Although the FReSMe project’s consortium strives to make all the reasonable
datasets available, it is explicitly not the intention to publish any raw
datasets or any datasets that can be considered as confidential or as a trade
secret, in agreement with the H2020 rules  3  .

  3. “Guidelines to the Rules on Open Access to Scientific Publications and Open Access to Research Data in Horizon 2020”. Version 

  

  

3.2. 21 March 2017 (p.4):

“In the context of research funding, open access requirements do not imply an
obligation to publish results. The decision to publish is entirely up to the
grant beneficiaries. Open access becomes an issue _only if_ publication is
chosen as a means of dissemination. Moreover, open access does not affect the
decision to exploit research results commercially, e.g. through patenting. The
decision on whether to publish through open access must come after the more
general decision on whether to publish directly or to first seek protection.”

#  2 FReSMe project and data management

The aim of FReSMe is to demonstrate the process to generate Methanol fuel from
blast furnace gases (BFG) supplemented with renewable hydrogen produced from
water electrolysis. The methanol fuel will be demonstrated in a ship. It is
expected that the technology developed generates several commercial
exploitation lines. On one hand, it is applicable for the reduction of GHG
emissions of the industry. On the other hand, it will become an alternative
source of fuel in different sectors, from transport to power generation. In
addition, it could also contribute to the storage of energy surplus coming
from renewable sources.

##  2.1 Decision tree for dissemination or preservation of the data

Since it is expected that the results of the project could be industrially
exploited and commercialised, most of the data generated is considered
confidential, so the main part cannot be made publicly available.
Nevertheless, it is expected that scientific publications will be generated
(at least 2 in relevant journals are planned in the DoA). These papers will be
open to the society. This scientific publications will be curated and the data
associated will be accessible for verification purposes. The decision to
disseminate or preserve the data is taken following the decision tree
established in figure 1:

**Figure 1.** Decision tree for data generated in FReSMe project.

During the first step of the decision making procedure, the data is identified
as confidential or public, following the criteria stated in the DoA of the
FReSMe GA (see section 2.2).

The confidential data generated will be preserved by the partner that produced
them. Meanwhile, the public data and those associated to scientific
publications of the partners related to the project results will be saved,
where appropriate, in an open access repository.

##  2.2 Dataset generated by the project

As it was stated above, most of the datasets of the project will be linked to
a confidential information. In this DMP, a summary of the sources from which
the data will be generated and the types of numerical dataset expected is
provided. Below, a list is provided with 5 sources of data and 5 types of
datasets expected from the implementation of the FReSMe project. This takes
into account all the data generated within the project, not only the public
data.

The dataset would be generated from the following sources (“source of data”):

  1. Lab-scale test of the technologies and materials involved 

  

  2. Simulation of the processes and of the performance of the materials 

  

  3. Test campaigns of the pilot plant unit 

  

  4. Techno-economic analysis of the production process 

  

  5. Life cycle analysis of the process 

  

  

From these sources, 5 types of dataset have been identified (“Type of
dataset”):

  1. Process parameters dataset 

  

  2. Materials parameters dataset 

  

  3. Modelling parameters dataset 

  

  4. Environmental impact dataset 

  

  5. Techno economic dataset 

  

  

As a way to establish a first approach to the data generated, the list of
deliverables identified in the DoA in FReSMe project GA is used. Table 1 shows
the deliverables of each work package and additional information indicated for
them in the GA. The last columns provide the characteristics of each
deliverable regarding the DMP.

The most relevant information included in table 1 regarding the DMP is the
following:

  * Column “Dissemination level”: reflects the dissemination level - public (PU) or Confidential (CO)- that was established in the DoA in FreSMe GA. It will be the first criteria to apply in the procedure established to identify which data is considered as public and which one as confidential (first step in the decision tree of figure 1, above). 

  

  * Column “Numerical dataset linked” (yes/no): to point out if the results that encompass the deliverables are (or not) based in numerical datasets. 

  

  * Column “Source of data”: In case that the previous columns were “yes”, in this column is stated the source of the data (in some cases, the data can come from different sources), in accordance with the list above: 1, 2, 3, 4, 5. Additional details are provided in section 3\. 

