#  Introduction

The current document constitutes the initial version of the **Data Management
Plan** (DMP) elaborated in the framework of the **INNO-4-AGRIFOOD** project,
which has received funding from the European Union’s Horizon 2020 Research and
Innovation Programme under Grant Agreement No 681482. INNO-4-AGRIFOOD is aimed
at fostering, supporting and stimulating **online collaboration for
innovation** amongst **agri-food SMEs** across Europe. To this end, the
project will enhance the service portfolio and practices of **innovation
intermediaries and SME support networks** across Europe by providing them with
a well-tailored blend of demand-driven **value propositions** , including:

  * A **new generation of value added innovation support services** aimed at empowering their agri-food SME clients to capitalise on the full potential of online collaboration for innovation; 

  

  * A **suite of smart and platform-independent ICT tools** to support and optimise the delivery of the novel online collaboration for innovation support services; and 

  

  * A **series of highly interactive and flexible e-training courses** that will equip them with the knowledge and skills required to successfully deliver these new services. 

  

On top of the above mentioned, the accumulated experience and lessons learned
through INNO-4-AGRIFOOD will be translated into meaningful **guidelines** to
be diffused across Europe so as to fuel the replication of its results and
thus enable SMEs in other European sectors to tap into the promising potential
of online collaboration for innovation as well.

INNO-4-AGRIFOOD is implemented by a well-balanced and complementary
**consortium** , which is comprised of 7 partners across 6 different European
countries, as presented in the following table.

##  _Table 1: INNO-4-AGRIFOOD consortium partners_  
  
<table>  
<tr>  
<th>

**Partner**

**No**

</th>  
<th>

**Partner Name**

</th>  
<th>

**Partner short name**

</th>  
<th>

**Country**

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

1

</td>  
<td>

Q-PLAN International Advisors Ltd (Coordinator)

</td>  
<td>

Q-PLAN

</td>  
<td>

Greece

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

2

</td>  
<td>

Agenzia per la Promozione della Ricerca Europea

</td>  
<td>

APRE

</td>  
<td>

Italy

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

3

</td>  
<td>

IMP  3  rove – European Innovation Management

Academy EWIV

</td>  
<td>

IMP  3  rove

</td>  
<td>

Germany

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

4

</td>  
<td>

European Federation of Food Science and Technology

</td>  
<td>

EFFoST

</td>  
<td>

Netherlands

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

5

</td>  
<td>

BioSense Institute

</td>  
<td>

BIOS

</td>  
<td>

Serbia

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

6

</td>  
<td>

National Documentation Centre

</td>  
<td>

EKT/NHRF

</td>  
<td>

Greece

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

7

</td>  
<td>

Europa Media szolgaltato non profitkozhasznu KFT

</td>  
<td>

EM

</td>  
<td>

Hungary

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

In this context, the **initial version of the DMP** presents the data
management principles set forth in the framework of INNO-4-AGRIFOOD by its
consortium partners. Moreover, it provides a first description of the datasets
that will be collected, processed and/or produced during the project, taking
into account the “Guidelines on Data Management in Horizon 2020” provided by
the European Commission  1  . In this respect, it addresses important relevant
points such as standards and metadata as well as outlines a provisional
approach to data sharing, archiving and preservation on a dataset by dataset
basis.

**Important remark**

The DMP is not a fixed document. To the contrary, it will evolve during the
lifespan of the project. In particular, the DMP will be updated at least twice
during INNO-4-AGRIFOOD (i.e. as D7.3 at M15 and D7.4 at M30) as well as ad hoc
when deemed necessary in order to include new datasets, reflect changes in the
already identified datasets, changes in consortium policies and plans or other
potential external factors. Q-PLAN is responsible for the elaboration of the
DMP and with the support of all Work Package Leaders will update and enrich it
when required.

#  Data management principles

##  Standards and metadata

All datasets produced by INNO-4-AGRIFOOD will be accompanied by data that will
facilitate their understanding and re-use by interested stakeholders. These
data may include basic details that will assist interested stakeholders to
locate the dataset, including its format and file type as well as meaningful
information about who created or contributed to the dataset, its name and
reference, date of creation and under what conditions it may be accessed.
Complementary documentation may also encompass details on the methodology used
to collect, process and/or generate the dataset, definitions of variables,
vocabularies and units of measurement as well as any assumptions made.
Finally, wherever possible consortium partners will identify and use existing
community standards.

