##  1\. EXECUTIVE SUMMARY

###  1.1. Description of the deliverable content and purpose

This deliverable reports the first version of the Data Management plan for the
project MEMERE. The deliverable is based on a document prepared by the
federation of the 3 technical universities of the Netherlands. The document
has been shared with all partners and each partner has described the way the
research data will be managed. To keep the data Management clear, the document
reports the information, partner by partner.

**1.2. Brief description of the state of the art and the innovation brought**
n/a

**1.3. Deviation from objectives** n/a **1.4. If relevant: corrective
actions** n/a **1.5. If relevant: Intellectual property rights** n/a

##  2\. Partner TUE  
  
<table>  
<tr>  
<th>

Name of

student/researcher(s)

</th>  
<th>

Dr. Fausto Gallucci, Dr. Vincenzo Spallina, Mr. Aitor Cruellas, Dr. Martin van
Sint Annaland

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

Name of group/project

</td>  
<td>

Eindhoven University of Technology, Chemical

Process Intensification

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

Description of your research

</td>  
<td>

Development of novel multifunctional reactors integrating reaction and
separation. Development and use of detailed models and novel non-invasive
monitoring techniques _._

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

Funding body(ies)

</td>  
<td>

H2020

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

Grant number

</td>  
<td>

**679933**

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

Partner organisations

</td>  
<td>

MEMERE consortium

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

Project duration

</td>  
<td>

Start: **10-01-2015** End: **09-30-2019**

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

Date written

</td>  
<td>

**04-01-2016**

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

Date last update

</td>  
<td>

**04-01-2016**

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

Version

</td>  
<td>

V0.1. A new version of the DMP will be created whenever important changes to
the project occur due to inclusion of new data sets, changes in consortium
policies or external factors.

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

Name of researcher(s) with

roles/responsibilities for data management

</td>  
<td>

_See above_

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

###  2.1 Data Collection

  * Data to be created/collected includes: 

    * Process parameter for membranes and membrane reactors. 

  

    * Characterization of the membranes at TUE: measurements 

  

    * Modelling data, both detailed models and Aspen Model 

  

    * Catalyst characterization 

  

    * High temperature fluidization with membranes, PIV data 

  

  

  * Sources per type of data are described below: 

  

  
<table>  
<tr>  
<th>

Type of data

</th>  
<th>

Possible source of data

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

Process parameter

</td>  
<td>

Experimental data.

Data will be generated along the project life.

Literature data will be also considered.

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

Characterization of the membranes

</td>  
<td>

Experimental data

Data will be generated along the project life.

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

Modelling

</td>  
<td>

In house codes for fluidized bed membrane reactors and aspen models will be
used.

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

Catalyst characterization

</td>  
<td>

Experimental data

Data will be generated along the project life

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

High temperature

fluidization with

membranes

</td>  
<td>

Experimental data including images

Data will be generated along the project life

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

Data will be collected either by means of data collection templates (mostly
Excel or Word files and TIF images), with version number explicitly stated in
the filename as well as in the file itself.

###  2.2 Data Storage and Back-up

Data are stored in different locations. Firstly on the computers of the
researcher and lab computers. The data from experimental facilities are also
generally saved on the PLC of the setup. SPI has adopted a CLOUD application
and each student saves the data on the cloud, thus stored on several computes
and accessible by staff members of SPI. Images are also stored on external HD
(generally 4 TB each).

TUE is also discussing the possibility to adopt electronic lab notebook, in
this case also this will be used for MEMERE.

###  2.3. Data Documentation

In the MEMERE project no specific data format will be used unless specifically
required in a given situation (to be decided along the project).

As far as naming convention, the project naming convention will be used if
there is one.

Data will be storage at least 5 years after the formal end of the project:
five years after the payment of the balance (see the Grant Agreement).

###  2.4. Data Access

Copyright or Intellectual Property Rights are applicable to main type of data
generated by TUE. The data store at TUE is fully secure as the system has been
design for this.

Data access is provided in the Project Folder by the Project Manager (name by
name).

###  2.5. Data Sharing and Reuse

Once any copyright or Intellectual Property Rights are protected part of the
data could be shared outside the consortium. Approval of the consortium
(according to the Grant Agreement / Consortium Agreement) will be required for
any publications outside the consortium

Publication will be carried out in different journals and websites. Open
Access following the Green or Golden Route will be used.

As policy of TUE, all data published should be made available through the
repository of TUE.

When possible, raw data will be published along the main articles as
supplementary material. All data generated by TUE (after IP protection) will
be also made available on MEMERE website.

