#  Introduction

The current document constitutes the interim 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. 

  

  * 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.

To this end, INNO-4-AGRIFOOD brings together and 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 (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 **interim version of the DMP** presents the data
management principles set forth in the framework of INNO-4-AGRIFOOD by its
consortium partners (Chapter 2). Moreover, it builds upon the initial version
of the DMP and provides an updated list of the datasets that have been or will
be collected, processed and/or produced during the project along with an up-
to-date description for each one (Chapter 3), addressing crucial aspects
pertaining to their management and taking into account the “  _Guidelines on
Data Management_ _in Horizon 2020_ ”  provided by the European Commission
(EC).

**Important remark**

The DMP is not a fixed document. To the contrary, it evolves during the
lifespan of the project. In particular, the DMP will be updated at least once
more during INNO-4-AGRIFOOD (i.e. as 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 will update and enrich it, when required, with the support of all
relevant members of the INNO-4-AGRIFOOD consortium.

#  Data management principles

##  Standards and metadata

Any open 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 standards.

##  Data sharing

The Coordinator (Q-PLAN) in collaboration with the respective Work Package
Leaders of the project, 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. In fact, we consider the use of  _Zenodo_ as one
of the best online and open services to enable open access to INNO-4-AGRIFOOD
datasets. In this respect, the Coordinator (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 communication 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 shed light to the training needs of
innovation intermediaries, etc.). The collection of data from participants in
such 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

##  Overview

INNO-4-AGRIFOOD places special emphasis on the management of the valuable data
that have been or will be collected, processed and generated throughout its
activities. In this respect, the table below provides a list of the datasets
identified by INNO-4-AGRIFOOD consortium members, indicating the name of the
dataset, its linked Work Package and the respective leading consortium member
(i.e. Work Package Leader) as well as its status compared to the previous
version of the DMP.

###  Table 2: List of INNO-4-AGRIFOOD datasets  
  
<table>  
<tr>  
<th>

**No**

</th>  
<th>

**Dataset Name**

</th>  
<th>

**Linked**

**Work**

**Package**

</th>  
<th>

**Work**

**Package**

**Leader**

</th>  
<th>

**Status**

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

1

</td>  
<td>

Analysis of the agri-food value chain

</td>  
<td>

WP1

</td>  
<td>

BIOS

</td>  
<td>

Updated

(M15)

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

2

</td>  
<td>

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

</td>  
<td>

WP1

</td>  
<td>

BIOS

</td>  
<td>

Updated

(M15)

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

3

</td>  
<td>

Skills of innovation intermediaries in terms of supporting online
collaboration for innovation

</td>  
<td>

WP1

</td>  
<td>

BIOS

</td>  
<td>

Updated

(M15)

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

4

</td>  
<td>

Outcomes of the INNO-4-AGRIFOOD Cocreation Workshop – E-learning

</td>  
<td>

WP2

</td>  
<td>

IMP  3  rove

</td>  
<td>

New entry  1

(M15)

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

5

</td>  
<td>

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

</td>  
<td>

WP2

</td>  
<td>

IMP  3  rove

</td>  
<td>

\-

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

6

</td>  
<td>

Outcomes of the INNO-4-AGRIFOOD Cocreation Workshop – Services and tools

</td>  
<td>

WP3

</td>  
<td>

Q-PLAN

</td>  
<td>

New entry  1

(M15)

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

7

</td>  
<td>

Pool of agri-food SMEs

</td>  
<td>

WP4

</td>  
<td>

APRE

</td>  
<td>

Updated

(M15)

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

8

</td>  
<td>

Roster of specialists database

</td>  
<td>

WP4

</td>  
<td>

APRE

</td>  
<td>

Updated

(M15)

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

9

</td>  
<td>

Service testing metrics

</td>  
<td>

WP4

</td>  
<td>

APRE

</td>  
<td>

Updated

(M15)

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

10

</th>  
<th>

User data and learning curve of e-learning participants

</th>  
<th>

WP5

</th>  
<th>

EM

</th>  
<th>

New entry  2

(M15)

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

11

</td>  
<td>

Feedback derived from e-learning participants

</td>  
<td>

WP5

</td>  
<td>

EM

</td>  
<td>

New entry  2

(M15)

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

12

</td>  
<td>

Awareness creation, dissemination and stakeholder engagement

</td>  
<td>

WP6

</td>  
<td>

EFFoST

</td>  
<td>

Updated

(M15)

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

With the identified datasets of INNO-4-AGRIFOOD in mind, the current section
of the DMP provides meaningful information per each one, 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) and/or metadata to be created. 

