Ecommerce Europe association data at a glance 2014 European Reports Reports include country profiles, trends & Infographics
providing us with the required data and information. We would also like to thank all participating company members, business partners and stakeholders for their
By using innovative technologies and data sciences, Gfk turns big data into smart data, enabling its clients to improve their competitive edge
and enrich consumers†experiences and choices Globalcollect is the most knowledgeable global Payment Service Provider in the world, processing international e-commerce payments for
More than 160 companies in 40 countries use Richrelevance to turn data into actionable insight, which delivers the most relevant experience for consumers as they shop across web, store and mobile.
INFA) is the world†s number one independent provider of data integration software. Organizations around the world rely on Informatica to realize their information potential and drive top business imperatives.
and only embeddable virtual data machine (VDM), powers the unique â€oemap Once. Deploy Anywhere. †capabilities of the Informatica Platform
With regard to information technology, Informatica helps wherever possible by delivering the right data in the right way to the right users
come from a clear interpretation of the insights to be derived from the data that exist
Huge volumes of data need to be analyzed in order to identify issues and The year of SEPA
By applying analytics and visualization to payments data merchants can track and compare performance per country, per payment method
According to data received from national e-commerce associations, Ecommerce Europe estimates the number of B2c websites to have grown to 645,250 at the end of
2013 Key B2c E-commerce Data of Goods and Services at a Glance Top 10 e-commerce countries in
2013 Key B2c E-commerce Data of Goods and Services at a Glance Top 5 mature e-commerce
2013 Key B2c E-commerce Data of Goods and Services at a Glance The netherlands Belgium France
2013 Key B2c E-commerce Data of Goods and Services at a Glance 1 Germany â 63,400
2013 Key B2c E-commerce Data of Goods and Services at a Glance Italy Spain Greece
2013 Key B2c E-commerce Data of Goods and Services at a glance 1. Sweden â 8, 622
2013 Key B2c E-commerce Data of Goods and Services at a Glance Ukraine Romania 1 Russia â 15,500
explored through patent data. The rationale for this choice is given below and explored in more detail in section 2. 2. Market potentials and application prospects are based summarised
situation of international competitiveness in each KET, patent data seem to be the most European Competitiveness in KETS ZEW and TNO
comparability of patent data is limited due to different economic values a patent may represent, different degrees of technological novelty and different degrees of actual
applicability, patent data are nevertheless a widely used source to analyse dynamics in certain fields of technology and identify the regional distribution of new knowledge generation
Figures based on data from AT, BE, CY, CZ, EE, ES, FR, GR, HR, HU, LT, LU, NL, PL, PT, RO, SK, TR
which statistical data would be available) since the cross-sectional nature of KETS implies that firms from different industries develop and apply
industry data such as market shares, trade performance, productivity and growth in value added cannot be applied to analyse competitiveness in emerging KETS
competitiveness in each KET, patent data seem to be the most relevant source. Patent applications refer to technical inventions that have reached a certain state of feasibility and
patent data is limited due to different economic values a patent may represent, different degrees of technological novelty and different regulations of national patent offices, patent
data are nevertheless a useful source to analyse dynamics in certain fields of technology and
) Patent data have widely been used to analyse technological performance particularly for KETS, such as nanotechnology
technological performance such as scientific publications or R&d expenditures, patent data are more closely related to innovations and product markets
Patent Data as Technology Indicators Using patent data as empirical base for analysing technological competitiveness of KETS has
several advantages Patent data contain information on the technological area (s) a certain patent is related to
based on an internationally standardised classification system (International Patent Classification-IPC. Since IPC classes are highly disaggregated,
Patent data also contain text information of the technical content of a patent (patent abstracts) which would provide an
Patent data allow to determining the"market share"of the EU in the total production of new
Patent data also enable to differentiating by country of applicant and thus to pattern technological competitiveness in each KET by EU member
Patent data contain information on the applicants which can be linked to other data in order to identify the institutional background of an applicant (higher education institution, public
sector research institution, private firm, individuals) or the sector affiliation. Sector affiliation of applicants is important information to evaluate the role of each KET for
Patent data allow to some degree an analysis of technological links between certain fields of
However, patent data also have a number of limitations (see Griliches, 1990; Moed et al 2004) that limit their applicability as technology indicators and that complicate their analysis
As a result, any count of patent data whether weighted by a"relevance factor "or not, is problematic as it is likely to compare
Patent data applied at different patent authorities are difficult to compare because of different patent national laws, different practices at patent offices and different application
As a consequence want cannot simply add up patent data applied at different patent offices Applying for patent protection at a specific patent office is linked to the applicant's strategy
Patent data are available only with a considerable time lag after the underlying invention has been made.