###  2.6. Data Preservation and Archiving

The consortium policy for data preservation and archiving shall be followed
(at least 5 years after the formal end of the project: five years after the
payment of the balance, see the Grant Agreement). In the absence of such a
project-specific policy, the data shall be archived and stored like the data
from any other TUE project. All data related to PhD thesis should be stored by
TUE for 5-10 year after the PhD has been granted.

##  3\. Partner TECNALIA  
  
<table>  
<tr>  
<th>

Name of

student/researcher(s)

</th>  
<th>

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

Name of group/project

</td>  
<td>

TECNALIA / MEMERE (WP3 Membrane development)

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

Description of your research

</td>  
<td>

_Briefly summarise the type of your research to help others understand the
purposes for which the data are being collected or created._

Development of oxygen supported membranes and membrane characterization
(Leader of WP on membrane development, Technical Manager, membrane developer)

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

Funding body(ies)

</td>  
<td>

H2020

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

Grant number

</td>  
<td>

**679933**

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

Partner organisations

</td>  
<td>

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

Project duration

</td>  
<td>

Start: **10-01-2015** End: **09-30-2019**

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

Date written

</td>  
<td>

**30-03-2016**

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

Date last update

</td>  
<td>

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

Version

</td>  
<td>

V0.1. A new version of the DMP will be created whenever important changes to
the project occur due to inclusion of new data sets, changes in consortium
policies or external factors.

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

Name of researcher(s) with

roles/responsibilities for data management

</td>  
<td>

Alfredo Pacheco Tanaka

Ekain Fernández

José Luis Viviente

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

###  3.1. Data Collection

  * Data to be created/collected includes: 

    * Process parameter for the development of oxygen membranes at TECNALIA. 

  

    * Characterization of the membranes at TECNALIA: measurements 

  

    * State-of-art on oxygen membranes 

  

  

  * Sources per type of data are described below: 

  

  
<table>  
<tr>  
<th>

Type of data

</th>  
<th>

Possible source of data

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

Process parameter for the development of oxygen membranes

</td>  
<td>

Experimental data.

Data will be generated along the project life.

Initially, it will be collected mostly from experience from past projects and
FP7 running projects.

Literature data will be also considered.

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

Characterization of the membranes

</td>  
<td>

Observational data

Data will be generated along the project life.

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

State-of-art on oxygen membranes

</td>  
<td>

From the literature including patents. It will be updated along the project.

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

Data will be collected either by means of data collection templates (mostly
Excel or Word files), with version number explicitly stated in the filename as
well as in the file itself.

###  3.2. Data Storage and Back-up

Both the collected and produced data are stored initially on TECNALIA staff
and/or individual testing computers (lab testing notebook). In addition, each
project at TECNALIA has a folder in the central server where all the data and
documents generated and related to the project are stored. Accession to this
folder is allowed to the staff working in this project (accession provided by
the Project Manager case by case). This sever is backed up every day, thereby
limiting the loss of data to its minimum.

###  3.3. Data Documentation

Data documentation is inherent to the activities at TECNALIA. TECNALIA holds
several accreditations and certificates such as the Certification of the
Quality Management System as per UNE-EN-ISO 9001:2008 for the Management of
Projects of Research, Technological Innovation and Development, Tests and
Assays, and Client Technological Assessment as well as the ISO 140001:2004
(Environmental Management System).

In the MEMERE project no specific data format will be used unless specifically
required in a given situation (to be decided along the project).

As far as naming convention, the project naming convention will be used if
there is one. If not, TECNALIA’ naming convention will be applied.

Data will be storage at least 5 years after the formal end of the project:
five years after the payment of the balance (see the Grant Agreement).

###  3.4. Data Access

How will you manage access and security?

Copyright or Intellectual Property Rights are applicable to main type of data
generated by TECNALIA (Process parameter for the development of oxygen
membranes and Characterization of the membranes: measurements). The data store
at TECNALIA is fully secure as the system has been design for this.

Process parameters for manufacturing the oxygen membranes will be only
accessible by TECNALIA team. Reader access to data coming from the
characterization of membranes may however be provided to specific project
partners upon request.

Data access is provided in the Project Folder by the Project Manager (name by
name).

###  3.5. Data Sharing and Reuse

Once any copyright or Intellectual Property Rights are protected part of the
data on membrane characterisation could be shared outside the consortium.
Approval of the consortium (according to the Grant Agreement / Consortium
Agreement) will be required for any publications outside the consortium

Deep details on process manufacturing will not be shared in any case to avoid
the loss of any intellectual property rights or copyright.

Publication will be mainly carried out in different journals and websites.
Open Access following the Green or Golden Route will be considered.