##  Data sharing

The Coordinator (Q-PLAN) in collaboration with the respective Work Package
Leaders, will determine how the data collected and produced in the framework
of INNO-4-AGRIFOOD will be shared. This includes the definition of access
procedures as well as potential embargo periods along with any necessary
software and/or other tools which may be required for data sharing and re-use.
In case the dataset cannot be shared, the reasons for this will be clearly
mentioned (e.g. ethical, rules of personal data, intellectual property,
commercial, privacy-related, security-related). A consent will be requested
from all external data providers in order to allow for their data to be shared
and all such data will be anonymised before sharing.

##  Data archiving and preservation

The datasets of the project which will be open for sharing will be deposited
to an open data repository and will be made accessible to all interested
stakeholders, ensuring their long-term preservation and accessibility beyond
the lifetime of the project. At the moment, we consider the use of Zenodo  2
as one of the best online and open services to enable open access to
INNO-4-AGRIFOOD datasets but similar repositories will also be considered and
an appropriate decision will be timely made at a future update of the DMP.

Q-PLAN will be responsible for uploading all open datasets to the repository
of choice, while all partners will be responsible for disseminating them
through their professional networks and other media channels.

##  Ethical considerations

INNO-4-AGRIFOOD entails activities which involve the collection of meaningful
data from selected individuals (e.g. the interview-based survey aimed at
revealing the needs of agri-food SMES in terms of online collaboration for
innovation support, the online survey that will shed light to the training
needs of innovation intermediaries in this respect, the co-creation workshop,
etc.). The collection of data from participants in these activities will be
based upon a process of informed consent. Any personal information will be
handled according to the principles laid out by the Directive 95/46/EC of the
European Parliament and of the Council on the “Protection of individuals with
regard to the processing of personal data and on the free movement of such
data” (24 October 1995) and its revisions. The participants’ right to control
their personal information will be respected at all times (including issues of
confidentiality). The Coordinator (Q-PLAN) will regulate and deal with any
ethical issues that may arise during the project in this respect, in
cooperation with the Steering

Committee of the project.

#  Data management plan

In perfect alignment with the paradigm shift towards openness, INNO-4-AGRIFOOD
participates in the Horizon 2020 Open Research Data Pilot and places special
emphasis on the management of the valuable data that will be collected,
processed and generated throughout its activities. The current section
provides meaningful information in this respect per each identified dataset,
including:

  * The name of the dataset. 

  

  * The type of study in the frame of which the dataset is produced. 

  

  * A concise description of the dataset. 

  

  * The methodology and tools employed for collecting/generating the data. 

  

  * The format and volume of the dataset. 

  

  * Any standards that will be used (if applicable) as well as metadata to be created. 

  

  * Potential external stakeholders for whom the data may prove useful. 

  

  * Provisions regarding the confidentiality of the data. 

  

**Important remark**

The information provided within this section reflects the current views and
plans of INNO-4-AGRIFOOD consortium partners at this early stage of the
project (M3) and may be adapted or updated in future versions of the DMP (e.g.
through the inclusion of more elaborate descriptions of the datasets,
standards and metadata, how the datasets may be preserved, accessed and re-
used in the long-term, etc.). The template employed for collecting the
information from project partners is annexed to this document.

##  Analysis of the agri-food value chain  
  
<table>  
<tr>  
<th>

**Dataset name**

</th>  
<th>

Analysis of the agri-food value chain (WP1)

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

**Type of study**

</td>  
<td>

Agri-food value chain analysis aimed at revealing the primary value chain
areas and SME actors to be targeted by the project based on both secondary and
primary research.

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

**Dataset description**

</td>  
<td>

Data derived from interviews with members of the Advisory and Beneficiaries
boards of INNO-4-AGRIFOOD.

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

**Methodologies for data collection / generation**

</td>  
<td>

A semi-structured questionnaire and a respective template will be employed in
order to collect and document data during the interviews.

