Synopsis: Ict: Data: Data:

Available data are not reassuring. As shown below, in Figure 1, the gap between the EU15 and the United states in terms of expenditure in R&d has been in place since the early 1980s.

Kristian Uppenberg, presentation at the first Task force meeting, 18 september 2009, OECD data. 14 INTRODUCTION. TOWARDS EUROPE 2020 An important issue is the ability of the European Investment Bank (EIB) to reach dynamic and innovative small firms

Section 6 briefly concludes. 27 2. A NEW APPROACH TO INNOVATION POLICY IN THE EU 2. 1 Innovation is a changing concept The data reported in the previous section show that Europe is facing a structural problem

Available data testify to a European †lag†vis-Ã-vis the United states, Asia and several emerging economies in terms of research, development and innovation (R&d&i.

Available data 6 See European Innovation Scoreboard 2009 at http://ec. europa. eu/enterprise/newsroom/cf/document. cfm?

Also, European companies perform about 30%of R&d outside the EU. Data presented at the Task force meetings are based on evidence of collaboration between EU

and data using common indicators. 2. 2. 3 Taking innovation seriously: improving governance through accountability and coordination Putting innovation at the core of the EU policy-making process cannot only be a declaration of intent.

Such data shows that companies with a large share of their business in the US or Japan receive a substantial advantage from their own patent 17 As a matter of fact,

p. 25.24 Data are available in the Communication from the Commission to the European parliament and the Council Enhancing the patent system in Europe, COM (2007) 165 def, p. 7. A NEW APPROACH TO INNOVATION POLICY IN THE EUROPEAN UNION 47 case of SMES.

together with studies and empirical data provide useful inputs for policy decision regarding a future patent system,

and available empirical data on the fact that European universities are good at sciences and technology,

New emerging technologies like smart materials, micro-mechanical sensors and wireless and faster data transfer solutions etc. have presented new opportunities to develop product features, especially those intangible features

and PDM (Product Data Management) can be used to manage product-related information. The main point is that ICT should fully support the business processes

for example Business intelligence solutions to manage business data and information from marketing and customers. Markets are providing a huge number of different solutions to different needs,

Companies should clarify their data administration vision: which kind of solutions best fits the company and

However, there were insufficient data on the cost-effectiveness of these systems and it was not possible to determine the extent to which the demonstrated benefits were generalisable.

and to create data exchange networks is more straightforward. Another structural barrier is the lack of standardisation and certification for EHR and health IT systems

resulting in the lack of system and data interoperability. A contributing factor to the delayed standard adoption is the lack of incentive for data exchange between and among providers as well Kaye, Kokia, Shalev, Idar and Chinitz 166 Â W s. Maney & Son

Ltd. 2010. Journal of Management & Marketing in Healthcare. VOL. 3 NO. 2. PP 163†175.

and confidentiality are also often barriers to health IT as they tend to restrict the sharing of patient data among providers.

better care based on better documentation and better management of resources based on better data. Over time, these goals were expanded

electronic data exchange between the EHR and other clinical data systems, lack of incentives and physician attitudes. 15 On the other hand, in summarising the critical success factors Kaye, Kokia, Shalev, Idar and Chinitz

fully integrated health information and communication system with a comprehensive database that includes more than 18 years of data on almost 2 million members.

and with continuous clinical data exchange taking place in real time. This system with all of its components, was developed over a period of 20 years,

setting stringent standards that all IT vendors had to meet to assure compatibility for purposes of connectivity to enable clinical data exchange,

and to provide ongoing feedback during implementation. 2. A minimum data set was agreed upon, with the gradual addition of new fields and tools over time. 3. It was agreed at a very early stage what the doctor would see first

when he opened the EHR †a summary page with the most relevant patient data. 4. In the case of each additional field or tool,

particularly when the EHRS had the capacity to store data with high fidelity, to make those data readily accessible,

and to help translate them into context-specific information that can empower providers in their workâ€. 17

and investment in the communication infrastructure for clinical data exchange is a must for a system that will be sustainable over time, in terms of benefit to doctors, patients and the healthcare system.

