#  Executive Summary

The purpose of this Data Management Plan (DMP) is to provide an analysis of
the main data foreseen to be generated in the course of the project and to
describe the data management policy that will be applied by CPSELabs. The
project consortium fully supports the endeavour to improve access to
scientific information and research data and will make information and data
generated within the project available on a voluntary basis, whenever
possible.

CPSELabs pursues the goal to contribute to establishing an open eco-system,
and the project plan has been conceived to broadly disseminate the project
findings and to contribute to the generation of broader knowledge in the
field. Therefore, the vast majority of the project deliverables are public,
containing information and data that can be used or re-used by various target
groups.

A variety of data and information will also be generated in CPSELabs
experiments, which involve ‘third parties’ through ‘cascading funding’.
CPSELabs perceives it as its’ role to accompany the third parties in aspects
of data management supporting open access of the generated research results,
along with publications, so they can be easily discovered, identified and re-
used, whenever possible.

#  Introduction and Context

As stated in the _‘Guidelines on Open Access to Scientific Publications and
Research Data in Horizon 2020’_ , fuller and wider access to scientific
publications and data helps to:

  * build on previous research results (improved quality of results) 

  

  * foster collaboration and avoid duplication of effort (greater efficiency) 

  

  * accelerate innovation (faster to market = faster growth) 

  

  * involve citizens and society (improved transparency of the scientific process) 

  

The CPSELabs consortium fully supports the endeavour to improve access to
scientific information and research data in order to enhance the benefits of
public investment. Especially, if the information and data have been derived
with the help of public funding, CPSELabs agrees, that this should benefit
European companies and citizens to the full.

The Open Research Data Pilot, aims to improve and maximize access to and re-
use of research data generated by projects. As defined in the guidelines,
openly accessible research data can typically be accessed, mined, exploited,
reproduced and disseminated free of charge for the user.

The CPSELabs project participates in the ‘Open Research Data Pilot’ and will
make its research data available on a voluntary basis, whenever possible.

The role of this Data Management Plan (DMP; D1.6), is to drive the policy
towards providing open access to the data generated in the scope of the
CPSELabs project, along with publications and other project results, so they
can be easily discovered, identified and re-used.

#  Project Goals and Implications on Data Sharing

A variety of data and information will be generated in CPSELabs, ranging from
interview outcomes, guidelines and best practices to software artefacts and
(raw) sensor data.

Whereas a part of that data will be generated by the consortium itself, and
will be made freely available via the website and public deliverables, much of
the data that could be categorized as ‘digital research data’ will be
generated in conjunction with ‘third parties’, participating via cascading
funding. (A part of the CPSELabs project funding is used to involve project
external ‘third parties’ through open calls in ‘experiments’.)

A major goal of the project is to build an open eco-system supporting the
whole stakeholder community (from CPS developers, integrators, and suppliers
to users), to enhance technology transfer by providing existing open platforms
and tools for application experiments and to enable stakeholders to benefit
from use and re-use of experiences, data and information.

A second major aim of the project is to efficiently involve SMEs and mid-caps
(as third parties), to help them in the development and commercialization
efforts of CPS enabled/related technologies and products (through open call
experiments) and with this increase European competitiveness.

While in the first case, opening information and data is well in-line with the
project goal, in the second case, sharing of data and information might
jeopardize the endeavour of exploiting and commercializing the results or
products developed in CPSELabs experiments with third parties.

In the course of the project, the CPSELabs consortium will have to carefully
consider and agree with the third parties on a case-by-case basis if, how and
to what extent data can be shared. Especially in the following cases, above
others, the collected/generated data will not be shared:

  * if the results can be expected to be commercially or industrially exploited by the project partners or third parties (or if sharing would contradict intellectual property rights and commercial exploitation in any way); 

  

  * if sharing would jeopardize efficient the involvement of SMEs; 

  

  * if incompatible with the need for confidentiality in connection with privacy-related or securityrelated issues; 

  

  * if incompatible with existing rules concerning the protection of personal data ; 

  

  * if incompatible with existing rules concerning ethical issues. (In the project’s ethical report, the consortium has clearly defined how sensitive / personal data will be treated.) 

