#  Executive Summary

This document constitutes the initial version of the Data Management Plan
(DMP) and has been elaborated as a deliverable (D7.2) in the framework of the
INVITE project. INVITE aims at co-creating a better connected Open Innovation
(OI) ecosystem across Europe. It envisions an OI ecosystem in which knowledge
meaningfully flows across borders and is translated into marketable
innovations, bringing increased socioeconomic benefits to European citizens.

To this end, INVITE will co-design, pilot and demonstrate a suite of well-
tailored mechanisms, skill-sets and measures to be deployed by a pan-European
service platform, the Open Innovation Lab, with a view to better linking the
currently fragmented innovation systems of the EU by facilitating meaningful
cross-border knowledge flows; empowering EU businesses with the skill-sets
required to tap into Europe’s knowledgebase and turn it into value; and
increasing the participation of private investors in OI as well as
collaborative innovation projects.

The Open Innovation Lab will experiment with novel bottom-up collaborative
models of innovation and leverage OI support services and ICT tools to
stimulate and support OI across Europe, building a vibrant community of OI
actors and stakeholders (including academia, government, industry and civil
society) along the way. The valuable knowledge, evidence and experiences
gained through the experiments of the Open Innovation Lab will be diffused
across the EU so as to fuel their replication and scale-up for the benefit of
the European economy and society as a whole.

Under this light, it becomes evident that INVITE entails several activities
within its framework which involve the collection, production and /or
processing of data, with a view to generating meaningful insights that will
feed into the project and fuel the co-creation and delivery of truly demand-
driven and evidence-based results.

In this context, the initial version of INVITE’s DMP sets out the overall
methodological principles pertaining to the management of the data that that
will be collected, processed and/or generated in the framework of INVITE,
safeguarding sound, FAIR and ethical data management along the entire duration
of the project. Moreover, it provides a first, yet still meaningful overview
of INVITE’s datasets, as identified in this early stage of the project, along
with information on the specific methodology pertaining to their management on
a dataset by dataset basis.

The initial version of the DMP is the first of the three versions of INVITE’s
Data Management Plan to be produced in the course of the project and will
serve as living document. Along these lines, the DMP will be updated and
further elaborated during the project in order to reflect an accurate, up-to-
date and ultimately comprehensive plan for managing the data that will be
collected, and/or generated by the project across their entire life cycle,
both during and after the completion of INVITE.

#  Introduction

The current document, titled Data Management Plan – Initial Version (DMP), has
been elaborated within the framework of the **INVITE** project which has
received funding by the European Union’s Horizon 2020 Research and Innovation
programme under Grant Agreement No 763651.

INVITE is set on co-creating a well-connected European Open Innovation (OI)
ecosystem. It envisions an OI ecosystem in which knowledge meaningfully flows
across borders and is translated into marketable innovations, bringing
increased socio-economic benefits to EU citizens. To this end, INVITE will co-
design, pilot and demonstrate a pan-European service platform, the **Open
Innovation Lab** , aiming to better link the currently fragmented innovation
systems of the EU by facilitating meaningful cross-border knowledge flows;
empower EU businesses with the skill-sets required to tap into Europe’s
knowledge-base and turn it into value; and increase the participation of
private investors in OI and collaborative innovation projects.

The Open Innovation Lab will experiment with novel bottom-up collaborative
models of innovation and leverage **OI support services** and **ICT tools** to
stimulate and support OI across Europe, building a vibrant community of OI
actors and stakeholders (including academia, government, industry and civil
society) along the way. The valuable knowledge, evidence and experiences
gained through the experiments of the Open Innovation Lab will be diffused
across the EU so as to fuel their replication and scale-up for the benefit of
the European economy and society as a whole.

To this end, INVITE has brought together a well-balanced and complementary
**consortium** , that consists of **9 partners across 5 different European
countries** , as presented in the following table.