  

  * Column “Type of dataset”: In case there are numerical datasets, this column is to state the type of dataset linked in accordance with the list above: a, b, c, d, e (in some cases, there can be different types of data associated to one deliverable). Additional details are provided in section 3. 

  

  
<table>  
<tr>  
<th>

</th>  
<th>

**description**

</th>  
<th>

**Lead Partner**

</th>  
<th>

**Type of Dissemin deliver ation able level**

</th>  
<th>

**Due month**

</th>  
<th>

**Numerical**

**Dataset linked**

</th>  
<th>

**Source of data**

</th>  
<th>

**Type of dataset**

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

D1.1

</td>  
<td>

Potential harm to the environment risk analysis

</td>  
<td>

i-deals

</td>  
<td>

R

</td>  
<td>

CO

</td>  
<td>

M3

</td>  
<td>

no

</td>  
<td>

N/A

</td>  
<td>

N/A

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

D1.2

</td>  
<td>

Health and safety procedures

</td>  
<td>

i-deals

</td>  
<td>

R

</td>  
<td>

CO

</td>  
<td>

M2

</td>  
<td>

no

</td>  
<td>

N/A

</td>  
<td>

N/A

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

D1.3

</td>  
<td>

Ethical standards H2020

</td>  
<td>

i-deals

</td>  
<td>

R

</td>  
<td>

CO

</td>  
<td>

M2

</td>  
<td>

no

</td>  
<td>

N/A

</td>  
<td>

N/A

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

D2.1

</td>  
<td>

Common Design Practice

</td>  
<td>

TNO

</td>  
<td>

R

</td>  
<td>

CO

</td>  
<td>

M2

</td>  
<td>

no

</td>  
<td>

N/A

</td>  
<td>

N/A

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

D2.2

</td>  
<td>

Basis of Design

</td>  
<td>

MEFOS

</td>  
<td>

R

</td>  
<td>

CO

</td>  
<td>

M3

</td>  
<td>

no

</td>  
<td>

N/A

</td>  
<td>

N/A

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

D2.3

</td>  
<td>

Basic Engineering Package

</td>  
<td>

TNO

</td>  
<td>

R

</td>  
<td>

CO

</td>  
<td>

M15

</td>  
<td>

no

</td>  
<td>

N/A

</td>  
<td>

N/A

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

D2.4

D2.5

D2.6

</td>  
<td>

Detailed Engineering

Package

Pilot Plant Construction and

Connection to battery limits

Site-Acceptance Test

</td>  
<td>

MEFOS

MEFOS

MEFOS

</td>  
<td>

R

DEM

R

</td>  
<td>

CO

</td>  
<td>

M22

M33

M36

</td>  
<td>

no no no

</td>  
<td>

N/A

N/A

N/A

</td>  
<td>

N/A

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

PU

</td>  
<td>

N/A

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

CO

</td>  
<td>

N/A

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

D2.7

</td>  
<td>

Lessons Learned Maintenance Log

</td>  
<td>

MEFOS

</td>  
<td>

R

</td>  
<td>

CO

</td>  
<td>

M48

</td>  
<td>

no

</td>  
<td>

N/A

</td>  
<td>

N/A

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

D2.8

</td>  
<td>

decommissioning

</td>  
<td>

MEFOS

</td>  
<td>

DEM

</td>  
<td>

CO

</td>  
<td>

M48

</td>  
<td>

no

</td>  
<td>

N/A

</td>  
<td>

N/A

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

D3.1

</td>  
<td>

5 appropriate and scalable catalyst formulations

</td>  
<td>

NIC

</td>  
<td>

DEM

</td>  
<td>

CO

</td>  
<td>

M24

</td>  
<td>

yes

</td>  
<td>

1

</td>  
<td>

b

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

D3.2

D3.3

D3.4

</td>  
<td>

SEWGS system report to support LCA

N  2  dilution experimentally assessed and modelled

Process conditions modelled and optimized

</td>  
<td>

TNO

NIC

NIC

</td>  
<td>

R

R

R

</td>  
