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 W s. Maney & Son Ltd. 2010.
Journal of Management & Marketing in Healthcare. VOL. 3 NO. 2. PP 163 175. JUNE 2010 as between providers and payers.
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 contextspecific information that can empower providers in their work'.
Connectivity 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 statistics 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,
Given the fact that the data available at regional level remains considerably scarce, the 2012 RIS does not provide an absolute ranking of individual regions,
The data have been normalized using the min-max procedure, the maximum normalised score being thus equal to 1 and the minimum normalised score being equal to 0. Figure 1 presents those regions that have scored above the average(>0. 5) for at least one of the two indicators in discussion (two regions that have scored above 0
Data represent SMES compared to Large firms. In the present analysis we consider sectors defined as all Core NACE rev 2.-Private, nonfinancial activities related to innovation1.
The data suggest that SMES innovate less than large firms across a range of categories including product innovation, process innovation, non-technological innovation, new to market product innovations and collaboration in innovation activities.
Eurostat, DIW econ, London Economics, MIOIR In a study employing Community Innovation Survey data over 16 countries,
Eurostat, DIW econ, London Economics, MIOIR Although increasing institutional efforts to harmonize data for the understanding of the relationship between innovation and SMES performance,
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:
Evidence from CIS III data for 16 countries, Small Business Economics, Vol. 33 pp 59 75.
and start running a monitoring framework suitable for data collection and analysis throughout the 2014-20 period Use of evaluations in a‘smarter'way Useful activities include organisation of high-level meetings,
and interpreting technological innovation data. Oslo Manual. European commission, Eurostat. Retrieved from http://www. oecd. org/dataoecd/35/61/2367580. pdf Ostrom, E. 1996.
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.
and making policy recommendations based on the cumulative work of WP8. 1 http://digitalsocial. eu/2‘Big data'refers to the vast amount of data that can be collected from the internet,
for example as made available by the public sector as open government data and as contributed by ordinary people through‘crowdsourcing'.
and networks and the network effect (see Annex 3). be logistically amenable to data and information collection and analysis, including suitable material accessible in the public domain,
& strengthen social cohesion Open-Corporates (UK) Making the corporate world transparent via open data to citizens, civil groups,
which manipulate, match and mine data, and which require access to information and systematised intelligence, will become codified
483 people with a mental illness trained, 387 started in a protected job or internship (255 in private sector), with very low dropout (2011-2013 data.
483 people with a mental illness trained, 387 started in a protected job or internship (255 in private sector), with very low dropout (2011-2013 data.
data entry and stewarding with flexible labour supply. 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 completed by 75-80 task providers).
data and data analysis, speed, connectivity, information, global reach and the long tail, virtually zero cost of forming online communities, dramatically reduced transaction costs, etc.?
How to guard against decisions being taken about peoples'lives based purely on big data, data analytics and closed algorithms?
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 locations and things,
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 governments and local authorities,
as well as proprietary, private or personal data which might be added or mashed together either as open or protected data to solve specific problems
and/or analyse specific issues or situations. Much ICT also supports activities (including social innovation)
data and data analytics to improve the efficiency and effectiveness of local systems (like transport, utilities, etc.)
interlink and make sense of their own and each other's data and through this their interconnected lives. The recent Mapping Smart Cities in the EU study36
and 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.
mobile and social media to collect data and organise, increasing civic engagement on issues, community voice and agency-Public lottery fund, many civil organisations, with public & private partners,
and enables them over the medium-term to capture data on where, when and what type of problems occur
and enables them over the medium-term to capture data on where, when and what type of problems occur
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 makers to reconsider the policy changes.
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 resources much more efficiently.
In the Hackney CAB Crowdmap case, it 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 other groups as well as data and information sharing across all partners and volunteers in real-time.