##  _Table 1: INVITE partners_  
  
<table>  
<tr>  
<th>

**No**

</th>  
<th>

**Name**

</th>  
<th>

**Short name**

</th>  
<th>

**Country**

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

1

</td>  
<td>

Q-PLAN INTERNATIONAL ADVISORS PC

</td>  
<td>

Q-PLAN

</td>  
<td>

Greece

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

2

</td>  
<td>

STEINBEIS INNOVATION GGMBH

</td>  
<td>

SEZ

</td>  
<td>

Germany

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

3

</td>  
<td>

EUROPE UNLIMITED SA

</td>  
<td>

E-UNLIMITED

</td>  
<td>

Belgium

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

4

</td>  
<td>

RTC NORTH LBG

</td>  
<td>

RTC NORTH

</td>  
<td>

United Kingdom

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

5

</td>  
<td>

NINESIGMA EUROPE BVBA

</td>  
<td>

NINESIGMA

</td>  
<td>

Belgium

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

6

</td>  
<td>

INTRASOFT INTERNATIONAL SA

</td>  
<td>

INTRASOFT

</td>  
<td>

Luxembourg

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

7

</td>  
<td>

CENTRE FOR RESEARCH AND TECHNOLOGY HELLAS

</td>  
<td>

CERTH/ITI

</td>  
<td>

Greece

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

8

</td>  
<td>

WIRTSCHAFTSFOERDERUNG REGION STUTTGART

</td>  
<td>

WRS

</td>  
<td>

Germany

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

9

</td>  
<td>

THE DURHAM, GATESHEAD, NEWCASTLE UPON TYNE, NORTH

TYNESIDE, NORTHUMBERLAND, SOUTH TYNESIDE AND

SUNDERLAND COMBINED AUTHORITY

</td>  
<td>

NELEP

</td>  
<td>

United Kingdom

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

In this context, **all partners of INVITE’s consortium will adhere to sound
data management** in order to ensure that the meaningful data that will be
collected, processed and/or generated throughout the duration of the project
are well-managed, archived and preserved, taking into account the  _Guidelines
on Data_ _Management in Horizon 2020_ .

Along these lines, the **objectives of this initial version of the DMP** are
to:

  * Provide an overview of the principles underpinning the data management methodology that will be employed with a view to safeguarding the sound management of the data to be collected, processed and/or generated in the framework of INVITE, while also making them Findable, Accessible, Interoperable and Re-usable (FAIR). 

  

  * Identify the data that will be collected, processed and/or generated during the project as well as present meaningful information on how they will be handled, the methodology and standards applied to each one as well as how they will be curated and preserved during and after the project (if applicable) on a dataset by dataset basis. 

  

With the above in mind, the initial version of **the DMP is** **structured in
4 distinct chapters** , as follows:

  * **Chapter 1** provides introductory information about the initial version of the DMP, the context in which it has been elaborated as well as about its objectives and structure. 

  

  * **Chapter 2** describes the principles that are applied in the framework of INVITE in order to safeguard the effective management of data across their entire lifecycle, in line with the guidelines of the Commission. 

  

  * **Chapter 3** presents a description of the data that will be collected, processed and/or generated, addressing important relevant aspects such as methodology and metadata as well as data sharing, archiving and preservation on a dataset by dataset basis. 

  

  * **Chapter 4** outlines concludes on the next steps of the project with respect to data management. 

  

Finally, the **Annex** of this document, includes the template for collecting
data management information per dataset in the framework of INVITE.

**The DMP is not a fixed document** . In fact, this is its **initial version**
and it will evolve during the lifespan of the project. In particular, the DMP
will be **further elaborated and updated twice throughout the duration of
INVITE** **(i.e. as D7.3 at M12 and as D7.4 at M36)** as well as ad hoc (if
necessary), in order to include new datasets, better detail and/or reflect
changes in the methodology applied or other aspects pertaining to the already
identified datasets (such as costs for making data FAIR, size of dataset,
metadata, etc.), 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 partners will update and enrich it when required.

#  Data management principles

This chapter of the DMP presents the **overall** **methodological principles**
**pertaining to data management** in the framework of INVITE. Further details
with respect to the specific methodology applied for each of the different
datasets to be collected, processed and/or generated over the course of INVITE
(as identified in this early stage of the project) are provided in Chapter 3.
With that in mind, the DMP’s second chapter starts by providing a general
summary of the data to be collected, processed and/or generated by the project
as well as their types and versioning. It proceeds and concludes by presenting
the overall approach employed for making data FAIR, ensuring data security and
ultimately taking into account ethical aspects in this context.