  

  * Potential 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 stage of the project
(M15) and may be adapted and/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.

</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, providing their opinions about the needs of SMEs
with respect to innovation support and the opportunities for online
collaboration for innovation.

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

**Methodologies for data collection / generation**

</td>  
<td>

A semi-structured questionnaire was employed in order to collect qualitative
data during the interviews.

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

**Format and volume of the dataset**

</td>  
<td>

The dataset is stored within a .zip file which comprises of 7 distinct
documents stored in .docx formats. The total size of the (uncompressed)
dataset is 1.12 MB.

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

**Metadata and**

**standards**

</td>  
<td>

Each document of the dataset is accompanied by descriptive metadata including
title, author and keywords.

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

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

</td>  
<td>

The dataset provided INNO-4-AGRIFOOD consortium members with valuable
information from the perspective of agri-food stakeholders, fuelling and
complementing the agri-food value chain analysis conducted in the context of
the project.

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

**Confidentiality**

</td>  
<td>

The outcomes of the study that produced the dataset have been published
through the  _Agri-food Value Chain Analysis Report_ ,  already available at
the web portal of the project. The dataset itself, used only in the context of
the project, is not intended for sharing and/or re-use, with a view to
safeguarding the privacy of interviewees. With that in mind, the dataset is
now archived at the private server of the Coordinator (Q-PLAN) and will be
preserved for at least 5 years following the end of the project, before
eventually being deleted.

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

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

**Dataset name**

</th>  
<th>

Needs of agri-food SMEs in terms of online collaboration for innovation
support.

</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 dataset contains the responses (mostly qualitative) provided by
interviewees who participated in the study, addressing different aspects of
the current situation in the EU with respect to online collaboration for
innovation amongst SMEs in the agri-food sector as well as diverse topics
relevant to collaborating for innovation by employing online means (e.g.
specific attributes of platforms and tools needed for online collaboration,
support that SMEs may seek or need in this respect, etc.).

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

**Methodologies for data collection / generation**

</td>  
<td>

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

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

**Format and volume of the dataset**

</td>  
<td>

The dataset is stored in spreadsheet (.xls) and .pdf formats, both of which
contain the 52 replies derived from the interview-based survey. The size of
the dataset in .xls format is 0.17MB, while in .pdf it is 0.76MB.

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

**Metadata and**

**standards**

</td>  
<td>

Descriptive metadata (i.e. title, author and keywords) have been created to
accompany the dataset.

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

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

</td>  
<td>

The insights derived from the analysis of the data have been key in the
process of co-creating and developing the novel services and tools of
INNO-4-AGRIFOOD according to the needs of agri-food SMEs and their innovation
intermediaries.

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

**Confidentiality**

</td>  
<td>

The findings and conclusions of the study based on the processing and analysis
of the data within this dataset, have been openly shared through the  _Agri-
food SME_ _Profiling and Needs Analysis Report_ ,  which is published at the
web portal of INNO4-AGRIFOOD. The raw data collected through the interview-
based survey will not be shared and/or re-used (outside the framework of the
project and/or beyond its completion) to ensure the confidentiality of the
interviewees and their responses. Hence, the dataset, currently archived at
the private server of the Coordinator (QPLAN), shall be preserved for at least
5 years following the end of the project, before eventually being deleted.