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

**Format and volume of the dataset**

</td>  
<td>

Standard spreadsheet (.csv or other) and document (e.g. .doc) formats will be
used in order to store and preserve the dataset. The report on the agri-food
value chain analysis will accompany the dataset in pdf format.

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

**Metadata and**

**standards**

</td>  
<td>

Data records will be accompanied by the following metadata: a) the name of the
person that generated it, b) information about the location where it was
generated, c) reproduction rights and d) annotations made by the interviewers.

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

**For whom might the dataset be useful?**

</td>  
<td>

The dataset may prove meaningful for a broad array of stakeholders of the
Agrifood Ecosystem, including agri-food SMEs along with their innovation
intermediaries and providers as well as policy makers at regional, national
and EU level.

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

**Confidentiality**

</td>  
<td>

All records will be open, provided that the corresponding interviewees have
provided their consent in this respect within the frame of the interviews.

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

##  Needs of agri-food SMEs in terms of on-line collaboration for innovation
support  
  
<table>  
<tr>  
<th>

**Dataset name**

</th>  
<th>

Needs of agri-food SMEs in terms of on-line collaboration for innovation
support

(WP1)

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

**Type of study**

</td>  
<td>

Interview-based survey of representatives of agri-food SMEs as well as
innovation intermediaries aimed at revealing the needs, level of readiness and
profiles of agrifood SMEs in terms of online collaboration for innovation.

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

**Dataset description**

</td>  
<td>

The data collected will be responses (plain text in English and/or numbers)
provided by the interviewees.

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

**Methodologies for data collection / generation**

</td>  
<td>

The collection of the data will be realised through a semi-structured
questionnaire that will be administered to survey participants in the frame of
interviews. An online (web) form will be employed for interviewers to submit a
record to the dataset.

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

**Format and volume of the dataset**

</td>  
<td>

The dataset will be stored in a typical spreadsheet format (.csv or other). It
is estimated that more than 50 interviews will be conducted across Europe with
agrifood SMEs and innovation intermediaries and the same number of records
will be collected and stored in the dataset. The report on the findings of the
interviewbased survey based on the analysis of the data will complement the
dataset and will be stored in pdf format.

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

**Metadata and**

**standards**

</td>  
<td>

The following metadata will be created for each record: a) the name of the
person that generated it, b) information about the location where it was
generated, c) reproduction rights and d) annotations made by the interviewers.

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

**For whom might the dataset be useful?**

</td>  
<td>

In addition to agri-food SMEs, the dataset would also be quite useful for
innovation intermediaries and consultants that focus on agri-food SMEs,
technology and innovation providers that operate within the agri-food sector,
on-line collaboration networks and platforms providers, academics and
researchers in relevant fields (e.g. SME collaboration, open innovation, etc.)
as well as policy makers at regional, national and EU level who design and
implement innovation support policies for SMEs.

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

**Confidentiality**

</td>  
<td>

All records will be open. A consent will be requested from users during the
interview so that their data may be anonymised and re-used.

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

##  Skills of innovation intermediaries in terms of supporting on-line
collaboration for innovation  
  
<table>  
<tr>  
<th>

**Dataset name**

</th>  
<th>

Skills of innovation intermediaries in terms of supporting on-line
collaboration for innovation (WP1)

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

**Type of study**

</td>  
<td>

Online survey of staff of innovation intermediaries and SME support networks
aimed at assessing the current level of their knowledge and skills in
providing support to the online collaboration for innovation endeavours of
agri-food SMEs.

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

**Dataset description**

</td>  
<td>

The data collected will be both qualitative and quantitative responses
provided by survey participants.

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

**Methodologies for data collection / generation**

</td>  
<td>

A structured questionnaire will be used in order to collect data. The
questionnaire will be self-administered and survey participants will be able
to access it online by following a dedicated link.

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

**Format and volume of the dataset**

</td>  
<td>

The dataset will be stored in standard spreadsheet format (.csv or other). At
least 50 filled in and successfully submitted questionnaires are expected. The
same number of records will be collected and stored in the dataset. The report
presenting the analysis of the data and the identified skill gaps and training
needs of innovation intermediaries will supplement the dataset and will be
preserved in pdf format.