##  Data Summary

INVITE will produce several datasets during the lifetime of the project. The
data included within these **datasets may be quantitative, qualitative or a
blend** of those in nature and will be **analysed from a range of
methodological perspectives** with a view to producing meaningful insights
that will feed the activities of the project and fuel the delivery of
evidence-based results. These datasets will be **available in a variety of
easily accessible formats** , including post scripts (e.g. pdf, xps, etc.),
spreadsheets (e.g. xlsx, csv, etc.), text documents (e.g. docx, rtf, etc.),
compressed formats (e.g. rar, zip, etc.) or any other format required
depending on the objectives and methodology of the activity within the frame
of which they are produced.

Moreover, in order to facilitate the reference of the datasets that will be
collected and/or generated during INVITE, a **standard naming and versioning
structure** will be employed, as follows:

**INVITE _ [Name of Study] _ [Issue Date]**

  * **INVITE:** The name of the project. 

  

  * **Name of Study:** A short version of the name of the study for which the dataset is created. 

  

  * **Issue Date:** The date on which the latest version of the dataset was modified (DD.MM.YYYY). 

  

With the above in mind, some **indicative examples** to showcase the naming
structure applied in the context of INVITE are provided below:

  * **INVITE_Needs &Requirements_31.10.2017 – ** A dataset generated within the framework of the survey conducted to identify the needs and requirements of diverse open innovation stakeholders. This is the version of the dataset that was last modified on the 31  st  of October 2017 (31/10/2017). 

  

  * **INVITE_BMValidation_01.02.2018 –** A dataset created in the process of validating and improving the business models developed for the Open Innovation Lab with a view to feeding the elaboration of the business plan that will guide its market rollout beyond the end of the project. The last modification of this dataset was on the 1  st  of February 2018 (01/02/2018). 

  

##  FAIR data principles

The  _Guidelines on Data Management in Horizon 2020_ of the Commission
emphasise the importance of making the data produced by projects funded under
Horizon 2020 **Findable, Accessible, Interoperable as well as Reusable
(FAIR)** , with a view to ensuring their sound management. This means using
standards and metadata to make data discoverable, specifying the data sharing
procedures and which data will be open, allowing data exchange via open
repositories as well as facilitating the reusability of the data. With that in
mind, the following sections of the DMP lay out the principles followed in the
framework of INVITE with respect to the standards and metadata required to
make data findable, the sharing procedures foreseen to make the data
accessible and safeguard their interoperability as well as ensure their
preservation and open access, making them easily reusable by interested
stakeholders.

###  Standards and Metadata

Any open datasets produced by INVITE 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.

###  Sharing, Re-use and Interoperability

The Project Coordinator (Q-PLAN) in collaboration with the respective Work
Package Leaders (WPL) and any other involved project partners, will determine
whether and how the data collected and/or produced in the framework of
INVITE’s different activities will be shared and/or re-used either by other
project partners or by external interested stakeholders, within and without
the framework of the project. 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). An informed consent form will
be requested from all external data providers in order to allow for their data
to be analysed and shared, while all such data will be anonymised before
sharing (for more details in this respect see Section 2.4 of the current
document).

###  Preservation and Open Access

Any datasets that will be deemed open for sharing and re-use 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  (
_www.zenodo.org_ )  as one of the best online and open services to enable open
access to INVITE’s 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.

##  Data security

INVITE will handle any collected / generated data securely throughout their
entire lifecycle. In this context, the project partner responsible for
collecting / generating, processing and/or storing the data will ensure that
they are protected and any necessary data security controls have been
implemented, so as minimize the risk of information leak and destruction.
Overall, data will be stored within the private server of the project partner
responsible for the respective dataset and will be backed-up frequently to
ensure their security.

##  Ethical aspects

INVITE entails activities which involve the collection of meaningful data from
selected individuals (e.g. interviews with users and stakeholders of the Open
Innovation Lab, 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 as well
as with relevant national regulations and laws. The participants’ right to
control their personal information will be respected at all times (including
issues of confidentiality). The Project Coordinator (Q-PLAN) will regulate and
deal with any ethical issue that may arise during the project in this respect,
in cooperation with the Steering Committee of the project.