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
as well as data collection and analysis (for example in Hackney CAB Crowdmap). ICT is also a critical enabler leading to new types of social innovation, for example enabling both quantitiative and qualitative changes in the speed, sophistication and richness of processes and relationships,
and provide valuable fine-grained data and information which can be used to improve policy overall. In some of the cases (such as Eastserve and TEM), policies may be needed to help stimulate demand and 58 activity,
collecting data, matching local assets & finance to local needs-Enabling: instant accurate matching & data mapping/analysis,
& widespread sharing Mainly civil financed & operated. Local campaigning, action & advocacy rely on local activist champions supported by professionals
& sometimes assisted by small external funds Bottom-up data & information collection, analysis, campaigning, advocacy and action can fill the gap in evidence on policy implementation
One challenge highlighted by Gansky (2010) is that data information and possibilities are widespread, whilst trust is relatively scarce so needs to be built
open data to citizens, civil groups, journalists to create new content & knowledge & hold corporates to account-Global database of companies, web scraping, reconciliation function, analysis and visualisation tools,
also spinning off physical events like hackathons where data are created and shared sometimes leading to new product
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; www. cookisto. co. uk 60 www. streetbank. com 61 http://repaircafe. org/about-repair-cafe 62 www. opencorporates. com 67 Social
It provides a global open 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
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 company names.
The core business of Opencorporates is to collect data on companies through web scraping tools and then to visualise the data
For example, every night data is imported from the London Gazette, the Belfast Gazette and the Edinburgh Gazette,
The case also sources data from the UK's Financial services Authority, the US's Central Contracting Registration system,
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.
Online platforms, communities and networks: In the Repair Cafés case, all online platforms used are used, except matching finance to needs:
or apply the open data to the tools they themselves wish to deploy. In both cases, this means that complementary online and offline knowledge communities are created,
online open data and open data communities create new content and knowledge for developing new products and services in for example hackathons and other physical events with economic value
online open data and open data communities, also supporting offline communities, create new content and knowledge for making the corporate world more transparent to citizens, civil groups and governments,
In the Opencorporates case an open 64 Interview with Kate Groves, Director of Marketing and Communications, Streetbank. com, 2014 74 data community has been developed
Opencorporates provides sophisticated data and tools which are applied then 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 some related challenges for Opencorporates around issues like data quality, ownership, data updating, provenance,
if something goes wrong (e g. if data errors lead to wrong conclusions) and the potential misuse of data.
For Opencorporates, the main driving trend is seeing corporate data as well as government and other data as a source of income.
hackathons and other events use the open data and tools provided, so in both cases new shared assets are created both physically and virtually.
Opencorporates inspires a social sharing concept to people who use its data, which is made openly available under the share-alike attribution of the Open Database License.
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 used also in physical events such as hackathons to create new shared assets in the form of new products and services or other content.
Strategic and operational considerations The Repair Cafés case operates in a relatively small, informal and very democratic, transparent and bottom-up manner, with finance,
and as, for example, in hackathons enabled by Opencorporates'data. This links the creation of intangible and virtual shared knowledge assets to the creation of tangible and physical shared assets
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 headquarter of the corporations being examine, with, in some examples, thousands of subsidiaries.
One example of this is how Opencorporates has made the often hidden world of some multinationals transparent by visualising the complex corporate structure of Goldman sachs'based on data from public filings and company registrations in the U s.
The promotion of new types of open data and the shared knowledge creation this enables,
and the Opencorporates case collates huge amounts of data on global corporates for open interrogation and use.
and as, for example, hackathons and other events enabled by Opencorporates data. 2. Strategic and operational considerations related to ICT in social innovation All cases operate in a relatively small and flat civil and voluntary organisations,
and as for example hackathons enabled by 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,
& technical expertise-Potential data knowledge & IPR challenges when cocreated, data quality & responsibility-Demand side ecosystem often weak-Vision of enthusiasts-Open data as income
essential for knowledge co-creation & ongoing dialogue-Data and knowledge creation and manipulation vary hugely from small to big data, depending on case-Civil, voluntary finance & operation-Flat, informal, open, bottom-up,
There is a lot of health related data created in different settings in hospitals outpatient clinics, social care, through mobile apps etc.
However, there is no agreed procedure for analysing the data for scientific and policy related issues.
knowledge generation and use How to ensure access to relevant data for the use of social enterprises
apps and other programs being developed that target chronic conditions, telemedicine and remote monitoring, patient data capture, electronic records,
smartphone enabled data aggregation, medical situation awareness and analysis (risk classification, root cause analysis and risk triggers),
and public health and social services agencies to turn data into information insights, so they can deliver higher quality care to more patients and citizens at a lower cost.
