##  Executive Summary

The Deliverable 5.2 “Project initial exploitation and open data management
plan” has the aim to report a first analysis about the exploitation
opportunity of FESTIVAL project, introduce some starting concept related to
the business model and define how the open (research) data will be managed
during the project. Considering the early stage of the project, the main
topics introduced in this document, exploitation, business model and open data
management, cannot be totally defined and analysed, but they will be updated
during the whole project duration and reported in the next

WP5 deliverables.

The Deliverable 5.2 is structured in four main chapters: the first one
“Initial exploitation plan” contains an initial analysis of the possible
exploitation opportunities for the FESTIVAL project: all the partners
contributed to this chapter. In particular are identified a list of existent
assets that can be reused in the project and how they will further improved
during the activities. Besides it has been defined an initial list of possible
exploitable outcomes that FESTIVAL should produce: this includes not only IT
assets but also other types of items (e.g. methodologies, physical
environments etc.). At the end of the chapter, some initial exploitation
intentions of the different project partners are presented.

Chapter 2 is about the analysis of the Experimentation as a Service ecosystem
that is the basic approach of FESTIVAL and fundamental for the future
definition of a business model. The first section of the chapter reports a
description of the entities, processes and the stakeholder involved in a
possible typical EaaS scenario: each of them is described and put in relation
with the others. The last section presented a series of existent initiatives
that can be related to EaaS model and initial considerations about FESTIVAL
exploitation and sustainability.

Chapter 3 is dedicated to the Open Data an important topic for FESTIVAL
project that has different activities on this field with a specific focus on
the Open research data that will come from the experimentations. Section 3.1
analyses the situation of the adoption and maturity of the open data approach
in the different countries of the world and in particular the ones involved in
FESTIVAL field trials. The second section of the chapter gives a general
overview of the Open Data market and the potential business opportunity. The
Open Data Management plan is the focus of the last section of chapter 3: in
this early phase of the project, it has been possible to define the processes
that will be followed and relative output in the management of the open data
and in particular open research data.

The last chapter presents a roadmap with the future activities to be performed
to refine the exploitation plan, define a first version of the concrete Data
Management plan and of the Business model that will be included in the next
two WP5 deliverables, D5.3 “ _First year update to communication,
dissemination, exploitation and open data management activities”_ and D5.4 “
_Experimentation as a Service business model analysis_ ”.

##  1\. Initial exploitation plan

###  1.1. Project general scenario and impact

The world we live in is a changing world, the European Union and Japan have
already to face many challenges, and more can be foreseen for the near future.
The transforming power of ICT is set to revolutionize our economies and lives
as the new forms of communication become the medium for organizing and
managing the complex eco-­‐systems we depend on (energy, transport,
industries, health…).

The achievement of this vision however requires significant investment in key
infrastructures. Test-­‐beds and experimental facilities, both of small scale
and up to city scale, will be an essential enabler to facilitate the
development of this vision. **Facilitating the access to these test-­‐beds to
a large community of experimenters in an “Experimentation as a Service”
approach is a key asset to the development of a large and active community of
application developers that are necessary to address the many challenges faced
by European and Japanese societies.** A global and far-­‐reaching
interoperability between applications is another essential enabling element of
the IoT vision, in that sense the approach of the project of an
intercontinental federated test-­‐bed will prove a key asset.

As presented in the description of work, the project targets important impact
not only from a scientific and technical aspect, but also at an economical and
societal level. While a significant aspect of the project is to study the
potential impacts (Work Package 4) of the project experiments and of the
project federated approach, this also translates in direct exploitation
opportunities that will be pursued by the project partners jointly:

  * The Federation in itself of the different experimentation environments, made available in Europe and Japan, in an Experimentation as a Service model can be expected to be the main and most tangible outcome of the project.The project will provide valuable experimentation facilities in particular for innovation creators (researchers, start-­‐ups, SMEs) who do not have necessary resources to setup and maintain large-­‐scale experimentation facilities. In the long run, these services will allow the IoT ecosystem to bring robust and good quality products to the market, while decreasing the time to market by diminishing the necessary effort for testing. The development of experimentation facilities, including large (city size) operational test-­‐beds, made available to a large community of stakeholders will be a key asset for the development of the IoT in Europe and Japan which economies will both strongly benefit from this technical leadership. **Maintaining and enhancing the provision of these EaaS services beyond the project lifespan and in a sustainable way will therefore be the main focus of the common exploitation work of the project.**

  

  * A global and far-­‐reaching interoperability between applications is another essential enabling element of the IoT vision, in that sense the approach of the project of an intercontinental federated test-­‐bed will prove a key asset. Thus, if sustaining the EaaS access to the project testbeds is a first priority of the project, **a second common exploitation objective will be to maintain and extend the federation and interoperability beyond the project.** The project exploitation work will therefore identify possible structures to carry on the federation work beyond the project lifespan and this deliverable already looks into potential possibilities. 

  

In addition to these main common opportunities and objectives, the scientific
knowledge and expertise acquired in several domains throughout the project
will be a strong asset for the project participants that can be translated in
additional individual or joint exploitation opportunities:

  * The experimentation organized during the project on the federation of testbeds, and the application developed by the consortium but also by third parties will generate an important exploitation opportunity. These experimentations and applications, supported by the project through the organization of contests and through dedicated services (especially to handle relationships to end users and to privacy and ethics issues) will generate business opportunities that some of the project partners will be able to pursue in close collaboration with the surrounding business ecosystem created thanks to the project. 

  

  * The project gives the opportunity to create a technological federated architecture that can be the base for a real service ecosystem to be delivered and maintained beyond the duration of the project. This will be an opportunity for all the industrial stakeholders involved in the project, due to the professional experience maturated in it, to have a primary role in future technological standardisation/regulation in the domain of IoT platforms. 

  

  * Each individual organization involved in the project has a plan for exploiting the knowledge and expertise developed in the project. Either as a competitive advantage for the provision of existing or new product and services, or as part of scientific education and dissemination for academic partners and research institutions. 

  

###  1.2. Existent reusable assets

This section presents a set of existent assets that the different partners of
FESTIVAL brought into the project as resources to be used in the concrete
activities. These assets, that are described in the following tables, consist
of IT artefacts (such as platforms or testbed) but also of other types of
resources such as living labs and collaborative spaces: all these assets will
be involved in the project experimentations and will be accessible by the
different FESTIVAL stakeholders. Each asset is described in a table including
a general description and consideration about innovation and interoperability
related to the project context; in addition to a plan about possible further
developments of the asset during the project implementation.

####  1.2.1. SmartSantander platform  
  
<table>  
<tr>  
<th>

**Asset name**

</th>  
<th>

SmartSantander platform

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

**Asset Overview**

</td>  
<td>

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

SmartSantander platform tier is the core of the SmartSantander testbed. It is
the top layer

within the SmartSantander

architecture and it is in charge of manage and control the

resources within the testbed. The description of the resources deployed in
SmartSantander

as well as the internal repositories for the data generated in the testbed
belong to this

layer. Furthermor

e, the SmartSantander core supports the integration of external services

to be stored and accessed using the SmartSantander APIs. Finally, all the
functionalities to

federate SmartSantander with other existing testbeds (FI

-­‐ 

WARE, Fed4Fire) are within this

l

ayer.

**Figure**

**1**

**-­‐**

**SmartSantander platform**  
  
<table>  
<tr>  
<th>

**Type**

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

Software platform

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

**Innovation**

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

The SmartSantander platform is a set of software tools that are ready to
manage a massive deployment of IoT devices in smart city scenarios. Currently,
the platform tier manages more than 12000 IoT sensors.

The platform is composed of several components depending on the functionality
foreseen:

  * IoT API: main interface for accessing and injecting new data to the platform. All the resources deployed within the SmartSantander testbed uses this interface to send data. Additionally, external information sources can use this interface to inject data into the platform. This interface implements all the authorization and authentication methods. 

  

  * Adapters/Wrappers: Set of software modules to integrate the SmartSantander platform in different federations approach (FI-­‐WARE, FED4FIRE). 

  

  * Internal data repository: a noSQL data repository to keep all the data injected from (external and internal) IoTs. 

  

  * Resource Directory: this module manages and keeps track of the resources injecting data into the platform. 

  

  * nodeManager: this module is in charge of monitoring the infrastructure, seeking for inactive nodes to be deactivated from the platform. 

  

  * Testbed runtime and OTAP tools: these software modules implemented within the testbed platform and gateways enable the possibility of flashing nodes with new programs using Over The Air Programming protocols. 

  

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

**Interoperability**

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

The SmartSantander platform foresee the integration of the resources with
other testbeds by use of a RESTful interface (aforementioned IoT API) which
enable a homogenous access to all the resources within the testbed, including
management and data mining. Additionally, as part of the FI-­‐WARE and
FED4FIRE initiatives, the platform is being federated following these two
approaches.

The use of IoT API is used to integrate external services into the
SmartSantander platform; therefore, different testbeds can inject generated
data into the platform and access it homogeneously. Furthermore, data injected
into the platform can easily be included as part of FED4FIRE and FI-­‐WARE,
accessing a much wider testbeds federation.

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

**Foreseen Improvements**

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

On the one hand, the SmartSantander platform envisions the federation with
other testbeds in Europe and Japan within FESTIVAL, enriching the accessing
possibilities for experimenters using SmartSantander. Enabling federation will
allow SmartSantander to access new resources not envisioned previously (e.g.
VMs with high-­‐speed connectivity).

On the other hand, smart shopping use cases in FESTIVAL will require new
software tools to manage smart-­‐shopping oriented sensors. Moreover, sensors
based on radio technologies such as Bluetooth are not part yet of the
SmartSantander platform, so specific management tools will be also
implemented.

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

**Owner/Responsible partner**

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

University of Cantabria

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

**1.2.2. Santander IoT Infrastructure**  
  
<table>  
<tr>  
<th>

**Asset name**

</th>  
<th>

Santander IoT Infrastructure

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

**Asset Overview**

</td>  
<td>

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

The Santander IoT Infrastructure, which is shown in the following figure, is
currently composed of around 3000 IEEE 802.15.4 devices, 200 devices including
GPS/GPRS capabilities and 2000 joint RFID tag/QR code labels deployed both at
static locations (streetlamps, facades, bus stops) as well as on-­‐board of
public vehicles (buses, taxis). It includes:

  * static nodes, such as environmental sensors (temperature, noise, luminosity), parking sensor nodes, parks and gardens irrigation sensors (air temperature and humidity, soil moisture and temperature), traffic sensors (road occupancy, number of vehicles, speed); 

  

  * mobile nodes, which measures specific environmental parameters, such as CO, 

  

NO2, Ozone, Microscope particles.

**Figure 2 -­‐ Santander IoT Infrastructure**

Additionally, in order to improve some municipality services such as Water and
Waste management, different kinds of sensors (fixed and mobiles) have been
deployed within the city.

In the case of Waste management, sensors capable of measuring garbage levels
in bins, system for identification and monitoring litter bins (NFC and RFiD
tags) have been installed in fixed positions, while fleet management system
(GPS) have been deployed in vehicles, together with activity and environmental
sensors. Additionally, mobiles’ operators will be provided with NFC tags and
GPS. The following figure shows some of the installed sensors.

All the information retrieved by these sensors will be stored in the
SmartSantander Platform, and after being processed it will be sent to the
corresponding actor. Several Apps will be developed: for internal use (street
cleaning operators; bins and trash cans maintenance) and for citizens (to
report incidences).  
  
<table>  
<tr>  
<th>

In the case of water management, a pilot project has been developed in an area
of the city, whose main objective is to optimize the provision, management and
use of this resource. Several sensors have been installed in the water
provision network (in order to monitor it) and also in citizens’ houses. The
information retrieved by these sensors, together with environmental
information will be gathered in order to improve not only water management but
also service provision. Additionally, tools for accessing to individual water
usage consumption and for reporting incidences on the network are available,
in order to improve the quality of service and optimize water consumption, by
involving citizens as key actors in this process.

Due to the positive results obtained in this project, a new phase will be
developed in another area of the city.

Santander IoT Infrastructure is being used in several research projects to
collaborate in the development of the future Smart City, being used to develop
use cases within these projects and generating real new services for the
citizens.

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

**Type**

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

Infrastructure (Hardware Platform)

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

**Innovation**

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

As University of Cantabria has mentioned previously, the smart shopping use
case will use new sensors based on radio technologies such as Bluetooth. So
they will have to be developed, deployed and also integrated within the
current infrastructure.

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

**Interoperability**

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

In order to ensure experimentation and service provision, different protocols
are used including standard based, such as 802.15.4, and proprietary ones,
such as Digimesh.

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

**Foreseen Improvements**

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

Deployed devices will also extend the SmartSantander testbed capabilities,
allowing external experimenters to access new kind of datasets with
information about positioning.

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

**Owner/Responsible partner**

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

Santander City Council

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

####  1.2.3. GIS Platform  
  
<table>  
<tr>  
<th>

**Asset name**

</th>  
<th>

GIS Platform

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

**Asset Overview**

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

A GIS Platform, which uses ESRI Technology, is provided by Santander City
Council in order to store and process geo referenced data, accordingly to the
city needs.

Some of the geo referenced data that will be used in this project are running
in this platform. The following figure shows a simplified vision of the
Platform Architecture:

**Figure 3 -­‐ Santander GIS platform**

ArcGIS Server is a powerful and flexible platform which provides not only a
variety of spatial data and services to GIS users and applications
requirements, but also the ability for our organization to implement
server-­‐based spatial functionality for focused applications utilizing the
rich functionality of ArcObjects. As it is known, building robust and scalable
applications is not a simple task, so proper application design is required.

This server is a distributed system whose different components can be
distributed across multiple machines. Each one of them plays a specific role
in the processes of managing, activating, deactivating, and load balancing the
resources located on a given server object or set of server objects.

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

**Type**

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

Software platform

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

**Innovation**

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

ArcGIS platform provides innovative features in order to manage geographic
information, such as present aggregated data as context-­‐rich maps, which
gives organizations powerful new tools to proactively manage their operations.
It also provides field data collection tools to be used in any mobile devices
without any additional software development. Additionally, it allows not only
to gather but also to manage geo located information. This server also
provides access to the GIS functionality that the resource contains. For
example, you might be able to share a map with someone through a server, but
it would be even better if that person could also interact with the map, like
find the closest hospital, restaurant, or bank and then get directions to it
from their location.

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

**Interoperability**

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

Santander GIS platform data Interoperability provides state-­‐of-­‐the-­‐art
direct data access and data translation tools in addition to the ability to
build complex spatial extraction, transformation, and loading (ETL) tools for
data validation, migration, and distribution.

GIS platform Data Interoperability supports various proprietary formats and
protocols as well as standardized formats from OGC such as GML and CityGML,
WFS, and KML/KMZ, also ISO, and other GIS Standards bodies such as CSV, CAD,
JSON, XML, and RSS.

GIS Platform also delivers two APIs for interoperability, one of type RESTFUL
and another of type SOAP.

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

**Foreseen Improvements**

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

This platform provides the capacity of provide geo location information
required for the

Smart Shopping use case.

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

**Owner/Responsible partner**

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

Santander City Council

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

**1.2.4. Santander Open Data Platform**  
  
<table>  
<tr>  
<th>

**Asset name**

</th>  
<th>

Santander Open Data Platform

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

**Asset Overview**

</td>  
<td>

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

Santander City Council has deployed an Open Data platform for offering to the
citizen all public data that resides in its internal databases, including
transportation, demography, shops. One of the main focus of this platform is
directed towards companies and entrepreneurs, in order to take advantage of
this data to create products and services on top of them, thereby fostering
not only the business opportunities but also the job creation. Additionally,
it is also focused on providing citizens proactively data, looking for a
better understanding of how an administration works internally, and reducing
and even eliminating in some cases, slow and costly administrative procedures
to access data that, although being public, it was not available to citizens.

The architectural definition of the platform, which includes a front-­‐end and
an back-­‐end, is shown in the next picture and described below:

**Figure 4 -­‐ Santander Open Data platform**

The front-­‐end may be defined as the graphical interface for the final user.
From the technological point of view, it is composed of three popular
components, developed by the open source community, which have been reused and
adapted to the specific needs of the platform. These components are:

  1. Wordpress: Prestigious CMS aimed from its birth to build blogs, but over time has incorporated features to be considered the most used content management system in the network. This component is in charge of implementing the final graphical user interface that provides access to the data and the Open Data portal. 

  

  2. CKan: It is a CMS focused in Open Government Projects, which is used and managed mainly by United Kingdom Government, and reused by main open data portals 

  

  
  
<table>  
<tr>  
<th>

worldwide. This component is in charge of outfitting with all infrastructures
for defining and meta-­‐dating datasets and resources and supplies APIs to
allow developers to automate data consumption.

3\. Virtuoso: Virtuoso is a web tool that allows the terminology definition,
for the creation and promotion of Semantic Web. Its role within the Platform
is to define those specific words associated to a Municipality or local
Authority, which have not been defined so far by any standardization
corporation or any other open data platforms.

The back-­‐end subsystem is in charge of doing data gathering tasks and
supporting Sparql engine. This subsystem is composed of two components, also
developed by Open Source Community, and adapted for the particular platforms
needs. These components are:

  1. iCMS: A data gathering system developed by Government of Andalucía, which main function is to maintain front-­‐end constantly fed with updated data. It is important to highlight that the data contained on the website is not mere snapshots of available data at a given time, but the system is being updated constantly by Municipal databases in order to always provide updated data. Therefore, this tool or technology component plays a transcendental role in the platform in order to enable a real time open data platform. 

  

  

As an example, in the case of census dataset, if we query the number of people
from one day to another, we will see its variation depending on the
registrations and cancellations occurred in that time interval.

This real-­‐time updating is made through ad-­‐hoc drivers developed for every
Municipality data producer.

  2. Marmota/Neogolsim: This tool is responsible for providing the SPARQL engine to the platform. The purpose of this engine is, on the one hand, to provide data in RDF format (format of choice for reuse) and on the other, to allow creating cross-­‐data queries with other Open Data Platforms world-­‐wide, thus providing platform with advance features that allows it to follow the Semantic Web path. 