<td>

CO

</td>  
<td>

M12

M36

M36

</td>  
<td>

yes

yes

yes

</td>  
<td>

1

1

1

</td>  
<td>

a, b,

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

PU

</td>  
<td>

a

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

CO

</td>  
<td>

c

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

D3.5

</td>  
<td>

Sorbent and cycle development and testing for methanol

</td>  
<td>

TNO

</td>  
<td>

R

</td>  
<td>

CO

</td>  
<td>

M36

</td>  
<td>

yes

</td>  
<td>

1, 2

</td>  
<td>

a,c

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

D3.6

</td>  
<td>

Long term behaviour assessments

</td>  
<td>

NIC

</td>  
<td>

R

</td>  
<td>

CO

</td>  
<td>

M36

</td>  
<td>

yes

</td>  
<td>

1

</td>  
<td>

a

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

D3.7

</td>  
<td>

Long term process operation optimized

</td>  
<td>

NIC

</td>  
<td>

R

</td>  
<td>

CO

</td>  
<td>

M36

</td>  
<td>

yes

</td>  
<td>

1

</td>  
<td>

a

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

D4.1

D4.2

</th>  
<th>

Delivery of scale-up methanol catalyst and sorbent

Report on the flexible Test

Campaign Results

</th>  
<th>

CRI

MEFOS

</th>  
<th>

DEM

R

</th>  
<th>

PU

</th>  
<th>

M36

M46

</th>  
<th>

no

yes

</th>  
<th>

N/A

3

</th>  
<th>

N/A

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

CO

</th>  
<th>

a

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

D4.3

</td>  
<td>

Combined Report on

Process and Data analysis

</td>  
<td>

NIC

</td>  
<td>

R

</td>  
<td>

CO

</td>  
<td>

M46

</td>  
<td>

yes

</td>  
<td>

3

</td>  
<td>

a

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

D4.4

</td>  
<td>

Synthesized Report on

Evaluation of the test runs

</td>  
<td>

CRI

</td>  
<td>

R

</td>  
<td>

CO

</td>  
<td>

M48

</td>  
<td>

yes

</td>  
<td>

3

</td>  
<td>

a

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

D5.1

D5.2

D5.3

</td>  
<td>

Definition of base and reference cases

Electrolysis in the Iron & Steel Industry

Enriched air for optimisation of Blast Furnace to methanol concept

</td>  
<td>

MEFOS

MEFOS

MEFOS

</td>  
<td>

R

R

R

</td>  
<td>

CO

</td>  
<td>

M14

M22

M24

</td>  
<td>

no

no

yes

</td>  
<td>

N/A

N/A

2

</td>  
<td>

N/A

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

PU

</td>  
<td>

N/A

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

CO

</td>  
<td>

c

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

D5.4

</td>  
<td>

Alternative sources of CO2, H2 and Heat Sources

</td>  
<td>

Tata Steel

</td>  
<td>

R

</td>  
<td>

CO

</td>  
<td>

M34

</td>  
<td>

yes

</td>  
<td>

2

</td>  
<td>

c

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

D5.5

</td>  
<td>

Full scale design and preliminary costing

</td>  
<td>

CRI

</td>  
<td>

R

</td>  
<td>

CO

</td>  
<td>

M48

</td>  
<td>

yes

</td>  
<td>

4

</td>  
<td>

e

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

D5.6

</td>  
<td>

Overall process optimisation for flexibility and future developments

</td>  
<td>

MEFOS

</td>  
<td>

R

</td>  
<td>

CO

</td>  
<td>

M48

</td>  
<td>

yes

</td>  
<td>

4

</td>  
<td>

e

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

D6.1

D6.2

D6.3

</td>  
<td>

Report on techno-economic assessment of methanol synthesis based on residual
steel gasses

Preliminary Life Cycle Inventory (LCI) report on proposed methanol synthesis

Report on Life Cycle Analysis (LCA)

