1. **Introduction**

  

  

INTEGROIL project is part of the Open Research Data Pilot (ORDP) in Horizon
2020. ORDP aims to improve and maximize access to and re-use of research data
generated by Horizon 2020 projects and takes into account the need to balance
openness and protection of scientific information, commercialization and
Intellectual Property Rights, privacy concerns, security as well as data
management and preservation questions. ORDP follows the principle “As open as
possible as closed as necessary”.

According to theses premises, the purpose of the present document is to ensure
that research data ( _i.e._ mainly data needed to validate the results
presented in scientific publications but open to other data) is soundly
managed by making them findable, accessible, interoperable and reusable
(FAIR). To this end, this document includes information on:

  * the handling of research data during and after the end of the project 

  

  * what data will be collected, processed and/or generated 

  

  * which methodology and standards will be applied 

  

  * whether data will be shared/made open access and 

  

  * how data will be curated and preserved (including after the end of the project). 

  

This document constitutes the initial Data Management Plan for the INTEGROIL
project and will be updated whenever significant changes arise and in time for
the latest final review (M36).

  2. **Open Research Data Pilot requirements.**

  

  

Contractual obligations in relation to Open Access to research data are
described in **Article 29.3 of the Grant Agreement:**

_Regarding the digital research data generated in the action (‘data’), the
beneficiaries must:_

  1. _deposit in a research data repository and take measures to make it possible for third parties to access, mine, exploit, reproduce and disseminate — free of charge for any user — the following:_

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

  

    2. _other data, including associated metadata, as specified and within the deadlines laid down in the 'data management plan' (see Annex 1);_

  
  

  

  2. _provide information — via the repository — about tools and instruments at the disposal of the beneficiaries and necessary for validating the results (and — where possible — provide the tools and instruments themselves)._

  

  

_This does not change the obligation to protect results in Article 27, the
confidentiality obligations in_

_Article 36, the security obligations in Article 37 or the obligations to
protect personal data in Article 39, all of which still apply._

_As an exception, the beneficiaries do not have to ensure open access to
specific parts of their research data if the achievement of the action's main
objective, as described in Annex 1, would be jeopardized by making those
specific parts of the research data openly accessible. In this case, the data
management plan must contain the reasons for not giving access._

#  2.1 Data set reference, name and description

This section shows a description of the information to be gathered, the nature
and the scale of the data generated or collected during the project.

The Data Management Plan will present in details only the procedures of
creating ‘primary data’ (data not available from any other sources) and of
their management.

##  2.1.1 DATASET 1: Real-time information of the treatment platform
(generated by ACCIONA AGUA and TUPRAS)  
  
<table>  
<tr>  
<th>

**DataSet: Real-time information of the treatment platform**

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

Data set reference name

</td>  
<td>

and

</td>  
<td>

INTEGROIL-001. Information of the treatment platform

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

Data set description

</td>  
<td>

</td>  
<td>

The project will generate water quality, energy consumption and other process
parameter data collected in Excel spreadsheets.

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

Origin of data

</td>  
<td>

</td>  
<td>

The data used will be original from the research project. The existing
information used relates to the prior know-how of the technology developers,
not particularly reflected in any specific set of data.

The data is originated in the sensors and other metering equipment installed
in the laboratory tests, individual prototypes (Work Package 2 and 3) and
integrated platform (Work Package 4). Additionally, point samples of water
quality parameters measured with test kits will also be a source of data (work
Packages 1, 2, 3 and 4).

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

Size of the data

</td>  
<td>

</td>  
<td>

The size of the data can range from 10-50 entries in the case of laboratory
and bench tests, to several thousand entries per each parameter during
demonstration.

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

Data applicability

</td>  
<td>

In order for the raw data to be useful, it will be processed first in order to
provide meaningful process information. The laboratory and prototype data will
then be useful to technology developers, and the integrated platform data will
be useful for the platform operators (end users of the technology).

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

##  2.1.2 DATASET 2: Optimization of the flotation technology (Generated by
ACCIONA)  
  
<table>  
<tr>  
<th>

**DataSet: Optimization of the flotation technology**

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

Data set reference and name

</td>  
<td>

INTEGROIL-002. Information of flotation process.

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

Data set description

</td>  
<td>

The project will generate data about optimal conditions for flotation
performance, collected in Excel sheets.

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

Origin of data

</td>  
<td>

The data used will be original from the research project. The data is
originated in the experimental lab test itself (experimental conditions
applied), in the laboratory analysis equipment and also in the sensors of the
individual prototype. Related work packages are WP2 and WP4.

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

Size of the data

</td>  
<td>

The size of the data is expected to range between 10-30 entries.

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

Data applicability

</td>  
<td>

The data will provide the information required for determining the optimum
operational conditions. It will be useful for the platform operators and also
for the technology/solution providers (operation and maintenance requirements,
OPEX estimation, etc.).