  

  

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

**Type**

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

_Software platform_

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

**Innovation**

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

Open Data Platform is a key component of the innovation in the City, providing
tools to generate new ideas from citizens, fostering Crowd Sourcing. Most of
these ideas conclude in projects, whose outputs are new services for citizens.
Therefore, the City gets a new innovative channel to create new services.

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

**Interoperability**

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

Santander Open Data Platform delivers Open standards for data exchange that
are independent of any individual supplier. These standards are essential for
systems and data to be interoperability. Without them, open data can realize
only a fraction of its value.

Because Santander Open Data platform built on open standards, it helps data
from different sources work together. It also ensures that users are never
“locked in”, because data and metadata can easily be harvested into a
different system.

Standards like HTML, REST, CSV, XML, RDF, JSON-­‐G, N3, TURTLE, ATOM, SHP,
WKT, are available and ready for use in the platform.

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

**Foreseen Improvements**

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

Open Data platform will provide the information required by the Smart shopping
use case. Additionally, output information may be included as a new category
in the current Open Data catalogue, which may be used by any other user in
order to develop a new application or service.

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

**Owner/Responsible partner**

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

Santander City Council

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

####  1.2.5. Pedestrian Flow Analyzer platform  
  
<table>  
<tr>  
<th>

**Asset name**

</th>  
<th>

Pedestrian Flow Analyzer platform

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

**Asset Overview**

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

Pedestrian Flow Analyzer (in short PFA) platform consists of Wi-­‐Fi packet
sensors and PFA server, and provides functionality to grasp the flow of
pedestrians equipped with Wi-­‐Fi-­enabled devices in real time. Wi-­‐Fi
packet sensors collect Probe Request frames, which are periodically
transmitted from Wi-­‐Fi-­‐enabled devices to search Wi-­‐Fi access points,
and anonymize MAC address fields then upload collected data to the PFA server,
where gathered data are used by a PFA engine to calculate the pedestrian flow
in real time. We aim to utilize analyzed data effectively for making disaster
prevention plans and for the evacuation guidance.

**Figure 5 -­‐ Pedestrian Flow Analyser platform**

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

**Type**

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

Software platform

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

**Innovation**

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

Pedestrian flow analysis based on Wi-­‐Fi probe request frames itself attracts
attention of researchers. The technology has already been incorporated into
several commercial products. Innovative challenge in FESTIVAL project is
integrating the PFA functionality with existing testbeds and exploring means
to facilitate experimentations using collected data including personal
information by following correct procedures taking care of users’ privacy
concerns.

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

**Interoperability**

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

PFA platform foresees to be deployed in JOSE testbed and widely used by
experimenters interested using the real-­‐time trajectory of pedestrians for
novel services. PFA has been incorporating communication functionality based
on MQTT over SSL, and will be able to accommodate both Wi-­‐Fi packet sensors
and IoT actuators using the MQTT protocol.

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

**Foreseen Improvements**

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

We have been using PFA platform for experimentations in the area of university
campuses, exhibition halls, shopping malls, and underground shopping areas so
far. It is, however, difficult to widely open collected data and the result of
analysis due to the nature of dealing with personal information. We expect to
improve the situation by deploying the PFA platform onto FESTIVAL testbeds and
provide it for use by various experimenters in a more controlled environment
to explore efficient procedures for utilizing pedestrian flow information for
novel services and applications. We also foresee to incorporate functionality
to improve PFA based on BLE advertising packets.

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

**Owner/Responsible partner**

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

Ritsumeikan University

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

####  1.2.6. PIAX  
  
<table>  
<tr>  
<th>

**Asset name**

</th>  
<th>

PIAX

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

**Asset Overview**

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

PIAX (Peer-­‐to-­‐peer Interactive Agent eXtensions) is an open source
framework that integrates P2P structured overlay network and agent platform.
PIAX is also a core of the PIAX Testbed.

Overlay network enables pervasive devices to communicate each other
efficiently, while agent platform on the overlay network encourages the
devices to cooperate with other devices. Consequently, a scalable and
efficient federated system can be realized not only in the ordinary
environment but also in a large-­‐scale distributed environment (e.g.,
pervasive environment, cloud environment) where various kinds of data and
processes are located in each device.

**Figure 6 -­‐ PIAX framework**

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

**Type**

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

Software platform

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

**Innovation**

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

PIAX is core networking platform of the PIAX Testbed and provides networking
features including peer discovery and messaging.

PIAX consists of 2-­‐layers, i.e., P2P structured overlay network layer and
agent platform layer. P2P overlay network has several overlay networks such as
DHT (Distributed Hash Table), LL-­‐Net (Location-­‐based Logical P2P Network),
and Skip Graph. Agent platform supports mobile agents that are processed on
the nodes and moves on the overlay network.

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

**Interoperability**

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

PIAX is a Java class library that integrates mobile agent platform and P2P
structured overlay network. PIAX therefore can be integrated into Java-­‐based
projects that can benefit powerful networking features. PIAX agent programs
can also be tested on PIAX Testbed before deploying to real environment. On
PIAX Testbed, sensor measurements from sensors connected to JOSE Testbed can
be tested.

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

**Foreseen Improvements**

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

  * New version PIAX 3.0.0 should be released soon. 

  

  * PIAX Testbed based on PIAX 3.0.0 will be deployed on April/May 2015\. 

  

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

**Owner/Responsible partner**

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

Owner: NICT

Responsible partner: ACUTUS

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

####  1.2.7. JOSE  
  
<table>  
<tr>  
<th>

**Asset name**

</th>  
<th>

JOSE

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

**Asset Overview**

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

JOSE provides a Japan-­‐wide open testbed, which consists of a large number of
sensors, SDN capabilities and distributed “CLOUD” resources. The facilities of
JOSE are connected via high-­‐speed network with SDN feature. JOSE will
accelerate field trials of “large‐scale smart ICT services” essential for
building future smart societies. JOSE has following four characteristics:

  1. Huge amount of computation resources 

  

  2. Provides dedicated ‘sensor network’ by SDN 

  

  3. “takeout” sensor facilities for users’ own experiments 

  

  4. Many field trial experiments coexists 

  

  

**Figure 7– JOSE testbed**

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

**Type**

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

IoT experiment service

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

**Innovation**

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

  * Distributed compute resources o 400 physical servers are available at 3 locations o 10 VMs run on each computer 

  

▪▪ 12,000 VMs are provided

  * Sensor data analysis data analysis 

  

  * Distributed storage resources o 10 servers are available at 5 locations 

  

▪▪ 50 storage servers, 500 VMs

  * Sensor data storage 

  

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

**Interoperability**

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

JOSE supports IEEE1888 and its protocol and data format is already
standardized. JOSE also supports RESTful interface.

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

**Foreseen Improvements**

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

Currently, JOSE does not support user defined new agent functions on FIAP
Storage for JOSE, which is an extension of an implementation of IEEE1888 to
share data among multiple FIAP Storage instances. An approach to exploit JOSE
as a distributed data analysis backend will be investigated and improved. How
to utilize a SDN functionality of JOSE is also investigated.

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

**Owner/Responsible partner**

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

Owner: NICT

Responsible partner: ACUTUS

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

####  1.2.8. Tuba Living Lab  
  
<table>  
<tr>  
<th>

**Asset name**

</th>  
<th>

Tuba Living Lab

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

**Asset Overview**

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

The TUBA is located in front the Part-­‐Dieu train station in Lyon, in a
public area. The site is strategic as almost 500 000 persons get through the
place every day. This position allows TUBA to get in touch with a great
variety of people and profiles.

The events TUBA organises attract this public, which constitutes a large panel
TUBA can mobilise on different experimentations.

On the ground floor, the Tuba LAB : a 180 sqm’s showroom fully opened to the
citizen. Everybody is invited to discover what makes the city smarter and to
experiment new ideas, even to propose some! The Tuba LAB exposes new services
and prototypes leveraging the data exposed by the city and the partners.
Domains covered are Well-­‐Being, Transportation,

Health and Culture.

On the first floor , the TubaMIX: 420 sqm dedicated to projects’ holders,
TUBÀ’s partners, and any other public or private entities involved in
Innovation & Smart City.

**Figure 8 -­‐ Tuba living lab**

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

**Type**

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

Service, Place

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

**Innovation**

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

The Tuba LAB could expose applications and services from other partners, using
Tuba and/or federated resources.

The Tuba Mix could co-­‐design applications and services with remote partners

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

**Interoperability**

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

Interoperability will be made through a common methodology and the use of Open
Data standards

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

**Foreseen Improvements**

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

During the FESTIVAL project, methodology will evolve to access to the
federation. The Tuba/Metropole de Lyon’s Open Data repository will evolve to
streamline the use of external partner’s data

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

**Owner/Responsible partner**

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

SOPRA/TUBA

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

####  1.2.9. Lyon’s Open Data Platform  
  
<table>  
<tr>  
<th>

**Asset name**

</th>  
<th>

Open Data platform

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

**Asset Overview**

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

TUBA has access to the Metropole of Lyon’s Open Data infrastructure, allowing
the partners to :

  * Use existing Open Data sets, published by the Metropole and its service providers 

  

  * Create/Access private repositories to inject/use custom data for a specific experimentation 

  

This Open Data repository leverages the following technologies: JSON, OGC, CSW
and KML and make use of Credentials when possible

.

Public

Specific

**Figure 9 -­‐ Lyon’s Open Data Platform**

Domains covered are : transportation, public services, geographical data,
culture, economy, environment, urbanization, equipments, accessibility,
demography.

These data are also provided by the service contractors of the Metropole.

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

**Type**

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

Software Platform, Service

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

**Innovation**

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

The Open Data infrastructure could interoperate with other Open Data
platforms, could get its data from external testbeds, and could interact live
with computational resources

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

**Interoperability**

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

Interoperability will be made through Open Data / API technologies

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

**Foreseen Improvements**

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

During the FESTIVAL project, methodology will evolve to find the right
architecture to access the resources and design complex applications/services.

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

**Owner/Responsible partner**

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

SOPRA/TUBA

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

####  1.2.10. End user engagement methodology  
  
<table>  
<tr>  
<th>

**Asset name**

</th>  
<th>

End user engagement methodology

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

**Asset Overview**

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

A methodology for end user involvement, including ethics and privacy
protections and an evaluation framework of Quality of Experience has been
developed and deployed within

PROBE-­‐IT (TRL 5) and BUTLER (TRL 6). The methodology includes:

  * Analysis of IoT Ethics, Privacy and Data Protection issues (BUTLER) 

  

  * Informed consent procedures (BUTLER) 

  

  * Co-­‐creation methodologies (BUTLER) 

  

  * Impact assessment methodologies (BUTLER) 

  

  * Security Risk Assessment Framework (BUTLER) 

  

  * Deployment evaluation methodology (PROBE-­‐IT) 

  

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

**Type**

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

Service / Methodology

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

**Innovation**

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

The necessity to involve multiple stakeholders that are not used to work
together in new use cases is a characteristic of the IoT innovations and its
ability to disrupt existing models and value chains. To be well accepted, the
new deployed solutions must be well understood by all involved stakeholders,
including the end users and citizens it will affect. In that matter,
co-­‐creation mechanisms and engagement of stakeholders throughout all the
phases of a deployment is a necessity

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

**Interoperability**

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

The methodology can be applied/adapted to other ICT / IoT projects.

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

**Foreseen Improvements**

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

The model will be extended and applied in FESTIVAL and will gain maturity. The
model and approach will be promoted to other deployments (TRL 7).

  * Creation of communication material (factsheets) to present key aspect and methodologies of user involvement in a short and rapidly understandable way. 

  

  * Evolutions of the informed consent procedures 

  

  * Set up of a Privacy Impact Assessment rapid evaluation framework 

  

  * Evolutions based on external inputs 

  

  * Support to co-­‐creation experiments 

  

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

**Owner/Responsible partner**

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

inno

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

####  1.2.11. The Lab. in Knowledge Capital  
  
<table>  
<tr>  
<th>

**Asset name**

</th>  
<th>

The Lab. in Knowledge Capital

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

**Asset Overview**

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

The Lab. is a showcase where general public, such as researchers, creators,
artists, students, senior citizens, housewives and children, can experience
the latest technologies and have interactions with other exhibitors.

The Lab. constitutes a space that attracts global prototypes and
world-­‐leading technologies, and is a hub from which the latest strains of
culture emanate. Visitors not only get to see and touch ingenious inventions,
but are also given the chance to participate in the creative process as befits
the description of this space as a laboratory.

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

**Type**

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

Location / Service

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

**Innovation**

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

Communicators are the specialists that introduce Knowledge Capital and
interlink people with other people, things, and information. At The Lab., they
are the ones who approach visitors, stir-­‐up interaction, and encourage the
deepening of new encounters and experiences.

Communicators also play the role of gathering the

comments and reactions of visiting members of the public, and feeding this
information back to companies, researchers, and other event organizers

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

**Interoperability**

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

The Lab. can perform interoperability when the fundamental devices required in
other experimentations are installed.

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

**Foreseen Improvements**

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

The Lab. itself will enhance its performance with increase of the
participation of general public and other companies, universities and research
institutes. Through the implementation and dissemination of FESTIVAL project,
The Lab. aims at attracting more entities to operate various kinds of
experimentations, which will benefit as a result both participants and
Knowledge Capital.

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

**Owner/Responsible partner**

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

Knowledge Capital

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

**1.2.12. Validation framework for platform based services**  
  
<table>  
<tr>  
<th>

**Asset name**

</th>  
<th>

Platform quality assessment framework

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

**Asset Overview**

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

A methodology for the evaluation of software components (enablers) based
platforms has been developed in the context of the EU FIWARE initiative as
part of the health use case.

The methodology identifies several analysis dimensions:

  * Readiness of Enabler implementation for use in software applications: black box-­testing (BBT) of Enablers with model-­‐based test case generation. 

  

  * Willingness of developers to adopt software components beyond the project: developers’ quality of experience (DQoE). 

  

  * Ability of Enablers to be used in software applications and services that target the healthcare sector: internal interoperability (IIO). 

  

  * Ability of Enablers to be appropriated in the healthcare sector: e-­‐health interoperability (HIO) within health care sector activities. 

  

  * Preparation of Enablers for sustained provision and use: reuse readiness level (RRL) of the Enablers. 

  

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

**Type**

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

Service / Methodology.

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

**Innovation**

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

Platforms involve several stakeholders having different interests and thus
different expectations from the proposed platform services. At the same time,
collection of performance indicators should be undergone in a way to reduce
resources required to collect and analyse the information. An innovation
socio-­‐technological alignment matrix has been proposed.

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

**Interoperability**

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

The methodology can be applied/adapted to other components based platforms

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

**Foreseen Improvements**

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

The model will be extended and applied in FESTIVAL and will gain maturity. The
model and approach will be promoted to other deployments (TRL 6).

  * Adaptation of the FISTAR model to FESTIVAL specificities 

  

  * Extend the model to more domains (being health focused today) • Evaluate relevance in the Japanese context 

  

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

**Owner/Responsible partner**

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

EGM

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

**1.2.13. Engineering FIWARE-­‐Lab**  
  
<table>  
<tr>  
<th>

**Asset name**

</th>  
<th>

Engineering FIWARE-­‐Lab

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

**Asset Overview**

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

The Engineering FIWARE-­‐Lab (https://FI-­‐WARE.eng.it) is a cloud instance of
FI-­‐WARE that allows the users to deploy, configure and execute a set of
Generic Enablers (GE). The FIWARE-­‐Lab allows managing virtual resources in
order to deploy and execute the GE: it is possible to a set of virtual
resources to different projects/users, manage Network configuration, virtual
images and their virtual resources (RAM, CPU, Storage, volumes).

The cloud infrastructure, hosted in the Engineering data centre located in
Vicenza (Italy) is based on OpenStack, an open source software for creating
cloud platforms. This FIWARE-­Lab instance is directly managed by Engineering
and offers a specific environment and functionalities dedicated to the
FESTIVAL stakeholders. For instance, a set of preconfigured VM of Generic
Enablers are available for the partners to perform experiments related to the
FESTIVAL use cases: the GE can be used in As-­‐A-­‐Service approach, executing
them directly in the cloud environment, or can be downloaded to be deployed in
other environments. The Engineering team will offer also support in the usage
and management of the infrastructure

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

**Type**

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

Software platform

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

**Innovation**

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

The FI-­‐Lab is an example of open innovation making available all the
potentials of the different component developed by the FI-­‐WARE project, the
Generic Enablers. The GE offer general-­‐purpose functionalities in different
innovative areas such as Internet of Things, Security, Cloud, Data Management,
Network infrastructure etc. The provision of GE in new context and in
particular for Japanese partner will allow finding innovative way to use them.

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

**Interoperability**

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

FI-­‐WARE provides a tool, called FI-­‐OPS, that simplifies the deployment,
setup and operation of FI-­‐WARE instances by Platform Providers. In
particular some tools are dedicated to the expansion of the FI-­‐Lab network
through the federation of additional nodes (data centres) and allowing
cooperation of multiple Platform Providers. OpenStack APIs allow to launch
server instances, create images, assign metadata to instances and images,
create containers and objects, and complete other actions in OpenStack cloud.

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

**Foreseen Improvements**

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

The main improvement to be achieved through FESTIVAL is the federation between
the FIWARE-­‐Lab and the other involved testbeds. In particular ,the
possibility to directly deploy a FIWARE-­‐LAB instance on different platforms
(e.g. JOSE platform)will be explored.

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

**Owner/Responsible partner**

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

Engineering

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

####  1.2.14. PTL: experimentation area in CEA  
  
<table>  
<tr>  
<th>

**Asset name**

</th>  
<th>

PTL: experimentation area in CEA

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

**Asset Overview**

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

Experimentation area of PTL (connecting technologies platform) is located in
the heart of CEA Grenoble. It’s a place composed of 150 sqm of modular
building, and 1300sqm of urban area.

**Figure 10 -­‐ PTL -­‐ Connecting technologies platform**

These areas allow its core partners to test and validate experimentations and
prototypes in a close to real environment.