Recent calculations by the authors of this paper, based on Germany†s official â€oestatistics portal†data, show that the high percentage of SMES amongst all enterprises continues to remain high.

2 These data exemplarily demonstrate the key-role which SMES play in Germany†s economy.

The rest was rejected because of containing incomplete and/or contradictory data. Figure 3 shows the representation of the industry sectors in the sample.

whereby the data is transmitted electronically from one centre to next. Such a step could be of crucial importance for time-critical projects,

G#1v 7764 Data G#2v 7765 Backup 0#3#backup Backup G#2v 7766 Big data

G#2v 7779 Data 0#3#data Data G#2v 7780 Data center 0#3#data center Data center

G#2v 7781 Data compression 0#3#data compression Data compression G#2v 7782 Data format 0#3#data format Data format

Given the fact that the data available at regional level remains considerably scarce, the 2012 RIS does not provide an absolute

The data have been normalized using the min-max procedure, the maximum normalised score being thus

Data represent SMES compared to Large firms. In the present analysis we consider sectors defined as â€oeall Core NACE rev 2

The data suggest that SMES innovate less than large firms across a range of categories including product innovation, process innovation, non-technological

In a study employing Community Innovation Survey data over 16 countries, Holzl (2009 found that high-growth SMES are more innovative

Although increasing institutional efforts to harmonize data for the understanding of the relationship between innovation and SMES performance, comparative exercises at the EU

Despite our analysis was bounded by data availability, it is relevant to remember that to increase SMES competitiveness other elements should be considered.

A system†s review of UK and international innovation data, NESTA Report, London (UK Baumol William J. 2002), The free-market innovation machine:

CIS III data for 16 countries, Small Business Economics, Vol. 33 pp 59†75 Kakati M. 2003), Success criteria in high-tech new ventures, Technovation, Vol. 23

and interpreting technological innovation data. Oslo Manual. European commission, Eurostat. Retrieved from http://www. oecd. org/dataoecd/35/61/2367580. pdf

information access and data usage; social choices; service models; financing and much more. In this context, Work Package 8 examines the impact of ICT on,

and analyse data of what social needs are being experienced by which people in different places at different times.

/2 †Big data†refers to the vast amount of data that can be collected from the internet,

by the public sector as open government data and as contributed by ordinary people through †crowdsourcingâ€

x be logistically amenable to data and information collection and analysis, including suitable material accessible in the public domain,

Making the corporate world transparent via open data to citizens civil groups, journalists to create new content & knowledge & hold

which manipulate, match and mine data, and which require access to information and systematised intelligence, will become codified

internship (255 in private sector), with very low dropout (2011-2013 data 26 x Eslife: promotes initiative and autonomy amongst unemployed, underemployed and

internship (255 in private sector), with very low dropout (2011-2013 data x Eslife: provides benefits of legal and insured work compared to informal work

data entry and stewarding with flexible labour supply x Eslife: Over 1, 000 unemployed, underemployed and volunteers looking for work, in 7

cities and growing to over 25 in 2014 (latest two months of data show 600-700 tasks

data and data analysis, speed, connectivity, information, global reach and the long tail, virtually zero cost of forming online communities, dramatically reduced

x How to guard against decisions being taken about peoples†lives based purely on big data, data

physical interactions with people, things and places. 33 For example, the so-called †geoweb†of data

linked to geogrpahic places provides †digital overlays†of different types of data related to physical

which locate the data to specific points in space or specific geographic areas. This characterises much of the so-called †open data†made available by

either as open or protected data to solve specific problems and/or analyse specific issues or situations.

data and data analytics to improve the efficiency and effectiveness of local systems (like transport, utilities, etc.