We try to tackle some of these shortcomings of patent data in the following way
and the same invention in patent data. In the following, the term"patent"always refers to
Identifying KETS in Patent Data There are two approaches to assign patents to technology areas. One is to identify key words
combining key words and searching across patent data from various patent authorities Given the large number of technology fields to be covered
patent data since patents only applied at USPTO or JPO often miss address information on
secondary data: scientific and vocational cluster publications, and publically available information. We structure the analysis along the systemic
-CNT data memory -CNT inter -connected circuits -moleculare electronics -nanowires for producing electricity -spintronic logics
http://www. meti. go. jp/english/aboutmeti/data/aorganizatione/pdf/chart2009. pdf 32 http://www. kansai. meti. go. jp/english/politics/kyoto-municipal. pdf
nanotechnology R&d is extremely difficult since enterprise R&d surveys rarely collect data on R&d expenditure devoted to nanotechnology
growth of the semiconductor industry, the most recent data available, of 2. 2 percent to $260
The most recent R&d data of the OECD Technology Outlook 2008 does not go beyond 2006
Analysing technological competitiveness in industrial biotechnology based on patent data using patent classification systems is challenging. It is even more difficult to identify whether
data. Information and knowledge are becoming our most valuable commodities †unlimited access to which is becoming arguably the most significant driver of productivity and
It is optical transmission networks that are enabling all of this, giving data accessibility to anyone, anywhere (Photonics21, 2006
However, this data is based on a survey from 2002. Others in the meantime (2007) speak of 69 Since 2005 the photonics clusters in Berlin-Brandenburg, Tucson, Arizona,
Analysing technological competitiveness in advanced materials based on patent data and using patent classification systems to identify advance in material technology is challenging
which in the ECO data is listed 4th in the chemical clusters category with high level of
but solely focus on quantitative analyses based on patent data. This decision reflects the specific nature of this KET (see the following section for more detail) which implies different
based on patent data. AMT patents are identified through a combination of IPC classes (see section 2. 2). Measured in terms of patents applied at EPO or through the PCT procedure
For quantitative analysis, patent data were employed Qualitative analysis of success factors, barriers and market and system failures rest on
Technologies (AMT) by The swiss Government Using Micro-Level Survey Data: some Methodological Considerations, in: OECD (ed.),Policy Evaluation in Innovation and Technology
An Empirical Analysis Based on Firm-level Data for Swiss Manufacturing, Zurich mimeo Arvanitis, S.,H. Hollenstein, S. Lenz (1998), Are Swiss Government Programmes of Promotion of
-level Survey Data, Paper Presented at the International Conference on The Economic Evaluation of Technological Change, Georgetown University Conference center, Washington, D c.,June 15†16
Firm-Level Analysis Using Comparable Micro-Data from Four European countries, NBER Working Paper No. 14216
 data  from  existing  studies  enable  us  to  probe
 data  describes  size  growth  rates  specialisms  successful  cluster
 data  and  insights  † as  we  have  referred
bibliometric data 62. Generally speaking, such studies have detected most of the factors and mechanisms inï uencing the
the analysis of patent data, Res. Policy 21 (1)( 1992) 79†93 75 A. Arora, A. Fosfuri, A. Gambardella, Markets for Technology:
Digital technologies †including social media, the cloud, data analytics and mobile †are rapidly emerging as disruptive forces for
data onto a smart phone to send to a health care provider. â€oethis is an example of how technology contributes to generate new
and data, among others †are transforming companies at both an operational and a strategic level.
chief data officer? In many respects, this depends on CIOS themselves, argues Bob Sydow, Americas IT Advisory Leader
organization, the amount of automation and data-driven information that they use in their daily business is magnitudes
data-driven information that they use in their daily business is magnitudes bigger than just
customer service, and uncovering new data-driven insights â€oemy job is to find interesting new ideas and innovations,
data-oriented, †he says Of course, this raises specific challenges in the interface between marketing, which is seeking this insight
whether it†s data consumption acquisition or analytics, people expect answers immediately. To deal with this
data-oriented, †he says Of course, this raises specific challenges in the interface between marketing, which is seeking this insight
whether it†s data consumption acquisition or analytics, people expect answers immediately. To deal with this
and mining of data captured to gain greater customer insights and design more effective sales
tasked her with applying data analytics to generate new customer insights †and then to work with the business to apply those
instant †whether it†s data consumption acquisition or analytics, people expect answers immediately. To deal with this
data to transform their business model, or the medical device CIO who articulates the impact of information technology on their
business processes, the value of collecting data from their products, the business around monetizing that data,
and creating value-added services. They know how to explain these new business models, which may be more profitable than actually
Get control of your data Set out the relevant standards Understand strategic alignment with the rest of
so you need a foundational architecture †for mobile, cloud, data applications, and so on. If you don†t, you wind up connecting
application and infrastructure delivery, ahead of data. But a shift into the cloud reduces the emphasis on the application front, and
makes data far more important again Digital transformation requires to radically simplify the business and to change the mindset around product development.