</td>  
<td>

POLIMI

POLIMI

POLIMI

</td>  
<td>

R

R

R

</td>  
<td>

CO

</td>  
<td>

M46

M28

M40

</td>  
<td>

yes

yes

yes

</td>  
<td>

4

1, 2, 3

5

</td>  
<td>

a, c, e

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

PU

</td>  
<td>

a, b, c

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

CO

</td>  
<td>

d

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

D6.4

</td>  
<td>

Report on market analysis

</td>  
<td>

CRI

</td>  
<td>

R

</td>  
<td>

CO

</td>  
<td>

M40

</td>  
<td>

no

</td>  
<td>

N/A

</td>  
<td>

N/A

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

D7.1

</td>  
<td>

Project management plan

</td>  
<td>

i-deals

</td>  
<td>

R

</td>  
<td>

CO

</td>  
<td>

M3

</td>  
<td>

no

</td>  
<td>

N/A

</td>  
<td>

N/A

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

D7.2

</td>  
<td>

Annual coordination report 1

</td>  
<td>

i-deals

</td>  
<td>

R

</td>  
<td>

CO

</td>  
<td>

M12

</td>  
<td>

no

</td>  
<td>

N/A

</td>  
<td>

N/A

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

D7.3

</td>  
<td>

1  st  Project management plan revision

</td>  
<td>

i-deals

</td>  
<td>

R

</td>  
<td>

CO

</td>  
<td>

M14

</td>  
<td>

no

</td>  
<td>

N/A

</td>  
<td>

N/A

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

D7.4

</td>  
<td>

Annual coordination report 2

</td>  
<td>

i-deals

</td>  
<td>

R

</td>  
<td>

CO

</td>  
<td>

M24

</td>  
<td>

no

</td>  
<td>

N/A

</td>  
<td>

N/A

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

D7.5

</td>  
<td>

2  nd  Project management plan revision

</td>  
<td>

i-deals

</td>  
<td>

R

</td>  
<td>

CO

</td>  
<td>

M30

</td>  
<td>

no

</td>  
<td>

N/A

</td>  
<td>

N/A

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

D7.6

</td>  
<td>

Annual coordination report 3

</td>  
<td>

i-deals

</td>  
<td>

R

</td>  
<td>

CO

</td>  
<td>

M36

</td>  
<td>

no

</td>  
<td>

N/A

</td>  
<td>

N/A

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

D7.7

</td>  
<td>

Annual coordination report 4

</td>  
<td>

i-deals

</td>  
<td>

R

</td>  
<td>

CO

</td>  
<td>

M48

</td>  
<td>

no

</td>  
<td>

N/A

</td>  
<td>

N/A

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

D7.8

</td>  
<td>

Business plan

</td>  
<td>

i-deals

</td>  
<td>

R

</td>  
<td>

CO

</td>  
<td>

M12

</td>  
<td>

no

</td>  
<td>

N/A

</td>  
<td>

N/A

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

D7.9

D7.10

</td>  
<td>

Dissemination and

Exploitation Plan

ORDP - Data Management

Plan

</td>  
<td>

i-deals i-deals

</td>  
<td>

R

ORDP

</td>  
<td>

CO

</td>  
<td>

M12

M6

</td>  
<td>

no no

</td>  
<td>

N/A

N/A

</td>  
<td>

N/A

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

PU

</td>  
<td>

N/A

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

**Table 1.** List of the deliverables and dataset linked.

##  2.3 Responsibilities

The procedures to curate and preserve the datasets established in the DMP are
mandatory for the data associated to an open access result, either public
result or scientific publication. However, the partners are encouraged to
follow it for all the results generated.

Open access datasets have to be created, managed, and stored in accordance
with this DMP. The project coordinator will make the procedures available to
deposit the open access data in an open access repository (please refer to
section 4). The validation and registration of datasets, with the associated
metadata, is the responsibility of the partner that generates the data,
following the procedures provided by the coordinator. Backing up data to be
shared through open access repositories is the responsibility of the partner
generating the data.

Confidential datasets must be curated and preserved by the partner that
generates them.

All partners must consult the concerned partners before publishing, in an open
domain, data associated to a result that would be feasible for a commercial
exploitation.