  

#  Data Generation and Management in the Scope of CPSELabs

The CPSELabs partners expect that most likely it will be mostly software
artefacts that are being produced (mainly within the third parties
experiments), rather than true research data. The latter includes simulated
data that can be used to test physical systems based on a simulation platform
that will be made available on an open source basis. Moreover, performance
analysis data, based on several configurations of the platform or systems
based on the Design Centre platform may provide a basis for decision making
for other third parties. More explicitly, the generated data within the third
parties experiments might include:

  * open-source software, either as standalone tools, or as libraries/plugins extending other existing (not necessarily open source) tool sets; 

  

  * experimental artefacts like use case descriptions, exemplary analysis or design models, exemplary analysis results 

  

  * descriptions of domains, co-models, descriptions of metrics used, tool extension data 

  

  * experimental sensor data sets (anonymized, if required) to repeat executed experiments 

  

  * reports on executed experiments, public deliverables synthesizing the experiments; and scientific publications 

  

  * reports on best practices using the Design Centre platforms 

  

Next to this, the Design Centres will yield other data, such as results of
interviews carried out with stakeholders in the context of eco-system
analysis, needs in professional training, measurement data on performance of
the Design Centres (in terms of KPI) and summary data related to literature
surveys (coded sources, categorizations, etc.). Moreover, results will include
information like contributions to the contacts database and information and
data on the Open Call content, process, outcome and response.

More explicitly, the information captured and data generated by the project
partners with the help of interviews, surveys and other investigations with
project internal and external participants will derive, among others:

  * overview of existing innovation practices and opportunities in innovation eco-systems 

  

  * inventory of existing professional training, good practices and effects 

  

  * investigation of needs for professional training as perceived by relevant stakeholders 

  

  * overview of CPS areas of relevance for stimulating innovation by means of Market Places 

  

(MP’s) including an overview of existing MP’s and best practices of MP’s

  * stakeholder needs and considerations for the MP pilots within CPSELabs 

  

  * information on open call process, (including FAQs), outcome, statistics, feedback 

  

A very important factor for sharing information and data within the CPSELabs
project is, as described above, by what means and with which aim this data is
generated. This can be sub-divided into two categories:

  1. Data collected / generated by the project consortium, with the aim of broad dissemination 

  

  2. Data generated by / with the third parties in the scope of open call experiments 

  

  

As these categories differ substantially, they will be described in two
separate sub-chapters.

##  Data and Information generated and shared by the Consortium

As CPSELabs pursues the goal to contribute to establishing an open eco-system
supporting the whole community of stakeholders, the vast majority of the
projects deliverables are public, containing information and data that can be
used or re-used by different target groups. Besides being publicized via the
CPSELabs website, the documents will be spread via the CPSElabs partners
networks. The following table gives an overview on a selection of the CPSELabs
(planned) public deliverables, conceived to broadly disseminate the projects
findings and contribute to the generation of broader knowledge in the field.
The table below lists the documents per work package (WP), deliverable number
(Del) and contains the publicizing month (M); M1 corresponds to February 2015.
A brief information is given on the type of data and the target group. More
detailed information in terms of information / data content, can be obtained
from the deliverables themselves.  
  
<table>  
<tr>  
<th>

**WP**

**Del**

</th>  
<th>

**Document name, Publicizing month**

</th>  
<th>

**Data / type of information**

**Target group for (re-) use**

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

**WP1 Project Management**

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

D1.6

</td>  
<td>

‘Collaboration plan with other Smart Anything Everywhere projects’ (M2)

</td>  
<td>

The public deliverable provides a shared vision of the current SAE
coordinators/teams on collaboration within and future evolvement of the SAE
initiative.