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

##  2.1.3 DATASET 3 and 4: Optimization of ceramic membranes (generated by
LIKUID)  
  
<table>  
<tr>  
<th>

**DataSet: Optimization of ceramic membrane filtration (DF and MBR)**

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

Data set reference name

</td>  
<td>

and

</td>  
<td>

INTEGROIL-003. Information of the performance of ceramic filtration at
different operational conditions, both for the direct filtration for produced
water treatment and the CBR process in MBR configuration for refinery
wastewater treatment .

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

Data set description

</td>  
<td>

</td>  
<td>

The project will generate data about filtration performance (flux, TMP,
permeability), filtration sequences, and permeate quality. Moreover, the data
related to the biological process in the MBR configuration will be also
generated.

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

Origin of data

</td>  
<td>

</td>  
<td>

The data used will be original from the research project. The data is
originated in the experimental lab test itself (experimental conditions
applied), in the sensors of the laboratory filtration rig, in the laboratory
analysis equipment and also in the sensors of the individual prototype.
Related work packages are WP2 and WP4.

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

Size of the data

</td>  
<td>

</td>  
<td>

The size of the data is expected to range between 10-30 entries for the
laboratory tests to several thousand entries during demonstration.

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

Data applicability

</td>  
<td>

The filtration performance data will provide the information required for
determining the optimum operational conditions of ceramic filtration. It will
be useful for the platform operators and also for the technology/solution
providers (operation and maintenance requirements, OPEX estimation, etc.).

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

**DataSet: Optimization of ceramic membranes’ chemical cleaning**

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

Data set reference name

</td>  
<td>

and

</td>  
<td>

INTEGROIL-004. Information of chemical cleaning protocols and membrane autopsy
studies – ceramic membranes.

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

Data set description

</td>  
<td>

</td>  
<td>

The project will generate data about cleaning chemicals, cleaning conditions,
cleaning efficiency and autopsy studies, collected in Excel sheets.

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

Origin of data

</td>  
<td>

</td>  
<td>

The data used will be original from the research project. The data is
originated in the experimental lab test itself (experimental conditions
applied), in the sensors of the laboratory filtration rig, in the laboratory
analysis equipment and also in the sensors of the individual prototype.
Related work packages are WP2 and WP4.

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

Size of the data

</td>  
<td>

</td>  
<td>

The size of the data is expected to range between 10-30 entries.

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

Data applicability

</td>  
<td>

The chemical cleaning and membrane autopsy data will provide the information
required for determining the optimum cleaning conditions and exactly reproduce
the corresponding protocol. It will be useful for the platform operators and
also for the technology/solution providers (operation and maintenance
requirements, OPEX estimation, etc.).

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

**2.1.4 DATASET 5, 6 and 7: Conventional advanced oxidation processes
(generated by URV).**  
  
<table>  
<tr>  
<th>

</th>  
<th>

**DataSet: Ozonolysis**

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

Data set reference name

</td>  
<td>

and

</td>  
<td>

Integroil-005. Information of ozonolysis process

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

Data set description

</td>  
<td>

</td>  
<td>

Application of ozone for the removal of dissolved organic compounds from O&G
wastewater, with the aim of mineralizing this organic fraction or increasing
biodegradability/ decreasing toxicity of the effluent.

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

Origin of data

</td>  
<td>

</td>  
<td>

The data used will be original from the research project. The existing
information used relates to the prior know-how of the technology developers,
not particularly reflected in any specific set of data.

The data originated will be due to optimization of the operating conditions
(reaction time, concentration of reagents needed i.e. ozone, H2O2, amount and
type of catalyst, pH, temperature…) for the different case studies considered
at laboratory scale as well as from the operation of the individual prototype.

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

Size of the data

</th>  
<th>

</th>  
<th>

The size of the data can range from 10-50 entries in the case of laboratory
and bench tests, to several thousand entries per each parameter during
demonstration.

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

Data applicability

</td>  
<td>

</td>  
<td>

Data will be useful in the validation of ozonolysis technology in treatment of
O&G wastewater at full scale. Also, these data will provide useful information
on the synergies with other techniques studied in the project. The laboratory
and prototype data will then be useful to technology developers, and the
configuration of integrated platform.

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

</td>  
<td>

**DataSet: Fenton processes**

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

Data set reference name

</td>  
<td>

and

</td>  
<td>

Integroil-006. Information of the Fenton processes

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

Data set description

</td>  
<td>

</td>  
<td>

Application of Fenton and Fenton-like processes to achieve maximum efficiency
in the removal and/or mineralization of organic compounds from O&G wastewater
and/or increase of biodegradability or decrease of toxicity.

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

Origin of data

</td>  
<td>

</td>  
<td>

The data used will be original from the research project.