##  2.4 Audience interested in the results of the FReSMe project

The particular objective of the project is to demonstrate the process to
produce Methanol fuel from the BFG in the steel industry in a relevant
environment. This objective has two main implicit benefits: reducing the GHG
emissions of the steel industry, and in this way its environmental impact, and
producing an alternative fuel, with lower emissions, that reduces the European
dependence on foreign fossil fuels.

In agreement with this main objective, the following groups can be identified
as interested audiences on the FReSMe project’s results:

  1. Scientific Community. More specifically, those in the area of chemistry, new fuels and GHG emission reduction technologies or industrial processes. 

  

  2. Related industries and SME’s. On one hand, those that could apply the technology to reduce their GHG emissions; on the other hand, those that could use the methanol as fuel or as chemical platform. Therefore, those enterprises that would be interested in the results of the project could come from economic sectors such as the following: 

     * Steel and Iron producers 

  

     * Fuel producers and distributors 

  

     * Transport sector: maritime and terrestrial 

  

     * Engineering 

  

  

  3. Venture Capitalists that can contribute to a further development of the technology by funding commercial scale projects. 

  

  4. Public entities. The results of the project can be used to define policies to reduce the carbon footprint of the industry and of the transport sector, as well as to define a legal framework to increase the competiveness of European industry. The results will also be of high value to define public support for further improvement of the technology in order to achieve a commercial stage technology. 

  

  5. Public in general interested in new ways to reduce GHG emissions and in the technologies related with Carbon Capture Sequestration and Utilization (CCU/CCS). 

  

  

#  3 Datasets description

In this section the metadata that shall be included in the dataset files and
the description of the 5 different numerical dataset types identified in the
FReSMe project is stated. Metadata will be included as a header of a numerical
data file.

##  3.1 Metadata

The data encompassed in the project will cover different areas of knowledge.
The metadata associated to the dataset will specify, on one hand, the
information about the generation of the dataset (project, organization, date,
dataset type, scientific keywords) and on the other hand, the list of
parameters (and its units) included in the file. Metadata will help make the
data accessible and reusable, in accordance with the open access principles of
the H2020 programme.

According to this, the following information will be stated as a header of a
data file:

  * Project Acronym: FReSMe 

  

  * Author Institution: Acronym of the partner that generates the data 

  

  * Date 

  

  * Dataset type: a / b / c / d / e. 

  

  * FReSMe Keywords (at least 1 keyword with a maximum of 3). Suggested keywords: Sorbent, Catalyst, Process, Test campaigns, Material, etc. This is an open field and will be determined by the partners during the project implementation _._

  

  * In a report, Scientific community Keywords: _Free_ (those that the partners usually use in their area of expertise that is significant to refer to the dataset) 

  

  * Parameter_A (unit) - Parameter_B (unit) - Parameter_C (unit) - ….. 

  

##  3.2 Description of dataset types

Below, the different numeric dataset types generated in the project are
described. This description will be updated along the project implementation
according to the data generated. The format described shall be applied to the
numerical dataset files related with open access results of the project. It is
recommended that the same rules and formats are applied, for the numerical
datasets associated to confidential data generated within the project.

###  a. Process parameters dataset

Development of the FReSMe technology encompasses the determination of the
parameters and boundary conditions of the processes involved, like materials
production, CO  2  Capture, H  2  recovery, H  2  production and Methanol
synthesis. Data included in Process parameter datasets could include the
following parameters: temperature, pressure, volumetric flow rate, yield,
efficiency, and tag name.

File format:

  * Text file – CSV. 

  

  * Header (metadata): FReSMe, Institution Acronym, date… parameter_A (unit), parameter_B (unit), parameter_C (unit)… 

  

  * Numerical data 

  

Applicable Standards N/A

###  b. Materials parameters dataset

FReSMe project results includes the formulation and characterisation of the
materials involved in the process, like the sorbent, catalyst and products.
The parameters that determine the characteristics of these materials will be
included in the Material parameter datasets. Data included in this dataset
comprise parameters such as activity, selectivity and stability.

File format:

  * Text file – CSV. 