(Targeted to SAE stakeholders, EC, policy makers)

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

**WP2 Communication and Outreach**

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

D2.1

D2.2

D2.4

</td>  
<td>

‘Web portal’ (M2)

‘Communication Plan’ (M3, 12, 18, 24, 30, 36)

‘Public Materials’ (M3)

</td>  
<td>

The data/information provides detailed information on the CPSELabs Design
Centres and their ‘open tools and platforms’, the CPSELabs Vision as well as
practical information and guidance for applicants of the open call process
(e.g. FAQs).

(Targeted to experiment proposers, stakeholders of the CPS ecosystem, broad
public)

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

**WP3 Open Call Process for Experiments**

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

D3.1

D3.3

</td>  
<td>

‘Open Call Process

Documents’ (M3)

‘Call Texts’ (M3, 9, 15)

</td>  
<td>

Information on the open calls content and the process: The data/information
provides detailed information and guidance on structuring and handling of the
open call process. Next to giving guidance to proposers and evaluators, these
documents provide ‘re-usable’ information on the call process and templates
for future open-call projects.

(Targeted to experiment proposers, evaluators, EC, other projects with cascade
funding)

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

D3.2

</td>  
<td>

‘Information events and coaching activities’ (M16)

</td>  
<td>

The data/information includes experiences and best practices from ‘Information
events and coaching activities’, which can be valuable in terms of ‘lessons
learnt’ for future endeavours.

(Targeted to experiment proposers, other projects with cascade funding)

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

**WP4 Design Centres**

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

D4.1

</td>  
<td>

‘Centre handbook’ (M4)

</td>  
<td>

The data includes information on centre management and exchange of best
practices among Design Centres, promoting synergies among them and their
regional eco-systems by:

  * establish a learning network among the Design Centres to exchange best practices in creating innovation eco-systems; 

  

  * carry out cross-centre opportunity scouting in which the research, industrial and business profiles of centres and their regional eco-systems are examined to identify innovation and other collaboration opportunities 

  

It also includes templates and guidelines for basic processes

(Targeted to Design Centres, regional eco-systems, educational institutions,
policy makers…)

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

D4.2

</td>  
<td>

‘Report on best practices and professional training’

(M12, M24, M36)

</td>  
<td>

Information will include results of:

Analysis of best practices and professional training within partner eco-
systems and exchange of best practices within the regional eco-systems of each
centre by

  * establishing regional learning networks 

  

-identifying industrial needs for professional training of particular relevance for CPSELabs 

  * matching these needs with existing competences and courses; 

  

  * implementing selected training 

  

(Targeted to Design Centres, regional eco-systems, educational institutions,
stakeholders of CPS eco-system, policy makers…)

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

D4.3

</td>  
<td>

Innovation management including ‘Annual report on innovation management
activities’ (M12, M24, M36).

</td>  
<td>

Information will include results of the innovation management activities of
CPSELabs

  * participating in reviews of experiments and marketplace efforts, including categorization, TRL assessments, and mapping and analysis of collaborative innovation activities using social network analysis, 

  

  * identifying business opportunities and improvements in practices for CPS innovation management. 

  

  * interview studies of firms having central roles in the innovation eco-systems based on cyber-physical systems in order to identify existing best practices for managing networked and open innovation in this field 

  

  * preparing an action plan for commercialization / standardization 

  

(Targeted to Design Centres, stakeholders of CPS eco-system, regional eco-
systems, EC, policy makers…)

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

D4.4

</th>  
<th>

‘Strategic Innovation

Agenda for CPS’ (M8, 14)

</th>  
<th>

The Strategic innovation agenda for CPSELabs contains information on setting
out the overall direction for experiments and other eco-system promoting
interactions, and provides plans for the open calls for experiments. The CPS-
SIA will also consider existing agendas as far as relevant, including for
example the Artemis strategic research agenda and the EIT ICT Labs strategic
innovation agenda.