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

##  Skills of innovation intermediaries in terms of supporting online
collaboration for innovation  
  
<table>  
<tr>  
<th>

**Dataset name**

</th>  
<th>

Skills of innovation intermediaries in terms of supporting online
collaboration for innovation.

</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 comprise predominantly quantitative responses provided by
the participants of the online survey, including demographic information as
well as their perceived level of skills (gauged via a 5-scale Likert scale) in
different skill areas, including agri-food industry, support services,
collaboration, innovation management and soft skills.

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

**Methodologies for data collection / generation**

</td>  
<td>

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

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

**Format and volume of the dataset**

</td>  
<td>

The dataset is stored in standard spreadsheet format (.xlsx). In total, 79
respondents from the EU filled in and successfully submitted a questionnaire.
The same number of records was collected and is now within the dataset. The
size of the dataset is 53KB.

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

**Metadata and**

**standards**

</td>  
<td>

The dataset is accompanied by descriptive metadata (i.e. title, author and
keywords).

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

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

</td>  
<td>

The dataset has been of great use to INNO-4-AGRIFOOD consortium members,
enabling them to unearth the insight required to set the stage for the need-
driven co-creation and development of the project’s e-learning curriculum and
modules.

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

**Confidentiality**

</td>  
<td>

The  _Skills Mapping and Training Needs Analysis Report_ ,  available at the
web portal of the project, provides public access to the findings of the study
in the frame of which this dataset has been produced. The records of the
database are available only to selected members of the INNO-4-AGRIFOOD project
team and are not intended for sharing and/or re-use, so as to ensure the
privacy of the study’s participants. The dataset itself is archived at the
private server of the Coordinator (Q-PLAN) and will be preserved for at least
5 years following the end of the project, before eventually being deleted.

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

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

**Dataset name**

</th>  
<th>

Outcomes of the INNO-4-AGRIFOOD Co-creation Workshop – E-learning.

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

**Type of study**

</td>  
<td>

The INNO-4-AGRIFOOD Co-creation Workshop which was held on the 15  th  of
September 2017 at Amsterdam, the Netherlands in order to co-create, along with
stakeholders of the agri-food ecosystem, the e-learning offer of
INNO-4-AGRIFOOD.

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

**Dataset description**

</td>  
<td>

The dataset generated encompasses the feedback as well as the innovative
concepts and ideas provided by participants of the INNO-4-AGRIFOOD Co-creation
Workshop during the structured activities of the co-creative session dedicated
to the e-learning offer of the project. The data is mostly textual (short
sentences) and refer to (i) the appropriateness of the e-learning material
developed at the time of the workshop and (ii) supplementary ideas for
consideration in the process of developing the e-learning material of the
project.

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

**Methodologies for data collection / generation**

</td>  
<td>

In addition to the minutes recorded throughout the co-creation workshop, the
participants’ input from the group discussions were tabulated for each of the
draft e-learning modules (which were provided as background information) using
preprepared templates. Comments of relevant consortium members on each module
were added remotely after the event. Conclusions were then drawn on the
content and weighting of elements within each module.

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

**Format and volume of the dataset**

</td>  
<td>

The data collected have been integrated within the report on the  _Outcomes of
the_ _INNO-4-AGRIFOOD Co-creation Workshop: Curriculum concept and key
training_ _topics_ .  The report is stored in .pdf format and its size is
1.08MB.

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

**Metadata and**

**standards**

</td>  
<td>

The report in which the dataset has been integrated includes meaningful
information with respect to the context in which the data have been collected
as well as the methodology for collecting them. The report itself is
accompanied with basic descriptive metadata including title and type of file.

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

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

</td>  
<td>

Innovation support service designers and 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>

The dataset has been openly shared through the public report on the  _Outcomes
of_ _the INNO-4-AGRIFOOD Co-creation Workshop: Curriculum concept and key
training_ _topics_ ,  which is available at the INNO-4-AGRIFOOD web portal.

</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.

</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 building upon
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 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 third-party 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 has been used to create the e-learning
material of the project, 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 this case-based 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
timely decided at a later stage of the project in consultation with the
Advisory Board of the project).