The modular building allows reorganising rooms for experimentation specific
needs, and already provide many sensors for building monitoring, such as
temperature and humidity, as well as some of the most popular communication
protocols like KNX, LON, Zigbee, etc.

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

**Type**

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

Place equipped with IoT devices

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

**Innovation**

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

The PTL testbed allows small and large enterprises to test their latest
products in close to real life conditions. FESTIVAL project’s Experimentation
as a Service model will bring an innovative approach to the existing
experimentation methodology by providing interoperability and possible
federation and replication with other testbeds. The approach will be validated
by deploying different use cases identified in the project.

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

**Interoperability**

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

Interoperability will be provided via the sensiNact platform, which will be
connected to platforms deployed in other testbeds. Experimentation as a
Service model will also play an important role for obtaining the
interoperability among the testbeds.

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

**Foreseen Improvements**

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

FESTIVAL project will allow PTL improving its experimentation methodology and
setup, as well as its replicability thanks to its Experimentation as a Service
model.

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

**Owner/Responsible partner**

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

CEA

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

####  1.2.15. sensiNact platform  
  
<table>  
<tr>  
<th>

**Asset name**

</th>  
<th>

sensiNactIoT Platform

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

**Asset Overview**

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

CEA’s IoT platform (sensiNact) is a set of enablers and services that provide
means for building context-­‐aware applications on top of smart connected
objects. It provides generic APIs to access resources provided by IoT devices.
The platform integrates different IoT devices and communication technologies
in order to provide a homogeneous access to the underlying heterogeneous
networks. The main advantage of the platform is simplicity of use and its
support of existing IoT protocols.

**Figure 11 – sensiNactIoT Platform**

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

**Type**

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

Platform

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

**Innovation**

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

The modular approach of the platform makes it easily extensible, thus allows
straightforwardly enhancing it with connections to testbeds. Its
service-­‐oriented architecture facilitates its integration with other
platforms and adoption of the Experimentation as a Service model. The support
of various IoT protocols is an advantage for easy integration of the physical
testbeds available in the project equipped with various IoT devices. Adding
support for new IoT devices is possible by creating the necessary protocol
bridge with a quite small effort.

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

**Interoperability**

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

The platform supports various IoT protocols such as CoAP, ZigBee, BLE,
enOcean, KNX, Sigfox, etc. as well as protocols for remote access to the
platform. In this way, the platform provides an abstraction of physical
devices allowing higher level applications accessing them without being aware
of their technical details. In order to access remotely the services available
on the gateway, different protocols can be used, such as HTTP REST,
JSON-­‐RPC, Web services, MQTT, etc. These different possibilities of
connection provide interoperable connection to other testbeds.

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

**Foreseen Improvements**

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

sensiNact will be integrating the Experimentation as a Service model of
FESTIVAL which will allow sensiNact to be used as a testing platform for IoT
applications. FESTIVAL project will also be an opportunity to test the
replicability of the platform in other testbeds.

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

**Owner/Responsible partner**

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

CEA

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

###  1.3. Exploitable project items first thoughts

The first stage of an exploitation plan is to clearly define the outputs that
the project will produce during its lifetime: although some concrete items are
well defined in the project scope, many others can be discovered only during
the project execution. A set of possible exploitable have been identified at
this stage of the project and are listed in the following sections. The items
identification process will continue during the whole duration of the project
and the following table will be updated in next releases of the exploitation
and business model deliverables to include new items that can be exploited
after the project end.

In the following table each item includes a description, the innovation
aspects and the exploitation opportunities beyond the project.  
  
<table>  
<tr>  
<th>

**Exploitable item name**

</th>  
<th>

**Description**

</th>  
<th>

**Innovation**

</th>  
<th>

**Exploitation beyond the project**

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

**SmartSantander SmartShopping deployment**

</td>  
<td>

A set of devices equipped with presence, environmental and radio-­‐based
sensors will be deployed within several shops in the city.

</td>  
<td>

A novel

indoor/outdoor testbed deployment within real scenarios to support
experimentation

based in indoor/outdoor

localisation in shops. It will also be integrated within the

SmartSantander

testbed to experiment with both indoor and outdoor sensors.

</td>  
<td>

The deployment of the smart shopping devices will seek two exploiting aspects:
On the one hand, it will introduce a novel Bluetooth ibeacon services in the
city of Santander, stimulating the consumption in the city centre shops.

On the other hand, including a new deployment on indoor/outdoor positioning
system aims at attracting the scientific community to the SmartSantander
testbed, pursuing novel results and an increased

scientific production.

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

**Exploitable item name**

</th>  
<th>

**Description**

</th>  
<th>

**Innovation**

</th>  
<th>

**Exploitation beyond the project**

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

**Pedestrian**

**analysis BLE**

**packets**

</td>  
<td>

**flow using**

**advertising**

</td>  
<td>

Pedestrian flow analysis based on Wi-­‐Fi packets is to be enhanced by
incorporating the functionality using BLE advertising packets transmitted from
a variety of wearable devices to further improve the accuracy of

pedestrian flows.

</td>  
<td>

Wi-­‐Fi packet-­‐based pedestrian flow analysis is suitable for

approximately

grasping both the flow and stagnant states of pedestrians with
Wi-­Fi-­‐enabled devices. By incorporating BLE advertising-­‐based

pedestrian flow analysis functionality, we envisage improving the accuracy and
the speed of analysis in the coming age of wearable computing

devices.

</td>  
<td>

We plan to maintain Wi-­‐Fi packets sensors already installed in an
underground shopping mall in Osaka area during/after the project lifetime.

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

**JOSE Sensing foundation deployment**

</td>  
<td>

JOSE sensing foundation will add sensor handling features to PIAX and JOSE
Testbed.

</td>  
<td>

JOSE sensing foundation provides support

experimentations on

PIAX and JOSE Testbed with sensor handling features and sensor data from
japan-­‐wide pre-­‐existing sensors.

</td>  
<td>

We will continue to maintain and improve JOSE sensing foundation for future
experimentations

after the project lifetime.

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

**Exploitable item name**

</th>  
<th>

**Description**

</th>  
<th>

**Innovation**

</th>  
<th>

**Exploitation beyond the project**

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

**Constructing an application and investigating a SDN function on**

**JOSE testbeds**

</td>  
<td>

KSU is planning to exploit JOSE testbed to construct a prototype Smart City
application using low cost sensors (e.g. current weather report) to
investigate the architecture required in Smart City applications.

KSU has also been developing a Pub/Sub middleware based on PIAX. The
middleware provides robustness by P2P functionality, and also optimizes packet
transfer path by SDN, especially OpenFlow functionality. The system can be a
prototype middleware to investigate mapping between abstracted application
requirements and network parameters.

</td>  
<td>

The prototype Smart City application will provide us typical requirements in
supporting Smart City experiment.

The developed middleware will provide robustness and efficiency
simultaneously. It also has a possibility to integrate SDNs operated by
multiple

policy domains.

</td>  
<td>

KSU will continue to apply and develop the architecture and middleware in
future

research projects.

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

**Federated Open**

**Data and**

**resources**

</td>  
<td>

The possibility to use federated resources to

experiment a new service

</td>  
<td>

Complex services require multiple resources not

available on site

</td>  
<td>

Propose this federated model as an offering to Tuba partners

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

**End user**

**engagement methodology**

</td>  
<td>

A methodology for end user involvement, including ethics and privacy
protections

</td>  
<td>

A dedicated methodology for IoT deployments.

</td>  
<td>

Inno will continue to apply and develop the methodology in future

research projects.

The methodology will be published as a project work

(to be reused by others).

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

**Exploitable item name**

</th>  
<th>

**Description**

</th>  
<th>

**Innovation**

</th>  
<th>

**Exploitation beyond the project**

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

**Socio economic**

**impact assessment framework**

</td>  
<td>

An evaluation framework to assess the potential socio economic impact of IoT
deployments

</td>  
<td>

A dedicated methodology for IoT deployments.

</td>  
<td>

Inno will continue to apply and develop the framework in future research
projects.

The methodology will be published as a project work

(to be reused by others).

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

**Quality evaluation framework for**

**EaaS built upon**

**federated testbeds.**

</td>  
<td>

Set of KPIs relevant to evaluate relevance and quality of EAAS offer

</td>  
<td>

A dedicated methodology being users oriented for platforms evaluation

</td>  
<td>

EGM will continue making use of the proposed methodology within other testbeds

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

**Active Lab.**

</td>  
<td>

This exhibition area introduces exciting technologies and activities from
corporations, universities, and other institutions.

</td>  
<td>

Implementation and dissemination of the experimentation with feedbacks from
general public.

</td>  
<td>

Knowledge Capital is to accept implementation of different kinds of
experimentations and the stock of knowledge will be succeeded and also reused
in the future.

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

**Active Studio**

</td>  
<td>

A venue used for workshops, seminars, and other kinds of

public presentation.

</td>  
<td>

Equipped with JGN-­‐X and other devices that encourage interactive
communication with the visitors.

</td>  
<td>

A number of events and workshops held in Active Studio continuously attract
public attention, which would result in improvements of its performance by
participations of any other companies, organizations and general public during
and beyond the project.

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

**Exploitable item name**

</th>  
<th>

**Description**

</th>  
<th>

**Innovation**

</th>  
<th>

**Exploitation beyond the project**

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

**xEMS system**

</td>  
<td>

Low-­‐latency, high-­‐speed, reliable, secure, stable and interoperable Energy
Management Systems for various facilities (xEMS:x = Building, Community,
House,

Factory, Datacenter, …).

</td>  
<td>

Integrating various and existing local EMS into ASP-­‐based large-­scale EMS
to further energy efficiency and cost reduction. Obtained EMS data will be
exploited as

Open Data.

</td>  
<td>

Applying our system to Real-­‐

world EMS based on experimental results on IoT federated testbeds.

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

**SNS-­‐like EMS system**

</td>  
<td>

A novel EMS architecture that exploits the concept of SNS to realize direct
device-­‐to-­‐device communication.

</td>  
<td>

Various operations are conducted via

``chatting’’ among system factors such as home appliances, sensors, and humans
such as operators and end users. Broker-­‐

based pub/sub protocol is used (MQTT). Devices communicate with each other

autonomously.

Obtained EMS data will be exploited as

Open Data.

</td>  
<td>

Applying our system to large-­‐scale EMS environment such as data centers,
that has huge number of servers, power supplies, air conditioners, and various
kinds of sensors/actuators.

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

**Exploitable item name**

</th>  
<th>

**Description**

</th>  
<th>

**Innovation**

</th>  
<th>

**Exploitation beyond the project**

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

**Big data analysis system**

</td>  
<td>

Efficient distributed system for data mining. Personalization is achieved by
clustering algorithms running on top of the distributed system.

</td>  
<td>

We develop a data partitioning technique that reduces the communication cost
and balances the load among different cores/computers.

Also, we develop an efficient technique for reducing contentions in parallel
data mining processing.

</td>  
<td>

Applying our system to other application domain, such as improving the care
quality for patients with cognitive impairment.

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

**Smart Shopping Santander app**

</td>  
<td>

A mobile application will be developed in order to deliver offers and
discounts generated by shops in the city center.

</td>  
<td>

The use of Bluetooth technology as communication channel, based on proximity
among users and shops.

</td>  
<td>

From City Council point of view, the objective is double: -­‐ Fostering and
reinforcing the consumption in the city centre, where due to several factors
including crisis and shopping centers located on the outskirts, by taking
advantage of new technological solutions, and -­‐ second, getting citizens
involvement in this initiative, as key factor of the project.

Finally, this app would be integrated within the city app (SmartSantander

Augmented Reality), once

FESTIVAL project ends.

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

**Exploitable item name**

</th>  
<th>

**Description**

</th>  
<th>

**Innovation**

</th>  
<th>

**Exploitation beyond the project**

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

**sensiNact platform**

</td>  
<td>

An IoT platform which provides a communication hub among various IoT protocols
as well as a programming model for IoT

applications.

</td>  
<td>

Its modular and service oriented approach allows easy integration of new
protocols, as well as rapid prototyping of

IoT applications.

</td>  
<td>

FESTIVAL project will allow validating the usability and replicability of the
sensiNact platform in different testbeds using various new technologies. The
feedback from experimenters will allow improving sensiNact and adding new test

features to the platform.

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

**Smart Image**

**sensors**

</td>  
<td>

A smart camera that can embed various image sensors and high-­‐level image
processing. Already developed image sensors can capture only relevant image
features, describing the content of an observed scene while taking

care of privacy aspects.

</td>  
<td>

The modularity of the smart camera and its capability in terms of embedded
processing allow a wide variety of applications. For instance, the camera can
be designed to be low power and privacy friendly. Alternatively, it can be
designed to provide high-­‐level interpretation of the scene.

</td>  
<td>

In the FESTIVAL project, a mock-­‐up of a smart camera using off-­‐the-­‐shelf
components (i.e. commercial image sensor, FPGA, embedded computer) and smart
imagers designed at the CEA will be developed and deployed. The goal is to
test the smart camera architecture in different IoT testbeds of the project
such as a public city area or a train station. This will allow the validation
of CEA smart sensor approaches and transfer this technology to industrial
partners after the project.

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

**Exploitable item name**

</td>  
<td>

**Description**

</td>  
<td>

**Innovation**

</td>  
<td>

**Exploitation beyond the project**

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

**Federated Open Data Catalogue**

</td>  
<td>

To be implemented in the

WP2, this web portal will be a single point of access for all the open data of
testbed. The

Federated Open Data

Catalogue will provide also services to access to open data from external
system and application in a standard way.

</td>  
<td>

The Federated Open Data will allow to access and search data in a federated
way. The open data stored in different repositories will be available through
a single portal with common data models and standards

</td>  
<td>

This asset can be exploitable after FESTIVAL in future projects, but also can
proposed as a business product for the public sector market.

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

**Testbed**

**Federation API and technologies**

</td>  
<td>

One of the main scope of the FESTIVAL project is to achieve the technical
federation among different testbed using a common and homogeneous

API and technologies

</td>  
<td>

The main innovation topic of this items the federation among completely
different testbed and platform

</td>  
<td>

The federation technologies defined in FESTIVAL can be proposed as specific
standards or exploited in the service and platform integration domain for the
development of commercial products.

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

###  1.4. Single partners exploitation plan

####  1.4.1. CEA  
  
<table>  
<tr>  
<th>

**Partner Profile**

</th>  
<th>

CEA-­‐LETI is one of the laboratories of the Technological Research Division
of CEA. Nearly 1,800 persons are serving innovation and the transfer of
technology in key domains such as ICT, wireless communications, security,
creativity and usage of new technologies. More than 85% of its activity is
dedicated to research finalised with external partners. The laboratory secures
more than 170 patents every year and has already sparked the creation of
nearly thirty high-­‐technology start-­‐ups. CEA-­‐LETI is today one of the
main contributors to European projects in the area of

Internet of Things and Smart ICT service such as SENSEI (coordinator),

IOT-­‐A, IOT-­‐I, SMART-­‐SANTANDER, BUTLER (technical coordinator), EXALTED,
OUTSMART, and the EU-­‐Japan project ClouT (coordinator).

CEA is a multidisciplinary institute of which different labs are participating
to the project. I) A software lab who has been involved in and coordinated
many projects in the domain of IoT, thus having broad experience on IoT
protocols and platforms in Europe and worldwide, ii) experimentation and
integration platform lab which provides a physical testbed for IoT
applications iii) a dedicated imaging lab that has a large experience and
competencies on smart cameras and image sensors and finally iv) art & science
division where artists and designers meet scientists to produce breakthrough
innovations responding real expectations of our society.

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

**Technical outcomes**

</td>  
<td>

FESTIVAL project will give the opportunity for CEA’s IoT platform and imaging
sensor to be validated in different testbeds of the project having particular
specificities and dealing with particular use cases. FESTIVAL project will
also allow applying the Experimentation as a Service model to its PTL
experimentation testbed, of which the aim is to speed up the development and
marketing of innovative products integrating advanced microelectronics
technologies in emerging and strategic fields of Health, Housing and
Transport, through the provision of technology platforms and associated
expertise.

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

**Competence and skills to be improved**

</td>  
<td>

FESTIVAL project will basically allow improving CEA’s testing skills in the
IoT domain. CEA will learn from the real life IoT deployment experiences of
the project partners, in addition to the possibility of experiencing with the
IoT testbeds of the project partners. The project will also extend CEA’s
competencies with the technologies used at those testbeds. Last but not least,
CEA will benefit from the project results obtained in terms of user
involvement in IoT experimentations...

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

**Individual exploitation**

**intentions**

</td>  
<td>

CEA has plans of commercially exploiting that platform with its industrial
partners. The results of the evaluation will determine the robustness of the
approach and better define its business plan. The results of the evaluation
will be published in scientific events. FESTIVAL project’s Experimentation as
a Service model will give the opportunity of testing it for CEA’s future offer
on reuse of those platforms by regional and national SMEs that need such
platforms to test their innovative applications.

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

**1.4.2. Engineering Ingegneria Informatica S.p.A.**  
  
<table>  
<tr>  
<th>

**Partner Profile**

</th>  
<th>

Engineering Group is a global IT player, the first at Italian level, leader in
the provision of complete integrated services throughout the software value
chain. The group produces IT innovation to more than 1.000 large clients, with
a complete offer combining system and business integration, outsourcing, cloud
services, consulting, and proprietary solutions. Engineering Data Centres
offer business continuity and IT infrastructure management to about 15.000
servers and 230.000 workstations.

Engineering holds different responsibilities within the international research
community, including technical and overall co-­‐ordination of large research
projects and consortia. In particular, the company is core partner of EIT ICT
Labs in Italy (European Institute of Innovation and Technology) focused on
leveraging ICT for Quality of Life; founding partner of the Future Internet
PPP initiative; member of the Board of EOS (European Organisation for
Security). Engineering is one if the partners that built and currently
supports FIWARE platform: in particular it is working in to build the FIWARE
Open Source Community to foster and support the evolution of standards for
Smart Cities and their spread worldwide. It is expected that the FIWARE Open
Source Community will be fully operational at the end of Q2-­‐2015.