and IT experts, to add additional context to our data and findings We focused on those sectors independently identified as
13,7%),Switzerland (11,5%),USA (10,1%)and Denmark (2, 2%).The data confirms a much tied connection between the work tax and the suburb economy, comparing that between the
3 CSO Census of Population, 2011 (Preliminary Results) †See data in Appendix 1 SOUTH EAST EMPLOYMENT ACTION PLAN †FORFà S
Ireland/Government of Ireland-Data Source: CSO Census of Population 2011 (Preliminary Results. Not to be reproduced without
CSO, Census of Population 2002 & 2006 and estimates based on preliminary data for 2011 The effect of the dispersed urban structure in the region is evident in the quite limited extent
Ireland/Government of Ireland-Data Source: CSO POWCAR data for 2006. Not to be reproduced without permission from AIRO
The age profile of the South East diverges only slightly from that of the State as a whole.
positive is that in 2006 (latest available data) the region had a higher proportion of its
Trend data over the period 2006 to 2009 shows that the number of small enterprises and employment overall in these firms has declined, and at a
s analysis of CSO Business Demography data. The South East region includes Carlow Kilkenny, Waterford, Wexford and Tipperary County †there is no breakdown of North/South
The GEM 2008 findings are reflected in EI data with respect to the emergence of high potential start-ups from the region.
FAS SLMRU/CSO QNHS Data Early school leaving: Recent Department of education data on education retention at
secondary level indicates that regional performance on educational attainment is likely to 8%6 %15
9 Refer to data tables in Appendix 3 22 percent). ) This would primarily relate to those working in manufacturing but also within
11 This is based on the 2006 Census data as 2011 data is not yet available by town.
sectoral data and trends through Forfã¡s ongoing sectoral research and policy development 20 Teagasc (2008) Towards 2030:
 Infrastructure-such as NGNS, data hosting, etc The broad sector displays strong growth prospects; driven by changing consumer
Data includes consumer spending on console (incl. handheld), PC games, online games and wireless/mobile games and video games
42 Refer to Appendix X for data tables 46 Table 5. 1 Education Providers in the South East participating in the 2010 Labour market
Data on the level of enrolments are not yet available Courses are available across a range of NFQ levels
43 See data in Appendix 3 SOUTH EAST EMPLOYMENT ACTION PLAN †FORFà S In addition, the disproportionate declines in particular occupational groups †Crafts/Plant and
research services, data analytics, patent research services etc. The increasing complexity of activities being outsourced often goes hand in hand with increased sensitivity of the related
data †which may impact on a company†s location decisions 50 The corporate shared services activities are evolving in much the same way requiring a strategic
changing business models of customers (driven by new technologies, the Cloud, data processing capacity, social media etc. and â€oemega-trends†such as ageing
Latest available regional data is for 2006 86 metric for a number of reasons, particularly because †transfer pricing†by multinational
by 2010.73 The table below shows the available data on the South East counties compared to
FAS SLMRU/CSO QNHS Data 92 Figure A 15 Employment Permits issued in the South East 2004-2010
Data entry/conversion or indexing services to various verticals including e g. FMCG businesses, Medical sector, publishing
Clinical data management Supply Chain/Procurement services Managing supply chain activities including Order to Cash,
including e g. data hosting, Software as a service, Infrastructure as a Service, Platform as a service etc 102 Appendix 7 Business Process Outsourcing An Evolving Sector
The changing nature of sectors, high data volumes and information intensity, the increased use of graphics and video, interactive web
25 Internet data transfer capacities are growing at a fast rate. Fibre or enhanced cable technology are
For ease of comparison across regions, data tables are provided in the Appendix Border The Border region,
Key Data and Statistics †Border Border State Average Dublin Unemployment (Q1 2009) 11.7%10.2%8. 9
used in its production †latest available data is for 2006 FORFà S REGIONAL COMPETITIVENESS AGENDAS:
Key Data and Statistics-West West State Average Dublin Unemployment (Q4 2009) 11%10.2%8. 9
Key Statistics and Data-Midlands Midlands State Average Dublin Unemployment (Q4 2009) 11.7 10.2%8. 9
Key Data and Statistics †Southwest Southwest State Average Dublin Unemployment (Q4 2009) 9. 9%10.2%8. 9
'Green'Data Centres Biotech FORFÃ S REGIONAL COMPETITIVENESS AGENDAS: OVERVIEW, FINDINGS & ACTIONS 24 HEIS to consider work placement where students would take up opportunities in a
Key Data and Statistics †Midwest Midwest State Average Dublin Unemployment (Q1 2009) 11.4%10.2%8. 9
Key Data and Statistics †Southeast Southeast State Average Dublin Unemployment (Q4 2009) 11.4%10.2%8. 9
Key Data and Statistics-East Dublin Mideast State Average Unemployment (Q1 2009) 8. 9%9. 2%10.2
Baseline Data and Analysis: Southeast Region which provides an overview of the region today based on an analysis of quantitative and
Data and Analysis for the region Figure 1: Factors of Competitiveness Overview †Population and Growth
e g. bio/pharma manufacturing, data intensive services Recent major IDA project announcements in the Southeast region
) The AR content embedded into the magazine includes a variety of 3d data-driven visualizations and animations to illustrate printed 2d scientific images.