The ethics aspects pertaining to the collection and processing of data in the
framework of INVITE will be addressed in further detail within the ethics
deliverables of the project namely “D8.1: H - Requirement No.

1” and “D8.2: POPD - Requirement No. 2”, both due for M6 of the project.

#  Data management plan

##  Overview

INVITE places special emphasis on the management of the valuable data that
will be collected and/or generated throughout its activities. In this respect,
the table below provides a list of the datasets identified by INVITE
consortium members at this stage of the project, indicating the name of the
dataset, its linked Work Package and the respective leading consortium member
(i.e. Work Package Leader).

###  Table 2: List of INVITE datasets  
  
<table>  
<tr>  
<th>

**No**

</th>  
<th>

**Dataset Name**

</th>  
<th>

**Linked**

**Work**

**Package**

</th>  
<th>

**Work Package**

**Leader**

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

1

</td>  
<td>

Market gaps and opportunities

</td>  
<td>

WP1

</td>  
<td>

CERTH/ITI

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

2

</td>  
<td>

User needs and requirements

</td>  
<td>

WP1

</td>  
<td>

CERTH/ITI

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

3

</td>  
<td>

Co-creation workshop outcomes

</td>  
<td>

WP1

</td>  
<td>

CERTH/ITI

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

4

</td>  
<td>

Pilot monitoring, co-evaluation and validation

</td>  
<td>

WP3

</td>  
<td>

RTC NORTH

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

5

</td>  
<td>

Open Innovation Lab user data

</td>  
<td>

WP3

</td>  
<td>

RTC NORTH

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

6

</td>  
<td>

Business model validation and improvement

</td>  
<td>

WP4

</td>  
<td>

Q-PLAN

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

7

</td>  
<td>

Dissemination and communication results

</td>  
<td>

WP6

</td>  
<td>

E-UNLIMITED

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

With the above in mind, **the current chapter provides meaningful information
per each dataset** , including:

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

  

  * A concise description of the dataset as well as its format and volume. 

  

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

  

  * 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. 

  

**The information provided within this section reflects the current views and
plans of INVITE at this early stage of the project (M3) and will be further
elaborated** **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.

##  Market gaps and opportunities (WP1)  
  
<table>  
<tr>  
<th>

**Dataset name**

</th>  
<th>

Analysis of Market Gaps and Opportunities (INVITE_Gaps&Opportunities).

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

**Type of study**

</td>  
<td>

This study involves an evaluation of three existing Open Innovation (OI)
platforms/service providers: Enterprise Europe Network (EEN), NineSigma and
Steinbeis. The data that supports this evaluation will be collected in two
phases. Phase 1 involves a desk review of secondary data sources that are in
the public domain, whereas Phase 2 involves a series of semi-structured
interviews with 6-8 respondents who work for either an EEN consortium member,
NineSigma or Steinbeis for the Open Innovation Lab.

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

**Dataset description**

</td>  
<td>

The data collected will consist of a combination of information extracted from
the secondary data sources and information provided by the respondents during
the depth interviews. In both cases, the data collected will be mainly of a
qualitative nature and will be recorded in plain text in English. Both the
secondary and primary data sources will be used as the basis of a report which
will summarise the strengths and weaknesses of the three existing OI
platforms/service providers and identify potential market gaps and
opportunities.

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

**Methodologies for data collection / generation**

</td>  
<td>

A semi-structured interview guide will be used to collect the data during the
depth interviews. The interviews will be conducted face-to-face, by telephone
or via Skype/WebEx (or similar online videoconferencing application).

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

**Storage and volume of the dataset**

</td>  
<td>

In the case of the secondary data sources, copies of the data will not be
stored. However, references and/or web links to the data sources consulted
will be included as an appendix to the final report. In the case of the
primary data collected during the depth interviews, the dataset will be stored
in standard Word format (.docx) on RTC NORTH’s in-house server and will be
preserved for 5 years following the end of the project, before eventually
being deleted. For security reasons, the dataset will be backed up at the end
of each night on removable tape and will be stored in a fireproof safe.