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

**Metadata and**

**standards**

</td>  
<td>

Each data record will be accompanied by metadata on a) a mandatory basis (e.g.
the country in which respondent is based; main business activities; type of
key clients) and b) on a voluntary basis (e.g. the name of the respondent, the
name of the organization the respondent works for, respondent´s email-address,
firm´s website).

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

**For whom might the dataset be useful?**

</td>  
<td>

Policy makers with an interest in the Agri-food Ecosystem as well as relevant
training designers and providers may also find this dataset useful.

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

**Confidentiality**

</td>  
<td>

Database records will be available only to selected members of the
INNO-4AGRIFOOD project team in order to safeguard the confidentiality of
participants.

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

##  Outcomes of the INNO-4-AGRIFOOD Co-creation Workshop  
  
<table>  
<tr>  
<th>

**Dataset name**

</th>  
<th>

Outcomes of the INNO-4-AGRIFOOD Co-creation Workshop (WP2 & WP3)

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

**Type of study**

</td>  
<td>

A co-creation workshop will be held at the Netherlands in order to co-create
along with project stakeholders the main value propositions of INNO-4-AGRIFOOD
(i.e. services, tools and e-learning curriculum).

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

**Dataset description**

</td>  
<td>

The dataset will include feedback, innovative concepts and ideas provided by
workshop participants along with their contact details.

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

**Methodologies for data collection / generation**

</td>  
<td>

Data will be will be collected by the dedicated minute takers of the co-
creation workshop and documented as transcript notes. The participants list
will serve as the main source of data for contact details and other relevant
background information.

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

**Format and volume of the dataset**

</td>  
<td>

The dataset will be preserved in simple spreadsheet or document format. The
two reports that will stem from the co-creation workshop will accompany the
dataset and will be preserved in pdf format.

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

**Metadata and**

**standards**

</td>  
<td>

Structural and descriptive metadata may be created.

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

**For whom might the dataset be useful?**

</td>  
<td>

Innovation support service designers and providers, ICT application providers
as well as relevant trainers and educators would find the dataset most useful,
especially those who operate within the agri-food sector or are interested to
do so.

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

**Confidentiality**

</td>  
<td>

Data will be open, provided that the person or partner who provided the
information grants permission.

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

##  Case-based training material supplemented by theoretical information on
the topic  
  
<table>  
<tr>  
<th>

**Dataset name**

</th>  
<th>

Case-based training material supplemented by theoretical information on the
topic

(WP2)

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

**Type of study**

</td>  
<td>

Development of educative case studies based on the services provided in the
framework of INNO-4-AGRIFOOD blended with theoretical training based on
existing material available to partners either from previous work or from open
sources.

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

**Dataset description**

</td>  
<td>

The data collected will be simple responses (plain text in English) provided
in the frame of interviews.

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

**Methodologies for data collection / generation**

</td>  
<td>

Data required for the development of the case studies will be collected with
the help of semi-structured questionnaires administered during the interviews
by project partners. Additional data will be gathered from the existing
knowledge base of project partners (e.g. previous project documentations,
previous service provision documentations, etc.) and/or from OER repositories
as well as other thirdparty secondary data sources.

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

**Format and volume of the dataset**

</td>  
<td>

Data collected during the interviews conducted in the framework of case study
development will be stored in document format (e.g. .doc). The case studies
stemming from the interviews will be preserved in pdf format.

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

**Metadata and**

**standards**

</td>  
<td>

All e-learning material developed based on the case studies will be SCORM
compliant to enable its packaging and facilitate the re-use of the learning
objects. The Articulate software, which will be used to create the e-learning,
can generate the Content Aggregation Metadata File required.

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

**For whom might the dataset be useful?**

</td>  
<td>

The dataset would be quite useful for innovation intermediaries and
consultants as well as educators who would use the e-learning material in
their own activities.

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

**Confidentiality**

</td>  
<td>

The e-learning material will be openly available to all interested
stakeholders, protected with an appropriate Creative Commons licence (to be
decided at a later stage of the project).