TECNALIA has recently developed its own institutional repository: TECNALIA
Publications  ( _http://dsp.tecnalia.com/_ )  . All the Scientific Publication
produced in MEMERE in which TECNALIA participates as author will be deposited,
regardless whether it is also deposited in some other repository(s), in this
repository for scientific publications.

TECNALIA Publications has been developed following RECOLECTA directions and
facilities in order to fulfil international interoperability standards and
protocols and gain long-term sustainability. RECOLECTA (Open Science
Harvester) is a platform that gathers all the Spanish scientific repositories
in one place and provides services to repository managers, researchers and
decision-makers  ( _http://recolecta.fecyt.es/_ )  . This platform is the
result of the collaboration between the Spanish Foundation for Science and
Technology (FECYT) and the Network of Spanish University Libraries (REBIUN)
run by the Conference of Vice-Chancellors of Spanish Universities (CRUE), with
the aims of creating a nationwide infrastructure of Open Access scientific
repositories.

TECNALIA Publications is indexed to Google, and harvested by Recolecta (Fecyt)
and OpenAire  ( _https://www.openaire.eu/_ )  , the open access infrastructure
by the EC.

###  3.6. Data Preservation and Archiving

The consortium policy for data preservation and archiving shall be followed
(at least 5 years after the formal end of the project: five years after the
payment of the balance, see the Grant Agreement). In the absence of such a
project-specific policy, the data shall be archived and stored like the data
from any other TECNALIA project.

##  4\. Partner VITO  
  
<table>  
<tr>  
<th>

Name of

student/researcher(s)

</th>  
<th>

Vesna Middelkoop

Bart Michielsen

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

</td>  
<td>

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

Name of group/project

</td>  
<td>

_Group_ : VITO-Sustainable Materials Management

_Project_ :“MEthane activation via integrated

MEmbrane Reactors” - MEMERE

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

Description of your research

</td>  
<td>

Development and characterisation of catalytic structures and membranes.
Characterisation will include acquiring, storing and processing a large volume
of data through

spectroscopic and X-ray measurements (ranging from 5 MB per run for ex situ
measurements to terabytes of data by operando/in situ

measurements)

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

Funding body(ies)

</td>  
<td>

H2020

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

Grant number

</td>  
<td>

**679933**

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

Partner organisations

</td>  
<td>

Eindhoven University of Technology, Tecnalia, Berlin University of Technology,
Marion Technology, Hygear Technology and Services B.V.

Quantis sarl, Finden Ltd, Johnson Matthey PLC

RAUSCHERT HEINERSDORF - PRESSIG GMBH

Ciaotech s.r.l. (100% PNO Group B.V.)

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

Project duration

</td>  
<td>

Start: **10-01-2015** End: **09-30-2019**

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

Date written

</td>  
<td>

**06-01-2016**

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

Date last update

</td>  
<td>

**11-01-2016**

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

Version

</td>  
<td>

V0.1. A new version of the DMP will be created whenever important changes to
the project occur due to inclusion of new data sets, changes in consortium
policies or external factors.

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

Name of researcher(s) with

roles/responsibilities for data management

</td>  
<td>

_See above_

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

</td>  
<td>

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

The partner VITO will make available all data produced in relation to MEMERE
on their repository and on the MEMERE Website.

##  5\. Partner Berlin University of Technology

The partner Berlin University of Technology will make available all data
produced in relation to MEMERE on their repository and on the MEMERE Website.

##  6\. Partner Marion Technologies

The partner Marion Technologies will make available all data produced in
relation to MEMERE on their repository and on the MEMERE Website.

**7\. Partner Hygear Technology and Services B.V.**  
  
<table>  
<tr>  
<th>

Name of

student/researcher(s)

</th>  
<th>

Leonardo Roses

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

Name of group/project

</td>  
<td>

HyGear Technology & Services B.V.

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

Description of your research

</td>  
<td>

_Pilot scale design and construction. Oxygen generator_

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

Funding body(ies)

</td>  
<td>

H2020

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

Grant number

</td>  
<td>

**679933**

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

Partner organisations

</td>  
<td>

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

Project duration

</td>  
<td>

Start: **10-01-2015** End: **09-30-2019**

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

Date written

</td>  
<td>

**06/06/2016**

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

Date last update

</td>  
<td>

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

Version

</td>  
<td>

V0.1. A new version of the DMP will be created whenever important changes to
the project occur due to inclusion of new data sets, changes in consortium
policies or external factors.

