sources defined depending on the
supported functionalities and their purpose. Source data constitute a valuable
source of information. Data sources can be a database, a dataset, a
spreadsheet or even hardcoded data.

Although raw data, often mentioned as source data, have the potential to
become information, meaning useful digital information for a specific
application and purpose, it requires selective extraction, organization,
analysis and formatting for presentation. Once processed data may reveal
valuable information and characteristics of their origin or even enable
certain predictive analytics forecasting, for example, future trends. Thus, it
becomes clear that the acquisition, preservation and proper management of data
may enable more efficient data-driven decision making approaches for
companies, forecasting, analysis of their current practices, and
identification of potential bottlenecks as well as the verification of
scientific and commercial published research results.

**SERENA** tackles with the acquisition of raw machine/sensor data and their
analysis towards enabling predictive analytics aiming towards forecasting
potential failures of the equipment. Such identification may result in
appropriate predictive maintenance operations to take place, while an early
failure identification may additionally result in a more effective scheduling
of the production operation with respect to a predictive maintenance plan,
thus, reducing the overall production cost.

During the lifetime of the **SERENA** project, various types of raw data will
be generated through the different pilot cases. These data will contain both
machine and sensor data. In addition, datasets will be generated through the
intermediate processing steps of the **SERENA** systems such as KPIs for
machine’s condition evaluation and/or training datasets for the machine
learning algorithms.

##  1.1 Purpose of the DMP

A DMP typically contains information on how data are created outlining the
steps for sharing and preserving them. In the context of the H2020, a DMP
details what kind of data will the project generate, whether and how they will
be exploited or made accessible for verification and reuse and how they will
be managed and preserved [1].

This particular document has been created in order to present and analyze the
first steps towards the creation of the **SERENA** project DMP. An
investigation of the data needed for the various developed sub-systems within
the project is ongoing and their formats and prerequisites are under
examination.

In addition, the deliverable focuses on the available web-based solutions for
archiving, accessing and preserving Project’s data made publicly available. At
this point, it should be stated that the data to be made available to the
public audience will be first examined for confidentiality issues and if
possible made anonymous.

##  1.2 Objectives and tasks of WP7

WP7 aims at the creation of impact through the dissemination of the project
results as widely as possible making them known to all relevant stakeholders,
maximizing at the same time the exploitation of the project’s results to the
benefit of the **SERENA** partners.

WP7 is appropriately structured into tasks that focus on achieving the above
objectives:

  * Task 7.1: is the task that focuses on the establishment of the project’s web portal intended for the communication with the public, in order to effectively disseminate the project’s results. 

  

  * Task 7.2: is the task that obtains the activities concerning the dissemination of projects results to scientific community and industry. 

  

  * Task 7.3: focuses on the exploitation of the project’s results with respect to the background and foreground IPR policies and the respective articles of the Grant Agreement. 

  

The consortium of the **SERENA** project acknowledges that impact may be
created through knowledge circulation and innovation. Making data publicly
available is recognized by the members of the consortium as well as by the
European Commission as an effective approach towards innovation in the public
and private sectors. As a result, an approach for the DMP of the **SERENA**
system that will be introduced and developed during the project, is presented
in the following sections. The confidentiality of the data will be examined
too, as well as the prerequisites for archiving, making them anonymous and
preserving them.

##  1.3 Background of the DMP

The DMP specifications are governed by the “Open access to research data”
article (article 29.2) of the AGA [2]. As such, the guidelines and rules are
defined on open access to scientific peer-reviewed publications and research
data that all beneficiaries have to follow in projects funded or co-funded
under Horizon 2020 programme.

In the context of research and innovation, OA includes providing online access
to scientific information free of charge and reusable [3]. Scientific
information can be:

  1. Research data, meaning data used in publications, curated data and/or raw machine/sensor data. 

  

  2. Peer-reviewed scientific articles which have been published in a journal. 

  

  

1.3.1 Open access to peer-reviewed journal Open access provided by journals is
called “gold” open access while open access delivered by repositories is
called “green” open access. Both terms are used by the OA community focused on
how OA is implemented. Gold stands for publications made available directly
from the publisher while Green means that a version is available somewhere
else, such as a repository. However, there are several dimensions in OA
including the following:  Rea der rights

  * Reuse rights 

  

  * Copyrights 

  

  * Author posting rights 

  

  * Machine readability 

  

  * Publishing costs 

  

  * Peer review 

  

In both cases, open access to publications and/or research data is a decision
of the grant beneficiaries and not an obligation. The main points towards
ensuring OA to research data and publications in the

context of the **SERENA** project is **Figure 1: SERENA OA approach for data
sets and publications** illustrated in Figure 1, which has been adapted from
[3].