Moreover, learning analytics based on such data are increasingly being incorporated across digital learning environments. Mobile devices such as
Narrative science â€oetransforms data into stories and insights through its proprietary artificial intelligence authoring system. †The algorithms the system uses are highly effective and have
-formance required data that were unavailable from suitable secondary data sources. Hence, we used subjective
measures of performance provided by the respondent managers to capture firms†relative profitability and growth
The model fits the data strongly c2=123.40, df=81, p<.05; CFI=0. 99
all 144 economies as well as an interactive data platform are available at www. weforum. org/gcr
higher education and training), the data suggest a slight downward trend of its performance in higher education
•Collection of data on green technologies and smart ICT systems, suitable to be applied on the corridors to improve performance
A quantitative definition of these KPIS was considered not and few data about them were collected. Thus, these extra KPIS were excluded from the baseline
a) Quantitative data on the technology impact, validated against real-life per -formance; and b) Detailed data about corridor transport routes,
such as traffic volumes, fre -quency of service, delivery time and vehicle features Since such data were not available for all corridors, a limited set of benchmark
scenarios was produced based on the baseline transport chains (Sect. 2) and the green technology review 3. 1 Green Technology Survey and Qualitative Assessment
collecting data from manufac -turers, research and academic works, and the project consortium. The survey
-ogy-specific and it was based on publicly available manufacturer data, technology success stories and research project results.
and mapped to technology performance data 12. For instance, a green technology that reduces fuel consumption can poten
to lack of data about capital costs for some of the green technologies, the return of
including data about basic functionalities, cost, funding mechanisms, and other technical performance characteristics Step 4:
Other relevant data could be collected also Step 5: Based on step 4, inter alia, investigation of potential impact of ICT on the
a) Data necessary to quantitatively compute the ICT impact on corridors gen -erally proved to be difficult
other sources to reveal such data (if any), and non-homogeneity in data quality The problem of data availability (such as cargo flows) is recognised in the EU
In some cases, estimates of such data can be produced based on mathematical models. A fortiori, any linkage of such data with particular ICTS is even more
complicated b) In contrast to the green technologies (Sect. 3) that can have a direct and
tangible impact on the corridor KPIS, the impact of ICTS on the greening of a
corridor is of a different nature. For instance, an innovative propulsion system consumes less fuel, resulting in less CO2 and SOX emissions.
to collect data and evaluate the importance of a set of proposed ICTS •Adaptive speed control
benchmark scenarios, for which there was sufficient availability of data This work revealed the need for adequate and consistent statistical information on
 •Real data for costs and benefits evaluation and decision process  •Possible security issues
Infrastructure & Data Processing Integration of RES, storage and EV Planning monitoring and control Cost
data MV Autom Ancillary services provided by DSOS TD3 50 Ecogrideu TWENTIES Ecogrideu EDISON Ecogrideu
Infrastructure & Data Processing Integration of RES, storage and EV Planning monitoring and control Cost
 †Meter data collection, management and energy efficiency pilot project (2011 second half of year  †2014
1. Meter Data Management system implementation pilot project; 2. Energy efficiency pilot project; 3. Pilot project for testing of
data processing Integration of Smart Metering Monitoring and control of MV networks Automation and control of
metering data processing -Smart metering data processing-DSO integration of small DER -Infrastrucutre to host EV/PHEV
-DSO integration of small DER -Infrastrucutre to host EV/PHEV Integration of Smart Metering Integration of
-Smart metering data processing -Metering Infrastructure -Smart metering data processing Integration of Smart Customers Integration of Smart
Customers Integration of Smart Metering Integration of Smart Metering -DSO integration of small DER -System integration
Flanders in action-breaktroughs 2020 www. flandersinaction. be/nlapps/data/docattachments/Brochure%20via%20 (EN%20-%20april%202009.