(Targeted to Design Centres, stakeholders of CPS eco-system, EC, policy
makers)

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

D4.5

</td>  
<td>

‘Market Place Report’

(D4.5)

</td>  
<td>

The report will contain information about the creation of marketplaces for
selected CPS technology platforms, such as middleware platforms for CPS and
tool integration platforms. Information on suitable models for a marketplace
(e.g. in terms of IP rights, open source, governance, codex, best practices)
will be presented. A first marketplace pilot will address the sharing of
software assets and best practices to promote interoperability for CPS
engineering environments. An early survey will identify the willingness of
research and industrial organizations to contribute to and take-up assets from
the marketplace.

(Targeted to stakeholders of CPS eco-system, regional ecosystems, EC, policy
makers…)

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

D4.6

</td>  
<td>

‘Design Centres final report’ (M36)

</td>  
<td>

The report will include the final evaluation and impact assessment. Additional
information on identified "take-aways" and further evolution of innovation
eco-systems in general, and for CPSELabs in particular; an overall evaluation
of the goals, methodology and achievements of CPSELabs will be included.

(Targeted to stakeholders of CPS eco-system, EC, policy makers, other projects
with cascade funding …)

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

**WP5 Dissemination and Exploitation**

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

D5.1

D5.2

</td>  
<td>

‘Dissemination and

Exploitation Plan’ (M3)

‘Annual Report on

Dissemination Activities’

(M12, M24, M36)

</td>  
<td>

WP5 will make projects outcomes public and will build an ecosystem for sharing
information and exploiting the knowledge generated during the projects
lifetime.

Next to publishing direct results the information will be related to: relevant
conferences and workshop outcomes, influencing research programs, influencing
standards bodies, influencing educational institutions, raising awareness and
setting up communities, open access; new or improved products and services,
incubation of business ideas, creation of start-up and spin-offs.

(Targeted to stakeholders of CPS eco-system, standardization bodies,
educational institutions, policy makers…)

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

**WP6 Execution of Experiments**

</td>  
<td>

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

</td>  
<td>

Public outcomes from experiments

</td>  
<td>

Experiments will produce a publishable summary of their work and results (not
including any confidential information). Moreover, a mean of 1 scientific or
market-oriented publication per experiment is expected. Additionally, research
data might be provided in an open database (to be decided on a case-by-case
basis).

(Targeted to stakeholders of CPS eco-system, academia, industry, EC, policy
makers, broad public)

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

D6.3

</td>  
<td>

‘Final Experiments Report’

(M36)

</td>  
<td>

This report will contain the main publishable outcomes of the experiments,
including an assessment of outcomes and extraction of exploitable results.

(Targeted to stakeholders of CPS eco-system, academia, industry, EC, policy
makers, broad public)

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

Table 1: Overview of data generated and shared by the consortium

Regarding additional (peer-reviewed) publications, which are foreseen to be
academic or marketrelated, the CPSELabs general policy is to require open
access for all publications. Self-archiving ("green" open access) is expected.
Partners will be required to ensure before submission that publications will
be eligible for archiving on institutional repositories of at least one of the
co-authors. It is recognized that, in a very few exceptional cases, "gold"
open access may be required. Data used in publications will be made available,
either on the web portal or by application to the CPSELabs Service Centre.

Besides the public deliverables and other publications, CPSELabs will create
an interactive open marketplace: The CPSELabs launches a marketplace for
sharing software assets related to integrated CPS engineering tools and
environments. CPSELabs is aiming at maximizing input with this marketplace by
establishing an enlarged forum of developers, integrators, and users from
global powerhouses as well as SMEs and mid-caps.