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

**Metadata and standards**

</td>  
<td>

The dataset will be accompanied with basic descriptive metadata (i.e. title,
author, date created and keywords).

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

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

</td>  
<td>

The dataset will be used by INVITE partners to help design and pilot the Open
Innovation Lab, based on the needs and requirements of a range of open
innovation stakeholders.

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

**Confidentiality**

</td>  
<td>

The primary data collected via the depth interviews will not be shared and/or
reused (outside the framework of the project and/or beyond its completion) to
ensure the confidentiality of the interviewees and their responses.

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

##  User needs and requirements (WP1)  
  
<table>  
<tr>  
<th>

**Dataset name**

</th>  
<th>

Analysis of user needs and requirements (INVITE_Needs&Requirements)

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

**Type of study**

</td>  
<td>

This qualitative study to be conducted in the framework of INVITE will follow
an interview-based survey of user needs and requirements. In particular, a
stratified, purposeful sampling will be employed, in order to include diverse
stakeholders of a quadruple helix innovation system (e.g. private sector,
academic organisations & research institutes, governmental and public services
and civil society), and aimed at revealing their views regarding Open
Innovation practices across Europe and informing the demand-driven development
of INVITE’s Open Innovation Lab. In this case, the sample will be stratified
in the sense that participants will vary according to stakeholder sector and
level of engagement and purposeful as sample participants will be recruited
through key organizations/businesses, which the project partners will identify
as impactful to the project’s expected outcomes.

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

**Dataset description**

</td>  
<td>

The data collected will contain the responses (mainly qualitative – plain text
in English) provided by interviewees who will participate in the interview-
based survey, addressing their different views of the current state-of-play in
Open Innovation across Europe. No secondary data or other third-party sources
will be used.

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

**Methodologies for data collection / generation**

</td>  
<td>

Data will be collected via semi-structured questionnaires administered to
study participants in the frame of interviews. Participants are to be
recruited from all actors of the quadruple helix and invited to participate in
the interviews over the phone, e-mail, or a face-to-face meeting.

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

**Format and volume of the dataset**

</td>  
<td>

Private versions of the dataset will be accommodated at the data management
portal created and maintained by CERTH/ITI, while links to the portal will
exist at the INVITE website with access restricted to the INVITE partners. The
dataset, comprised of interview responses, will be stored in standard
spreadsheet format (.xlsx). At least 50 interviews will be conducted across
Europe and the same number of records will be collected and stored in the
dataset. Furthermore, in order to avoid data losses, RAID and other common
backup mechanisms will be utilized ensuring data reliability and performance
improvement. The archiving system of CERTH/ITI will contain the initial data
as sent to the INVITE repository. The dataset will remain at the data
management portal for the whole project duration, as well as at least 2 years
after the end of the project. The volume of data is estimated to be
approximately 10 MB for all interview responses collected and the analysis
report submitted. Finally, after the end of the project, the portal is going
to be accommodated with other portals at the same server for 5 years following
the end of the project, before eventually being deleted, so as to minimize the
cost of

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

</td>  
<td>

maintenance. For security reasons, the dataset will be backed up in an
external hard-drive every month.

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

**Metadata and standards**

</td>  
<td>

Basic descriptive metadata (such as title, author, date created and keywords)
will accompany the dataset.

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

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

</td>  
<td>

The dataset will be used by CERTH/ITI in order to analyse and extract the
topics of interest that will inform INVITE partners in the process of
designing the INVITE Cocreation Workshop and ultimately the first version of
the Open Innovation Lab according to the needs and requirements of open
innovation stakeholders.

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

**Confidentiality**

</td>  
<td>

The dataset will remain confidential. Participant names will be protected and
replaced by an abbreviated version of their sector, a sequential two-digit
number and the initials of the project partner who conducted the interview
(e.g. ARxxQPLN for Academia/Research sector, PSxxQPLN for Public Sector,
BSxxQPLN for the Private Sector, CSxxQPLN for Civil Society Sector, where xx
is a sequential two-digit number corresponding to the interviewee). 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.

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

##  Co-creation workshop outcomes (WP1)  
  
<table>  
<tr>  
<th>

**Dataset name**

</th>  
<th>

Co-creation workshop outcomes (INVITE_Co-creation).