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

**Technical outcomes**

</td>  
<td>

The FESTIVAL project will be a concrete chance to improve the FIWARE platform
and the FIWARE-­‐LAB adding new components (i.e. Generic Enablers) or extend
the open specifications to support federation with different testbeds and
platforms.

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

**Competence and skills to be improved**

</td>  
<td>

The skills that will be improved through the participation to the FESTIVAL
activities are main related to the FIWARE platform deployment and integration
in relation with the external testbed; also other competences will be acquired
thanks to the research on open data, defining new data models and standard API
suitable for the federation of the information among the different pilot
sites.

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

**Individual exploitation**

**intentions**

</td>  
<td>

ENG will take FESTIVAL as real opportunity to keep on consolidating its role
within FIWARE world and to expand the use of FIWARE also in different domains
covered by the project experimentations. It will be also interested in
exploring the opportunities to interoperate with other platforms, highlighting
FIWARE flexibility and enlarge the FIWARE ecosystem involving Japanese
stakeholders.

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

**1.4.3. University of Cantabria**  
  
<table>  
<tr>  
<th>

**Partner Profile**

</th>  
<th>

University of Cantabria and, concretely, The Network Planning and Mobile
Communications Laboratory group, have a strong background in the research of
wireless technologies, such as data transmission techniques, mobile networks,
traffic engineering and network management. During the last years, the group
has increased its research in the IoT and smart city research areas with
projects like SmartSantander, Lexnet or EAR-­‐IT, creating, promoting and
enhancing a unique-­‐in-­‐the-­‐world urban testbed of IoT connected devices.
The testbed is also part of several federation initiatives looking to reach
the scientific IoT research community as much as possible. As part of
FESTIVAL, University of Cantabria will be able to expand the SmartSantander
testbed increasing international scientific collaborations. University of
Cantabria will also support FESTIVAL federation objective by sharing his
experience in previous federation projects.

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

**Technical outcomes**

</td>  
<td>

University of Cantabria will increase the possibilities of the SmartSantander
testbed by federating it with other testbeds of Europe and Japan.

Additionally, as part of the Smart Shopping use cases, University of Cantabria
expects to increase the SmartSantander testbed capabilities and services by
integrating new sensors devices in real scenarios to experiment with
indoor/outdoor positioning.

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

**Competence and skills to be improved**

</td>  
<td>

As expected from the project results, University of Cantabria will expand its
research by including a new field, indoor/outdoor positioning. Additionally,
new learnings on external testbeds are expected as part of the federation work
carried out within FESTIVAL. This will lead to experiment with more resources
in new areas by using several testbeds within the project.

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

**Individual exploitation**

**intentions**

</td>  
<td>

University of Cantabria pursue increasing the scientific production of the
institute by several means:

  * Novel scientific papers, posters and conferences as result of the works carried out in the project. 

  

  * Increased possibilities in research fields for students of the university, such as end of degree projects, master thesis and 

  

PhDs.

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

**1.4.4. Ritsumeikan University**  
  
<table>  
<tr>  
<th>

**Partner Profile**

</th>  
<th>

The members of Ubiquitous Computing and Networking Laboratory at Ritsumeikan
University have a strong background in the research of indoor positioning
technologies using Wi-­‐Fi, BLE, PDA, and the hybrid of them, as well as
wearable computing and pedestrian flow analysis method using Wi-­‐Fi packet
sensors. As a member of FESTIVAL project, our research interest lies in
exploring how pedestrian flow information is effectively utilized in
experimentation testbeds in the context of smart shopping and smart cities
with different cultural backgrounds.

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

**Technical outcomes**

</td>  
<td>

Ritsumeikan University expects the system deployment onto the JOSE testbed in
Japan and possible federation with European testbed to further integrate with
IoT infrastructure and investigate novel applications and services.

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

**Competence and skills to be improved**

</td>  
<td>

Ritsumeikan University will expect to acquire information and experience of
IoT testbeds actively used in Europe to further collaborate with research
partners worldwide during/after FESTIVAL project.

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

**Individual exploitation**

**intentions**

</td>  
<td>

Ritsumeikan University intends to utilize experimentation opportunities using
a federated testbed between EU and Japan to further improve the system
deployed in existing experimentation fields in Osaka area to produce
scientific results.

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

**1.4.5. Acutus Software, Inc.**  
  
<table>  
<tr>  
<th>

**Partner Profile**

</th>  
<th>

Acutus Software is software development company. The company provides custom
software development service including following areas:

  * Video transmission for Android / iOS applications 

  

  * HDTV video transmission systems 

  

  * High quality voice transmission systems 

  

  * Low-­‐latency TV conference systems 

  

  * Network monitoring softwares 

  

  * Tuning of high-­‐definition video for software CODEC 

  

  * P2P platforms 

  

Acutus Software will provide support for experimentations on PIAX and

JOSE Testeds and development of the required software components.

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

**Technical outcomes**

</td>  
<td>

Acutus Software will increase usability of PIAX and JOSE Testbeds by
development of the software components and federating it with other testbeds
of Europe and Japan.

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

**Competence and skills to be improved**

</td>  
<td>

As expected from the project results, Acutus Software will improve its own
skills and knowledge on the sensing platforms.

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

**Individual exploitation intentions**

</td>  
<td>

Acutus Software aims improvement of the sensing features of PIAX and JOSE
Testbeds and producing scientific papers on the area. In addition, Acutus
Software will be collecting the know-­‐how of IoT and sensing platform for
future business opportunity.

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

####  1.4.6. KSU  
  
<table>  
<tr>  
<th>

**Partner Profile**

</th>  
<th>

Kyoto Sangyo University (KSU) is one of the private leading universities of
Japan. KSU has a project of developing a Software Defined Network (SDN) aware
Pub/Sub. Cyber Kansai Project (CKP) is a joint research consortium among
commercial sectors and academic entities in Japan. Several board members of
CKP are belonging to KSU. Its research topics are focused on leading-­‐edge
technologies for the next generation Internet.

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

**Technical outcomes**

</td>  
<td>

KSU basically provides network environment in GFO area and connecting them
into the testbeds JOSE, PIAX and so on. KSU tries to construct a fundamental
Smart City application for investigating JOSE testbeds. KSU also tries to
investigate SDN function of JOSE testbed by applying existing Pub/Sub
middleware.

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

**Competence and skills to be improved**

</td>  
<td>

KSU will have significant experiences in the following competences and skills:

  * knowledge of IoT 

  

  * knowledge of JOSE and PIAX testbed 

  

  * IoT application use case analysis 

  

  * IoT testbed analysis 

  

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

**Individual exploitation intentions**

</td>  
<td>

KSU uses JOSE testbed for constructing a prototype Smart City application and
investigating SDN functionality of JOSE.

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

**1.4.7. SOPRA**  
  
<table>  
<tr>  
<th>

**Partner Profile**

</th>  
<th>

Sopra Steria, European leader in digital transformation, provides one of the
most comprehensive portfolios of end to end service offerings in the market:
Consulting, Systems Integration, Software Development, Infrastructure
Management and Business Process Services.

Sopra helps its customers in their digital transformation by designing,
building and operating key business services.

Sopra Steria is a key founder of the Tuba Living Lab and is part of a mixed
consortium of public and private entities: Metropole ofLyon, Rhône-­‐Alpes
Region, major companies as VEOLIA, , KEOLIS, EDF, ERDF and SFR, SMEs,
competitiveness clusters, research laboratories and start-­‐ups.

Sopra Steria works with the Tuba to experiment new services related to Health,
Transportation, Public Services.

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

**Technical outcomes**

</td>  
<td>

Sopra Steria is dedicated to offer the best experimentation tools to its
partners and customers. Therefore Sopra Steria, the Tuba and FESTIVAL partners
can mutually benefit from:

  * Federated Resources made accessible to experimenters, through interoperability 

  

  * User/Experimenter access made accessible to FESTIVAL partners 

  

  * A better testing/experimenting methodology and tools, based on the measure of performance done by Tuba 

  

  * The building and operating of an Experimentation as a Service instance 

  

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

**Competence and skills to be improved**

</td>  
<td>

Sopra Steria provides through the Tuba its expertise and skills around
communication, project management and innovation management

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

**Individual exploitation**

**intentions**

</td>  
<td>

Sopra Steria plans to use the FESTIVAL end-­‐to-­‐end federation to design
better services and optimize their time-­‐to-­‐market.

FESTIVAL resources could be part of the economic model of selected projects
for its customers and partners.

Also the cultural aspect of an international federation helps understand the
local requirements and issues with organizations and end users.

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

**1.4.8. Inno**  
  
<table>  
<tr>  
<th>

**Partner Profile**

</th>  
<th>

Inno group is a leading strategic management consultancy company operating in
nearly all-­‐European countries. Inno group has offices in Karlsruhe (Inno
AG), Rostock, Berlin, Sophia-­‐Antipolis and Stockholm. Inno offers a
multi-­‐national, highly qualified team of more than 50 consultants. Over the
last 20 years, inno has combined highly specialized expertise, creativity and
pragmatism to assist more than 500 clients all over Europe. One of the core
activities of inno is to provide management, dissemination and exploitation
support to scientific leaders of complex inter-­‐institutional and
trans-­‐national projects, with particular focus on ICT. This includes support
in consortium & knowledge management, IPR issues, dissemination and
exploitation of research results, marketing and public relations activities,
event organization, and coordination of industrial case studies and animation
of working groups and industrial panels. Inno-­‐group runs a patent
commercialization office in Germany.

Inno has over 15 years of experience in implementation of EU-­‐wide
dissemination campaigns.

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

**Technical outcomes**

</td>  
<td>

  * End user engagement tools 

  

  * Socio economic impact assessment framework 

  

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

**Competence and skills to be improved**

</td>  
<td>

The following competences and skills will be improved through the project:

  * End user engagement methodology 

  

  * Socio economic impact assessment methodologies 

  

  * Knowledge of the IoT and FIRE ecosystem 

  

  * Knowledge of Japanese IoT ecosystem 

  

  * Research and Innovation Project dissemination and communication 

  

  * Exploitation and support to innovation 

  

  * Project management 

  

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

**Individual exploitation**

**intentions**

</td>  
<td>

Inno plans to reuse the knowledge and experience achieved through the
participation to the FESTIVAL project to reinforce its expertise of the Future
Internet Experimentation innovation ecosystem and its potential
socio-­‐economic impact. This will fuel future consultancy business
development in helping public authorities take up and support FI innovations.

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

**1.4.9. Easy Global Market**  
  
<table>  
<tr>  
<th>

**Partner Profile**

</th>  
<th>

EGM is providing solutions and services to develop market confidence in
technologies making the global market easy for companies looking for
globalisation. EGM is specialised in validation, interoperability,
Certification and label programmes including for FIRE and IoT areas. EGM is
working with state of the art testing and interoperability tools, validation
approaches and advanced techniques using experience gained by EGM’ Directors
working in +25 FP/H2020 projects and designing +10 worldwide label or
certification programmes. EGM is currently involved in 7 FP7 and H2020
projects including IoT (SA Smart Action), H2020 U-­‐TEST on Model Based
Testing for CPS, Future Internet Experiment FIRE on IoT test beds (i.e. H2020
FIESTA) , FIWARE (FICORE) and FI-­‐PPP Use Case FI-­STAR Project. EGM is
founder member of the IoT Forum and lead one out the three WGs on “market
confidence”.

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

**Technical outcomes**

</td>  
<td>

• Validation tools and methods for federated testbeds

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

**Competence and skills to be improved**

</td>  
<td>

The following competences and skills will be improved through the project:

  * Interoperability events organisation 

  

  * Data and Semantic interoperability 

  

  * Knowledge of on-­‐going standardisation for IoT 

  

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

**Individual exploitation**

**intentions**

</td>  
<td>

EGM intends to better identify the forthcoming standards of interest for IoT
at the worldwide scale and support the development of tools and methods
related to their conformance and interoperability evaluation. These tools
would be used in the possible development of labels and certifications within
the IoT sphere.

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

**1.4.10. Knowledge Capital**  
  
<table>  
<tr>  
<th>

**Partner Profile**

</th>  
<th>

Knowledge Capital is a center for intellectual creation, where businesspeople,
researchers, creators, and ordinary people come together to create new values
by exchanging and combining knowledge and ideas. The center is fully equipped
with facilities for interpersonal exchanges, such as various sized offices, a
salon, labs, showrooms, a theater, event spaces, and a convention center. The
name Knowledge Capital represents the facilities, the organization, and the
activities itself. They will go beyond the conventional focus on the economy
to generate brand new activities that can possibly emerge only through human
interactions. Knowledge Capital believes this is the way to create innovative
culture, ideas, goods, and services.

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

**Technical outcomes**

</td>  
<td>

N/A

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

**Competence and skills to be improved**

</td>  
<td>

Knowledge Capital offers the experimentation location for FESTIVAL project,
close interactions and communication with general public and participants.
Also the coordination of the use of other Knowledge Capital facilities as
EU-­‐Japan collaboration project, including other companies that concern Grand
Front Osaka. Through these contributions, Knowledge Capital will be able to
reinforce the partnership with participants and general public. Also the
implementation of different kinds of experimentations by utilizing the stock
of knowledge acquired during this project will bring about further engagement
and interaction.

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

**Individual exploitation**

**intentions**

</td>  
<td>

Supporting and facilitating the implementation of experimentation by realising
the requirements from other partners in order to secure the performance of
FESTIVAL experimentation.

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

**1.4.11. OSAKA University**  
  
<table>  
<tr>  
<th>

**Partner Profile**

</th>  
<th>

Osaka University research team is the leading organization as an expert group
on Big Data technology and Green ICT, including energy management, smart grid,
and information protocols. The communication interface standardization project
for the interoperability supported by the Ministry of Internal Affairs in
Japan is being promoted. One of the members of the Osaka University has been
promoting the standardization as a Chair. In addition, in terms of Big Data
technology, Osaka University has been successful representing the world of
high-­speed algorithm of graph mining and distributed processing platform.

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

**Technical outcomes**

</td>  
<td>

Osaka University will develop a novel EMS protocol, based on web-­‐based
communication protocol, for realizing large-­‐scale xEMS that integrates
existing EMS cites on buildings, datacenters, factories, homes. SNS-­‐like EMS
is also constructed for direct communication among devices, sensors and
actuators, based on existing MQTT protocol over WebSocket protocol.

We will also develop two techniques for Big data analysis system and apply the
system to smart shopping applications. The first technique is a data
partitioning technique that reduces the communication cost and balances the
load among different cores/computers. The second one is for reducing
contentions in parallel data mining processing.

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

**Competence and skills to be improved**

</td>  
<td>

Osaka University will have significant amount of experiences and
technical/non-­‐technical insights on IoT testbeds and their utilization for
establishing smart energy and smart shopping architecture. Osaka University
will also obtain tight relationship to Europe research organizations in
FESTIVAL project regarding to IoT testbeds for further research collaboration.

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

**Individual exploitation intentions**

</td>  
<td>

Osaka University will utilize the experimental experiences and obtained
results to apply real-­‐world EMS like FEMS (Factory EMS), DEMS (Datacenter
EMS), BEMS (Building EMS), as well as CEMS (Community EMS) including them.
Standardization of communication protocol for EMS is also an important
exploitation by OSK.

In addition, Osaka university will make smart shopping experiments and
evaluate the effectiveness of the personalization and the efficiency of the

Big data analysis system. Then, we will make feedback to our system.

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

**1.4.12. Japan Research Institute for Social Systems**  
  
<table>  
<tr>  
<th>

**Partner Profile**

</th>  
<th>

JRISS is a private company dedicating fundamental technologies applied to
civil engineering and information science, excel in development information
systems as well as urban and transportation planning.

We provide a linked data oriented digital signage system with touch panel
operation that is now already installed at many railway stations. This signage
system provides information about railway services, digital maps around
stations, railway timetables and also provides multimedia advertisement
messages on idling.

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

**Technical outcomes**

</td>  
<td>

Our main mission is project management. Our research interest lies in how to
apply the IoT technology on the actual urban development project.

JRISS and RU have data being able to be shared in FESTIVAL project, which
gathered from some experiments of the Wi-­‐Fi packet sensor in the some
traffic survey on car traffic flow and pedestrian flow analysis.

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

**Competence and skills to be improved**

</td>  
<td>

JRISS provide legal and economic problem solving skills to install IoT
technology on the real world.

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

**Individual exploitation intentions**

</td>  
<td>

We intend to utilize experimentation opportunities using a federated testbed
between EU and Japan In order to explore the applicability on the real world.

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

**1.4.13. City of Santander**  
  
<table>  
<tr>  
<th>

**Partner Profile**

</th>  
<th>

The city of Santander is the capital of the Cantabria region located in the
north of Spain and with a current population of 174,000 inhabitants. The city
Council is strongly committed with the Innovation and, in this way, is working
to provide a more efficient and closer to the citizen city management through
the use of new technologies.

The city participates in diverse initiatives related to smart cities. Among
them, the SmartSantander project has established a before and after in the way
of conceiving and organizing innovation in the city. Thus, Santander is well
known as a unique living lab in which to experiment with new technologies,
applications and services. Currently, it is supporting other European
Projects, such as ClouT and FESTIVAL.

A sustainability model has been developed based on the creation of a City
Platform, which will be fed with data coming from all the urban services. In
order to ensure this data provision, urban service tenders will include
innovation clauses, as has occurred with the waste and water management
services.

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

**Technical outcomes**

</td>  
<td>

Santander Municipality will:

  * Improve existing mobile app through the smart shopping use case, by adding new functionalities, 

  

  * Include Smart shopping use case outputs in the current Open Data catalogue, adding new categories which may be used to develop new applications and/or services, 

  

  * Improve the existing IoT infrastructure by the federation with other EU and JP testbeds, which may provide future projects 

  

  * Increase IoT infrastructure by the integration of new sensors, which will be used not only in this project, but also in future ones. 