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

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

**Dataset name**

</th>  
<th>

Outcomes of the INNO-4-AGRIFOOD Co-creation Workshop – Services and tools.

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

**Type of study**

</td>  
<td>

The INNO-4-AGRIFOOD Co-creation Workshop, which was held on the 15  th  of
September 2017 at Amsterdam, the Netherlands with a view to co-creating
innovative ideas and designs for the innovation support services and smart
tools of the project, building upon the valuable contribution of diverse agri-
food stakeholders.

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

**Dataset description**

</td>  
<td>

The data include innovative concepts and ideas provided by the participants of
the workshop’s co-creative session that focused on the innovation support
services and smart tools of INNO-4-AGRIFOOD.

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

**Methodologies for data collection / generation**

</td>  
<td>

The data were collected during the INNO-4-AGRIFOOD Co-creation Workshop and
documented as transcript notes.

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

**Format and volume of the dataset**

</td>  
<td>

The data have been integrated into the report on the  _Outcomes of the
INNO-4AGRIFOOD Co-creation Workshop: Innovation support_ _services and ICT
tools_ ,  which is stored in .pdf format. The size of the file is 5.53MB.

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

**Metadata and**

**standards**

</td>  
<td>

The report in which the data have been incorporated provides insights into the
objectives and methodology of the INNO-4-AGRIFOOD Co-Creation Workshop,
elaborates on the outcomes of its session on the services and tools and
translates the aforementioned outcomes into meaningful conclusions and key
potential characteristics for innovation support services and tools. Basic
descriptive metadata are provided along with the report (i.e. title and type
of file).

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

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

</td>  
<td>

The dataset has contributed significantly in developing the services, smart
tools and e-learning modules of the project in line with the needs and
preferences of agrifood stakeholders in the context of INNO-4-AGRIFOOD. Beyond
the context of the project, innovation support service designers and providers
as well as ICT application developers and training providers could potentially
find the dataset and its accompanying report useful.

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

**Confidentiality**

</td>  
<td>

The report on the  _Outcomes of the INNO-4-AGRIFOOD Co-creation Workshop:_
_Innovation support services and ICT tools_ ,  which includes the dataset, is
already published and available at the web portal of the project.

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

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

**Dataset name**

</th>  
<th>

Pool of agri-food SMEs.

</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>

The dataset consists of 2 separate lists of agri-food SMEs which may be
interested in benefiting from the innovation support services of the project
in the framework of its 3 iterative testing, validation and fine-tuning
rounds. The 1  st  list includes SMEs which are either clients or among the
professional network of INNO-4-AGRIFOOD consortium partners, and to which
services may be delivered by these partners. The 2  nd  list includes SMEs who
have been identified through other channels (e.g. through the
INNO-4-AGRIFOOD’s Beneficiaries and Advisory Boards, the online contact form
of the project’s web portal, etc.), and to which services may be delivered by
external innovation consultants.

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

**Methodologies for data collection / generation**

</td>  
<td>

In addition to the professional networks of INNO-4-AGRIFOOD (1  st  list of
the dataset), several sources have been employed to identify suitable SMEs to
participate in the real-life deployment of the novel services and tools of the
project, including (among others) networks and member organisations of
INNO-4AGRIFOOD’s Advisory and Beneficiaries Boards as well as interested SMEs
which participated in the surveys launched in the context of the project or
expressed their interest through the online contact form of its web portal (2
nd  list of the dataset).

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

**Format and volume of the dataset**

</td>  
<td>

A spreadsheet (in .xlsx format) with two separate tabs (each for one of the
two lists described above) is used to store the Pool of agri-food SMEs, which,
by the end of the project, will contain at least 125 records. In fact, the
complete dataset will contain the following data for each recorded SME: (i)
Name of the SME; (ii) Contact person; (iii) Country, (iv) City, (v) Telephone
number; and (vi) E-mail address. In the case of the 1  st  list, information
about the INNO-4-AGRIFOOD consortium partner connected to a recorded SME will
also be included.