Moreover, CPSELabs aims at contributing to standardization: Relationships with
standardization body and open platform groups are planned to make the results
available and acceptable for a wider audience. This includes presentation and
visit to specific groups such ‘The Open Group Open Platform 3.0’ (as
http://www.opengroup.org/) which is cross-domain, or Autosar, which is
dedicated to automotive standard. The Open Group has committed to support
(non-funded) the CPSELabs in identifying standardization opportunities and to
also participate in open call evaluation and in reviews of experiments for
identifying standardization opportunities.

##  Data generated in conjunction with Third Parties Experiments

Third party experiments are carried out in close collaboration with the
partners of one of the CPSELabs Design Centres in South Germany (fortiss),
North Germany (Offis), France (ONERA and LAAS-CNRS), Sweden (KTH), the UK
(Newcastle Univ.) and Spain (Univ. Politécnica de Madrid and Indra Sistemas).
The Design Centres offer expertise and training in developing cyber-physical
systems, as well as development environments, tool chains, architectural
frameworks, and technology platforms that form the basis for the experiments,
including:

  * 4DIAC framework for distributed industrial automation and control 

  

  * FMI-based virtual co-simulation 

  

  * eMIR - open source test platform for maritime systems (  _www.emaritime.de_ ) 

  

  * Model-based safety assessment techniques (AltaRica, Hazop UML) 

  

  * GenoM and Mauve-OROCOS frameworks for robotics systems programming 

  

  * Open Services for Life-Cycle-Collaboration (OSLC) open standard 

  

  * Overture family of VDM-based technologies (Overture, Crescendo, Symphony) 

  

  * SOFIA2 interoperability platform for smart spaces 

  

At the time of the deliverable (M6, July 2015), the first round of calls has
been closed, but the process of experiment selection, invitation and
confirmation has not yet been completely concluded. The collection/generation
and sharing of data heavily depends on the experiments performed, and the
third parties involved. Considering this, a detailed analysis of the data
foreseen to be collected and possibly shared can only be performed at a later
time point.

Nevertheless, the Design Centres, based on their calls and platforms
available, have made some assumptions on the data that could be generated and
the handling of it. The results of a first survey and discussions amongst the
consortium is shown in the following table.  
  
<table>  
<tr>  
<th>

**Centre/ Partner**

</th>  
<th>

**Type of data expected to be generated in conjunction with third parties**

**Plan for sharing the data**

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

Design Centre Germany South

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

FOR

</td>  
<td>

The data generated will most likely be software artefacts, rather than true
research data. “Data” in the stricter sense might come from simulation runs
that will be executed within the virtual co-simulation experiments, which will
enable to improve the key technologies of the Design Centre. In cases where
third parties generate the data (or participate therein) consent to share the
data will be required.

Developments on some of the core technologies provided by the Design Centre
will be provided as open-source software artefacts, or in the form of
publishable research reports. The example below illustrates how this will be
mapped to the data management plan.

**Data set reference and name**

4DIAC: Framework for Distributed Industrial Automation and Control

**Data set description**

4DIAC presents an open source software solution implementing IEC 61499\. It
consists of a run-time and a GUI part. The run-time is called FORTE and is
deployed to the individual controllers as a basic execution framework allowing
the execution of the applications in real-time on top. The GUI represents an
IDE

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

</th>  
<th>

realized in Eclipse. It supports the developers by creating their applications
and deploying them to the controllers running an instance of FORTE.

As 4DIAC is licensed under EPL (Eclipse Public License) all extensions and
adaptations to it have to be provided under EPL again. This ensures that all
improvements performed with in the project are offered to all the other users
of 4DIAC, which allows them to benefit from the modifications as well.

**Standards and metadata**

The 4DIAC GUI is implemented using Java in Eclipse and consists of a set of
individual Eclipse plug-ins distributed as RCP (Rich Client Platform) and
source code.

FORTE itself is implemented using C/C++ and is currently ported to a set of
different platforms, e.g. Raspberry Pi, Beaglebone Black, Wago PLCs, etc.