So a data base with knowledge from and for the E-Energy Projects exist, but it is not publicly
Detailed information about single projects can be found in the Energy research data base of the SFOE (Swiss Federal office of Energy.
data included in this study. Neither the Commission nor any person acting on the Commission†s behalf may be
data †open data. Open data increases awareness and coordination, creates new opportunities for innovation,
and strengthens inclusion, participation and ultimately, human well-being Society, economy, and even human psychology itself are undergoing an irreversible change, which we as citizens and
open data to create more transparency around public spending. We call this Digital Social Innovation (DSI
Open Data and Open Knowledge Open hardware: These projects are inspired by the global do-it-yourself maker movement and the spread of maker spaces
All data is plotted on a map that visualises radia -tion levels in a given geographical area,
Open data: This refers to innovative ways of opening up, capturing, using, analyzing and interpreting data
Opencorporates (OC) provides a good example of the opportunities in open data. It was set up to in the wake of the financial
crisis to make information about companies and the corporate world more transparent and accessible. It has grown since to
including data on 60 million companies and their subsidiaries and searchable maps and visualizations. OC is used widely by journalists
decentralised environment for open data 3. Educate a technology-savvy multidisciplinary workforce, and use all their powers
data, open hardware, open networks, and open knowledge; and they give rise to new DSI areas such as:(
Open Data Open Hardware Organisations M or e Fi lt er s Screenshot of the crowdmap www. digitalsocial. eu
Open Data Open Hardware Organisations M or e Fi lt er s 1 2 3
of scientific data allows for some scientific research to be conducted by nonprofessional scientists; new ways of making
cognitive mapping based on real-time data analysis and visualisation There have been lots of attempts to har -ness collective intelligence to address
of environmental data, where people col -lectively identify their own high-carbon intensive behaviour, then brainstorm and
amounts of data available for collective transformation into knowledge 17growing a Digital Social Innovation Ecosystem for Europe
-mitting data coming from people, sensors the environment and objects themselves However, we cannot expect the Internet
-cess to social data held on third-party sites and permissions to get into proprietary †app stores. †The lack of standards forces
hands of a few data aggregators, none of which are based in Europe (Google controlling nearly 82%of the global search
-lytics and are producing valuable data about people, the environment and bio -metric and sensor data.
The amount of data produced by open platforms and used for social innovation is dwarfed still
by the amount of data collected on propri -etary platforms, with the danger that much of this data is not available for the social
good. For example, even the European Smart Cities project risks being dominated by US companies such as IBM, Google
and Ciscos, partly because of the lack of alternatives Take for example the commercial success of Google:
-der to expand into other data-driven ser -vices in order to increase their value, profit and marketability.
environmental data, which raises signifi -cant issues of privacy and competition Right now few of these opportunities are
all data-driven services, this threatens the ability of the European innovation system to compete
the network, service and data layer. We emphasize the importance of building European public distributed, privacy-aware architectures that can provide the underlying open digital
The development of open data federated identity, bottom-up wireless and sensor networks, open hardware and distributed social
Making data available as part of a common distributed and decentralised architecture open to all, allow new entrants to aggregate data
on demand and create new services. Competition based on open standards, protocols and formats are essential to deploy interoperability between data
devices, services and networks. This vision requires more investment in fundamental research to promote net-neutrality, strong encryption, banning of trivial
appropriating users†data and discriminating network traffic. By centralising computing, data storage and service provision (via the Cloud), and
by striking strategic alliances between the largest Over-The-Top (OTT) iand largest network operators
NSA data-gate showed that intelligence agencies and governments have been engaging in mass surveillance operations, with huge implication on civil
used to capture data on DSI organisa -tion via www. digitalsocial. eu. We have mapped 1000 DSI organisations and 630
Data is categorised by 1. A typology of organisations (e g Government and public sector organi -sations, businesses, academia and re
e g. open data, open networks, open knowledge, open hardware 4. The area of society the organisa
Open Knowledge, Open Hardware, Open Data, Open Network. 4 Areas of Society: Health and Wellbeing, Finance and Economy, Energy and
data. In East Africa the development of M-PESA (a mobile financial payment system born
send open data information requests to Spanish public bodies Goteo SHARING ECONOMY NETWORK A vibrant ecosystem of makers is developing across Europe and globally.
results in open business, open government or open data. Projects like Open source Ecology are promoting a shift towards a more sustainable lifestyle
open source software and open data. Projects and areas of work like Safecast or open source Geiger, the Smart Citizen Kit and open wearables are showing interesting
transaction across the world and to present that data in a useful and engaging form.
Anyone interested in spending data of any kind is invited to contribute data to the Openspending data
andâ CKAN, the biggest repository of open data in Europe, which is underpinning a new
now able to aggregate data coming from people and the environment in order to create a new generation
data and open sensor networks that are changing the provision and delivery of public services;
-ning to aggregate the layers of data that increasingly permeate the urban environment, in order to create a new generation of products and services, fostering behavioural change9
and freely share their radiation measurements in open data sets. The overarching aim of Safecast
is to encourage people to actively contribute to the generation of a body of data that might alleviate environmental problems
decided to take part in surfacing data on radiation levels across Japan, caused by the meltdown at the power plant.
were massive holes in the public radiation data sets available. As a response to this, the team developed the bgiegie Geiger
-work where bgiegie owners could share the data they were collecting. Safecast then worked with hackerspaces and used
use GPS technology to timestamp the data and log the location. All Safecast data is uploaded to an open data set, which
visualises radiation levels across Japan. To date, the Safecast network has used the Geiger counter to map more than 13
and organise crisis data from a variety sources, such as social media, sensors or even quasi-real-time data.