1.3.2 Open access to research data

Apart from publishing to an open access journal, self-archiving to an
institutional repository such as INDIGO [4], or a repository supported by the
EC, such as ZENODO [5], or other like the re3data repository [6], could be an
option towards making something publicly available. In fact, making data
publicly available is more related to making science open, which may enable
the following benefits: 1. Effective scientific practices include a level
communicating the evidence and validating the results.

  2. Open data practices have enabled breakthroughs in certain areas of research such as crystallography, Earth observation, DNA sequencing, AI, especially when data could be reused. 

  

  3. As a result, open data may accelerate discovery through the reuse of data from the academic system and others. 

  

  
  
<table>  
<tr>  
<th>

**2**

</th>  
<th>

**Guiding principles**

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

This deliverable is a living document, which will be updated regularly during
the lifetime of the project. The intention of the DMP is to describe numerical
models and/or datasets collected or created within **SERENA** during the
runtime of the project following the guiding principles of Annex 1 as well as
of the FAIR original policies [7].

Due to the fact that the project started in October 2017, there is no dataset
generated or collected by the time of the compilation of this deliverable. The
datasets to be made publicly available will deliver information considering
the following:

  * **Dataset reference and name** : Identifier for the data set to be produced. In order to be able to identify and distinguish each data set, unique object identifiers will be assigned. 

  

  * **Dataset description** : Descriptions of the data that will be generated or collected, the description element includes its types (text, spreadsheets, software, models, images, movies, audio, etc.), source (human observation, laboratory, field instruments, experiments, simulations, compilations, etc.), volume (volume of data, number of files, etc.), data and file formats (non-proprietary formats, used within community). 

  

  * **Standards and metadata** : Reference to existing suitable standards of the discipline, such as Dublin Core. If these do not exist, an outline on how and what metadata will be created. Metadata helps to categorize, understand and interpret data and may provide details about experimental setup as well as facilitate identification and discovery of new data. Metadata also tunes the data that is suggested to users. 

  

  * **Data sharing** : Description of how data will be shared, including access procedures, embargo periods (if any), outlines of technical mechanisms for dissemination and necessary software and other tools for enabling re-use, and definition of whether access will be wide open or restricted to specific groups. Identification of the repository where data will be stored, if already existing and identified, indicating, in particular, the type of repository (institutional, standard repository for the discipline, etc.). In case the dataset cannot be shared, the reasons for this should be mentioned (e.g. 

  

ethical, rules of personal data, intellectual property, commercial, privacy-
related, security-related).

  * **Archiving and preservation** (including storage and backup): Description of the procedures that will be put in place for the long-term preservation of the data. An 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. 

  

The information listed above reflects the current concept and design of the
individual work packages. The information follows a specific template and will
be updated by the project-partners responsible for the different datasets to
be created. With respect to the FAIR data principles [8], an initial version
of a dataset template to be used for making data FAIR in an automatic approach
is included in Appendix A:

XML template, while a description of each field is provided in the following
section.  
  
<table>  
<tr>  
<th>

**3**

</th>  
<th>

**Data Management related to SERENA**

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

The **SERENA** consortium recognizing the importance of making research data
available and easily reusable is participating in the Open Research Data Pilot
in Horizon 2020. As such and with respect to section “2.2.5 Management of
Data” of the DoA, observational data consisting of sensor and machine
recordings have started to be collected, but are not available at the time of
compiling this document. As a result, the data format is constrained to the
raw data format of each source. After the collection of those datasets, from
their source, the conversion to the suitable data format will be defined along
with the appropriate sharing format. In order to facilitate the retrieval and
reuse of the related dataset appropriate metadata values will be defined and
integrated, after resolving any confidentiality issues that may be raised by
the data provider. Towards this direction anonymization approaches will be
considered. Datasets that will be decided to become publically available will
be following the dataset format that is presented in section 3.2 of this
document. Apart from sensor data, the consortium will evaluate during the
development stage of the several **SERENA** components making publicly
available through the channel described in the following section additional
experimental data.

##  3.1 DMP Platforms introduction and documentation

For the **SERENA** project, the Zenodo platform has been selected for the data
which will be decided by the members of the consortium to become publicly
available. All research outputs from the entire scientific field can be stored
in the particular platform, such as publications, posters, presentations,
images and videos/audio.