**Data sharing**

All the code of 4DIAC is publicly available for download under
http://www.fordiac.org. Within the near future the code base of 4DIAC will be
ported into the Eclipse repository, where it is even better visible to the
public.

**Archiving and preservation (including storage and backup)**

Currently the individual code versions are handled using Hg. Later on the
individual development states will be supported using a Git repository.

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

Design Centre Germany North

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

OFF

</td>  
<td>

**Type of Data**

OFF will focus on architecture development. Work will be based on eMIR (open
source test platform for maritime systems (  _www.emaritime.de_ )  .

The following types of data sets may be provided: Simulated data that can be
used to test physical systems based on the simulation platform, which will be
made available on an open source basis. Examples of simulated data can be
simulated traffic data or engine performance simulation. Performance analysis
data based on several configurations of the platform may provide a basis for
decision making for other third parties.

**Data sharing**

Experiments done by OFF without restrictions of third parties will be
published corresponding to DFG guidelines (Deutsche Forschungsgemeinschaft,
German Research Foundation) for scientific best practices, most likely in
conference papers or journal articles. However, OFF will also archive and
publish digital data, if available. In cases where third parties generate the
data (or participate therein) consent to share the data will be required.

The collection/generation and sharing of data heavily depends on the
experiments performed, data collected and third parties involved. As the first
experiments at the Design Centre North Germany are only foreseen in the second
round of calls, further details can only be elaborated at a later stage.

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

Design Centre France

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

ONR

</th>  
<th>

**Type of Data**

_Data foreseen to be generated by ONR include:_

Numerical models of concept of operation of robots (AltaRica CONOPS model).
The concept of operation can be devised by the labs or in answer to an actual
business case of external companies.

Numerical models of software and hardware architecture of robots (AltaRica
system model and MAUVE system architecture). The robots are owned either by
the CPSE-Labs or by external companies.

Software, which implements the robot function for ONERA robots / external
companies robot with a focus on the implementation of: safety functions,
decision making functions, real-time execution management.

Update of the design tools that have been used to build or analyse the
numerical models or the embedded software: safety assessment tools owned by
ONERA (e.g. DAL-culator, EPOCH), decision making libraries, MAUVE to OROCOS
translator Publishable materials are foreseen to include:

  * AltaRica Libraries 

  

  * MAUVE Libraries 

  

  * Decision making libraries 

  

  * Update of ONERA design tools 

  

  * Simplified version of models / software developed for ONERA or other company use cases 

  

_Data foreseen to be generated jointly by third parties and ONR include:_

Simplified models of robots of the external the companies + specification of
the software embedded in ONERA robot to mimic company use case _Data foreseen
to be generated by third parties include:_

Specialization of the publishable results for the robots owned by the company

  * Detailed AltaRica / Mauve models 

  

  * Adaptation of the decision making algorithms 

  

OROCOS modules derived from the detailed Mauve models

**Data sharing**

The data are interesting for different focused communities of end users and
are considered to be put in, e.g.,  _http://www.orocos.org/_ or
_http://altarica.labri.fr/wp/_ and general platforms that exist to deliver
open source software (e.g.  _https://www.polarsys.org/_ )  .

Consent of the third parties participating in the data generation will be
required.

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

LAAS- CNRS

</td>  
<td>

**Type of Data**

Most of the experimental artefacts will be produced together with the third
parties.

The experiments are expected to generate (i) open-source software, either as
standalone tools, or as libraries/plugins extending other existing (not
necessarily open source) toolsets; (ii) experimental artefacts like use case
descriptions, exemplary analysis or design models, exemplary analysis results;
(iii) Public deliverables synthesizing the

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

</th>  
<th>

experiments; (iv) scientific publications. Who generates what depends on the
experiments.