  

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

**Competence and skills to be improved**

</td>  
<td>

</td>  
<td>

Santander Municipality expects to improve the following competences and skills
related to provide a more efficient city management, closer to the citizen
through the use of new technologies:

  * Improve relationship with Market associations and shopkeepers, listening to their necessities and providing them new tools in order to foster the consumption in the city center. 

  

  * Improve citizens communication, reinforcing their involvement as key actors in the use case, 

  

Take advantage of federation of EU and JP testbeds, which may provide not only
new collaborative opportunities, but also new services/apps development.

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

**Individual exploitation**

**intentions**

</td>  
<td>

The purpose of field trials for Santander is to start carrying out valuable
services to the citizen. Santander City Council is at the moment drawing the
strategy that it will follow in the next years around the Smart City concept.

As aforementioned, the main goal of this project is to foster the consumption
in the city centre shops, together with getting citizens involvement.

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

**1.4.14. West Japan Marketing Communications Inc.**  
  
<table>  
<tr>  
<th>

**Partner Profile**

</th>  
<th>

West Japan Marketing Inc. (jcomm) is a Japanese advertising agency subsidiary
of West Japan Railway Company. We are handling all types of advertisement and
publicity including ones for newspapers, magazines, TVs, radios,
transportation, sales promotion.We are exclusively contributing with
advertising solutions at the train stations and buildings around the stations.

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

**Technical outcomes**

</td>  
<td>

Our main mission is providing the experimental location for FESTIVAL project,
while protecting personal information of the common space. This policy will
comply even in FESTIVAL experiments.

Jcomm and JRISS has succeeded in joint development of touch-­‐panel digital
signage system. Taking advantage of this relationship, we will work even in
solutions of FESTIVAL project.

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

**Competence and skills to be improved**

</td>  
<td>

Jcomm offers the experimentation location for FESTIVAL project, for example
train stations and buildings around the stations. In this area we install many
digital signage for the provision of advertising and rail way information. The
digital signage system use Wi-­‐Fi and WiMAX technologies. We can thus
contribute to location owners to make them try new communication system.

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

**Individual exploitation**

**intentions**

</td>  
<td>

We intend to utilize experimentation opportunities using a federated testbed
between EU and Japan and to explore the applicability on the train station and
buildings around the station.

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

##  2\. Experimentation as a Service ecosystem

FESTIVAL project is based on the Experimentation as a Service approach. In
order to define the exploitation opportunities and the business model for the
services and products that the project will provide as outcomes, it is
fundamental to define and study the possible ecosystem based on EaaS that
involves entities and processes. This section presents an initial definition
of this ecosystem trying to describe the processes that are necessary to
collect the resources to create federated testbeds and to manage and run
experiments, as well as the user’s roles and the concrete stakeholders that
participate in the process. In this version, our analysis is at its early
stage and will be improved and updated in the next deliverables related to
business models.

###  2.1. EaaS processes and stakeholders

The first step to define the “Experimentation as a Service” ecosystem is to
identify the processes and the entities that are involved in it. The following
tables give a brief description of four main identified entities, and the
related process group that will be presented in details in the next sections.
It is important to say that the processes listed in this chapter are not only
the ones to be executed in the FESTIVAL project, but are included also the
processes that could be present in a generic Experimentation as a Service
ecosystem  
  
<table>  
<tr>  
<th>

**Entities**

</th>  
<th>

**Description**

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

**Resource**

</td>  
<td>

It is a generic basic IT or non-­‐IT resource that can be part of an asset.
Examples of IT resources are, for instance, servers, virtual machines, network
connections, but in the same category are included also human resources or
physical items. The resources usually can be dynamically assigned or released
during an experiment.

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

**Asset**

</td>  
<td>

The asset represents a complex item that can be used to compose a testbed:
examples of asset can be a software platform, a physical space, an open data
repository, etc.

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

**Testbed**

</td>  
<td>

It is the environment in which can be executed the experiments. In addition,
in FESTIVAL case the testbed can be an IT infrastructure, a living lab or any
other environment suitable for experiment execution. The testbeds can be
federated to create a distributed environment.

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

**Experiment**

</td>  
<td>

This entity represents the experiment executed in the testbed or in a
federation of testbeds.

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

**Table 1 -­‐ Entities in the FESTIVAL EaaS ecosystem**

The Figure 12 shows an example of possible concrete entities and their
relationship in an EaaS ecosystem:

**Figure 12 -­‐ Resources, Assets, Testbed and Federation**

Next section describes the process involved in the ecosystem: each process is
classified in process groups based on its application scope, as reported in
Table 2.  
  
<table>  
<tr>  
<th>

**Process groups**

</th>  
<th>

**Description**

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

**Resource scope**

</td>  
<td>

Resource scope is the lowest level scope of FESTIVAL EaaS ecosystem. It
includes all the processes concerning the management of resources. Main aim of
the processes of this scope is the collection of resources necessary for
running experiments.

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

**Asset scope**

</td>  
<td>

Asset scope includes all the processes related to the management of assets
that are valuable in setting testbeds up.

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

**Testbed scope**

</td>  
<td>

Testbed scope includes all the processes related to the management of testbeds
that are valuable in setting federation up, in order to provide required
functionalities for running “Experimentation as a Service” platform.

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

**Experiment scope**

</td>  
<td>

Experiment scope includes all processes concerning the management of
experiments running on FESTIVAL’s environments through the “Experimentation as
a Service” approach

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

**Table 2 -­‐Process groups in FESTIVAL EaaS ecosystem**

For each scope, actors involved in the execution of processes are identified.
Each actor is described in Section **Errore. L'origine riferimento non è stata
trovata.** .

####  2.1.1. Resource scope

Main aim of processes included in resource scope is the management of
resources for running experiments. Resources can be ICT resources (physical or
virtualised: virtual machines, storage capacity, memory, computing capacity,
etcetera) or human resources, for example people that perform specific task
during the execution of an experiment. Amount and typology of resource
involved in an experiment can be adjusted during its execution of in order to
guarantee its correct progress. Processes related to this scope are:

  * **Resource discovery** : this process identifies necessary resources for experiment running in order to guarantee suitable service performance for experiment running itself. 

  

  * **Resource provisioning** : this process includes all activities related to resources acquisition, for instance the deployment of necessary virtual machines in compliance with result obtained by resource discovery process. 

  

  * **Resource monitoring** : this process includes all activities devoted to the maintenance of service level performance identified through “resource discovery” process; moreover this process is cyclical and it is continuously performed during experiment running. Resource monitoring includes, for instance, activities such as adjustment of amount of storage capacity or changing assignment to people involved in the experiment. 

  

  * **Resource release** : this process includes all activities related to resources release, such as 

  

“un-­‐deployment” of necessary virtual servers, freeing of storage space etc.

**Figure 13 -­‐ Execution sequence of resource processes**

Processes of resources scope are executed in sequence, as depicted in Figure
13.

####  2.1.2. Asset scope

Main aim of processes included in asset scope is building a new testbed. In
order to achieve this objective, assets are identified and integrated in the
testbed. Processes related to this scope are:

  * **Testbed requirements identification** : main aim of this process is the identification of requirements for experimental testbed; output of this process represents inputs of asset identification process. 

  

  * **Asset identification** : this process includes all activities devoted to the identification of existing potential reusable assets, such as infrastructures, HW/software platforms, HW/SW components, etcetera, that complies with testbed requirements identified through testbed requirements identification process. 

  

  * **Asset analysis** : through this process, an analysis of assets identified in the previous asset identification process is performed; a deep analysis of identified assets is necessary in order to understand their capabilities and limitations in the perspective of testbed set. In this context, each asset should be well documented and training materials should be available to support the analysis. 

  

  * **Asset selection** : results achieved through asset analysis process represent the starting point of asset selection process; through this process, a selection of assets that are of interest to the set up the testbed is performed. The selection is made on the basis of the requirements of the testbed and on the results of the analysis of identified assets; moreover asset selection process takes into account non technical aspects, such as IPRs (intellectual property rights) rules associated with the assets, available support resources, respect of ethics and privacy issues, adequate level of quality, etcetera. Involved actor is Testbed Manager. 

  

  * **Asset integration** : asset integration process represents the last macro activity useful for making a testbed; in particular, this process includes all activities necessary to integrate assets selected in asset selection process. In order to solve, technological and operational problems derived from possible heterogeneity of selected assets, this process includes the design and building of adaptation components. Moreover, assets integration process faces possible political constraints issues. Final result of asset integration process is realization of the testbed. 

  

  * **Asset monitoring** : this process includes all activities devoted to the maintenance of integrated assets into the testbed, in order to guarantee the integrity (in terms of provided services and functionalities) of the testbed itself; this process is cyclical and it is continuously performed. Moreover, through this process it is possible to identify possible enhancements on integrated assets and in general on the whole testbed. 

  

**Figure 14 -­‐ Execution sequence of asset processes**

Similarly to processes of resources scope, processes of assets scope are
executed in sequence, as depicted in Figure 14; their final result is the set
up of the testbed and the continuous monitoring of integrated assets.

####  2.1.3. Testbed scope

Main aim of processes included in testbed scope is the integration of a
testbed into the testbed federation; all actions needed to build the
federation among testbeds and make them interoperable are included in this
scope. In order to achieve this result, processes included in this scope cover
not only technical aspects, but also non-­‐technical, such as agreement
subscription, users privacy, policies definition, etcetera. Processes related
to this scope are:

  * **Standards and data models agreement subscription** : this process includes action devoted to the establishment of set of commonly agreed standards and data models among federated testbeds, in order to provide a homogeneous abstraction layer on top of the heterogeneous testbeds. 

  

  * **Testbed technical integration** : through this process a specific testbed is integrated in the federation of testbeds, according to standards and data models agreed in the previous process. This process includes the implementation of necessary adapters, in order to enable the testbed to interoperate with the entire federation of testbeds; in particular, adapters will be in charge of translation between data formats and interoperability among the different standards. 

  

  * **Testbed integration check** : testbed integration check includes action to verify the correct integration of the testbed with the entire federation of testbeds and to ensure expected results and performance. 

  

  * **Policies and conditions definition** : through this process, policies and conditions of access to testbeds are defined, such as the way in which the testbed is used or for what it is used (e.g. commercial or non-­‐commercial use). 

    * **End users privacy** : this sub process defines necessary measures and actions to guarantee protection of end-­‐users against privacy concerns; testbed must be in accordance with defined rules and actions. 

  

    * **Service Level Agreement** : this sub process defines service level agreements for the testbed in order to guarantee suitable quality of service and quality of experience to experimenters and users. 

  

  

  * **Drafting and publication of experimenter guidelines** : final result of this sub process is publication of documents about the specific testbed; in particular a set of guidelines in order to enable experimenters to use the testbed and to “create” experiments. Involved actor is Testbed Manager. 

  

**Figure 15 -­‐ Execution sequence of testbed processes**

####  2.1.4. Experiment scope

Main aim of processes included in experiment scope is the management of
experiments, from their definition to the collection and analysis of results
obtained from them; processes related to this scope are:

  * **Experiment definition** : this process represents the first step of experiment management; in particular, it enables experimenters to define both main aim and details of an experiment; definition of experiment obtained from this process represents “what” the experiment wants to demonstrate or to obtain. 

  

  * **Experiment setup** : definition of an experiment is the input of this process; experiment setup process includes all necessary actions that enables the execution of the experiment, both technical (e.g. use of web application, mobile application or both, etc.) and non – technical (e.g. target end-­‐users, channels of communication, etc); output of this process represents “how” the experiment should obtain expected results. 

  

  * **Experiment running** : this process includes all necessary action for executing an experiment; moreover it includes actions for collecting obtained results; experiment running process contains three main sub processes: o **End users involvement** : this sub process includes needed actions for involving end users and to collect information. 

    * **Experiment control** : this sub process includes actions for controlling and managing the evolution and the execution of the experiment. 

  

    * **Experiment monitoring** : this sub process includes actions for monitoring the experiment and evaluating its execution, in order to plan measures for its progression. 

  

  

  * **Evaluation of results** : inputs of this process is formation obtained from execution of an experiment through experiment running process; evaluation of results process includes actions for evaluating and analysing collected information. 

  

**Figure 16 -­‐ Execution sequence of experiment processes**

Processes of experiment scope (Figure 16) are executed in sequence and their
end point is the global result obtained from the execution of an experiment.

####  2.1.5. Roles

**Figure 17 -­‐ FESTIVAL's roles and relations among them**

  * **Testbed Manager** : it is responsible for a testbed; its main assignment is to guarantee efficiency of and retention of the testbed into the federation. Moreover, it is responsible for the management of assets that compose the testbed, including their identification, evaluation, integration and maintenance. It also manages the execution of experiments and provides support to experimenters in order to define and manage experiments. Finally, it is responsible for the management of resources (storage, memory, computing capacity, etcetera) that enable execution of experiments. To achieve this result it collaborates with Federation Manager, Service Provider and Experimenter. 

  

  * **Federation Manager** : it is responsible for the entire federation of testbeds; in particular, it manages the federation in order to maintain both efficiency levels and functionalities; to achieve this results, it works with Testbed Manager. 

  

  * **EndUser** : it is an end user involved in an experiment; it uses functionalities provided by an experiment: in that way, it supplies information to experimenters. 

  

  * **Service Provider** : it provides possible services necessary for establishment of testbed and for it maintenance; it provides the services toTestbed Manager. 

  

  * **Experimenter** : it is a fundamental role of FESTIVAL’s ecosystem, since it is the end user of the functionalities provided by the Experimentation as a Service ecosystem itself. With support of Testbed Manager, it plans, defines, designs and executes experiment and finally analyses results. 

  

In this section, a summary table describing relation between roles and
processes is provided.  
  
<table>  
<tr>  
<th>

**Role**

</th>  
<th>

</th>  
<th>

**Processes**

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

Federation Manager

</td>  
<td>

•

</td>  
<td>

Standards and data models agreement subscription

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

</td>  
<td>

•

</td>  
<td>

Testbed integration check

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

</td>  
<td>

•

</td>  
<td>

Policies and conditions definition

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

</td>  
<td>

•

</td>  
<td>

Service Level Agreement

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

Testbed Manager

</td>  
<td>

•

</td>  
<td>

Resource discovery

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

</td>  
<td>

•

</td>  
<td>

Resource provisioning

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

</td>  
<td>

•

</td>  
<td>

Resource monitoring

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

</td>  
<td>

•

</td>  
<td>

Resource release

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

</td>  
<td>

•

</td>  
<td>

Testbed requirements identification

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

</td>  
<td>

•

</td>  
<td>

Asset identification

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

</td>  
<td>

•

</td>  
<td>

Asset analysis

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

</td>  
<td>

•

</td>  
<td>

Asset selection

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

</td>  
<td>

•

</td>  
<td>

Asset integration

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

</td>  
<td>

•

</td>  
<td>

Asset monitoring

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

</td>  
<td>

•

</td>  
<td>

Standards and data models agreement subscription

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

</td>  
<td>

•

</td>  
<td>

Testbed technical integration

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

</td>  
<td>

•

</td>  
<td>

Testbed integration check

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

</td>  
<td>

•

</td>  
<td>

Policies and conditions definition

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

</td>  
<td>

•

</td>  
<td>

End users privacy

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

</td>  
<td>

•

</td>  
<td>

Service Level Agreement

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

</td>  
<td>

•

</td>  
<td>

Drafting and publication of experimenter’s guides

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

</td>  
<td>

•

</td>  
<td>

Experiment definition

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

</td>  
<td>

•

</td>  
<td>

Experiment setup

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

</td>  
<td>

•

</td>  
<td>

Experiment running

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

Service Provider

</td>  
<td>

•

</td>  
<td>

Asset integration

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

</td>  
<td>

•

</td>  
<td>

Testbed technical integration

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

</td>  
<td>

•

</td>  
<td>

Testbed integration check

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

Experimenter

</td>  
<td>

•

</td>  
<td>

Experiment definition

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

</td>  
<td>

•

</td>  
<td>

Experiment setup

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

</td>  
<td>

•

</td>  
<td>

Experiment running

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

</td>  
<td>

•

</td>  
<td>

End users involvement

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

</td>  
<td>

•

</td>  
<td>

Experiment control

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

</td>  
<td>

•

</td>  
<td>

Experiment monitoring

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

</td>  
<td>

•

</td>  
<td>

Evaluation of results

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

End User

</td>  
<td>

•

</td>  
<td>

Experiment running

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

**Table 3 -­‐Roles -­‐ Processes summary table**

####  2.1.6. Stakeholder analysis

The roles that were described in the previous section are now mapped with
possible concrete stakeholders involved in the experimentation ecosystem and
interested in general in the FESTIVAL project results are identified and
described.

#####  Testbed Manager

In FESTIVAL’s ecosystem, Testbed Manager is responsible for the management of
a specific testbed integrated in the federation. Testbed Manager could be
represented by Enterprises, Research Centres and Universities, which are the
ideal candidates for holding the role of Testbed Manager, because of the
importance the role itself. Testbed Manager should hold specific skills,
competences and expertise in order to successfully manage all aspects of a
testbed, from its conception to its maintenance.

#####  Federation Manager

Differently from Testbed Manager, in FESTIVAL’s ecosystem Federation Manager
is responsible for the management of the entire federation of testbeds, but
similarly to Testbed Manager, it could be represented by Enterprises, Research
Centres and Universities. These three subjects hold necessary skills,
competences and expertise for successfully managing all aspects of the
federation from both technical and not technical point of views.

#####  Experimenter

Experimenter is the main stakeholder of FESTIVAL ecosystem and it represents
the crucial point around which processes described inChapter2and internal
stakeholders of the ecosystem revolve. Experimenter could be represented by:

  * **Research Center** , **University** , **Living Lab** : Research Center, University and Living Lab could be interested in experimentations for validating and verifying application (that could be in early stage of development) or to undertake studies in specific fields. 

  

  * **Researcher, Application Developer** , **Start-­‐up** : similarly to Research Center, University and Living Lab, Researcher, Application Developer and Start-­‐up could be interested in experimentations for validating and verifying application or to undertake studies in specific fields; in this particular case, they could be driven by business purpose in addition to scientific purposes. 