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

Name of researcher(s) with

roles/responsibilities for data management

</td>  
<td>

_Leonardo Roses_

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

###  7.1. Data Collection

Test data. I/O to PLC (flows, temperatures, pressures, levels,
concentrations). Gas analysis. Generally in summary form such as excel graphs,
powerpoint presentations and tables/plots in deliverables.

###  7.2. Data Storage and Back-up

Data stored on company server. Storage and back-up managed at corporate level
and implemented by IT department.

Data will be stored at least 5 years after the formal end of the project: five
years after the payment of the balance (see the Grant Agreement).

**7.3. Data Documentation**

Periodic (interim) reports (deliverables D1.3-D1.7) and RTD deliverables in
WP3-WP9.

###  7.4. Data Access

Internal access limited by control of password protected network access with
restricted access. IPR managed by CTO.

###  7.5. Data Sharing and Reuse

Data access restricted outside of consortium by agreed publication process
within MEMERE partner consortium agreement. Approval for publication to be
authorized by project manager.

**7.6. Data Preservation and Archiving**

Long term data archiving of electronic data managed centrally IT department.

##  8\. Partner Quantis sarl  
  
<table>  
<tr>  
<th>

Name of

student/researcher(s)

</th>  
<th>

Angela Adams, Andrea Del Duce and Arnaud

Dauriat

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

Name of group/project

</td>  
<td>

Quantis / MEMERE (WP8)

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

Description of your research

</td>  
<td>

In the frame of WP8, Quantis will be responsible for the environmental life
cycle assessment (LCA) and life cycle costing (LCC). The objectives of the LCA
and LCC are to i) evaluate the environmental and cost performance of the
investigated novel OCM technology, and ii) guide the design and development of
the novel OCM technology towards more sustainable solutions.

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

Funding body(ies)

</td>  
<td>

H2020

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

Grant number

</td>  
<td>

**679933**

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

Partner organisations

</td>  
<td>

WP8 partners: Quantis, Johnson Matthey, HyGear, PNO

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

Project duration

</td>  
<td>

Start: **10-01-2015** End: **09-30-2019**

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

Date written

</td>  
<td>

**10-01-2016**

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

Date last update

</td>  
<td>

**06-06-2016**

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

Version

</td>  
<td>

V0.1. A new version of the DMP will be created whenever important changes to
the project occur due to inclusion of new data sets, changes in consortium
policies or external factors.

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

Name of researcher(s) with

roles/responsibilities for data management

</td>  
<td>

Angela Adams, Quantis

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

**8.1. Data Collection**

_Data to be collected_ includes:

##   Ethylene manufacturing

  * Characteristics of the investigated production facility (incl. annual feed capacity, annual production capacity, location, etc.) 

  

  * Yield (kg ethylene per Nm  3  natural gas) 

  

  * Input of raw materials (e.g. natural gas, compressed air, steam), chemicals, consumables, etc. 

  

  * Output of main product (ethylene) and co-products (e.g. syngas, ethane, heat) o Direct process emissions 

  

  * Electricity and fuel/net thermal energy use o Water use 

  

  * Generation of solid wastes and liquid effluents 

  

  * **Infrastructure data** o Characteristics of the reactor, membranes, catalysts o Reactor data, incl. materials and mass 

    * Membrane data, incl. design area, type of membrane, composition, number of tubes, lifetime, etc. o Catalyst data, incl. catalyst amount and composition, filler amount and composition, lifetime, etc. 

  

  

  * **Ethylene application** o Definition of the application 

    * Characterisation of the distribution stage 

  

    * Characterisation of use stage o Characterisation of the end-of-life stage 

  

  

  * **Cost data for LCC** o Market prices of all exchanges (input to/output from the system) 

  

  * **Emission factors (EFs) for LCA** o EFs of all exchanges (input to/output from the system) 

  

Sources per type of data are described in the table below:  
  
<table>  
<tr>  
<th>

**Type of data**

</th>  
<th>

**Possible sources of data**

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

Ethylene manufacturing

</td>  
<td>

Data to be collected mostly from process modelling partner TU/e, based on
strong experience from past and running FP7 projects, in the form of e.g.
ASPEN export data sheets including complete mass and energy balance

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

Infrastructure data

</td>  
<td>

Data to be collected from membrane/catalyst project partners, building upon
the experience from the DEMCAMER project (data collection template based on
existing DEMCAMER template)

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

Ethylene application

</td>  
<td>

Literature data, life cycle inventory databases, expert judgment from
technical partners and endusers, experience from former related projects (e.g.