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

##  Pool of agri-food SMEs  
  
<table>  
<tr>  
<th>

**Dataset name**

</th>  
<th>

Pool of agri-food SMEs (WP4)

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

**Type of study**

</td>  
<td>

Deployment of INNO-4-AGRIFOOD services and tools in real-life contexts.

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

**Dataset description**

</td>  
<td>

List of agri-food SMEs which may be interested in benefiting from the online
collaboration for innovation support services of the project in the framework
of its 3 iterative testing, validation and fine-tuning rounds.

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

**Methodologies for data collection / generation**

</td>  
<td>

In addition to the professional networks of INNO-4-AGRIFOOD, several sources
will be employed to identify suitable SMEs to participate in the deployment of
the novel services and tools, including (among others) networks and member
organisations of the Advisory and Beneficiaries boards of the project as well
as interested SME participants in the surveys launched under WP1. Online
sources may also be utilised to complement the dataset with useful information
regarding the companies.

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

**Format and volume of the dataset**

</td>  
<td>

A spreadsheet (e.g. using an .xlsx format) will be created to maintain the
list of agrifood SMEs, which by the end of the project will contain at least
125 records.

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

**Metadata and**

**standards**

</td>  
<td>

Structural metadata may be provided.

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

**For whom might the dataset be useful?**

</td>  
<td>

The dataset would be most useful for consortium partners during the activities
of the project.

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

**Confidentiality**

</td>  
<td>

The dataset will be available only to relevant INNO-4-AGRIFOOD partners and
may not be disclosed or used for purposes outside the framework of the
project, unless otherwise allowed by either the project partner or the
external stakeholder that has provided the respective data.

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

##  Roster of specialists database  
  
<table>  
<tr>  
<th>

**Dataset name**

</th>  
<th>

Roster of Specialists Database (WP4)

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

**Type of study**

</td>  
<td>

Involvement of trained staff of innovation intermediaries and SME support
networks in the deployment of INNO-4-AGRIFOOD services and tools in real-life
contexts.

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

**Dataset description**

</td>  
<td>

Pool of SME consultants who have successfully completed the INNO-4-AGRIFOOD
e-training courses and may participate in the testing of services and tools of
the project by providing them to agri-food SMEs. The Roster of Specialists
Database will encompass valuable information, such as contact details and
areas of expertise of the specialists, (e.g. in terms of sector, industry,
etc.).

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

**Methodologies for data collection / generation**

</td>  
<td>

The Roster of Specialists Database will be enriched as the activities of WP5
progress and an increasing number of staff of innovation intermediaries and
SME support networks complete the e-learning of the project. Data on the
specialists who will participate in the e-learning as well as on the degree to
which they will have completed it will be collected/generated by the
e-learning platform.

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

**Format and volume of the dataset**

</td>  
<td>

The Roster of Specialists Database will be preserved in a standard spreadsheet
format and will be comprised of at least 50 SME consultants across the EU.

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

**Metadata and**

**standards**

</td>  
<td>

Structural metadata may be provided.

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

**For whom might the dataset be useful?**

</td>  
<td>

Agri-food SMEs who would, like to receive support from innovation consultants
specialised in supporting online collaboration for innovation.

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

**Confidentiality**

</td>  
<td>

Records in the database will be open as long as the provider of the
corresponding information has given the relevant permission.

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

##  Service testing metrics  
  
<table>  
<tr>  
<th>

**Dataset name**

</th>  
<th>

Service testing metrics (WP4)

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

**Type of study**

</td>  
<td>

Testing, validation and fine-tuning of INNO-4-AGRIFOOD services.

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

**Dataset description**

</td>  
<td>

Metrics collected during the iterative real-life deployment of INNO-4-AGRIFOOD
services and tools aimed at managing ambiguity during the various iterations
as well as measuring the impact of improvements after each iteration.
Indicative metrics that may be incorporated in the dedicated model of the
project and fuel the dataset include: basic metrics related to the willingness
of end-users to try the services, their level of satisfaction from them, etc.;
tailored innovative performance metrics such as number of new on-line
contacts, conversion ratio of new contacts to innovation partners, number of
innovation projects launched with partners identified through INNO-4-AGRIFOOD
services, etc.; as well as forward looking

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

</td>  
<td>

metrics related to the estimation of potential future growth of the developed
services.