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

**Type of study**

</td>  
<td>

A co-creation workshop whereby all invited participants will explore and
provide feedback on the various aspects and features of the Open Innovation
Lab to be cocreated.

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

**Dataset description**

</td>  
<td>

A record of feedback and suggestions expressed by participants of the
workshop.

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

**Methodologies for data collection / generation**

</td>  
<td>

All participants will be introduced to a series of ideas and concepts and
along with them INVITE partners will co-create and conclude on user-driven
characteristics for the Open Innovation Lab and interconnected pilot programme
of the project. Different workshop sessions will be dedicated to discussing
and co-creating the different components of the Open Innovation Lab (i.e.
service, capacity building and ICT components) while at the same time
collecting interesting ideas and feedback with respect to the design of INVITE
pilots. Participants will be engaged in creative brainstorm and ideation
sessions that will also include gamified exercises, which will serve as ice
breakers allowing them to get to know each other better, break down their
inhibitions and thus unlock their imagination. Simple illustrators will be
employed to visually capture ideas and help them grow into concrete concepts.

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

</td>  
<td>

These will be recorded and be made available to INVITE partners for the design
of the Open Innovation Lab.

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

**Format and volume of the dataset**

</td>  
<td>

In the case of the primary data collected, including feedback and ideas
resulting from the co-creation process, the dataset will be stored in standard
Word format (.docx) on RTC NORTH’s in-house server and will be preserved for 5
years following the end of the project, before eventually being deleted. For
security reasons, the dataset will be backed up at the end of each night on
removable tape and will be stored in a fireproof safe.

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

**Metadata and standards**

</td>  
<td>

The dataset will be accompanied with basic descriptive metadata (i.e. title,
author, date created and keywords).

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

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

</td>  
<td>

The dataset will be used by INVITE partners to help better design and shape
the Open Innovation Lab to its users, based on the resulting feedback and
ideas of the co-creation workshop participants.

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

**Confidentiality**

</td>  
<td>

The primary data collected via the co-creation workshop 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 participants and their
contributions.

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

##  Pilot monitoring, co-evaluation and validation (WP3)  
  
<table>  
<tr>  
<th>

**Dataset name**

</th>  
<th>

Pilot monitoring, co-evaluation and validation (INVITE_PilotMCV)

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

**Type of study**

</td>  
<td>

The study will involve deploying the pilots of INVITE through the Open
Innovation Lab in two rounds, in order to address the needs of users and
stakeholders of the open innovation ecosystem as well as to collect data and
feedback from them, so as to improve and fine tune the design of the pilots
and the Open Innovation Lab.

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

**Dataset description**

</td>  
<td>

Data and feedback provided by users (mainly SMEs) and other stakeholders
participating in the pilots of INVITE based on a custom-made multi-layer
framework for monitoring the operation, performance and results of the pilots.
Indicative core themes to be monitored and measured include the integration of
open innovation in the users’ business model, external knowledge and
technology search and acquisition, collaboration with other stakeholders,
occasional vs continuous engagement in open innovation activities, disruptive
vs incremental innovation, internal innovation capability, time-to-market,
level of proficiency gained in collaborative innovation, scale achieved in
terms of outreach (volume, sectoral and geographical), fundraising capacity,
staff impact, organizational impact, costbenefit and overall satisfaction.
Moreover, the dataset will include qualitative data

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

</td>  
<td>

on the perceived most significant change which pilots have brought about
within the organizations of pilot users.

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

**Methodologies for data collection / generation**

</td>  
<td>

Users and stakeholders who will participate in the pilots will be required to
provide feedback as part of the ongoing monitoring framework that will be
established to keep track of the performance and results of the pilots through
a semi-structured questionnaire designed to mine both qualitative and
quantitative and administered via a blend of face-to-face, telephone and/or
digital means.

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

**Storage and volume of the dataset**

</td>  
<td>

The dataset will be stored in either standard Word (.docx) or standard Excel
(.xlsx) format on RTC NORTH’s on-premise server and will be preserved for 5
years following the end of the project, before eventually being deleted. For
security reasons, the dataset will be backed up at the end of each night on
removable tape and will be stored in a secure place.