DEMCAMER)

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

Cost data for LCC

</td>  
<td>

Market prices to be obtained from specialised literature or cost databases,
from partners

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

Emission factors (EFs) for environmental LCA

</td>  
<td>

Emission factors to be obtained from available LCI databases (standard
processes), or developed by Quantis when not available in LCI database or not
specific enough (custom processes)

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

Data will be collected either by means of data collection templates (mostly
Excel or Word files), with version number explicitly stated in the filename as
well as in the file itself. The data from the templates will then be
implemented in the LCA/LCC models in our LCA software Quantis SUITE 2.0,
thereby preventing any risk of losing the data.

Pre-existing data will be used as much as possible, e.g. from DEMCAMER.

_Data to be produced_ includes:

  * LCA/LCC model in professional LCA software (accessible only by Quantis although reader access to the results may be provided to specific project partners upon request) 

  

  * LCA/LCC results in the form of graphs and tables (Excel file, PowerPoint for reporting) 

  

###  8.2. Data Storage and Back-up

Both the collected and produced data are stored on Quantis staff computers.
All Quantis computers are backed up on a weekly basis. In addition, most
projects at Quantis are stored on Quantis’s Google Drive (which is an
additional backup). The data in our LCA software Quantis SUITE 2.0 are backed
up every day, thereby limiting the loss of data to its minimum.

###  8.3. Data Documentation

Data documentation is inherent to the activities in LCA. All the data in the
LCA/LCC models are fully documented and related to the data collection
templates. This is for other colleagues to be able to determine where the data
are coming from and/or how the data were obtained/calculated.

LCI/LCA data are generally based on the EcoSpold data format. The latter may
be useful for sharing data across LCA software or platforms, but it is not so
relevant in the context of the present project. In the MEMERE project, no
specific LCI/LCA data format will be used unless specifically required in a
given specific situation (to be decided throughout the project).

As for the naming convention, the project naming convention will be used if
there is one. If not, Quantis’s naming convention will be applied.

###  8.4. Data Access

Copyright or Intellectual Property Rights are not applicable to the data
generated by Quantis. Access to project data within Quantis will be limited to
the project team. The data stored in Quantis SUITE 2.0 are fully secure,
following the security policy of our professional LCA software.

As stated previously, the LCA/LCC model in Quantis SUITE 2.0 shall be
accessible only by Quantis team. Reader access to the project in Quantis SUITE
2.0 may however be provided to specific project partners upon request.

###  8.5. Data Sharing and Reuse

Whether the results of the LCA/LCC can be shared or disclosed outside the
project shall be discussed and agreed upon at the consortium level. Unless a
specific decision has been made, Quantis will not share any of the LCA/LCC
results outside of the consortium.

###  8.6. Data Preservation and Archiving

The consortium policy for data preservation and archiving shall be followed.
In the absence of such a project-specific policy, the data and LCA models
shall be archived and stored like the data from any other Quantis project
(i.e. on Quantis SUITE 2.0 server and on Quantis’s Google Drive).

##  9\. Partner Finden ltd  
  
<table>  
<tr>  
<th>

Name of

student/researcher(s)

</th>  
<th>

Simon Jacques, Andrew Beale, Dorota Matras

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

Name of group/project

</td>  
<td>

Finden / MEMERE (WP2 & WP4)

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

Description of your research

</td>  
<td>

In the frame of WP2 and WP4 Finden will be responsible for the static, in situ
and operando characterisation of catalyst materials and catalytic

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

</td>  
<td>

membrane reactors predominantly by X-ray diffraction methods.

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

Funding body(ies)

</td>  
<td>

H2020

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

Grant number

</td>  
<td>

**679933**

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

Partner organisations

</td>  
<td>

WP2 partners: TUE, VITO, TUB, MARION, JM

WP4 partners: TUE, TUB, TECHNALIA, VITO, HYG

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

Project duration

</td>  
<td>

Start: **10-01-2015** End: **09-30-2019**

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

Date written

</td>  
<td>

**05-02-2016**

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

Date last update

</td>  
<td>

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

Version

</td>  
<td>

V0.1. A new version of the DMP will be created whenever important changes to
the project occur due to inclusion of new data sets, changes in consortium
policies or external factors.