  

  * **Public Administration** : a Public Administration could provide access to its applications and databases, such as civil registry or land registry, in order to enable the execution of experiments that involve themselves; this is mainly due to the fact that a Public Administration can play the roles of Service Provider and Experimenter and it can run experiments that involves its services, in addition to make this services available to other experimenters. 

  

  * **Enterprise** : in general, an enterprise could be interested in functionalities provided by FESTIVAL’s Experimentation as a Service in order to check for example prototype application or solution or to investigate new fields of business; an enterprise could be represented by a large range of subjects, from micro enterprise to large enterprise, such as industries. 

  

#####  Service Provider

Service Provider supports Testbed Manager both in the establishment and in
maintenance of the testbed providing specific services. Service Provider could
be represented by:

  * **Research Center** , **University** : Research Center and University could provide innovative services and functionalities in their early stage of development in order to take advantage of a largest test bench. 

  

  * **Public Administration** : a Public Administration cloud provide access to its applications and databases, such as civil registry or land registry, in order to enable the execution of experiments that involve themselves; this is mainly due to the fact that a Public Administration can play the roles of Service Provider and Experimenter and it can run experiments that involves its services, in addition to make this services available to other experimenters. 

  

  * **Other EaaS Projects or Initiatives** : other EaaS projects or initiatives could provide new and solid technologies and/or specific applications that are valuable for comprising new functionalities in the testbed. 

  

  * **Enterprise** : in general, an Enterprise could provide services and functionalities that are strengthened and well organized in order to build up the testbed; similarly to Public Administration, an Enterprise can play the role of Service Provider and the role of Experimenter in FESTIVAL’s ecosystem. 

  

#####  End User

End User represents the final user of applications and services provided
during the execution of the experiments. Specific end users should be
identified for each experiments that will run in EaaS ecosystem; for instance,
in the context of FESTIVAL’s project end-­‐users could be Citizen, Art &
Science performer, Industrial User, etc.; in general, specific typologies of
end users can be identified for each experiment.

####  2.1.7. Experiment: from definition to results

In this section, a description of processes involved in a generic
experimentation is provided, from definition of the experiment to results
coming from its execution (Figure 18 illustrates the execution flow).

First process involved is “Experiment definition” (experiment scope): Testbed
Manager and Experiment collaborate in order to define the new experiment
pinpointing technical and non-­technical aspects.

Results obtained from Experiment definition represent the input for
“Experiment running” process (experiment scope); also in this process, Testbed
Manager and Experiment collaborate in order to setup the new experiment.
Moreover, “Experiment running” process includes two other processes: “Resource
discovery” and “Resource provisioning” (resource scope), in which only Testbed
Manager is involved.

When the new experiment is ready to run, “Experiment running” process
(experiment scope) starts; similarly to “Experiment running” process, also
this process includes other process: “End users involvement”, “Experiment
control” and “Experiment monitoring” that belong to experiment scope, and
“Resource monitoring” that belong to resource scope. “End users involvement”,
“Experiment control”, “Experiment monitoring” and “Resource monitoring” start
together when “Experiment running” process starts and they run simultaneously.
Similarly, they stop when “Experiment running” process finishes its execution.

At the end of the execution of “Experiment running” process, “Evaluation of
results” process (experiment scope) starts; in this process Experimenter
analyses information collected through execution of the experiments. Once
Experimenter obtains the expected results “Evaluation of results” ends and the
last process starts: “Resource release” (resource scope). In this last
process, Testbed Manager releases all resources involved in the experiment and
makes them available for other experiments.

**Figure 18 -­‐ Execution sequence of processes involved in a generic
experimentation**

###  2.2. Existent Projects and initiatives in the context of EaaS

Based on this definition of what the experimenters may expect from an EaaS
offer we can look at related initiatives that follow either the EaaS model or
present similar characteristics that can answer to some of the expectations
presented above.

####  2.2.1. FIRE community

The FIRE community of project is a natural and first source for comparison of
the FESTIVAL approach with other related approaches. FIRE current ecosystem
regroups 12 facility projects.

**Figure 19 -­‐ FIRE Ecosystem**

The FIRE Facility projects are building a variety of network experimentation
infrastructures and tools with different characteristics. The CREW [1],
Fed4FIRE [2]and OneLab [3]project provide free and or paid access to testbeds.
Most projects also provide access to their facilities through open competitive
calls that are limited in time and scope. The FIRE Testbed Search
[4]references the facility/testbeds involved in the projects and can be used
to get information on access to individual testbeds.

The different individual facilities involved in the FIRE initiative, as well
as the initiative as a whole demonstrate some of the characteristics we
defined above for the EaaS model. One of the main current limitations of the
FIRE community in regards to the EaaS model and expectations is the limited
number of case of “on demand” availability. Many testbed facilities have still
limitation to the access of the experimentation facilities to consortium
members and participants in the open calls. It can also be expected that this
will increase in the coming years as other H2020 projects will go closer and
closer to the EaaS model, and FESTIVAL will have to keep in touch with the
community to see how others implement the EaaS model.

In regard to post project activities, although some independent facilities are
sustained on their own, the federation of testbed and numerous of the past
project infrastructures are mostly sustained by new projects integrating past
infrastructures.

####  2.2.2. Technology platforms and labs

Various technology platforms and lab initiatives that offer experimentation
possibilities for external users present characteristics of the EaaS model and
answers to the expectations presented above. In most case they link the
provisioning of experimentation service with other services and we can
characterize them as follows (note that the proposed characterization
represent general trends rather than strict boundaries and some
experimentation facilities or actors can be linked with one or more of these
trends):

  * **Experimentation services linked with research and education services:** Their scope and size can vary from EU wide initiative (such as the EU Research Infrastructures supported by DG Research [5]) to national initiative (an outstanding example being the Fraunhofer institutes) and to local initiatives (such as the Plateformes Technologiques in France [6]). Their main mission is usually to provide research services, which can include experimentation services and access to experimentation facilities for third parties. In most cases, they cannot be directly characterized as EaaS, but provide services that answers to some of the needs of potential EaaS users. 

  

  * **Experimentation services linked with end user access:** This is characteristic of the Living labs movement **.** Here the focus will be on the engagement of end users in the experimentation through demonstration, usage and/or co-­‐creation activities. Their scope is usually local limiting the possibility for remote, on demand access to experimentation capability that would be necessary to characterize fully an EaaS model. 

  

  * **Experimentation services linked with prototyping activities:** The FabLab movement is a notable example of such initiative. The focus of such initiative is to provide experimentation and prototyping facilities to enable rapid prototyping activities. Their local scope, lack of scalability ability and (for most) lack of research grade quality don’t qualify them as EaaS but these initiative can also be interesting inspiration sources for defining the EaaS offering to broaden its reach. 

  

  * **Experimentation services linked with innovation support:** Several innovation support initiative can provide access to experimentation platforms, this is the case of the EIT KIC labs at European Level, or of several economic cluster associations. This provisioning of service is accompanied by support to Innovation and business modeling activities. 

  

The structures providing these services can be public, private or public
private partnerships. They rely on different sources of funding to sustain
their activities:

In the case of public or partially public funded initiative, the funding of
the experimentation service provisioning is conditioned to benefits for the
society. This can comprise various motivations: education opportunities
(exchanges between the external experimenters and local universities /
students), support to economic development, innovation and competitiveness (by
providing experimentation and prototyping abilities to local actors), or the
support of research excellence. The ability for the experimentation facility
to demonstrate some of these public benefits conditions the public funding and
the set of evaluation and KPI linked to these objectives can be important to
gain public support.

In the case of private or partially private funded initiative, two models of
funding can be found (and can be used together), either the **co-­‐sponsorship
model** (where industrials and established actors will participate to the
funding of the experimentation facility) or the **service-­‐provisioning
model** (where experimenters will directly pay per use of the experimentation
services). Motivations for industrial co-­‐sponsoring of experimentation
facilities can range from sharing the cost of the infrastructures with other
actors, to the control of their value chain and subcontractors, or the support
of their business ecosystem. It is to be noted that due to the cost of set up
and maintenance of research level experimentation platforms, the
service-­provisioning model is in most cases not used as the funding for
experimentation facilities.

####  2.2.3. Initial conclusions for FESTIVAL exploitation approach

This initial analysis of the EaaS requirement and existing initiative enables
us to provide some initial conclusions on the direction that the FESTIVAL
project exploitation may take.

A first step for the FESTIVAL project is that it will enable the use of the
Experimentation as a Service model (or at least the fulfilment of most of the
requirements related to the EaaS approach) for the individual experimentation
facilities integrated in the project. This will be possible both on a
technical level (through the homogeneous access API of the project and
additional tools and services) and on a business model level (through
increased knowledge of the possible business models and by the set-­‐up of an
initial community of user through task 3.4). Each individual experimentation
facility of the project has its own exploitation plan (defined in section1.3.
) and will therefore be able to be financially sustainable individually.

The second step and challenge for the FESTIVAL project will be the
continuation of the federated approach beyond the project. The work of work
package 4 and 5 will help to assess the benefit of the federation of testbed
as well as the potential costs of maintaining federation beyond the project.
Based on this evaluation different options will be considered such as:

  * **Break-­‐up of the federation** : if the positive impacts of the federation are deemed insufficient to compensate the costs, it is a possibility that each testbed continues on its own. This is, on the base of the currently available information, considered as an unlikely option. 

  

  * **Integration in a larger initiative** : if similar federation initiative emerges over the course of the project providing “Experimentation as a Service” solutions, the merge with other initiative to gain visibility and traction will be considered. This is, on the base of the currently available information, considered as a possible option. 

  

  * **Set-­‐up of a non-­‐profit association to maintain the federation** : Once it is established and functioning, and as long as each individual platform is able to maintain itself on its own (based on their individual exploitation strategy), the cost of maintaining the federation should be limited. In that case, the set-­‐up of a non-­‐profit association between the consortium partners could be a good way to sustain the federation. The funding of the association could be based on membership fees and/or on commissions on the experimentation services sold to external experimenters by the individual testbeds that have adopted a service provisioning business model. This is, on the base of the currently available information, considered to be a likely option. 

  

  * **Set-­‐up of a commercial venture:** If the benefits of the federation provide a strongly valuable advantage and if the experimentation services provided can reach to an audience with the ability to generate significant revenues, the set-­‐up of commercial ventures between the partners will be considered. The revenues would come from pay per use by experimenters using the federation and be spread among the experimentation infrastructures based on their usage by experimenters. This is, on the base of the currently available information, considered to be a possible option. 

  

##  3\. Open Data opportunities and management in FESTIVAL

The Open Data are one of the most important topics in the FESTIVAL project.
Specific activities are dedicated to the analysis and provision of the data,
produced during the project, in an open way. In particular we have to
distinguish between two different categories of Open Data that will be managed
during the project: the first category includes the research data that will
produced by the experimentations performed in the FESTIVAL use case using the
federated testbeds: this type of data will be managed following the guidelines
of the European Commission regarding the Open Research Data in H2020 [7]. The
second category involves other existent Open datasets that will be identified
and collected in the different pilot sites involved in the FESTIVAL federated
ecosystem in order to enrich the knowledge base of the project and to improve
the reuse. The Open Data collected during the project can represent not only a
way to share the project results with the research community, but also a
concrete business opportunity for the whole FESTIVAL stakeholders: in order to
better identify the business potential offered by the Open Data provisioning
and reuse in an international context, the following section presents some
research and reports about the diffusion and the impact of open data in the
world and the business market related to it. We will use this information as a
starting point for the exploitation of the Open Data in the FESTIVAL business
model.

The end of the chapter includes a first version of the Management Data plan in
terms of processes and outputs to be produced during the FESTIVAL project to
collect and manage Open Data in compliance with the H2020 guidelines.

###  3.1. Open Data in a federated scenario

This section presents a report about the diffusion and the maturity of open
data approach in different countries in the world with a specific focus on the
countries directly involved in the FESTIVAL project experimentations. This
analysis is based on the data contained in the Open Data Barometer Global
Report 2015 document [8], produced by the World Wide Web Foundation, that
describes the state of the policies for the promotion of the dataset of public
data and open government in the world.

The study recognizes the progress made with regard to the provision of public
information, such as the subscription by the G8 leaders of the Open Data
Charter in 2013, which promotes the release of public sector data, free of
charge, in open and reusable formats. This purpose has been reiterated during
the last G20, in which the major industrial economies have committed to
promote open data as a tool against corruption, and the United Nations have
recognized the need for a "data revolution" to achieve the global development
goals.

The Open Data Barometer provides a snapshot of the state of open data around
the world. This type of analysis is very interesting in the context of the
FESTIVAL project showing the importance of Open Data and their diffusion and
how impacts from open data can best be secured in the different Countries of
the world. The Open Data Barometer analyzed, with a specific methodology
[9]based on surveys and several certified sources, several factors related to
the open data, but in particular have been taken in consideration, readiness
to secure benefits from open data, implementation of open data practice,
impacts of open data: calculating and aggregating the score for each these
three key factor the Open Data Barometer created a raking of the different
country of the world. In the following, only few results of this analysis has
been reported, the ones that have been considered interesting for the FESTIVAL
context.

**Figure 20 -­‐ Country clusters based on Open Data Barometer Readiness and
Impact questions**

Based on an analysis of readiness and impact variables, the countries analyzed
in the study are classified into four groups:

**High capacity** – These countries are the advanced ones in terms of open
data policies and adoption: they have a deep culture of open data adopting an
open data approach at different government levels. These countries also
promotes the adoption of open licensing in order to maximize the impact of
open data in the society and the private sector that are ready to take benefit
from open data. Countries included in this cluster are UK, US, Sweden,
**France** , New Zealand, Netherlands, Canada, Norway, Denmark, Australia,
Germany, Finland, Estonia, Korea, Austria, **Japan** , Israel, Switzerland,
Belgium, Iceland and Singapore.

**Emerging & advancing ** -­‐ These countries have emerging or established
open data programs, often as dedicated initiatives, and sometimes built into
existing policy agendas. In particular, most of these countries are working on
developing open data adoption enlarging the available datasets in different
contexts. This category contains countries with a different level of open data
maturity. Many of these countries are currently working to promote the open
data practice in the different government and institutions. Countries that are
part of this group are **Spain** , Chile, Czech Republic, Brazil, **Italy** ,
Mexico, Uruguay, Russia, Portugal, Greece, Ireland, Hungary, Peru, Poland,
Argentina, Ecuador, India, Colombia, Costa Rica, South Africa, Tunisia, China,
the Philippines and Morocco.

**Capacity constrained** –The countries included in this category have small
or very limited open data initiatives. This is mainly due to limitation
regarding the government processes, the internet access and in general the
availability of technology and related knowledge. Countries included this

cluster are Indonesia, Turkey, Ghana, Rwanda, Jamaica, Kenya, Mauritius,
Ukraine, Thailand, Vietnam, Mozambique, Jordan, Nepal, Egypt, Uganda,
Pakistan, Benin, Bangladesh, Malawi, Nigeria, Tanzania, Venezuela, Burkina
Faso, Senegal, Zimbabwe, Namibia, Botswana, Ethiopia, Sierra Leone, Zambia,
Yemen, Cameroon, Mali, Haiti and Myanmar.

**One-­‐sided initiatives** – the countries included in this cluster are
considered with a limited freedoms: they have basic open data initiatives
(e.g. open data web portals) but with a very limited social impact. The
countries in this cluster are Malaysia, Kazakhstan, United Arab Emirates,
Saudi Arabia, Bahrain and Qatar

Another import analysis performed by the barometer is related to the available
datasets. 15 categories of datasets have been taken in consideration and for
each category is assessed the availability and openness based on a 10-­‐point
checklist and a weighted aggregation (further information about the
calculation technique can be found in [9]). The result is expressed in a score
of 0-­‐100. The dataset categories are described in the following tables, as
defined by the open data barometer.  
  
<table>  
<tr>  
<th>

</th>  
<th>

**Dataset**

</th>  
<th>

</th>  
<th>

</th>  
<th>

**Description**

</th>  
<th>

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

</th>  
<th>

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

**Mapping data**

</td>  
<td>

_“A detailed digital map of the country provided by a national mapping agency
and kept updated with key features such as official administrative borders,
roads and other important infrastructure. Please look for maps of at least a
scale of 1:250,000 or better (1cm = 2.5km).”_

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

**Land ownership**

**data**

</td>  
<td>

_“A dataset that provides national level information on land ownership. This
will usually be held by a land registration agency, and usually relies on the
existence of a national land registration database.”_

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

**National statistics**

</td>  
<td>

_“Key national statistics such as demographic and economic indicators (GDP,
unemployment, population, etc), often provided by a National Statistics
Agency. Aggregate data (e.g. GDP for whole country at a quarterly level, or
population at an annual level) is considered acceptable for this category.”_

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

**Detailed budget**

**data**

</td>  
<td>

_“National government budget at a high level (e.g. spending by sector,
department etc). Budgets are government plans for expenditure, (not details of
actual expenditure in the past which is covered in the spend category).”_

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

**Government**

**spend data**

</td>  
<td>

_“Records of actual (past) national government spending at a detailed
transactional level; at the level of month to month government expenditure on
specific items (usually this means individual records of spending amounts
under $1m or even under $100k). Note: A database of contracts awarded or
similar is not sufficient for this category, which refers to detailed ongoing
data on actual expenditure.”_

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

**Company**

**registration data**

</th>  
<th>

_“A list of registered (limited liability) companies in the country including
name, unique identifier and additional information such as address, registered
activities. The data in this category does not need to include detailed
financial data such as balance sheet etc.”_

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

**Legislation data**

</td>  
<td>

_“The constitution and laws of a country.”_

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

**Public transport timetable data**

</td>  
<td>

_“Details of when and where public transport services such as buses and rail
services are expected to run. Please provide details for both bus and rail
services if applicable. If no national data is available, please check and
provide details related to the capital city.”_

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

**International trade data**

</td>  
<td>

_“Details of the import and export of specific commodities and/or balance of
trade data against other countries.”_

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

**Health sector performance data**

</td>  
<td>

_“Statistics generated from administrative data that could be used to indicate
performance of specific services, or the healthcare system as a whole. The
performance of health services in a country has a significant impact on the
welfare of citizens. Look for ongoing statistics generated from administrative
data that could be used to indicate performance of specific services, or the
healthcare system as a whole. Health performance data might include: Levels of
vaccination; Levels of access to health care; Health care outcomes for
particular groups; Patient satisfaction with health services.”_

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

**Primary and**

**secondary education performance data**

</td>  
<td>

_“The performance of education services in a country has a significant impact
on the welfare of citizens. Look for ongoing statistics generated from
administrative data that could be used to indicate performance of specific
services, or the education system as a whole. Performance data might include:
Test scores for pupils in national examinations; School attendance rates;
Teacher attendance rates. Simple lists of schools do not qualify as education
performance data.”_

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

**Crime statistics**

**data**

</td>  
<td>

_“Annual returns on levels of crime and/or detailed crime reports. Crime
statistics can be provided at a variety of levels of granularity, from annual
returns on levels of crime, to detailed real-­‐time crime-­‐by-­‐crime reports
published online and geolocated, allowing the creation of crime maps.”_

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

**National environmental**

**statistics data**

</td>  
<td>

_“Data on one or more of: carbon emissions, emission of pollutants (e.g.
carbon monoxides, nitrogen oxides, particulate matter etc.), and
deforestation. Please provide links to sources for each if available.”_

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

**National election results data**

</td>  
<td>

_“Results by constituency / district for the most all national electoral
contests over the last ten years.”_

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

**Public contracting data**

</td>  
<td>

_“Details of the contracts issued by the national government.”_

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

**Table 4 -­‐ Open data barometer dataset categories**

For each category of data in each country the availability and openness have
been estimated based on a 10-­point checklist, and after a weighted
aggregation, for each dataset is assigned a score of 0– 100.The chart below
shows the average scores for each category across all countries surveyed.