A first trial account for **SERENA** project purposes was created in Zenodo.
After the profile is registered and the account is activated the user can
easily upload and manipulate his data files. The profile constitutes an
example profile in order to serve the presentation of the platform
installation to the needs of the project. A space or community for the
**SERENA** project has been established, named **SERENA** Data under the
following link:  _https://zenodo.org/communities/serena/edit/_ .

One of the main aspects that the platform offers is the creation of the
aforementioned communities. Communities imply the dedicated storage space for
a defined entity. This entity could be from research project to any other
scientific procedure which demands data storage for archiving and reuse
purposes Figure 2.

**Figure 2: SERENA project community creation in ZENODO**

After the creation of the community, the creator or administrator may access
it and proceed to any of the following options:

  1. view the uploaded contents, 

  

  2. manage them, and 

  

  3. export the datasets 

  

  

Moreover, any user with access to the community link may either search and
download content or upload new datasets. In order to upload new datasets the
creation of a new account is required or use of an existing one from GitHub or
ORCID. In order to download pre-existing files, no registration is required.
Furthermore, it provides the user with the option of uploading to establish
the access rights of the files. Four types of access rights can be selected as
it is depicted in, depending on

the confidentiality of the data.

License type can be configured in

the relative tab

as well as **Figure 3: Log in screen, access rights and license options**
funding related information to be provided Figure 3\.

Two example files have been uploaded to the community of the **SERENA** Data,
for which the Creative Commons Attribution-Share – Alike 4.0 has been
selected. The type of the license can be reconfigured depending on the terms
of each suggested license and the confidentiality level of the data Figure 4.

**Figure 4: SERENA data community uploaded test files**

##  3.2 Dataset template description

As mentioned in section 2, an initial dataset template in the form of XML has
been created for storing data. The XML format suggested can automate in the
future the upload of data to ZENODO through a mechanism that will consume the
XML and take all the required info from the XML elements. Such a mechanism can
make the upload and manipulation of data a very efficient procedure and will
be investigated in the future. A short description of the main data field
elements included in the template is provided in the table below.

**Table 1: XML elements**

###  ELEMENT NAME PURPOSE  
  
<table>  
<tr>  
<th>

**SERENA_subject**

</th>  
<th>

The root name of each datasets referring to the **SERENA** community

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

**datasetID**

</td>  
<td>

A unique identifier of the dataset

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

**datasetDescription**

</td>  
<td>

A textual description of the dataset

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

**sharingOptions**

</td>  
<td>

It included the sharing options of the **SERENA** subject, embargo periods,
licenses, etc.

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

**origin**

</td>  
<td>

It defines the main source of the dataset, such as machine name

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

**volume**

</td>  
<td>

It includes the size of the dataset in MBs or GBs

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

**Date**

</td>  
<td>

The date element includes the initial upload and any modification date.
Furthermore, it contains a reference element which can be further linked to
any other element of the XML.

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

**contents**

</td>  
<td>

Under the content element, multiple elements may be included such as images,
videos, documents (doc, docx, docm, pdf, ppt, etc.) as well as raw data either
as plain text or in another format such as odt.

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

**standards**

</td>  
<td>

This field defines any incorporated mechanism for encoding the specific
dataset, along with the organization and the description of the standard.

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

**metadata**

</td>  
<td>

The metadata element contains additional information over the dataset
including the total number of downloads, the times that the dataset has been
parsed, the ranking of the **SERENA** subject as well as the last time it was
updated.

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

**4**

</th>  
<th>

**Conclusions**

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

In conclusion, the requirements imposed on **SERENA** with regards to granting
OA to research data have been discussed. The adopted online platform for
archiving and preserving research data under the guiding principles of Annex 1
has been described. Additionally, the first steps towards populating the newly
created **SERENA** data community has been made by means of two test files.
The responsible partner for the archiving of the data in the proposed online
platform will manage the in time update of the aforementioned tables in order
for the consortium to be kept updated on the project outcomes.

This DMP includes also an XML schema to upload in a formatted and structured
approach the datasets that are intended to become publicly available. Last but
not least, OA regarding publications have been discussed, however for the
publications, papers or deliverables, as well as for the data that are not
made anonymous or are confidential the project portal will be used.

At this point the **SERENA** consortium has initiated the process of
collecting data from the pilot cases. However this process also considering
the confidentiality policies and data sharing restrictions of each company
will require additional time. In the next stages of the project and under the
decision of the responsible companies, datasets consisting primarily of sensor
data may be uploaded and managed by the responsible partners according to the
guidelines described in this document.