The data originated will be due to optimization of the operating conditions
(reaction time, concentration of reagents needed, amount and type of catalyst,
pH, temperature…) for the different case studies considered at laboratory
scale as well as from the operation of the individual prototype if considered.

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

Size of the data

</td>  
<td>

</td>  
<td>

The size of the data can range from 10-50 entries in the case of laboratory
and bench tests, to several thousand entries per each parameter during
demonstration.

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

Data applicability

</td>  
<td>

</td>  
<td>

Data will be useful in the validation of Fenton-like processes in treatment of
O&G wastewater at full scale. Also, these data will provide useful information
on the synergies with other AOPs techniques studied in the project. The
laboratory and prototype data will then be useful to technology developers,
and the configuration of integrated platform.

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

</td>  
<td>

**DataSet: Photocatalysis processes**

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

Data set reference name

</td>  
<td>

and

</td>  
<td>

Integroil-007. Information of the photocatalytic processes

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

Data set description

</td>  
<td>

</td>  
<td>

Application of photocatalysis to achieve maximum efficiency in the removal
and/or mineralization of organic compounds from O&G wastewater and/or increase
of biodegradability or decrease of toxicity.

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

Origin of data

</td>  
<td>

The data used will be original from the research project.

The data originated will be due to optimization of the operating conditions
(reaction time, amount and type of catalyst, pH, temperature…) for the
different case studies considered at laboratory scale as well as from the
operation of the individual prototype if considered.

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

Size of the data

</td>  
<td>

The size of the data can range from 10-50 entries in the case of laboratory
and bench tests, to several thousand entries per each parameter during
demonstration.

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

Data applicability

</td>  
<td>

Data will be useful in the validation of photocatalysis in treatment of O&G
wastewater at full scale. Also, these data will provide useful information on
the synergies with other AOPs techniques studied in the project. The
laboratory and prototype data will then be useful to technology developers,
and the configuration of integrated platform.

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

##  2.1.5 DATASET 8: Catalytic Wet Air Oxidation (CWAO)(generated by APLICAT)  
  
<table>  
<tr>  
<th>

</th>  
<th>

**DataSet: CWAO**

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

Data set reference name

</td>  
<td>

and

</td>  
<td>

Integroil-008. Information of Catalytic Wet Air Oxidation process

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

Data set description

</td>  
<td>

</td>  
<td>

Application of a catalytic process for the removal of dissolved organic
compounds from O&G wastewater, with the aim reduce around 30% of TOC and COD.

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

Origin of data

</td>  
<td>

</td>  
<td>

The data used will be original from the research project.

The data originated will be used for the optimization of the operating
conditions (reaction time, amount and type of catalyst, pH, catalyst
regeneration conditions…) for the different case studies considered at
laboratory scale as well as from the operation of the individual prototype.

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

Size of the data

</td>  
<td>

</td>  
<td>

The size of the data can range from 10-50 entries in the case of laboratory
and bench tests, to several thousand entries per each parameter during
demonstration.

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

Data applicability

</td>  
<td>

</td>  
<td>

Data will be useful in the validation of CWAO technology in the treatment of
O&G wastewater at full scale. Also, these data will provide useful information
on the synergies with other techniques studied in the project. The laboratory
and prototype data will then be useful to technology developers, and the
configuration of integrated platform.

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

##  2.1.6 DATASET 9: Life cycle assessment and costing of the treatment
platform (generated by LCA)  
  
<table>  
<tr>  
<th>

**DataSet: Life cycle assessment and costing of the treatment platform**

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

Data set reference name

</td>  
<td>

and

</td>  
<td>

INTEGROIL-009. Life cycle assessment and life cycle costing

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

Data set description

</td>  
<td>

</td>  
<td>

The data set will include all the underlying information used in the life
cycle assessment and life cycle costing studies applied to the treatment
platform. It will mainly consist of mass and energy balances of the assessed
processes, as well as the derived costs.

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

Origin of data

</td>  
<td>

</td>  
<td>

Primary data to build this data set will originate mainly from the project
itself. Secondary data sources will include literature and previous studies
conducted by 2.-0 LCA consultants.

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

Size of the data

</td>  
<td>

</td>  
<td>

The data will be made available as excel tables and word documents.

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

Data applicability

</td>  
<td>

These data can be used by other LCA practitioners or cost assessors within the
oil and gas and wastewater treatment sectors for similar studies.

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

#  2.2 Standards and metadata

Metadata is ‘data about data’ and is the information that enables data users
to find and/or use a dataset.

##  2.2.1 DATASET 1: Real-time information of the treatment platform

The data will be held in transcript form in accessible file formats such as
.xls (Excel), Metadata will include date and/or time, location of measurement
(if relevant), and parameter measured.