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

**Metadata and standards**

</td>  
<td>

The dataset will be accompanied with basic descriptive metadata (i.e. pilot
description, pilot participant name, organisation, etc.).

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

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

</td>  
<td>

The dataset will be used by INVITE partners to validate and fine-tune the Open
Innovation Lab with the help of its Advisory Board members, based on the needs
and requirements of a range of open innovation users and stakeholders who will
have taken part in its interconnected pilot programme. Moreover, the dataset
would be useful for open innovation intermediaries as well as (e-)training
providers who design and/or offer relevant open innovation services.

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

**Confidentiality**

</td>  
<td>

The data and feedback collected 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 pilot programme participants and their input into the
iterative pilot deployment, validation and fine-tuning phase. Still, some
selected meaningful and properly anonymised aggregated data and results from
pilot activities will be integrated within the INVITE Replication and Scale-up
Guide that will be openly disseminated, with a view to providing interested
stakeholders with insights and practical guidelines on how to replicate the
results of INVITE within their context.

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

##  Open Innovation Lab user data (WP3)  
  
<table>  
<tr>  
<th>

**Dataset name**

</th>  
<th>

Open Innovation Lab user data (INVITE_OI2Labdata)

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

**Type of study**

</td>  
<td>

Study aimed at informing the validation and fine-tuning of the Open Innovation
Lab and its ICT infrastructure (including the online collaborative space, open
multi-sided marketplace, crowdfunding tool and e-learning environment) as well
as of the business models designed to guide its market rollout and scale up.

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

**Dataset description**

</td>  
<td>

The dataset will contain demographic data of the users registered to Open
Innovation Lab as well as data stemming from the use of the functionalities
offered by the ICT tools integrated within its platform.

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

**Methodologies for data collection / generation**

</td>  
<td>

Users and stakeholders wishing to employ the ICT tools of the Open Innovation
Lab will be required to provide basic data through a dedicated online
registration form built-in the ICT infrastructure to be implemented by
INTRASOFT. Moreover, the platform will automatically keep track of all
necessary data pertaining to the online activities of the users who will
access the Open Innovation Lab via their unique username-password combination.

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

**Storage and volume of the dataset**

</td>  
<td>

The data collected will be stored on a secure database to be employed by the
ICT infrastructure of the Open Innovation Lab. INTRASOFT will be the main
responsible partner to manage the server and to assign specific user roles
with access and administration privileges. Administration privileges can be
assigned only to the consortium members. There will be a secure environment
per user, in order to guarantee the integrity of the user’s personal data.

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

**Metadata and standards**

</td>  
<td>

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

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

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

</td>  
<td>

The dataset will be used by INVITE consortium members to gain insights,
analyze and improve the experience of users within the ICT infrastructure of
the Open Innovation Lab and thus provide the evidence required to fuel its
demand-driven validation and fine-tuning.

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

**Confidentiality**

</td>  
<td>

In order to ensure the privacy of the users of the Open Innovation Lab as well
as safeguard the project partners’ commercial interests in view of its post-
project market roll-out, the dataset will remain confidential. The data will
not be shared and/or reused outside the framework of the project and/or beyond
the time of its completion.

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

##  Business model validation and improvement (WP4)  
  
<table>  
<tr>  
<th>

**Dataset name**

</th>  
<th>

Business model validation and improvement (INVITE_BMCValidation).

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

**Type of study**

</td>  
<td>

A study blending both quantitative and qualitative elements based on an
interviewbased survey of users and stakeholders participating in the pilot
activities of the Open Innovation Lab as well as members identified as
potential early adopters and lead users from the Advisory Board of the
project. The main target of the study is to validate and improve the business
models developed for the Open Innovation Lab with a view to feeding the
elaboration of the business plan that will guide its market rollout beyond the
end of the project.

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

**Dataset description**

</td>  
<td>

The dataset will be comprised of both qualitative as well as quantitative data
regarding the different elements (e.g. revenue streams, value propositions,
collaborators, etc.) of the business models designed for the Open Innovation
Lab.