and make sense of their own and each other†s data and through this their interconnected lives. The

is concerned especially with using data and coordinating resources to improve the lives of the neighbourhood†s inhabitants in terms of improved physical environments and mobility.

social media to collect data and organise, increasing civic engagement on issues, community voice and agency

over the medium-term to capture data on where, when and what type of problems occur

them over the medium-term to capture data on where, when and what type of problems

generating and analysing data and campaigning through citizen advocacy. The main purpose of gathering impact data stories was to increase the voice of local people,

campaign against the changes by providing reasoned evidence of negative impact, and hopefully influence decision

in the process of decision making, providing data and knowledge about local problems and areas of concern. Collecting such data and knowledge over the medium-term on where, when and what

type of problems occur also makes it possible to plan and use their maintenance, repair and other

facilitates gathering information and data, assists in analysing the data, and increases the efficiency of managing and organising campaigns and advocacy.

It also supports many of the traditional and physical activities associated with such campaigning. By sharing data, stories and research findings

online and via social media, ICT makes it easier for research findings to be found and accessed by

data and information sharing across all partners and volunteers in real-time. ICT enables the experiences of those who are heard rarely

By sharing experiences and data on the issue, it also has the potential to help others generate social innovation related to housing.

The two cases show how relevant data, information, finance and volunteers are needed and can be identified

in some cases also matching local financial assets to needs (as in the IOBY case), as well as data

fine-grained data and information which can be used to improve policy overall. In some of the

collecting data matching local assets & finance to local needs -Enabling: instant accurate matching & data map

-ping/analysis, & widespread sharing Mainly civil financed & operated. Local campaigning action & advocacy rely on

Bottom-up data & information collection analysis, campaigning, advocacy and action can fill the gap in evidence on policy

by Gansky (2010) is that data, information and possibilities are widespread, whilst trust is relatively

open data to citizens civil groups, journal -ists to create new content & knowledge & hold corporates to

events like hackathons where data are created and shared sometimes leading to new product and services

incubated in Open Data Institute, some foundation funding, other civil partners and civil operated -from 3 to 75 jurisdictions by 2014,60 million companies in

database, small fees given to people providing data 58 www. time-exchange. gr 59 www. cookisto. gr;

data database of over 60 million companies in 75 jurisdictions, together with web scraping reconciliation functions, analysis and visualisation tools, all in open format for anyone to use to

support an open data community. The main activity is to collaborate with Scraperwiki, a platform for doing data science on the web,

to help get corporate data by scraping it from the web. The site also has a Google Refine reconciliation function that matches legal entities to

The core business of Opencorporates is to collect data on companies through web scraping tools and then to visualise the data which is mainly from company registers, but

also from a wide range of other published datasets, both national and global. For example every night data is imported from the London Gazette, the Belfast Gazette and the

Edinburgh Gazette, which is where official insolvency notices are published. Every day 63 Interview with Kate Groves, Director of Marketing and Communications, Streetbank. com, 2014

The case also sources data from the UK€ s Financial services Authority, the US€ s Central Contracting Registration system, and a wide

This data is used often by Opencorporates, as well as independently by third parties, in physical hackathon-type events where data are created and shared, sometimes

leading to new products and services x Online platforms, communities and networks: In the Repair Cafã s case, all online platforms

open data to the tools they themselves wish to deploy In both cases, this means that complementary online and offline knowledge communities are

online open data and open data communities create new content and knowledge for developing new products and services in for example hackathons and other

online open data and open data communities, also supporting offline communities, create new content and knowledge for making the corporate world more

data community has been developed and this is spinning off many groups in many countries, as well as physical and other events like hackathons.

Opencorporates provides sophisticated data and tools which are then applied in many other contexts by a wide variety of disparate groups,

The Opencorporates case has, alongside many open data portals, barriers like technology scale problems when handling huge amounts of data.