No particular standard will be used, since the data format is simple and
Acciona Agua’s commonlyused format should be sufficient. In this format,
process parameters are located the first row of an Excel file, while the
sampling times (in date or time, whatever is applicable depending on the
duration of the experiment and the frequency of sampling) are located in the
first column. In the intersection of different parameters and times, the data
is registered. In the general spreadsheet, the experiment type and location of
sampling is also described, if relevant.

##  2.2.2 DATASET 2: Optimization of flotation process

The data will be held in transcript form in accessible file formats such as
.xls (Excel), and will include the conditions of process optimization
(coagulant concentration, microsphere concentrations, etc.) with the main
process parameters (type of chemical, concentration, temperature, time, etc.)
and the removal efficiency for different parameters (turbidity, O&G, etc.)
distributed in columns.

##  2.2.3 DATASET 3 and 4: Optimization of ceramic membranes

The data will be held in transcript form in accessible file formats such as
.xls (Excel), and will include (1) the operational conditions of ceramic
filtration and the corresponding performance parameters (permeability, fouling
rate), (2) the operational conditions of the biological reactor in MBR
configuration, (3) the parameters related to effluent quality and (4) the
conditions of each cleaning stage (one stage in each row) with the main
cleaning parameters (type of chemical, concentration, temperature, pH, time,
etc.) and the cleaning efficiency distributed in columns.

##  2.2.4 DATASET 5, 6 and 7: Advanced oxidation processes

The data will be held in transcript form in accessible file formats such as
.xls (Excel), Metadata will include date and/or time, location of measurement
(if relevant), and parameter measured. URV will use Excel files templates for
any relevant AOP experiment. Experiment type, description and process
parameters will be given.

##  2.2.1 DATASET 8: CWAO

The data will be held in transcript form in accessible file formats such as
.xls (Excel). Metadata will include date and/or time, location of measurement
(if relevant), and parameters measured. APLICAT will use Excel files templates
for any relevant experiment. Experiment type, description and process
parameters will be given.

##  2.2.2 DATASET 9: life cycle assessment and costing of the treatment
platform

The data stored in the repository will be fully documented with metadata
including data sources and data quality, assumptions made and methods
employed. All metadata will be incorporated in the word and excel tables.

LCA simulation of the treatment platform will be carried out with the
commercial software SimaPro and for this reason the actual SimaPro files
cannot be shared. However the shared word and excel documents will allow data
users to reproduce the methods and results with other software

#  2.3 Data sharing

The data sharing procedures are the same across the datasets and are in
accordance with the Grant Agreement (Article 29.3).

The partners will deposit the research data, including associated metadata,
needed to validate the results presented in the deposited scientific
publications. Research papers written and published during the funding period
will be made available with a subset of the data necessary to verify the
research findings.

The collected and elaborated data will be stored in an open access repository.
ZENODO repository will be used by all project partners in those cases data can
be shared.

The data collected are likely to be two components:

  * Data collected, assembled, or generated in each experiment. It could be date and/or time, location of measurement (if relevant), and parameter measured. 

  

  * Data that may receive copyright protection due to intellectual property rights. Each partner will decide in such a case how the data is stored and managed and will decide what data needs to be fully included in a database, how to organize the data, and how to relate different data elements. In these cases when a dataset cannot be totally shared due to conflicts with intellectual properties, a range of data will be included instead. 

  

Research data will be made available in a way that can be shared and easily
reused by others, sharing data using open file format (whenever possible), so
that they can be implemented by both proprietary and open source software.

Documenting datasets, data sources, and methodology by which the data were
acquired establishes the basis for interpreting and appropriately using data.
Each generated or collected and then deposited dataset, will include
documentation to help users to re-use it.

##  _Opt Out_

It is important to note that in the case a dataset adversely affects
operations and reputation of any partner, it must be kept as confidential and
it must not be published or shared in an open access platforms.

**DATASET 1 generated by TUPRAS will not be publicly available due the need
for confidentiality in connection with security issues.** TUPRAS has ISO/IEC
27001:2013 Information Security Management System Certification. Regarding to
ISO/IEC 27001: 2013, Asset management system classify the shared data as
public, internal, confidential and highly confidential. Internal, confidential
and highly confidential data cannot be published. In the case that these type
of data are published legal action will be initiated.

#  2.4 Archiving and preservation

Data will be preserved for 10 years after the end of the project. After this
time, it is considered that new technologies would have appeared and stored
data will have little value.

To ensure high-quality long-term management and maintenance of the dataset,
the consortium will use repositories that aim to provide archiving and
preservation of long-tail research data (Zenodo).

#  2.5 Ethical aspects

INTEGROIL is not going to deal with personal data. Notwithstanding, any
contract/agreement with suppliers and workers is issued in compliance with the
terms of article 12 of the current Spanish Organic Law on Personal Data
Protection.

#  2.6 Other issues

Not applicable.