The hope is that the quick and easy access to real-time crisis data will make it
easier for organisations and developers to quickly to build their own applications without the need to spend days locating
identifying and processing data, thereby enabling much quicker responses to crises such as Ebola or conflicts
Many activities in this area exploit the power of open data, open APIS, and citizen sci
-ence such as Open Data Challenge and Open Cities that provide citizens with better public services, or Citysdk which is defining interoperable interfaces for city-scale
open data, free and open software and open hardware Github, the collaborative service for open software developers, is revolutionising
The Open Data Institute†s start up programme, which has supported organisations like Open Corporate and Provenance
to grow their open data projects, is one of them. 13 Although incubators and accelerators have been always around, their pres
The Open Data Institute (ODI) OPEN DATA ACCELLERATOR Traditional business accelerators offer advice and resources to fledgling firms to help
up public data sets Delivering or partnering with DSI services Delivering services Providing funding for
open knowledge, open data, open net -works, and open hardware Through case study analysis we have
such as open data, open networks, open hardware and open knowledge, are be -ing harnessed by digital social innova
data to share and analyse the data cap -tured across all of the Geiger counters Within these broader technology areas
we have been identifying a variety of more specific technologies and activities adopted by DSI activities such as:
and to pass their data through the network to a single or replicated data -processing location.
An open sensor network (OSN) is a wireless sensor network that manages open information in an open environment.
The open sensor network connects the sensor with the data repository where the information is processed
as it uses public data from different sensors and forwards the gathered information to the central point within a
Sensor networks are the key infrastructures of a smart city, providing basic data on the
fed by open data from the OSN A number of European cities have established sensors that detect traffic density and
order to provide external parties a single point to consume this data For instance, Smart Santander demonstrates the potential of creating large networks
OPEN DATA Innovative ways to capture use, analyse, and interpret open data coming from people and
from the environment The explosion of new types of data analytics and machine learning means that it is no
longer only government or corporate forecasters who have the opportunity to access and analyse data.
By making data open, governments and other large organisations and companies that hold or generate data about society have the opportunity to enable
citizens to hold government to account for what it spends, the contracts it gives and the assets it holds
Local authorities are playing a leading role in implementing open data policies and driving forward the open data movement.
The social benefits of open government vary from citizen engagement to increased transparency and accountability, as well
as enhanced interaction between governments, other institutions, and the public. For instance, citizens are gaining greater insight into how their tax payments are being spent
Beyond the social aspects, open data also supports public sector innovation by break -ing the competitive advantage gained by proprietary access to data
and data lock in Innovation is most likely to occur when data is available online in open, structured
computer-friendly formats for anyone to download, use, and analyse, as long as the privacy and data protection of all citizens is preserved
and that communities are entitled to share the value and social benefits of public assets. Thus, open data, together with
open and standardised APIS is crucial for open innovation, as developers are able to access and use public data and mesh it with other sources of data produced by the
crowd to build novel applications that have a social utility Another important trend, boosting the diffusion of open data is the increasing number
of mobile devices. Smartphones, tablets, PDAS and other devices are becoming smaller faster, smarter, more networked and personal.
For instance, the city of Vienna has, with its Open Data in Vienna programme demonstrated the potential in opening up its data.
The city opened its data records to the population, businesses and the scientific community. Released data ranges from
statistics and geographic data on traffic and transport to economic figures. It then in -vited programmers and developers to make apps and web services based on the data
which to date have resulted in more than 60 applications for citizens. Other pioneering examples include the work by the Estonian Government and the not-for-profit Praxis
on the Meiraha project, which focuses on opening up and visualising the Estonian budget. The citizen science project Globe at Night is yet another example of this
where citizens using the camera and geo-tagging functions on their smartphones help the research project measure global levels of light pollution,
data and citizen science 42 Growing a Digital Social Innovation Ecosystem for Europe Helsinki Region Infoshare OPEN DATA FOR REGIONS
Through an entity called Helsinki Region Infoshare34, Helsinki and three of its neighbouring cities publish all of their data in
formats that make it easy for software developers, researchers, journalists and others to analyse, combine or turn into web
The movement for more and better open data has grown significantly over the last few years through projects funded by the European commission, such as City SDK that help cities to standardise
open data portals. In the United states, the cities of Chicago, San francisco, Philadelphia and New york are only a few of the examples worth mentioning.
set up open data websites at the regional level that can be considered good practices and in the Barcelona Metropolitan Region, the city of Barcelona is leading Multicouncil
Open Data Open Data Challenge OPEN DATA FOR REGIONS There are several examples where Governments and the developer communities interact.