There are also significant challenges in establishing and nurturing a demand-side ecosystem of users which,

There are some related challenges for Opencorporates around issues like data quality, ownership, data updating, provenance, who is responsible for mistakes

if something goes wrong (e g. if data errors lead to wrong conclusions) and the potential misuse of data

In terms of drivers, the Repair Cafã s case was started and is sustained by its active members and

For Opencorporates, the main driving trend is seeing corporate data as well as government and other data as a source of income.

There is also increasing interest in corporates and their activities because of their importance and their role in the economic and financial crisis

hackathons and other events use the open data and tools provided, so in both cases new shared assets are created both physically and virtually.

people who use its data, which is made openly available under the share-alike attribution of the

In return, any product of that data must also be open for others to use. For

users who do not give back data, they pay Opencorporates a fee. Data from Opencorporates is also

used in physical events such as hackathons to create new shared assets in the form of new

Opencorporates†data. This links the creation of intangible and virtual shared knowledge assets to the creation of tangible and physical shared assets, mutually supportive of each other, and

In the Opencorporates case, the strategic output is capturing data in searchable maps and visualisations of complex corporate structures with multiple layers of control below the

data from public filings and company registrations in the U s.,New zealand, the Cayman islands Luxembourg and the UK.

The promotion of new types of open data and the shared knowledge creation this enables, exemplified by the Opencorporates and the Repair Cafã s cases,

Opencorporates case collates huge amounts of data on global corporates for open interrogation and use.

for example, hackathons and other events enabled by Opencorporates data 2. Strategic and operational considerations related to ICT in social innovation

Opencorporates data. This extends the creation of intangible and virtual shared knowledge assets to the creation of tangible and physical shared assets,

The promotion of new types of open data and the shared knowledge creation this enables, exemplified by the Repair Cafã s and the Opencorporates cases, shows that this

-Potential data knowledge & IPR challenges when co -created, data quality & responsibility -Demand side eco

-system often weak -Vision of enthusiasts -Open data as income source -Social trends to DIY, partic

-ipation, scrut -iny of large organisations -Crisis as catalyst -Supporting: creation of traditional & physical

-Data and knowledge creation and manipula -tion vary hugely from small to big data depending on case

x There is a lot of health related data created in different settings †in hospitals, outpatient clinics, social care

However, there is no agreed procedure for analysing the data for scientific and policy related issues

x How to ensure access to relevant data for the use of social enterprises and the potential for Social

data These key trends can be summarised as follows x The rise of integrated, patient-centred health care models †In broad terms, future models of health and

conditions, telemedicine and remote monitoring, patient data capture, electronic records, e-prescribing and the parallel industries of fitness and wellness. mhealth holds promise for improvement along the value chain

data aggregation, medical situation awareness and analysis (risk classification, root cause analysis and risk triggers

agencies to turn data into information insights, so they can deliver higher quality care to more patients and citizens

x Tools which enable patients to share data regarding their experiences with particular health providers e g

data collection, organisation, or analysis. Moreover Penda sends SMS messages once a week on Mondays to

providers and patients outside of traditional doctor visits and to improve data collection, organisation, or

outside of traditional doctor visits and to improve data collection, organisation, or analysis. Theclinipak automates and standardises primary health care workflows and data collection, health assessment forms

and patient records in a suitcase. It contains a solar powered touch screen laptop and other health

The team modified an Open Data Kit (ODK) Collect, an open-source tool for mobile data collection and loaded it onto an Android Smartphone that the Community Health Workers

CHWS) carry when visiting patients. The completed surveys are uploaded then to a Vecna-hosted server

where the data is available for download and reporting. This has been a vast improvement over the paper

clinics with new features for improved patient outreach, data capture and reporting capabilities Most of the described examples are already in the post pilot phase

process, they generate data about the real-world nature of disease that help researchers, pharmaceutical companies, regulators, providers and nonprofits develop more effective products, services and care.

allows for data derived from proprietary devices carried by the patients to be transmitted to an online platform

the art data aggregation system and the end-users'device. This is a â€oematching assets to needs†platform.