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

**Metadata and**

**standards**

</td>  
<td>

Descriptive and structural metadata may be created and provided at a later
stage of the project.

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

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

</td>  
<td>

The dataset would be most useful for consortium partners during the real-life
deployment activities of the project.

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

**Confidentiality**

</td>  
<td>

The dataset will be available only to relevant INNO-4-AGRIFOOD consortium
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.

</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 appropriately qualified SME consultants who may participate in the
testing of project’s services and tools by providing them to agri-food SMEs.
The Roster of Specialists Database (RSD) will encompass valuable information
about the recorded consultants, such as demographics and contact details of
themselves and their affiliated organisations, data about their progress
towards completing the project’s e-learning offer and providing its services
as well as miscellaneous data that can help INNO-4-AGRIFOOD consortium members
to better match them with appropriate agri-food SMEs to service.

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

**Methodologies for data collection / generation**

</td>  
<td>

The RSD will be populated with consultants who will have successfully
completed the INNO-4-AGRIFOOD e-learning courses addressing the project’s
services, participated in the project’s 1  st  webinar and/or have been
personally trained by a designated INNO-4-AGRIFOOD Coach. The database will be
enriched as the real-life deployment activities of INNO-4-AGRIFOOD progress
and the staff of innovation intermediaries and SME support networks gain
experience in the project’s services and e-learning modules.

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

**Format and volume of the dataset**

</td>  
<td>

The Roster of Specialists Database is stored in a standard spreadsheet format
and by the end of the project will comprise of at least 50 records of SME
consultants across the EU.

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

**Metadata and**

**standards**

</td>  
<td>

Descriptive and structural metadata may be created to accompany the dataset at
a later stage of the project.

</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 remain for internal use only during the lifecycle
of the project.

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

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

**Dataset name**

</th>  
<th>

Service testing metrics.

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

**Type of study**

</td>  
<td>

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

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

**Dataset description**

</td>  
<td>

The dataset includes data collected during the iterative testing, validation
and finetuning of the INNO-4-AGRIFOOD services and smart tools, aimed at
managing ambiguity during the various iterations as well as measuring the
impact of improvements after each iteration. In particular, it contains both
qualitative and quantitative data on (i) the satisfaction of SMEs that
received INNO-4-AGRIFOOD services, (ii) the satisfaction of SMEs and
innovation consultants that have used the INNO-4-AGRIFOOD smart tools, (iii)
the impact of the INNO-4-AGRIFOOD services on the business of the SMEs that
received them, (iv) the activities performed in the framework of each
INNO-4-AGRIFOOD service provided in the context of the project, and (v)
different aspects of the services and smart tools that can be further
streamlined according to users’ needs and expectations.

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

**Methodologies for data collection / generation**

</td>  
<td>

In line with the  _INNO-4-AGRIFOOD Metrics Model_ ,  this dataset will be
fuelled by the respective surveys that will run over the 3 real-life
deployment rounds of the project’s services and smart tools as well as by the
service stories that will be produced under this framework. All surveys will
employ questionnaire-based tools aiming at mining both qualitative and
quantitative data from agri-food SMEs and innovation consultants.

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

**Format and volume of the dataset**

</td>  
<td>

The dataset will employ a typical spreadsheet format. The volume of the
dataset’s final version will depend on the number of users that will
participate in the real-life deployment of the INNO-4-AGRIFOOD services and
smart tools.

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

**Metadata and**

**standards**

</td>  
<td>

Descriptive metadata will be provided (such as title, abstract, author, type
of data, data collection method and keywords).

</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 provided the necessary consent has been provided by
users who provided the data and any required anonymization has been performed.

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

##  User data and learning curve of e-learning participants  
  
<table>  
<tr>  
<th>

**Dataset name**

</th>  
<th>

User data and learning curve of e-learning participants.

</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>

The dataset contains demographic data of the people who have registered to the
e-learning platform of INNO-4-AGRIFOOD and their affiliated organisations
along with data reflecting their e-learning progress.