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

**Methodologies for data collection / generation**

</td>  
<td>

Data will be collected via interviews utilising semi-structured questionnaires
that will balance the flexibility of open-ended questions and the focus of
restricted ones that can be easily quantified. The questionnaires will be
administered either faceto-face or via electronic means of communication (e.g.
web conferencing apps, telephone, etc.).

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

**Storage and volume of the dataset**

</td>  
<td>

The dataset will be stored in a simple spreadsheet format (such as .xlsx or
similar) which will be kept at the private server of Q-PLAN. The number of the
records within the dataset will depend on the methodology which will be
designed at a later stage of the project and utilised in the framework of the
study. For security reasons, the dataset will be backed-up on a daily basis
automatically from Q-PLAN’s server in an external hard disk drive owned by the
company and kept in its premises.

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

**Metadata and standards**

</td>  
<td>

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

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

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

</td>  
<td>

The dataset will be of great use to INVITE consortium members, enabling them
to validate and refine the business models of the Open Innovation Lab, paving
the way for its commercial exploitation after the completion of the project.

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

**Confidentiality**

</td>  
<td>

In order to ensure the privacy of the study’s participants as well as
safeguard the project partners’ commercial interests that may arise from the
exploitation of the Open Innovation Lab, the dataset will remain confidential.
The data will not be shared and/or reused outside the framework of the project
and/or beyond the time of its completion.

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

##  Dissemination and communication results (WP6)  
  
<table>  
<tr>  
<th>

**Dataset name**

</th>  
<th>

Dissemination and communication results (INVITE_Dissemination).

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

**Type of study**

</td>  
<td>

Study aimed at monitoring and assessing the results of the different
dissemination and communication activities of the project using an appropriate
framework with quantitative metrics.

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

**Dataset description**

</td>  
<td>

Data collected with a view to measuring and assessing the results of the
project in terms of dissemination and communication with measurable metrics
tailored to the different respective channels and tools employed as well as
the activities deployed.

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

**Methodologies for data collection / generation**

</td>  
<td>

Primary data will be collected through the dissemination activity reports of
project partners regarding media products, project events, external events,
general publicity, etc. Third party tools will be employed as well (e.g.
Google analytics for metrics related to the website, social media statistics,
information reported by the partners about published articles in media,
outreach at third party events etc.). Only aggregated data will be collected
in this dataset.

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

**Storage and volume of the dataset**

</td>  
<td>

The dataset will be stored in standard spreadsheet format (.xlsx) and its size
will evolve throughout the course of the project. Moreover, the dataset is
being kept at the private server of the project’s Dissemination Manager
(E-UNLIMITED) and will be shared with the project partners for reporting and
progress assessment purposes. It will be preserved for 5 years following the
end of the project, before eventually being deleted and for security reasons,
it will be backed up in an external hard-drive every week.

</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 will be used by INVITE partners for reporting and progress
assessment purposes. The data might also be used for dissemination purposes to
promote achievements of the project.

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

**Confidentiality**

</td>  
<td>

The raw data collected will not be shared and/or re-used (outside the
framework of the project and/or beyond its completion). Still, some selected
anonymous extracts might be included in project reports and deliverables which
are public and therefore become publicly available. No personal information
shall be included in the dataset and therefore no personal information shall
be made public.

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

#  Conclusions and way forward

This initial version of INVITE’s Data management Plan (DMP) has set the stage
for the implementation of a sound data management methodology in the framework
of INVITE. To this end, it has laid out the overall methodological principles
to be followed by project partners in this respect with a view to making the
data which they will collect, process and or generate as FAIR as possible,
while also taking into account data security and ethical aspects.

Moreover, it has provided an initial, yet still meaningful overview of the
valuable datasets that are expected to be created within the context of the
project along with a description of each dataset emphasizing the methodology
to be followed for their management during the lifespan of the project and
beyond. The information provided in this respect will be enriched as the
activities of the project progress to provide a more accurate description at
later stages of INVITE’s implementation.

Indeed, the DMP is a living document to be updated throughout the course of
INVITE based on the latest developments and available project results. In
fact, its initial version will serve as the basis for producing two
additional, further elaborated versions, on M12 and M36 of the project, with a
view to delivering an accurate, up-to-date and comprehensive data management
plan before the completion of INVITE.