**Figure 21 -­‐ Availability and openness of dataset categories**

This analysis shows a positive trend with a general slow increment of the
openness between 2013 and 2014 in the most of datasets. It is important to
underline the difference between the availability of different categories of
datasets: for example, there is a large availability of census datasets but a
limited provision of other information for instance about company registration
or territory. In general the research identified a high presence of data
coming from national statistical agency despite should be necessary a direct
flow of data from government to the citizens in order to provide updated and
useful data for real services. Other important considerations can be
elaborated analyzing the datasets about budgets and spending: the governments
usually make available plans related to spending plans, but few dataset about
the real expenses performed. This gap should be filled in order to improve
transparency and accountability at the different government levels.

One of the most open issues related to the open data is the real impact that
the availability of these information have on the society. The barometer
research tried to quantify this impact analyzing the possible use cases and
success stories reported by media and academic literature (year 2013).The
results shows that there is an increment in the perceived use of open data by
entrepreneurs to create new services, but on other topics, for instance
environmental sustainability or economic, it is possible to identify a little
impact. It is important to underline that this global result that does not
show the difference between different countries in the world. Another analysis
shows how the impact is strictly related with the open data readiness and that
is unevenly distributed across the different countries in the world.

**Figure 22 -­‐ Open Data impact**

In the next figures are shown the results about the single countries that are
involved in FESTIVAL pilots, Japan, France Spain and Italy. This is very
interesting in order to analyze the real open data maturity in these
countries. For each country is presented a radar chart that aggregates the
three main values of the

Open Data Barometer as global values:

  * **Readiness** : measure if there are the necessary political, economic and social condition in the country to implement an open data strategy that can produce real benefits 

  

  * **Implementation** : measure the level of provision of different key categories of open data. These categories are also aggregated in three cluster: o _Innovation_ (Map Data, Public Transport Timetables, Crime Statistics, International Trade 

  

Data, Public contracts) o _Social Policy_ (Health Sector Performance, Primary
or Secondary Education, Performance

Data, National Environment Statistics, Detailed Census Data) o
_Accountability_ (Land Ownership Data, Legislation, National Election Results,
Detailed Government Budget, Detailed Government Spend, Company Register)

  * **Emerging impacts** : the level of perceived impact 

  

The purple line represents the 2014 data, the blue one the information coming
from 2013 report:

**Figure 23 -­‐ Open data report -­‐ Japan**

**Figure 24 -­‐ Open data report -­‐ Spain**

**Figure 25 -­‐ Open data report -­‐ France**

**Figure 26 -­‐ Open data report -­‐ Italy**

The complete report of the Open Data Barometer shows the current situation of
the adoption and the impact of the open data model in different countries in
the world. From this analysis is clear that there is a big gap among the
different countries in terms of open data availability and in general open
data approach: this is often related with the technological maturity of the
country but also with the economic and political situation and maturity. It
was interesting to analyze the specific ranking of the key values (Readiness,
implementation and impact) and the dataset type availability for Japan, Spain
and France and Italy the countries directly involved in the project
experimentation: the report showed that these four countries have good
performance for some indicators, in particular readiness, but at the same time
they can improve the level of political, economic and social impact. FESTIVAL
will be, for these countries, a way to improve this key value through a
federated approach of the open data model.

###  3.2. Analysis of Open Data business opportunities

The term “reuse” in the context of “public information” represents the
capability to reprocess (i.e. modify, combine and transform) the data
originally collected (in example from government) for different purposes, in
order to make them more useful and interesting. The reuse implies the design
of solutions based on the use of open data by individual developers,
companies, civil societies or other governments, in order to exploit the value
of public information, even commercially. The following sections report some
studies related to the open data business opportunities and potentials in an
international context.

####  3.2.1. Public Sector Open Data Market

Governments collect and produce large amounts of data, carrying out their
activities. They can use this data for various reasons:

  * financial and economic benefits for themselves or third parties; 

  

  * economic growth; 

  

  * management of internal policies; 

  

  * transparency and accountability; 

  

  * direct involvement of citizens in public services; 

  

To achieve the above objectives, many governments have implemented initiatives
to make their data open, available, usable and machine-­‐readable, so
enterprises and citizens can access and use this data for their own purposes.

Collection and generation of data represents an important benefit for
governments that can use this data for their purposes, but at the same time,
collected data represent a “treasure trove”, because the opening of the data
generates a new type of services market, with new opportunities for economic
growth and jobs.

It is important to note that the European Commission published guidelines
about the use of public information to support the application by the member
countries of the PSI (Public Sector Information) Directive. In particular,
guidelines focus on:

  * the license use of open standard; 

  

  * the publication priority of dataset; 

  

  * how to make the published datasets more easily reusable; 

  

  * the application of the rule of marginal cost to define the reuse cost of information. 

  

In order to achieve this results, European Commission itself launched and
initiative named ePSI platform [10] for promoting PSI and Open Data market. In
particular, ePSI platform provides a portal for publishing news about PSI and
Open Data developments, notify events and workshops, disseminating good
practices and examples, etcetera.

EPSI Platform provides a PSI scoreboard to evaluate the status of Open Data
and the overall PSI reuse throughout the EU.

The scoreboard is compiled based on internet search and of expert advices.
Moreover, ePSI Platform is open to feedback and suggestion for improving
accuracy of scoreboard; ePsi Platform provides scoreboard data that are
published on online under CC0 (Creative Commons 0) license.

**Figure 27 -­‐ the Europe open data reuse state**

Scoreboard takes into account seven aspects of PSI reuse; each of these
aspects includes one or more indicators and on each of them a country can
reach up to 100 points, for a maximum score of 700 points.

  * Implementation of the PSI Directive; this aspects includes two indicators: 

    * Implementation and absence of infringement procedures (50 points): it is about the correct implementation of the PSI Directive into national law and about the absence of infringement procedures. 

  

    * Exemptions granted (50 points): it is about the inclusion of one or more of the following in the implementation of the PSI Directive: national meteorological institute, Cadastre, Chamber of Commerce and national repository for legal information. 

  

  

  * National re-­‐use policy; this aspects includes five indicators: 

    * General right of reuse (20 points): it is about possible obligations of national law for public sector bodies to allow reuse of PSI. 

  

    * Distinction between commercial and non-­‐commercial re-­‐use (20 points): it is about the absence of distinctions between commercial and non-­‐commercial into national law. 

  

    * Redress mechanisms (20 points): it is about implementation of redress procedures for appeals against public sector bodies that deny requests for reuse. 

  

    * Pro-­‐active publishing of PSI for re-­‐use (20 points): it is about obligation for public sector bodies to be pro-­‐active in publication of PSI. 

  

    * Availability of standard licences (20 points): it is about the availability of a standard licence under which public sector bodies are encouraged to publish PSI. 

  

  

  * Formats; this aspects includes four indicators: 

    * Endorsement of “raw” data and open standards (20 points): it is about the existence of a body promoting or endorsing the publication of PSI for reuse under the form of “raw” data and in open standards. 

  

    * Obligatory ‘raw’ data and open standards (30 points): it is about the existence of an obligation for public sector bodies to publish PSI for reuse under the form of “raw” data in open standards. 

  

    * Endorsement of “Linked Open Data” (20 points): it is about the existence of actions devoted to the promotion and endorsement of “Linked Open Data”. 

  

    * Existence of national or regional data catalogue(s) (30 points): it is about the existence of a national or regional data catalogue or portal providing data sets available for reuse. 

  

  

  * Pricing; this aspects includes three indicators: 

    * Cost-­‐recovery model (cancelled out if 4.2. applies) (30 points): it is about the existence of a PSI-­‐pricing mechanism based on a cost-­‐recovery model. 

  

    * Marginal costing model (cancelled out if 4.1. applies) (50 points): it is about the existence of ePSI-­‐pricing mechanism based on a marginal costing model. 

  

    * No exceptions to marginal costing model (50 points): it is about existence of possible exceptions to the application marginal costing model for PSI re-­‐use. 

  

  

  * Exclusive arrangements; this aspects includes three indicators: 

    * Prohibition of exclusive arrangements (50 points): it is about the prohibition for PSI holders to granting exclusive rights to resell or reuse data to any legal entity. 

  

    * Legal action against exclusive arrangements (30 points): it is about the existence of legal action from the Member State or a private party against public sector bodies granting exclusive agreements to third parties. 

  

    * Ending exclusive arrangements (20 points): it is about the successfully ending of at least two exclusive agreements arrangements by the Member State. 

  

  

  * Local and regional PSI availability and open data communities; this aspects includes three indicators: 

    * Some local or regional PSI available and community activity (40 points): it is about the existence of at least two local or regional bodies publishing at least 10 PSI data sets for reuse and at the same time having active open data communities. 

  

    * Moderate local or regional PSI available and community activity (40 points): it is about the existence of at least six local or regional bodies publishing at least 10 PSI data sets for reuse and at the same time having active open data communities. 

  

    * Considerable local or regional PSI available and community activity (20 points): it is about the existence of at least twelve local or regional bodies publishing at least 10 PSI data sets for reuse and at the same time having active open data communities. 

  

  

  * Events and activities; this aspects includes three indicators: 

    * Some national or inter-­‐regional events (50 points): it is about the organizations of at least four annual national or inter-­‐regional events for promoting Open Data and PSI reuse. 

  

    * A moderate number of national or inter-­‐regional events (25 points): it is about the organizations of at least eight annual national or inter-­‐regional events for promoting Open Data and PSI reuse. o A considerable number of national or inter-­‐regional events (25 points): it is about the organizations of at least twelve annual national or inter-­‐regional events for promoting Open Data and PSI reuse. 

  

  

Full description of indicators is available in [10].

**Figure 28 -­‐ PSI aggregated scoreboard**

**Figure 29 -­‐ PSI Overall Score**

Figure 28 and Figure 29 report the ranking of ePSI for the different
categories presented above and in aggregated format. At the time of writing
this report, first three positions were held by United Kingdom (585 point),
Spain (550 points) and France (535 points).

Other studies have been undertaken in Europe to measure different aspects of
PSI and their reuse, such as POPSIS (Pricing Of Public Sector Information
Study) [11]and Vickery [12]. POPSIS (undertaken by Deloitte Consulting
Belgium)measured the effects of PSI charging models on the market and their
effects. It has analyzed some case studies of public sector bodies and
different PSI sectors across Europe, such as meteorological data, geographical
data, business registries and others.

Vickery (provided by Graham Vickery of Information Economics) indicated that
the size of PSI reuse market was of the order of 28 billion € in 2008 with an
annual growth rate of around 7%, increasing to 40 billion Euro a year.

Moreover, an independent review of Public Sector Information [13] estimates
the direct economic benefits of public sector information at around £1.8bn a
year, with an overall impact including direct and indirect benefits of around
£6.8bn.

####  3.2.2. Open Data Market

The consulting firm McKinsey published at the end of 2013 a report addressing
the issue of the value of open data and their ability to generate easily
distributable digital information. The report analyzes how open data creates
economic value in terms of revenue, reducing costs and saving time. The survey
focuses on the provision of open data by both governments and private
institutions, providing the basis for using applications that require large
volumes of data or producing innovative applications.

In particular, McKinsey evaluates the potential of open data in seven business
sectors: education, transportation, consumer products, energy, oil and gas,
health and consumer finance [14].

**Figure 30 -­‐ Open business potential**

McKinsey claims that the opening of the data could produce an additional value
globally in the seven sectors: more than $3 trillion a year and as much as $5
trillion a year.

Moreover, McKinsey demonstrates that the open data allow:

  * to give rise to hundreds of entrepreneurial businesses; 

  

  * to help established companies further in the marketplaces; 

  

  * to define new products and services; 

  

  * to improve the efficiency and effectiveness of operations. 

  

In addition to McKinsey’s study, other two studies underline the importance of
Open Data Market: a study by Oxera estimates the Gross Value Added (GVA) by
the Geospatial Services Sector as $150-­‐$270 billion per year, 0.2% of global
GVA and approximately half the GVA of the global airline industry; Oxera
points to additional indirect benefits including $17 billion in time savings,
$5 billion in fuel savings and $13 billion in education [15]. In addition, a
report by Lateral Economics (commissioned by Omidyar Network) shows an
international economic growth of $13 trillion and presents an overview of
findings starting from a survey of the international and local Australian
policy context for open government; in particular it explores the economic
value of open data providing case studies on its impacts [16].

In order to prove potentiality of open data market, four success stories are
shown below. Zillow, Zoopla, Waze and The Climate Corporation created a
business activity based on open data. The usage of open data allowed them to
grow economically and to expand their market of products and services
provision. In particular, two of them provide services in the field of real
estate (Zillow, Zoopla), while another one (The Climate Corporation) provides
services in the field of agriculture combining data about weather, agronomic
modelling, and weather simulation; the last one (Waze) provides not only a
service (a GPS-­‐based geographical navigation application), but sets up a
community of drivers that collaborates providing information about routes,
traffic, etcetera.

  * **Zillow** : it provides an on-­‐line marketplace for home and real estate to help homeowners people involved in this field (e.g. buyers, renters, sellers, agents, etcetera) to manage their businesses; in particular Zillow provides a large database of homes both for sale ad for rent. Moreover it provides information about homes not on the market. Finally, Zillow has with a market capitalisation of over $3 billion. 

  

  * **Zoopla** : similarly to Zillow, it provides services in the real estate field based on data from the UK Land Registry. Zoopla was launched in 2008 and at present it has annual sales of £76m (most of them came from estate agents) and profit of £25m. 

  

  * **The Climate Corporation** : it provides services in the field of agriculture on the basis of hyper-­local weather monitoring, agronomic modelling, high-­‐resolution weather simulations and data that comes from third party providers, such as the US National Weather Service. The Climate Corporation was founded in 2006 and in October 2013 it was acquired by Monsanto (multinational agrochemical and agricultural biotechnology corporation) for $930 million. 

  

  * **Waze** : it provides geographical navigation application for smartphones, with turn-­‐by-­‐turn information, and a social network for drivers. Through a game based approach, drivers can notify new roads, traffics, etcetera. In June 2013 Waze was acquired by Google for $1.3 billion. Also in 2013 it was awarded as the “Best Overall Mobile App” at Mobile World 

  

Congress.

All the success stories are based on a strong business model; possible
business models for open data are shown below. In particular, two studies are
taken into account: the first one by Deloitte [17], a network of professionals
collaborating to provide audit, consulting, financial advisory, etcetera, and
the second one [18] by “Osservatorio ICT -­‐ PIEMONTE” (Piedmont ICT
Observatory), a public authority of Regione Piemonte.

Deloitte highlighted five emerging business models based on open data
representing five different approaches, referring to the UK market. The five
"archetypes" business models are:

**Figure**

**31**

**-­‐**

**F**

**ive "archetypes" business models**

Suppliers

Aggregators

Developers

Enrichers

Enablers

  * **Suppliers** : although there is no still a direct financial return, private companies, organizations or public authorities are starting to make available their data in an open format, allowing others subjects to reuse it. In this case, suppliers do not gain direct economic returns; returns are represented by an increased level of engagement and loyalty of customers, citizens, etcetera. Moreover, as consequence engagement of customers, private companies should gain greater revenues. 

  

  * **Aggregators** : public or private companies could collect and process open data in order to extract new values end information. In this case, the key factor is the relevance of the new information produced from the data analysis; success depends on the usefulness of produced data and their marketability. Revenues should come from aggregation of data that come from different sources and/or correlation of different types of data (e.g. correlation of geographic data and data about evolution of temperature); in addition, ravenous should come from data access services such as APIs. 

  

  * **Developers** : developers could reuse open data to offer new services. In example, one of the fields of major development could be represented by applications for mobile devices (such as smart phones, tablets, etcetera) about public transports, health, etcetera. In order to facilitate reuse of published data, generating in turn useful applications, it is necessary that published data must be of good quality, up-­‐to-­‐date and easy to reuse. 

  

  * **Enrichers** : companies could offer consulting services through the aggregating open data and proprietary information held by large private companies, in order to offer new products and services. Moreover, companies could use open data in order to improve their existing services and products. In this particular case, revenues do not come from open data, but open data can help to save money, because better products and services can increase efficiency. 