addresses the lack of reliable patient data, timely monitoring of patients condition and availability to the

since opinions can be made based on concrete, long term data, and not patient observations, often affected by personal embellishments, the patients†emotional condition or inability or unwillingness to share

platform hosted by DIABETIVA can motivate patients to share data and knowledge on how to better understand

A as DIABETIVA users become better able to use their DIABETIVA generated data and use it as leverage to

practitioners able to apply the data to some uses, but unable to promote a cohesive and intelligent analysis and

Eventually, more tech-savvy patients will find new methods of using their data, thus leveraging the benefit

As these initiatives are set up currently and in the context of the sensitivity of health data, knowledge generation

•The problems associated with the release of commercially sensitive information and data which potential

generate data about the real-world nature of disease that help researchers, pharmaceutical companies, regulators providers and nonprofits develop more effective products, services and care.

relevant when it comes to the use of data that users inevitably leave when using such portals or apps.

as the data displayed is potentially highly sensitive and personal, yet can potentially support transformative medical

rather than just querying data collected from online systems. The relation of learning design to learning analytics is also being considered,

querying large data sets c) Crowd learning-Crowd learning describes the process of learning from the expertise and opinions of

carry out a controlled intervention if appropriate, collect data using desktop and mobile technologies as research tools,

collecting and sharing local data e) Gamification-There is increasing interest in the connections between games and education.

It creates and produces data by collecting data on the children monitored. Giving information on

hierarchical, the data collection follows a bottom-up approach. MONDEY combines codified knowledge and tacit knowledge existing among researchers worldwide (who can be seen as acting within a network of practice) into

by providing new data. They are doing so by sharing their tacit knowledge filling in the data on the MONDEY

platform or making the filled in short scales available for the MONDEY team or giving feedback during training

Data from the Department for Education shows that, in 2013, Q2l†s average score on The english Language Arts

Also, in the future data generated by MONDEY allows for an evidence-based approach in the development of early childhood education

In the future data generated by MONDEY allows for an evidence-based approach in the development of early childhood education

conversely, researchers gain new knowledge by getting new and representative data for future research. Awareness on important steps in childhood development is increased.

but also to gain new data for future research. One of the basic ideas of MONDEY is to create a win†win†situation

future research it is paramount to get good data in the first hand. This means,

data parents generally hesitate to submit. It is important to have representative data and samples to give realistic

feedback to the parents and to advance research. The long term objective is a large data base for research projects

and thus data needs to be highly secure. Further all of the systems require a high degree of ICT support particularly as such initiatives often operate with less tech-savy user groups such as

higher educated as demographic data for Courserians shows that 75%have a Bachelor†s degree or higher.

At the same time it collects data on real developments of young children to establish a database that can be used by researchers.

when MONDEY receives data on the monitoring of babies and toddlers. This is definitely innovative. MONDEY is dynamic and interactive.

and other questions it takes data gathering decentralised and bottom up. This is only thinkable and possible by the use of ICT

particularly if data is used further for research about learnintg processes. But without getting this sensitive date no reliable data will be won for research

Conclusions and reflections Drawing directly on the above analysis, conclusions regarding the three generic research issues, introduced in the

policies regarding data security 131 References Bertot, J. C.,Jaeger, P. T, . & Hansen, D. 2012).

which ICT is used (e g. communicate with beneficiaries/partners, collect data, etc. etc.),), and how is this

data usage; social choices; service models; financing and much more. Although this report has no

networks collect and share peer produced and crowdsourced data from communities in order to uncover

and establishing an open data system 6. 7. 1. Preventing legislation from having a negative effect on competitiveness

6. 7. 5. Introduction of open data In the evolution towards a network society, a new, relational model of innovation is

public data to enable businesses and citizens to create products and generate wealth and value