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

Name of researcher(s) with

roles/responsibilities for data management

</td>  
<td>

Simon Jacques

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

###  9.1. Data Collection

_Data (and sizes) to be collected includes:_

 **Standard laboratory XRD (typically 100 Kb per set)** o Static 1D powder
patterns of powdered catalysts o Static 1D powder patterns of powdered
membrane

o In situ 1D powder pattern series of powdered catalysts under imposed
conditions o In situ 1D powder pattern series of powdered membranes under
imposed conditions

##   Laboratory micro-CT (typically 20 Gb per set) o Static micro-CT of
structured catalysts  Laboratory fluorescence / diffraction imaging
(typically 100 Mb per set) o Static hyperspectral (3d data cubes) images

o In situ hyperspectral (3d data cubes) series under imposed conditions

  * **Synchrotron based micro-CT (typically 20 Gb per set)** o Static micro-CT of structured catalysts (3d images) o Static micro-CT of CMR’s catalysts (3d images) 

  

  * **Synchrotron based XRD-CT (typically 0.1 Tb per set)** o In situ and in operando XRD-CT yielding very large volume raw data sets each XRD-CT comprising many thousands of 2D images 

  

o

_Data processing will yield new data_ :

  * **Standard laboratory XRD (typically 100 Kb per set)** o Crystallographic phases will be identified, quantified. Physical parameters such as peak width will be also be extracted. This will yield tabulated data (stored in XL or equivalent file format). Various stack plots will be generated yielding graphs (sored as png or equivalent format). 

  

  * **Laboratory micro-CT (typically 20 Gb per set)** o Data will reconstructed yielding volume images (stored as vol files which are a binary file format) with processing steps along the way stored as Matlab file format 

  

  * **Laboratory fluorescence / diffraction imaging (typically 100 Mb per set)** o Data will reconstructed yielding volume images (stored as hxt file format also binary) with processing steps along the way stored as Matlab file format 

  

  * **Synchrotron based micro-CT (typically 20 Gb per set)** o Data will reconstructed yielding volume images (stored as vol files which are a binary file format) with processing steps along the way stored as Matlab file format 

  

  * **Synchrotron based XRD-CT (typically 250 Mb per set)** o Raw files will pre-processed to yield reduced XRD-CT data sets stored as hxt and or Matlab file format. Processing steps along the way stored as Matlab file format 

  

_Reproducibility:_ Raw data will not reproducible without repeat measurement.
Processed data can be regenerated from the raw data. Crucially processing
scripts (stored as .m files) will be needed to quickly regenerate processed
data.

_Storage:_ We estimate we will need ca. 100 TB for raw data and 50 TB for
temporary storage of processed data and 10 TB for final processed data.

_Version control:_ We will creation date stamp and date modify processing
scripts. For reasons of disc space usage we will, in most cases, overwrite
processed data where this processing is to be modified.

_Software tools:_ Almost all processing will be done using Matlab. We will
also use a variety of image processing and standard XRD software programs,
including imagej, Avizo, Expert High Score Plus, GSAS, TOPAS.

_Pre-existing data:_ We will use various powder diffraction databases
including ICSD and ICDD databases.

###  9.2. Data Storage and Back-up

All raw XRD-CT and synchrotron micro CT data will be copied to portable NAS
discs. All raw XRD-CT and synchrotron micro CT data will also be archived up
to a 100 TB data space (this data backup is itself mirrored). Processing of
XRD-CT and synchrotron micro CT will take place in a 50 Tb space. Laboratory
micro CT, fluorescence and imaging data and laboratory XRD data will be stored
on a distributive NAS raid system which itself is mirrored. A small amount of
cloud storage (ca. 10 Tb) will be used for processing and exchanging data.
Backup frequency will be weekly on local PC’s. This will cover written scripts
etc. Mirror’s should operate nightly or over weekends for most raw data, where
the mirrors are in different physical locations. All raw data will be read-
only. Archives will be restricted only to Finden personnel and any associated
Finden/Memere research students.

###  9.3. Data Documentation

Data documentation is yet to be fully determined. Processing scripts will use
soft links to be more versatile. Data inside Matlab files will be stored in
structures. Electronic log books (this will include XL sheets and OneNote or
equivalent formats) will be used to store the locations, indexes and
descriptions of archived and processed files. For processed data, we will use
dates within file names as additional level of version control and associated
text or html files as file descriptions.

###  9.4. Data Access

Copyright or Intellectual Property Rights are not applicable to the data
generated by Finden but certain scripts, algorithms and process flows will
remain the property of Finden. Access to processed data within Finden will be
limited to the project team unless further dissemination is agreed/required by
the project partners. Access to the raw large volume data will be restricted
for data security reasons but can be shared upon request; this data unless
copied will be read only.

###  9.5. Data Sharing and Reuse

Processed data will be shared with project partners via a secure cloud storage
system. For smaller files, data can be shared via email. Publishing of data
will be in accordance with the Memere policies and subservient to this the
Journal/Repository policy. We will seek permission for reuse of data or
sharing with outside parties from the project partners. Shared multi-
dimensional imaging data will be visualised using Matlab and/or imagej and
using inhouse developed software (that we can share with the partners). All
other graphs etc can be shared as standard formats such as xls, png, tif, pdf.