  

  * **Enablers** : companies could provide platform and technologies for commercial or personal use. Enablers represent a key factor of the Open Data ecosystem, because they provide services and infrastructures for data suppliers and data consumers in order to facilitate access to open data and their reuse. In this case revenues come from access to data. Moreover, it is important to note that enablers act as catalyst, because they can offer cost effective solution for enterprises and organizations without founds for the development of a proprietary platform. 

  

On the other side, in [18] examples of generic business models that can be
adopted in the field of open data are carried out from a survey. In
particular, eight different models are identified.

_**Premium Product /** _

_**Service** _

**Freemium Product /**

**Service**

**Open Source**

**Infrastructural Razor**

** & Blades **

**Demand**

**-­‐**

**Oriented**

**Platform**

**Supply**

**-­‐**

**Oriented**

**Platform**

**Free, as Branded**

**Advertising**

**White**

**-­‐**

**Label**

**Development**

**Figure 32 -­‐ Examples of emerging business models**

  * Premium Product / Service: products and services based on open data (presumably characterized by high intrinsic value) are supplied to the end market; companies and organizations that provide products and services typically require a payment for accessing/consuming them. 

  

  * Freemium Product / Service: in this case, products and services based on open data are supplied to the end market for free with limited functionalities, while for the more advanced features a payment is required. 

  

  * Open Source: products and services are supplied for free; in this case, revenues come from added values services provided to specific customers, such as customization of products or services, implementation of particular functionalities, technical advices, etcetera. 

  

  * Infrastructural Razor & Blades: brokers facilitate access to PSI for developers; in this case the strategy is as follows: in a first stage the product/service is sold at a very low price in order to increase the subsequent request of complementary goods, on which it is possible to achieve significant gains. In the case of PSI, brokers could provide API (Application Programming Interface) to access data sets and then could charge the use of computational power required for processing incoming requests. 

  

  * Demand-­‐Oriented Platform: in this model, large sets of PSI are stored, classified (e.g. through metadata), harmonized in terms of formats and exposed through APIon intermediate and proprietary servers with high reliability, in order to facilitate their retrieval. 

  

  * Supply-­‐Oriented Platform: in this model a provider acts as a broker; provider supplies infrastructural services providing PSI for free to developers; on the other hand PSI holders apply a tariff to PAs, which consequently become holders of data management platforms. 

  

  * Free, as Branded Advertising: this model is based on the concept of “service advertising”, a form of communication that aims at encouraging an audience to a particular company or brand; in this model, advertiser draws the attention of customers by providing them with services based on PSI; generally, offered services do not produce revenues, but support other business lines in achieving expected economic results. 

  

  * White-­‐Label Development: in this case, third parties develop services and solution on behalf of advertisers; services and solutions are developed in a white-­‐label manner: in developed services and solutions, third parties hide their brand and gives visibility to the brand of advertiser. 

  

It is important to note that governments have an important role in the growth
of open data market. In promoting and enhancing its growth, governments can
play four roles: Supplier, Leader, Catalyst and User.

**Figure**

**33**

**-­‐**

**Roles involved in PSI management**

Supplier

Leader

Catalyst

User

  * **Supplier** : are subjects (e.g. Governments, Public Administrations and other companies) that release data in order to increase the economic growth and the business innovation, steadily improving quality and access possibility. 

  

  * **Leader** : are subjects that encourage the release of data that are important for economic growth and business innovation. This subjects could be Public Institutions at regional and city level, state owned enterprises and private companies providing important public services. 

  

  * **Catalyst** : are subjects that promote the use of open data in order to develop a prosperous ecosystem of users, coders, application developers and in general to boost new data-­‐driven businesses. It is important to note that the use Open Data is a catalyst for the business innovation in all sectors, and not solely or primarily in the ICT sector. 

  

  * **User** : are subject that take advantage of their published data and reuse them; in order to take advantage of their data, they need to develop specific “Open Data skills”, such as interpretation, extraction, publication in machine-­‐readable formats, ensure personal privacy, assist user (business or not) to use available data and support them to face and solve possible problems, such as technical or legal. 

  

###  3.3. Data management plan in FESTIVAL

The Data management plan described in the following sections defines the
process that will be followed to collect, manage process and share open data
produced during the project. The definition of a Data management plan is
required by the Guidelines on Open Access to Scientific Publication and
Research Data [19]and Guidelines on Data Management in H2020 [7] in particular
for the projects that participate in the Open Research Data Pilot as FESTIVAL.
FESTIVAL will provide the research data and the associated metadata generated
during the project as open data using specific research data repositories and
will enable all the interested stakeholder to access and reuse this data. This
section represents a first version of the Data Management Plan that will be
continuously updated in the following months. In particular, specific
activities related in general to open data and open research data will be
performed in task 2.3 “Federated Open Data” where will be identified a
federated open data provision methodology, data model and specific project
guidelines. The results of these activities will be reported in deliverable
D5.3 “First year update to communication, dissemination, exploitation and open
data management activities”. The following Data Management plan is an initial
description of the phases to be performed in the open data (research data and
generic open data) life cycle in the FESTIVAL project. We have identified 4
phases:

####  Data Identification

This is the initial phase to be performed in order to identify the right data
sources and the specific information to be provided as open data. In this
phase, the types of data to be shared in the context of FESTIVAL will be
identified. The data typology will be strictly related to the experimentation
that will be performed on the testbeds and to the existent data sources
available in the test sites. The analysis will be conducted taking in account
the needs of the federation scenario in which the data provided should be
linked among the different testbeds/pilots. In this initial phase, the privacy
issues will be analyzed. Considering that, many data produced by the
experimentation will be related to citizens’ information or behavior, national
and international legislations will be studied in order to identify the type
of information that can be shared and the level of dissemination (consortium
level, public, etc.) that can be applied. It is also particularly important to
identify structured archives, directories, databases available in the testbed
pilot/area: external open data available can be collected and linked to
existing data sources to create new datasets.

It is desirable to define the data of interest for FESTIVAL stakeholder
communities that will be involved in the testbeds. In the context of the
project, it is important to identify priorities for opening the data that are
related to the real interests of the community. In this sense, the definition
of priorities is an opportunity for discussions and debates with the citizen
and the local community, by consulting and involving them in the definition of
the open data. This activity is also related to the definition of ecosystem
and the specific stakeholders of FESTIVAL community that has been started in
this deliverable. The result of this activity will be included in Deliverable
2.3 and Deliverable 5.3

OUTPUT: Data sources, existent data set, privacy policies

####  Data Collection

This phase is related to the definition of the standards of the data formats
and data models and the collection of the data sets identified in the previous
step. Once the type of data to be provided is defined, it is necessary to
define the standards and the data model that are more suitable to share the
information and to be easily reused by all the interested stakeholders. In
this sense, during the task 2.3, a federated approach for the open data based
on the definition of a common data model among the different testbeds will be
proposed. During this activity, different factors that affect the quality of
the individual data and the impact of these factors on the datasetwill be
taken into account:

  * Syntactic accuracy, i.e. the degree of proximity of the data value to a value in the syntactic definition domain; 

  

  * Semantic accuracy, i.e. the degree of the proximity of the data value to a value in the semantic definition domain; 

  

  * Topicality, that is the adequacy of the data value with respect to the timing requirements of the context of use; 

  

  * Completeness; 

  

  * Internal consistency, indicating the degree of coherence of the data contained in a data set related to the same entity; 

  

  * External consistency, indicating the degree of coherence between different but related data 

  

elements present in a dataset.

Some of the above mentioned requirements can represent an obstacle to provide
the open data set, but in other cases (for example, the completeness) the
choice of opening the dataset can be functional to improve quality, possibly
through processes of community involvement reference.

After the analysis of the data set quality, it will be necessary to identify
the right standards and data formats suitable for the different contexts in
FESTIVAL. Considering that there is an absence of clear international
standards for representing key datasets, this situation could produce the
effect that no standard of measurement about the data of certain kinds of data
can be assessed; also in this case if users want to make relations among data
of different countries or want to reuse an application in a different open
data context, they have to re-­‐learn and re-­‐code their data. In order to
avoid this situation it will be necessary to analyze the different national
guidelines and standards for the open data provisioning finding a common
approach. It will be useful also to refer to existent initiatives such as The
Open Contracting Data Standard [20], launched in November 2014 that is one
experiment with providing both standards for technical interoperability and
for assessing good contracting data publication.

OUTPUT: Data models, standards, data formats, open research datasets

**Publication and federation**

This is the phase in which the different datasets will be concretely published
and shared in open formats. This activity will be performed during the whole
experimentation conducted on the federated testbeds. Part of this activity
will consist in the identification of repositories and tools to publish the
open data sets. In order to be compliant with [19] the open research data will
be published in specific research data repositories. Also all the open data
provided in FESTIVAL will be available through a Federated Open Data Catalogue
a web portal that will be a single point of access for all the open data
produced in the testbeds. This web portal will be developed during the task
2.3 and it will provide a set of services and API that will allow end users
and external systems to access to the data. One important objective in
FESTIVAL is to provide data with a high level of openness, availability and
reusability. In order to measure these characteristics the 5 stars deployment
model proposed by Tim Barners-­‐Lee [21] is followed. The model proposes
gradual opening data process composed by five steps from raw unstructured data
to Linked Data:

  1. The data are available in any format, but with an open license. In addition, they are incorporated in documents without structure and therefore readable and interpretable only by human (documents). In this case, any service cannot be enabled from data contained in the documents, without significant human intervention of extraction and possible data processing. 

  

  2. The data are available in a format automatically readable by an agent. Typically, data that are part of this level are data in proprietary formats (e.g. Excel), which are readable by a program, but human intervention is still necessary for particular data processing (raw data). In this case, enabled services are inefficient and it is ad-­‐hoc applications that use and incorporate the data within them. 

  

  3. The data have the same features of the previous level, but with a non-­‐proprietary format (e.g., usage of CSV instead of Excel) 

  

  4. The data have the same characteristics of the previous level, but they are exposed using W3C, RDF and SPARQL standards and they are described semantically using metadata and 

  

  

ontologies (semantically enriched data). In this case, enabled services and
app are very efficient;

  5. The data have the same characteristics of the previous level and are semantically described using metadata and ontologies, but they are connected to the data exposed by other people and organizations. In fact, the human intervention is minimized and sometimes it is even eliminated (semantically enriched and connected data). In this case, the services are very efficient and they are enabled with data mash-­‐up; 

  

  

One of the challenges in FESTIVAL is to provide the most of dataset in 4 or 5
stars in order to habilitate the data federation among the different testbeds.
The achievement of this objectives is related to the specific skills required
to create dataset based on Linked Open Data but also on the publication
process: for all the data collected in a data set, it is appropriate to
describe the datasets by accompanying it with useful information (metadata) to
understand its contents, that make explicit some features and make it easier
to identify. For instance, to facilitate the availability of datasets and
their interoperability is important to use descriptive elements such as Title,
Description, Link, License, Validity Period, Managing Authority, Format etc.
In this phase will be concretely implemented the open data federation: through
the Federated Open Data Catalogue and the interoperable data model the open
research data produced during the different experimentations will be
accessible through a single entry point and a common way to search for the
needed up to date information.

OUTPUT: Federated Open Data Catalogue, Federated Published datasets

**Archiving and preservation**

This phase includes all the activities to assure that all the open research
data collected during FESTIVAL project will be correctly managed for a
long-­‐term preservation. In this sense it will be identified, in the FESTIVAL
business model, how to sustain the costs for the data preservation beyond the
project duration. Also, during this process will be identified the technical
infrastructure for the data archiving and the human resources needed to
perform support and maintenance.

OUTPUT: Long-­‐term preservation technical and business model

The next figure shows an overview of the data management processes and their
relationship: it is important to notice that “Data identification and “Data
collection” are two iterative processes that can be executed several times
during project lifetime in order to identify new open data sources or refining
standard and data models.

**Figure 34 -­‐ Data management plan processes**

##  4\. Project exploitation and business model roadmap

This deliverable has started the definition of an exploitation approach and
the analysis of a business model to be applied in the context of
Experimentation as a Service in FESTIVAL project. This analysis will continue
in the following months to be refined with the results coming from the project
activities and with a clearer definition of the EaaS market. In this section
is presented a roadmap that shows the next activities to be performed in the
field of exploitation, business model and open data management. The next
picture summarizes the outcomes of this activities performed that will be
included in the Deliverable 5.3 “ _First year update to communication,
dissemination, exploitation and open data management activities”_ to be
releases in month 12 (September 2015) and Deliverable 5.4 “ _Experimentation
as a Service business model analysis_ ” (month 18, March 2016).

**Figure 35 -­‐ Project exploitation and business model roadmap**

A brief description of the results that will be included in D5.3 is given as
follows:

**FESTIVAL SWOT analysis:**

It will be important to identify the strong points that characterize the
FESTIVAL federated testbeds, the experimentations and in general the EaaS
model. A SWOT analysis will allow to identify, in a structured way, the
internal and external factors that are favourable and unfavourable to achieve
a specific objective. In this approach, will be taken in consideration:

  * Strengths: characteristics of the FESTIVAL project that give an advantage over others. 

  

  * Weaknesses: characteristics that place the FESTIVAL project at a disadvantage relative to others. 

  

  * Opportunities: elements that FESTIVAL could exploit to its advantage. 

  

  * Threats: elements in the environment that could cause trouble for the FESTIVAL 

  

The results of the SWOT analysis will be also an input in the definition of
the correct business model and will be updated with insights matured during
the project and a qualification of each of the items listed under the SWOT.
This qualification will serve as a further analysis and to better understand
the critical points.

###  **Products definition**

The definition of FESTIVAL products will be fundamental to plan an
exploitation strategy. In particular, the FESTIVAL product value proposition
will be defined, where the product offer intersects with customer’s desires.
In the context of FESTIVAL, the value proposition is how the FESTIVAL EaaS
approach meets the needs of its stakeholders. Defining the value proposition
represents one of the fundamental elements of business models and is the first
step to defining the FESTIVAL business model.

###  **Expected impact analysis**

Taking into consideration that the impact assessment will be performed at
different stages of the project, in particular after the execution of the
trials, in the initial phase of FESTIVAL, it will be important to identify the
possible impact of the project from technological, economic and social point
of view. In this activity, starting from the initial project impact definition
and the analysis of the FESTIVAL ecosystem, the different types of impact of
the project and the stakeholder involved in them will be identified and
classified.

**Data management plan** Starting from the processes planned in this
deliverable, the D5.3 will present a first version of the Data management plan
that includes the open research data produced in the project. This plan is
related with the activities performed in task 2.3 and follows the specific
guidelines and template proposed by [7].

The results of the activities related to the business model definition will be
included in the deliverable D5.4:

###  **Updated stakeholder analysis**

The analysis of the stakeholders has started in this deliverable. The list of
stakeholders and the information related to them will be refined during the
next months thanks to a more complete knowledge of the project ecosystem, and
also to the input from the stakeholders themselves (for instance collected
through surveys). A more detailed stakeholder analysis will allow to classify
them in specific target groups and in particular identify their role in the
project though:

  * Influence/Power – the ability of the stakeholder to affect the adoption of FESTIVAL products/approach. 

  

  * Position – why the stakeholder should support or opposes or is neutral about the FESTIVAL project and its enabled services. 

  

  * Interest -­‐ the stakeholder’s interest or concerns towards the adoption of the FESTIVAL products/approach. 

  

###  **Review of business model literature**

In order to define a business model for FESTIVAL it will be explored the
fundamental elements of business models, in particular to analyse the impact
of ICT technology and the Experimentation as a Service approach on these
modules. Starting from business reference models and templates it will be
analysed the basic building blocks and their relationship with the elements
present in FESTIVAL ecosystem such as, products, infrastructures (e.g.
testbeds), customers (e.g. experimenters) and financial aspects.

###  **Business model definition**

Using as input the different analysis previously presented, the D5.4 will
define a first version of the FESTIVAL business model. This model will be
updated during the whole duration of the project and the final version will be
included in D5.6 due for month 30.

##  Conclusions

The Deliverable 5.2 “Project initial exploitation and open data management
plan”, reported an initial analysis and considerations about the exploitation
opportunities, the Experimentation as a Service ecosystem and the Open Data
management in the FESTIVAL project.

The first part of the document, more focused on the exploitation topic,
presented several assets that will be used or exploited during and after the
project: the different project partners that contributed to this analysis,
identified several items that can be considered project outputs. From this
analysis is clear that the project will produce and exploit not only IT asset
(e.g. software platform, integration component) strictly related to the
technical testbed federation, but also methodologies, frameworks and
standards. The list of these exploitable items will be refined during the
project and updated in the next exploitation deliverables (i.e. Deliverable
5.3 “ _First year update to communication, dissemination, exploitation and
open data management activities”_ ).

The chapter 2 gave a first definition of the EaaS ecosystem describing the
entities, processes and the possible stakeholders involved in it. This
analysis, that can be considered an input for the business model to be defined
in the next phase of the project, showed the relationship between the
categories of stakeholder with different roles and the activities that can be
performed in the ecosystem, from the definition of the assets to the execution
of an experiment in the testbed. In the same chapter is also presented a
series of initiatives related to the Experimentation as A Service, including
projects but also commercial platforms or services, that is a relevant
starting point for the competitor analysis to be performed in the next months
.

Chapter 3 was focused on Open Data analysing the business opportunities
related to the adoption and reuse of Open Data approach in the different
countries of the world and in particular the ones involved in FESTIVAL project
(Japan, France, Spain, Italy): the sections of this chapter, that reported the
results of different international studies, underlined the business potential
of the open data market in the public sector but also in other business
domains (e.g. transportation, education, utilities). The results of the
presented study will contribute to the FESTIVAL business plan development.

Last part of the chapter 3 described the specific Open (Research) Data
management in FESTIVAL project showing the processes that will be followed in
the different phases of open data life cycle during the project and in
particular in the management of the data coming from the experimentations.
This analysis is the initial part of the Data Management Plan that will be
produced following the EU guidelines and that will be included in the
Deliverable 5.3. The last part of the document presented the roadmap for the
next activities related to the exploitation and business plan describing how
the analysis and information collected in D5.2 will be further updated and in
which deliverables the results will be included.