One of them is the examples of competitions and challenges. One of Europe†s biggest open data competitions is the Open Data Challenge15.
It was organized by the Open Knowledge Foundation, the Openforum Academy and Share-PSI. eu. It offered 20,000 Euros in prizes to win and
Price Visualization, Better Data Award, Open Data Award, and Talis Award for Linked data. In total, 13 awards were given
There are many other competitions, such as Apps4finland16, the biggest European apps contest organized since 2009 and
Apps for Amsterdam promoted by the City of Amsterdam to make accessible to developers and citizens the data of the City
emerged, such as Apps for Goodi or the Open Data Institute†s (UK) open data training
itself and the platform used to share data between people operating a kit. The kit is an electronic board based on the Arduino
equipped with sensors that capture data on air quality, temperature, noise, humidity and light. The board also contains a Wifi
antenna that enables the direct upload of data from the sensors in real time. A number of cities, including Manchester in the
UK and Amsterdam in The netherlands, have shown an interest in supporting citizens to monitor environmental data and have
and measure data about real-world activity. This is possible due to the increasing number of powerful smart personal devices, which facilitate the
personal and social data in massive data centres. This can also mean increased surveil -lance, prediction and control of people and the environment.
allocation, the best possible decision making based on a real time data and information from open sources and the best possible alignments of my local providers with the
Open Data Arduino Avaaz Avoin Ministeriã Bethnal Green Ventures Citysdk Clearlyso Angels Communia Commons 4 Europe
Open Data Arduino Avaaz Avoin Ministeriã Bethnal Green Ventures Citysdk Clearlyso Angels Communia Commons 4 Europe
streams of data from interviews to social media into a central repository capable of giving a †big picture†of European DSI
Using the network data, stored as W3c Linked Data at http://data. digitalsocial. eu in combination with our hybrid iterative
strategy of case study interviews, work -shops and events relevant to these com -munities, we have identified DSI actors as
Open data for open access is the last dense community (4. 95 per cent), with
working on open data, such as Salford in the UK. Interestingly, although the open hardware network is the smallest overall
-munities, such as those around open data are connected developing communities Nonetheless, the vast majority of commu
such as those of open data, open knowl -edge, open hardware and open networks Even if an organisation is not central and
-bining open hardware, open data, open knowledge and open networks 56 Growing a Digital Social Innovation Ecosystem for Europe
data (turquoise Successful actors in DSI have managed to leverage large networks using the Internet in order to accomplish innova
social innovation in the data in Figure 4 at least for organisations with more than 3 connections.
Looking at the data, if we want a single scaling European DSI network, an additional magnitude more of
for the creation of an open data incuba -tor within Horizon 2020 aims to help SMES
information and sensor data to improve collective wellbeing Furthermore, there are initiatives in the area of open access, such as Global System
identity and payment data Many US companies have patents on identity, social and payment data.
There is a need to require the European Public sector and EC funded projects to not fall into this trap
and provide open data sets in particular on social identity and payment. Public data sets will remove barriers for social
innovators who often rely too much on proprietary data 2. EU public Digital ID with
citizen control Create a European standardised public digital ID for all citizens with guidelines and rules to
open data distributed repositories, distributed cloud, distributed search decentralised social networking public identity management and encrypted email service
open data, ubiqui -tous broadband Enabling some of the radical, disruptive innovations emerging from digital SI †new
Open data Privacy-aware technologies and encryption Federated identity management Data control and data ownership
The EU data protection reform package Directive on the reuse of public sector information Copyright reform Net Neutrality
Open data Privacy-aware technologies and encryption Federated identity management Data control and data ownership
The EU data protection reform package Directive on the reuse of public sector information Copyright reform Net Neutrality
waste, data to education. In 2014 Nesta revived the 300 year old Longitude Prize and
The Open Data Challenge Series42 is a collaboration between Nesta and the Open Data Institute and has been very suc
-cessful, attracting developers and social entrepreneurs to develop innovative solutions to social challenges using open data
The European Social Innovation Challenge44 was launched by the European commission in 2013 in memory of Diogo
-serving citizens†rights and data protec -tion. One of the first steps of DSI policy implementation should be to integrate
-ve transparency/open data and privacy /data protection as complementary issues and not as opposites. In fact, the right
in both legal frameworks (such as data protection) and technologies (such as en -cryption) should apply to individual citi
-tween data, devices, services and networks Standards will enable new business models for co-operation between multiple stake
so that innovators can build data mashups on top of a distributed data infrastructure (technological neutrality) without fear of unfair licens
-ing issues Open standard licences, for exampleâ Creative Commons (CC) licencesâ could allow the reuse of PSI without the need to develop
-ers who have the right to use the future Internet infrastructure (including both data in
All functionality must be exposed by way of open APIS51 that expose data using open standards.