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

**Methodologies for data collection / generation**

</td>  
<td>

A semi-structured questionnaire will be employed to mine both qualitative and
quantitative data from agri-food SME participants in the various deployment
rounds of the project.

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

**Format and volume of the dataset**

</td>  
<td>

The dataset will employ a typical spreadsheet format.

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

**Metadata and**

**standards**

</td>  
<td>

Structural and descriptive metadata may be provided.

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

**For whom might the dataset be useful?**

</td>  
<td>

Innovation support service designers and providers may find use in this
dataset.

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

**Confidentiality**

</td>  
<td>

All records will be open after the necessary consent has been provided by
interviewees and any required anonymization has been performed.

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

##  Personal data, profile and learning curve of e-learning participants  
  
<table>  
<tr>  
<th>

**Dataset name**

</th>  
<th>

Personal data, profile and learning curve of e-learning participants (WP5)

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

**Type of study**

</td>  
<td>

Provision of e-training courses to staff of innovation intermediaries and SME
support networks.

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

**Dataset description**

</td>  
<td>

Personal data of e-learning participants including statistics of accessing the
system, duration of stay and movements of the learner on the portal.

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

**Methodologies for data collection / generation**

</td>  
<td>

Individuals who will register to the INNO-4-AGRIFOOD e-learning will
voluntarily share the personal data and profile needed for their registration.
The e-learning platform will automatically collect all necessary data based on
the visitors accessing the system using one username-password combination.

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

**Format and volume of the dataset**

</td>  
<td>

Dataset will be stored in MySQL database that can be exported to standard
spreadsheet format (.csv or other). At least 150 registered learners are
expected.

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

**Metadata and**

**standards**

</td>  
<td>

Any potential standards to be used or metadata to be created will be
determined at a later stage of the project.

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

**For whom might the dataset be useful?**

</td>  
<td>

The dataset will be used to analyse the learning behaviour of the participants
in the frame of the project and thus may be useful for educators and/or
e-learning organisers targeting the same target group.

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

**Confidentiality**

</td>  
<td>

Personal data of training participants will be confidential, the
administrators will have access to their data, but not to password
information. Training participants can configure their profile and the open
data they want to share. Regarding the learning curve related data, the
statistics on accessing the e-learning, watching and existing material,
concluding tests, etc. will be available for the administrators of the
e-learning portal. Any analysis or conclusions drawn from these data will be
shared unanimously.

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

##  Awareness creation, dissemination and stakeholder engagement  
  
<table>  
<tr>  
<th>

**Dataset name**

</th>  
<th>

Awareness creation, dissemination and stakeholder engagement

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

**Type of study**

</td>  
<td>

Assessment of the results and impact of the awareness creation, dissemination
and stakeholder engagement activities of the project employing an indicator-
based framework.

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

**Dataset description**

</td>  
<td>

Metrics collected during INNO-4-AGRIFOOD with a view to measuring and
assessing the performance and results of the project in terms of awareness
creation, dissemination, stakeholder engagement.

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

**Methodologies for data collection / generation**

</td>  
<td>

Primary data will be collected through the activity reports of project
partners regarding media products, events, external events, general publicity,
etc. along with any supporting material (e.g. photos presentations,
participants lists, etc.). Third party tools will be used as well (e.g. Google
analytics, social media statistics, etc.).

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

**Format and volume of the dataset**

</td>  
<td>

All data will be collected and preserved in a document format (e.g. .doc)
along with any complementary material in their original format (e.g. JPEG,
PPT, etc.)

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

**Metadata and**

**standards**

</td>  
<td>

Any potential standards to be used or metadata to be created will be
determined at a later stage of the project.

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

**For whom might the dataset be useful?**

</td>  
<td>

The dataset would be meaningful to the EC as well as researchers who study
relevant aspects of EU-funded projects.

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

**Confidentiality**

</td>  
<td>

All records will be open

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