The experimental artefacts produced together with third parties include:

  * GenoM: GenoM3 templates, exemplary verification results 

  

  * HAZOP UML : exemplary models and safety analysis results 

  

  * SMOF : exemplary SMOF models and monitoring strategies generated from the models 

  

  * MORSE: exemplary test experiments and robustness evaluation results 

  

LAAS-specific data during the project will be:

  * GenoM: updated open-source distribution, updated tutorial, scientific papers; 

  

  * HAZOP UML: scientific papers and tutorial; 

  

  * SMOF: updated version and open source distribution by the end of the project, scientific papers, tutorial; 

  

  * MORSE: distribution of exemplary test components, scientific papers and tutorial for MORSE-based testing; 

  

**Data sharing**

The definition call topics for experiments by the French CPSE-labs Design
Centre will include explicit concerns for delivering publicly available
material, e.g. by focusing on extending an open source framework, called GenoM
1  , or by requiring that applied techniques shall be illustrated on artefacts
derived from use cases that are representative enough but do not raise IP or
confidentiality issues, and that results must be summarized in a publishable
experiment description document.

Industrial experiment partners may be less used to sharing data. CPSELabs
perceives it as its role to accompany them in this opening process. CPSELabs
will help them in scoping their use cases and demonstration artefacts, in
order to extract information that is sufficient to exemplify the concepts and
problems, while not disclosing too much about their systems and know how.

Not only the code of the tools/libraries but also tutorials can be made
available. For the most mature tools, there also are mailing lists gathering a
community of users. A repository of courseware material would be useful to the
community.

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

Design Centre Sweden

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

KTH

</td>  
<td>

**Type of Data**

The collaboration with third parties will probably generate software
artefacts, rather than research data.

Moreover, interview transcripts and measurement data (KPI-related) will be the
most relevant research data generated. Possibly, there will also be summary
data related to literature surveys (coded sources, categorizations, etc.)

**Data sharing**

KTH will push for open source software artefacts related to CPS marketplaces.

Consent of the third parties participating in the data generation will be
required.

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

Design Centre UK

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

UNEW

</td>  
<td>

**Type of Data**

Descriptions of domains, co-models, descriptions of metrics used, tool
extension data.

**Data sharing**

Consent of the third parties participating in the data generation will be
required.

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

Design Centre Spain

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

IND

</td>  
<td>

**Type of Data**

Data foreseen to be collected/generated in conjunction with third parties
include:

  * Environmental data: Data automatically taken from sensors 

  

  * Personal data: Data taken from sensor that can identify an individual. Information privacy must be considered for these data. 

  

  * Generated data: Data not taken from sensors, but inferred from the previous kinds of data using traditional or non-traditional processing application - Test data: as above but generated under lab conditions 

  

Indra’s activities are foreseen to generate logs of automatically generated
data (such as 1 reading of temperature per every thermometer and minute during
the period); information that can be inferred from these (the results of CEP
engine using the previous sensors as inputs) and the commands sent by human
agents answering this (to provide non-automatic answers or to perform forensic
analysis).

The data in and by themselves are probably not suitable to be published as
such. The results will nevertheless most likely provide opportunities to
manually generate material that will be interesting - such as documentation
for new functionalities, video tutorials, etc. The details of third-party
(including SME's and public institutions) activities about data generation
will depend on the specifics of their experiment. We do think their functional
interests will lead to more visible and friendlier data.

Besides this, IND considers the data generated as potential input for pattern-
inference analysis if possible. Moreover, it could provide input to identify
potential shortages or improvement points for our technology.

**Data sharing**

Not all the data will be offered to the public _as is_ . Some data must be
protected due to legislation and/or to ethical concerns. This includes, but is
not restricted to, personal data. Moreover, consent of the third parties
generating the data will be required.

The collection/generation and sharing of data heavily depends on the
experiments performed, data collected and third parties involved. As the first
experiments at the Design Centre Spain are only foreseen in the second round
of calls, further details can only be elaborated at a later stage.