User data and metadata should be represented in open formats such as XML52 and RDF53 (which includes Linked Data54 and SPARQL end-points55.
OPEN DATA People are not passive consumers of the data, but actively engaged in producing it.
primary advantage of open data is that it prevents the concentration power by leverag -ing asymmetries of information and differentials of access.
Open access to data would enable developers to create applications and services built on freely acquired data, as
long as they respect provisions in the license. Private data should also have its privacy
dimension encoded using open standards and the correct licensing, as well as clear requirements for how to access this data
and determine its ownership, both by vendors and end-users. This should include the right to remove data by its creators
Growing a Digital Social Innovation Ecosystem for Europe 75 The preservation of Net Neutrality56 is a crucial to define
and governments should treat data traffic equally. Net neutrality protects freedom of expression and freedom of information online, reasserts the principle of fair
data policies. The directive provided an EU-wide framework for governments, at all levels, to begin opening data.
The European Commission estimates the economic value of the PSI market at approximately â 40 billion per annum.
European commission Directive on the reuse of public sector information will further enable the opening of public sector data
Although changes in the European legal framework in the field of transparency and open data have already been implemented
over their social data and sensitive information, to make it easier for businesses to innovate on top of the infrastructure.
role of data brokers64 will be crucial for understanding the future of bottom-up digital economies. New forms of data control and data collective ownership by citizens
should be encouraged. For instance, in the UK, the government backedâ Midataâ pro -gramme is encouraging companies to bring data back to public control, while the US
has introduced green, yellow and blue buttons to simplify the option of taking back your data (in energy, education and the Veterans Administration respectively
76 Growing a Digital Social Innovation Ecosystem for Europe DATA CONTROL AND DATA OWNERSHIP PRIVACY-AWARE
TECHNOLOGIES AND ENCRYPTION An important effort towards a federated identity system Is federated the W3c Social Web Working Group58 to develop
standards to make it easier to build and integrate social applications. These standards will give citizens greater control over
their own social data, allowing them to share their data selectively across various systems. The federated web standards will
User data is moving more and more into the †Cloud†and people are getting their music
The aggregated data extracted from the analysis of our identities (what companies define as â€oesocial graphsâ€) and behavioural patterns of the
In this context, the infrastructure should preserve the right of data-portability57, and prevent lock in, therefore allowing for innovation in the wider economy based on the
management, fully respecting the users†privacy and ownership of the data Personal data stores There are also new available solutions, such as Mydex, Qiy,
receive guidance on data anonymisation and pseudonymisation. This should prevent any unauthorised collection processing and tracking of personal information
or by the Open Data Institute (ODI) and Open Knowledge Foundation on open data, and by organisations such as Tactical tech or Open Rights Group on privacy and digital rights
Most reports about innovation refer to GDP and financial return as one of the main in
or analysing existing data sets to understand the extent of the social issue •Online responses to the proposed service from partners or potential
draw upon existing data and research from other sources Level 2 You are gathering data that shows
some change amongst those using your product /service At this stage, data can begin to show effect but
it will not evidence direct causality. You could consider such methods as: pre and post survey
standardisation of delivery and you will need data on costs of production and acceptable price point
The Global Open Data Index developed by the Open Knowledge Foundation80 and the Webindex developed by the World
statistical sources for measuring input (such as firm level micro data, R&d statistics, labour force survey), which could evolve
à Explore DSI specific indicators such as Open Data access, digital skills and proliferation of open source projects or creative commons licenses
As an example, the Fukushima prefecture in Japan hosts a map of the Safecast data on its website, and in
what public data is, and the question of who controls it, is becoming more important.
Thus data portability, federated identity management and trust frameworks should be encouraged. Defining sensible governance modalities for the data infrastructure and the DSI ecosystem will require a large col
-laboration between public and private Ultimately, just as in science and technology, innovation in society needs carefully crafted investment and support.
The incubator programme run by the UK€ s Open Data Institute and the DSI accelerator programme run by Bethnal Green Ventures have demonstrated potential in how models developed to support
/open-data-challenge-series 44 http://ec. europa. eu/enterprise /policies/innovation/policy /social-innovation/competition
/documents/reports/data-brokers -call-transparency-accountability -report-federal-trade-commission-may -2014/140527databrokerreport. pdf 65 http://www. citizenme. com
Brendan Lea (2013) â€oeopen Data Institute Annual Summit 2013†online Flickr Open Data Institute Knowledge for
Everyone. Available from: https://www flickr. com/photos/ukodi/10590223144 /in/photostream/Accessed 29th january 2015
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