  

  * Header (metadata): FReSMe, Institution Acronym, date… parameter_A (unit), Parameter_B (unit), Parameter_C (unit)… 

  

  * Numerical data 

  

Applicable Standards N/A

###  c. Modelling parameters dataset

The process involved in the technology of the project will be modelled in
order to understand and foresee the influence of different parameters,
conditions, materials, and compositions of blast furnace gases in the
performance of the process.

In addition to the data of the materials involved in the process modelled, the
data included in this dataset covers aspects like process conditions,
materials conditions, and parameters of adjustments to the model.

File format:

  * Text file – CSV. 

  

  * Header (metadata): FReSMe, Institution Acronym, date… parameter_A (unit), Parameter_B (unit), Parameter_C (unit)… 

  

  * Numerical data 

  

Applicable Standards N/A

###  d. Environmental impact dataset

As an important aspect to be addressed by the project, the environmental
impact of the process to produce Methanol fuel will be analysed and
quantified. For this analysis, data available from the related sectors as well
as those coming from the activities developed within the project will be used:
process implementation, modelling and simulation. Data included in this
dataset covers parameters like process efficiency, environmental footprint of
the materials, and percentage of emissions reduced.

File format:

  * Text file – CSV. 

  

  * Header (metadata): FReSMe, Institution Acronym, date… parameter_A (unit), Parameter_B (unit), Parameter_C (unit)… 

  

  * Numerical data 

  

Applicable Standards N/A

###  e. Techno economic dataset

In accordance with the H2020 final objectives, the aim of the project is to go
further in the development of a commercially viable technology to produce
Methanol fuel from the residual gases of steel industry. With this final
objective, a techno-economic analysis will be addressed within the project
implementation. For this analysis, data such as process efficiency, cost of
materials, and market price of the products will be used. These parameters
will be saved in the Techno-economic parameters dataset.

File format:

  * Text file – CSV. 

  

  * Header (metadata): FReSMe, Institution Acronym, date… parameter_A (unit), Parameter_B (unit), Parameter_C (unit)…. 

  

  * Numerical data 

  

Applicable Standards N/A

#  4 FReSMe open access data repository

Scientific communications and public reports of the project will be made
accessible to the public. These materials and the data associated with them
will be curated in an open access data repository.

As it was established in the GA, the scheme followed for this open access to
the data will be **“Gold” Open Access:** Authors make a one-off payment to the
publisher so that the scientific publication is immediately published in open
access mode.

The open access data results and scientific publications of the FReSMe project
will be curated and made available through an open access repository. As first
option, ZENODO repository is proposed to the partners.

**Figure 1 - H2020 Open Access Mandate**

#  5 Conclusions

The data management plan of the FReSMe project is designed to guarantee the
open access rules established in H2020 programme. The DMP describes the
general procedures to enssure that the public data generated by the project is
FAIR (findable, accessible, interoperable and reusable). Despite most of the
results of the project being confidential, it is expected that at least two
scientific publications will be “open access”, in addition to the public
deliverables, as stated in Table 1.

This is a living document that will be updated every 6 months, during the
project execution according to the results generated, scientific publications
delivered by the partners and actual implementation of the project.

#  6 Glossary

**DMP:** Data Management Plan.

**“Gold” Open Access:** Authors make a one-off payment to the publisher so
that the scientific publication is immediately published in open access mode.

**“Green” Open Access:** Due to the contractual conditions of the publisher,
the scientific publication can undergo an embargo period up to six months
since publication date before the author can deposit the published article or
the final peer-reviewed manuscript in open access mode.

**Curate** : elect, organize, and look after the items in a collection or
exhibition.

**Tag name:** in the data set generated by the processes, tag name identify
the device that generates the signal/data. **BFG:** Blast Furnace Gases

**GHG:** Green House Gases

**GA:** Grant Agreement

**DoA:** Definition of Action

**N/A:** Not Applicable

**R:** Report, document

**DEM:** DEMonstrator, pilot, prototype, plan designs

**PU** : PUblic report or data

**CO:** COnfidential report or data

“This project has received funding from the _European Union’s Horizon 2020
research and innovation programme_ under grant agreement No 727504”.