###  9.6. Data Preservation and Archiving

During the course of the project all reduced raw and processed data will be
stored and archived; the archive will be maintained for a minimum of 12 months
after termination of the project. We can, at this time, guarantee the archive
of the large volume raw data for a minimum of 3 months after data collection
and are currently looking into ways to extend this archive period.

##  10\. Partner Johnson Matthey PLC  
  
<table>  
<tr>  
<th>

Name of

student/researcher(s)

</th>  
<th>

Stephen Poulston

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

Name of group/project

</td>  
<td>

Johnson Matthey Technology Centre

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

Description of your research

</td>  
<td>

_Catalyst preparation and testing._

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

Funding body(ies)

</td>  
<td>

H2020

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

Grant number

</td>  
<td>

**679933**

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

Partner organisations

</td>  
<td>

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

Project duration

</td>  
<td>

Start: **10-01-2015** End: **09-30-2019**

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

Date written

</td>  
<td>

**04/02/2016**

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

Date last update

</td>  
<td>

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

Version

</td>  
<td>

V0.1. A new version of the DMP will be created whenever important changes to
the project occur due to inclusion of new data sets, changes in consortium
policies or external factors.

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

Name of researcher(s) with

roles/responsibilities for data management

</td>  
<td>

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

**10.1. Data Collection**

Experimental data. Generally in summary form such as excel graphs and
powerpoint presentations

###  10.2. Data Storage and Back-up

Data stored on company server. Storage and back-up managed at corporate level
by IT department.

**10.3. Data Documentation** Periodic reports; monthly, 6 monthly etc.
Experiments recorded electronically in ‘electronic notebook’ with links to
additional data files. Each experiment recorded in this way has a unique
identification code assigned.

###  10.4. Data Access

Internal access limited by control of password protected network access with
restricted access. IPR managed by relevant group business manager and group
legal.

###  10.5. Data Sharing and Reuse

Data access restricted outside of consortium by agreed publication process
within MEMERE partner consortium agreement. Internal approval for publication
within JM controlled by internal approval process agreed at group level.

**10.6. Data Preservation and Archiving**

Long term data archiving of electronic data managed centrally by group IT.

##  11\. Partner Rauschert Heinersdorf-Pressig GmbH  
  
<table>  
<tr>  
<th>

Name of

student/researcher(s)

</th>  
<th>

Ulrich Werr Ralph Weckel

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

</td>  
<td>

Violetta Prehn

Dr. Ralf Girmscheid

Egbert Martin

Rainer Thoma

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

Name of group/project

</td>  
<td>

Rauschert Heinersdorf-Pressig GmbH (RHP)/

MEMERE-Project

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

Description of your research

</td>  
<td>

_Development and Production of porous ceramic supports for MIEC-membranes
based on Y-FSZ and/or MgO. Also includes dense feed tubes and_

_seals to metal tubes suitable at elevated temperatures_

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

Funding body(ies)

</td>  
<td>

H2020

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

Grant number

</td>  
<td>

**679933**

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

Partner organisations

</td>  
<td>

WP3: TUE, TECNALIA, VITO, HYGEAR, MARION

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

Project duration

</td>  
<td>

Start: **10-01-2015** End: **09-30-2019**

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

Date written

</td>  
<td>

**02-05-2016**

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

Date last update

</td>  
<td>

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

Version

</td>  
<td>

V0.1. A new version of the DMP will be created whenever important changes to
the project occur due to inclusion of new data sets, changes in consortium
policies or external factors.

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

Name of researcher(s) with

roles/responsibilities for data management

</td>  
<td>

_Ulrich Werr (Project Manager RHP for MEMERE)_

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

###  11.1. Data Collection

RHP will collect data during development and manufacturing of porous ceramics
substrates. It will be handwritten observations in Lab journals, results from
Analysis and pictures (photos)

Excel-files, Word-files, pdf-files, jpg-files

Important data will be summarised in reports and printed out. So they will be
available in paper form for long periods as well.

Estimated size of the project folder: 2 GB

Windows based software is used as preferred software to create/process and
visualise data. Pre-existing data will be used from DEMCAMER (FP7)

###  11.2. Data Storage and Back-up

All data, no matter if raw date or processed date will be stored at a shared
folder on the Rauschert file server. This is back up daily and stored
externally in a different location by a service company on hard disks. It is
not allowed to safe any data only on hard discs on PCs or laptop-computers
(Acc. To the ITuser-rules any RHP-employee has signed).

###  11.3. Data Documentation

Data created are easy to understand, they will be summarised in regular
reports that help to understand them.