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

**Methodologies for data collection / generation**

</td>  
<td>

Data are provided voluntarily by the individuals who register to the
INNO-4AGRIFOOD e-learning platform through a dedicated online form which aims
at creating the profile necessary for their registration. Moreover, the
e-learning platform automatically collects all necessary data about the online
activities of the participants who access the system via a unique username-
password combination.

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

**Format and volume of the dataset**

</td>  
<td>

The dataset is stored in a MySQL database and exported to standard spreadsheet
format (.csv or other). At least 150 registered participants are expected to
be recorded within the dataset by the end of the project.

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

**Metadata and**

**standards**

</td>  
<td>

The dataset is not intended for sharing and re-use and thus will not be
accompanied by metadata.

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

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

</td>  
<td>

The dataset will be used by selected INNO-4-AGRIFOOD consortium members to
analyse the learning behaviour of the e-learning participants in the frame of
the project.

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

**Confidentiality**

</td>  
<td>

The data of e-learning participants will be confidential and used only in the
context of the project. With that in mind, the administrators of the
e-learning platform will have access to the data provided by e-learning
participants, apart from their password information (which will be known only
to the e-learning participants themselves). E-learning participants can
configure their profile indicating the open data they would like to share.
Still, the data of the participants’ learning curve (e.g. statistics on
accessing the e-learning, following existing material, concluding tests, etc.)
will be accessible only to the administrators of the e-learning platform as
well. Any meaningful analysis or conclusions drawn from these data will be
shared in relevant upcoming reports that will be produced by the project.

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

##  Feedback derived from e-learning participants  
  
<table>  
<tr>  
<th>

**Dataset name**

</th>  
<th>

Feedback derived from e-learning participants.

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

**Type of study**

</td>  
<td>

Testing, validation and fine-tuning of the e-learning environment.

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

**Dataset description**

</td>  
<td>

The dataset includes feedback on technical and content-wise aspects of the
elearning environment of INNO-4-AGRIFOOD (including the e-learning platform as
well as its constituent e-learning modules), gathered from e-learning
participants with a view to evaluating its functionalities, graphics and
content.

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

**Methodologies for data collection / generation**

</td>  
<td>

Data will be provided voluntarily by e-learning participants of
INNO-4-AGRIFOOD via dedicated questionnaire-based feedback forms. The
questionnaires utilised by the feedback forms employ the Likert scale (1 \-
Strongly Disagree to 5 - Strongly Agree) so that participants can quickly
provide their opinion on the functionalities and content of the different
e-learning modules as well as the platform as a whole.

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

**Format and volume of the dataset**

</td>  
<td>

The dataset is stored in a MySQL database and can be exported to standard
spreadsheet format (.csv or other). The volume of the final dataset will
depend on the number of people who will have provided their feedback on the
e-learning platform and/or its modules by the end of the project.

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

**Metadata and**

**standards**

</td>  
<td>

The dataset is not intended for sharing and re-use and thus will not be
accompanied by metadata.

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

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

</td>  
<td>

The dataset will be used by selected INNO-4-AGRIFOOD consortium members to
analyse user experience on the e-learning environment and thus provide the
basis for further improvement in the future iterations in the context of the
project.

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

**Confidentiality**

</td>  
<td>

In order to ensure the privacy of the participants who provided their
feedback, the records of the database will remain confidential. The
administrators of the elearning platform will have access to the feedback
provided, however they will not disclose that information to third parties.

</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>

Data 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 are being collected through the dissemination activity reports of
project partners regarding media products, events, external events, general
publicity, etc. Third party tools are being employed as well (e.g. Google
analytics, social media statistics, etc.).

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

**Format and volume of the dataset**

</td>  
<td>

The collected data are preserved in a spreadsheet format (.xlsx).

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

**Metadata and**

**standards**

</td>  
<td>

Descriptive metadata will be provided (such as title, type of data, data
collection method and keywords).

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

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

</td>  
<td>

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

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

**Confidentiality**

</td>  
<td>

All records will be openly shared.

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