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

UPM

</td>  
<td>

**Type of Data**

The following data is foreseen to be generated in conjunction with the third
party experiments

  * Data from IED 

  

  * Data from humans-CPS interactions 

  

  * Data from Social networks in the context of CPSs 

  

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

</td>  
<td>

  * Data from assessing the work performed by 3rd parties 

  

  * Data from applying changes to the work performed by 3rd parties suggested by conclusions from assessment 

  

  * Code that could be shared 

  

  * Models 

  

**Data sharing**

The implications of releasing data will be checked on a case by case basis. To
publish the “raw data”, will, in many cases, not be possible. Moreover,
consent of the third parties generating the data will be required. While third
parties might object to publish raw data, their consent to publish the
research results conclusions, with processed data, might still be possible.

The collection/generation and sharing of data heavily depends on the
experiments performed, data collected and third parties involved. As the first
experiments at the Design Centre Spain are only foreseen in the second round
of calls, further details can only be elaborated at a later stage.

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

Table 2: Overview of data generated in conjunction with third party
experiments

Data sets will be provided by the Design Centres, whenever possible. Data
generated together with or by third parties will only be shared upon their
consent. The Design Centres will provide the data for the execution open
experiments during the course of the project. The Design Centres will also
publish the data on open access data platforms to ensure availability of data
also after the end of the project. In order to manage these data, partner
hosted repositories, as well as external repositories will be used to ensure
maximum visibility, serve as backups, and ensure availability well after the
end of the project. The CPSELabs market place will also be considered for
providing a repository for some of the data or to have links to specific
forges in the market place. As the data need to be easily updated by their
producers and to avoid fragmentation of open data platforms some data are
considered to be put in the general market place or focused places (e.g
_http://www.orocos.org/_ or  _http://altarica.labri.fr/wp/_ )  . Moreover,
general platforms exist to deliver open source software (e.g.
_https://www.polarsys.org/_ )  . The usage of well-known platforms like
OpenAIRE (or even opendata.eu in future) would be advantageous in some cases.

With respect to software developed during the course of the project, whenever
possible (i.e. not violating IPR) it will also be provided under open-source
license to allow for their re-use, adaptation and further enhancement to match
possibly different application contexts and serve as a baseline for future
business and research endeavours. The project will consider using the Open
Access Infrastructure for Research in Europe (OpenAIRE)  2  as well as
exploiting the expected support to be provided on research data management for
projects funded under Horizon 2020.

#  Conclusion

The CPSELabs consortium fully supports the endeavour to improve access to
scientific information and research data in order to enhance the benefits of
public investment. To fully exploit possibilities of data sharing, the project
participates in the ‘Open Research Data Pilot’ and will make its research data
available on a voluntary basis, whenever possible.

A variety of data and information will be generated in CPSELabs, whereof a
part will be generated by the consortium itself, and will be made freely
available e.g. via the website and public deliverables, while another part,
will be generated in conjunction with ‘third parties’, participating via
cascading funding in so called ‘experiments’. In the course of the project,
the CPSELabs consortium will have to carefully consider and agree with the
third parties on a case to case basis if, how and to what extend data can be
shared. CPSELabs perceives it as its role to accompany the mainly industrial
third parties in this opening process. CPSELabs will help them in scoping
their use cases and demonstration artefacts, in order to extract information
that is sufficient to exemplify the concepts and problems, while not
disclosing too much about their systems and know how.

As the project is just on the way of concluding the first round of ‘open call’
selection and invitation process, only assumptions on the data generated
through the ‘third party experiments’ and possible ways of sharing this data
could be provided within this deliverable. Future version of this document may
provide more refined policies to manage and share such data when the scope and
contents of experiments can be assessed more clearly. In addition, the
deliverable also aims at giving a brief overview on other data and information
elaborated by the project consortium that could be useful for specific
stakeholders or other projects pursuing similar aims in future.