The convention is to name the files with self-explaining names and to use
folders to bring a logical structure into the data storage. The project
manager in RHP is responsible to set up the general structure of the folder
and to share it with the other collaborators.

###  11.4. Data Access

Copyright and intellectual properties will be handled acc. to German law
(especially:

Arbeitnehmererfindergesetz) and the rules of the EC, Grant Agreement etc..

Data are only accessible for co-workers in the project and the IT-staff. It is
controlled by the project manager for MEMERE in RHP.

###  11.5. Data Sharing and Reuse

All members of MEMERE-project are allowed to use data within the project. Any
further distribution, use or share of the data requires the written approval
of RHP. RHP will deny the external use in case, the data are commercial
important data or know-how, that will endanger the commercial use of the new
development made.

Scientific important data will that cannot be converted into commercial
products can be shared upon request and approval through RHP to external
parties. Windows-based software is as a standard tool to share such data.

##  11\. 6. Data Preservation and Archiving

The full data will be stored for 5 years minimum, after that period it may be
allowed to reduce the date to only relevant data.

Written reports will be kept for 10 years min in paper form.

##  12\. Partner Ciaotech s.r.l. (100% PNO Group B.V.)  
  
<table>  
<tr>  
<th>

Name of

student/researcher(s)

</th>  
<th>

Marco Molica Colella

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

Name of group/project

</td>  
<td>

CiaoTech/PNO / MEMERE (WP9)

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

Description of your research

</td>  
<td>

In the frame of WP9 CiaoTech/PNO will have a major role in carrying on a
Stakeholder analysis to be used as a reference point for the following
exploitation and dissemination activities

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

Funding body(ies)

</td>  
<td>

H2020

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

Grant number

</td>  
<td>

**679933**

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

Partner organisations

</td>  
<td>

WP9 partners: ALL

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

Project duration

</td>  
<td>

Start: **10-01-2015** End: **09-30-2019**

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

Date written

</td>  
<td>

**10-01-2016**

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

Date last update

</td>  
<td>

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

Version

</td>  
<td>

V0.1. A new version of the DMP will be created whenever important changes to
the project occur due to inclusion of new data sets, changes in consortium
policies or external factors.

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

Name of researcher(s) with

roles/responsibilities for data management

</td>  
<td>

Marco Molica Colella, CiaoTech

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

###  12.1. Data Collection

_Data to be collected_ include:

  * Sets of Keywords related to project topics needed to search for 

  

  * Partners’ own – already known - stakeholder lists 

  

  * Dedicated survey forms 

  

  * EU projects - related to similar topics - data 

  

Sources per type of data are described in the table below:  
  
<table>  
<tr>  
<th>

**Type of data**

</th>  
<th>

**Possible sources of data**

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

Keywords and

stakeholders list

</td>  
<td>

These data will be collected through discussion among partners and put on
dedicated text files on Excel and Word documents format.

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

Dedicated Surveys form

</td>  
<td>

Word Document and, possibly, standard on-line platforms to assemble the survey
(to be chosen through a shared set of possibilities among partners) and
provide easier access

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

EU project data

</td>  
<td>

Literature data, CORDIS database and CiaoTech/PNO own databases and Open

Innovation Platform _‘Innovation Place’_

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

Data are to be collected mostly by Excel or Word files, provided with version
numbers in the name as well as into the file. A final version to be used in
the following project deliverables will be opportunely identified and also
marked by the finalization date.

_Main Data to be produced_ include:

  * A _survey form_ to be spread among stakeholders 

  

  * A _Power Point_ presentation and a _Word_ summary document for the complete Stakeholder analysis, detailing activities, methodologies and extracted results 

  

###  12.2. Data Storage and Back-up

All the collected data will be stored on CiaoTech/PNO hardware, accessible
only by consultants dedicated to the activities, which are standardly
protected by partners.

**12.3. Data Documentation**

The name standard will be sufficient to keep trace of different versions and
release dates.

**12.4. Data Access**

No IPR will be claimed. Data will be kept on CiaoTech/PNO own hardware, as
said before.

###  12.5. Data Sharing and Reuse

No sharing will be allowed outside project consortium or unless the consortium
allows it. Sharing and Reuse among partners will be available continuously. It
will be done by standard e-mail, if not specifically decided.

###  12.6. Data Preservation and Archiving

The consortium policy for data preservation and archiving shall be followed.
In the absence of such a project-specific policy, the data will be kept on
CiaoTech/PNO hardware. A specific folder can be loaded on shared archives only
accessible to Ciaotech/PNO consultants’ network. For the sake of simplicity,
only the final version of each file will be retained at project end.