7. 5. Introduction of open data 7. 6. Modernising and making it more flexible the Administration of Justice

network people, ideas and data across boundaries of any nature: geographical, cultural disciplinary, linguistic, social, economic

social media, distributed knowledge creation and data from real environments "Internet of things")in order to create awareness of problems and possible solutions

collaboration of human and nonhuman actors we can think of data being gathered by engaging both citizens and sensors,

Safecast, which†after the March 2011 earthquake in Japan†provided data about radiation by using a sensor network;

surround personal and sensitive data With reference to more action-oriented research questions we have, first of all, questions

Moving from citizen engagement to the data that these citizens produce on the web intentionally or unintentionally, a main research question is how to make that data

reliable, trustworthy and meaningful? To this end CAPS projects study manners of visualising behavioural patterns and information diffusion, of supporting and

official and unofficial statistical data In addition, CAPS projects support existing communities by intensifying the analysis

knowledge, visualisation of digital (open) data, and copyright All such topics involve the understanding of collective forms of behaviour and of self

†Users of online communities interested in knowing more about their data and in defending their online rights

could be used as a useful data source to identify the type of organisations, technologies and movements with which CAPS projects are already engaging

statistical data collections (WEB-COSI), and reputation and rating systems (WIKIRATE e-Democracy, e-Participation, Direct Democracy

Open) Data Integration Each social network has a different affordance for users. Twitter, Facebook and other widely-adopted social systems format the content in different ways,

Integrating user-generated data from different media, analysing the content as well as user participation, and providing

insightful visualisations are some of the complex tasks related to data integration addressed by CAPS projects

and WEB-COSI are focused on open data integration by providing different standards, tools and methods for data federation.

DECARBONET and D-CENT work on the modelling of social media data for mining and presenting it in an aggregated

way. CATALYST, DECARBONET, and WIKIRATE are also together in that they aggregate data from different social media sources (such as Facebook, Twitter and emailing systems

Online Deliberation†From Group-Based to Large-scale Recent events have given evidence to the fact that communities can be created and

provide unstructured conversations where data is not presented in a way that makes it easy for other people

results, from statistical data (SCICAFE2. 0) to scientific themes (SCICAFE2. 0), and passing through knowledge on corporate social responsibility (WIKIRATE

and data quality discrimination WIKIRATE and WEB-COSI 38 Privacy-Aware Tools and Applications Privacy-aware systems have evolved over the last decade from privacy-enhancing

full control of their data, maintaining privacy and trust in the technology they use FOCAL is motivated by privacy concerns about the data and location of the end users that

contribute to CAPS. It is concerned thus with the analysis of privacy, reputation and trust in

provide a secure environment for effective control over relevant data Social networking & Social media Enhancement The confluence of network-centric systems, mobile telecommunications, semantic web

with tools to enable the use of their data by entities outside of the OSN, for example, in

7. CKAN http://ckan. org CKAN is a powerful data management system that makes data accessible†by providing tools to streamline publishing, sharing, finding and

using data. CKAN is aimed at data publishers (national and regional governments companies and organisations) wanting to make their data open and available

8. Climate Quiz https://apps. facebook. com/climate-quiz A Facebook application in the tradition of â€oegames with a Purpose†for Measuring Environmental Knowledge

9. Cohere http://cohere. open. ac. uk Cohere is a visual tool to create, connect and

share ideas, and back them up with websites. By using Cohere people can support or challenge each other's ideas

and maintain data about roads, trails, cafã s railway stations, and much more, all over the world

to perform semantic fusion of data that can make sense of the underlying causal processes of a problem situation (i e. the

Integrating quantitative data with content analysis of self-reports is a possible way to evaluate,

The results of the data and evidence collected in such a way can be used to

Systems Methodology to Analyse Qualitative Data'.'Proceedings of the 2nd International Conference on Systems Thinking in Management, Salford, UK, April 2002

Data De Paoli, S. & Teli, M. eds. 2011)' New Groups and New Methods? The Ethnography and

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