Tools which enable patients to share data regarding their experiences with particular health providers e g.
and patients outside of traditional doctor visits and to improve data collection, organisation, or analysis. Moreover Penda sends SMS messages once a week on Mondays to provide patients with clinic updates
and patients outside of traditional doctor visits and to improve data collection, organisation, or analysis. Access Afya staff record all patient information, consultations,
and patients 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
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 and pen survey collection method. Vecna Cares upgraded the Clinipak software at Enoosaen and Olereko 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
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.
its online platform allows for data derived from proprietary devices carried by the patients to be transmitted to an online platform.
In reality, telecommunications and information sciences play an equally important role in how they facilitate the connection between this state of the art data aggregation system and the end-users'device.
lang=en 95 addresses the lack of reliable patient data, timely monitoring of patients condition and availability to the medical professional handling the patient's case.
long term data, and not patient observations, often affected by personal embellishments, the patients'emotional condition or inability or unwillingness to share.
The platform hosted by DIABETIVA can motivate patients to share data and knowledge on how to better understand it
A as DIABETIVA users become better able to use their DIABETIVA generated data and use it as leverage to improve their lives the undertaking they will attract more patients who wish to partake of their communal knowledge
in time, create a group of practitioners able to apply the data to some uses, but unable to promote a cohesive and intelligent analysis
Eventually, more tech-savvy patients will find new methods of using their data, thus leveraging the benefit for patients
-and off-market niches that will keep the market vital long after market saturation has set in. 100 As these initiatives are set up currently and in the context of the sensitivity of health data,
The problems associated with the release of commercially sensitive information and data which potential competitors might exploit.
In the process, they generate data about the real-world nature of disease that help researchers
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 advancement.
rather than just querying data collected from online systems. The relation of learning design to learning analytics is also being considered,
and querying large data sets. c) Crowd learning-Crowd learning describes the process of learning from the expertise and opinions of others,
collect data using desktop and mobile technologies as research tools, and validate and share findings.
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 early childhood development, MONDEY works also to disseminate knowledge on this topic.
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 explicit knowledge.
At the same time, users help to verify and further knowledge 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 sessions
Data from the Department for Education shows that, in 2013, Q2l's average score on The english Language Arts state exam was higher than the average overall citywide test score for Middle schools
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
To get good norm samples for future research it is paramount to get good data in the first hand.
It is important to have representative data and samples to give realistic feedback to the parents and to advance research.
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 pedagogues
However Coursera is primarily targeting the educational needs for the 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 methodological approach in section 2
which ICT is used (e g. communicate with beneficiaries/partners, collect data, etc.,etc.),), and how is this better than non-ICT tools (e g. speed,
information access and data usage; social choices; service models; financing and much more. Although this report has no intention of being a comprehensive and complete review of the impact of online networks on social innovation,
and crowdsourced data from communities in order to uncover or identify issues and societal challenges. This could be by uncovering new
as well as rationalising resources. 6. 7. 5. Introduction of open data In the evolution towards a network society, a new,
open public data to enable businesses and citizens to create products and generate wealth and value.
and the Public Administration 7. 4. Using ICTS to modernise the Administration 7. 5. Introduction of open data 7. 6. Modernising
The latest data for enterprises with foreign investment are available for the end 2009: their number was 20,552,
See also the operationalisation exercise and data in Morais Camanho, 2011.5 This is the consensus opinion of Hungarian researchers publishing on metropolitan development
International comparative statistics, e g. the Eurostat Urban Audit provide data up till the mid-2000s
According to data on the distribution of national resources for innovation support purposes, CH absorbed 60%of total innovation support from the National Research and Technological Innovation Fund (KTIA) between 2004 and 2008 and a similar
As for the regional data as might be expected CH is above the national average: 4. 3%(150%of the national average.
evidence is in principle available in the form of statistical data, analyses and regional innovation intermediaries'databases.
Hungarian regional innovation data as part of an international comparison is available in the Regional Innovation Scoreboard, on the PRO-INNO EUROPE website.
Statistical data on regional economic and innovation performance is compiled regularly and published by the Central Statistical Office.
author's calculation from NKTH, 2010 data. National policy schemes to support innovation are diversified highly each individual policy objective is supported by a number of partly overlapping policy measures (Havas,
Both data are higher then the national average. Life expectancy indicators are better than the national average.
Data about the number of applications, information about the results of evaluations and the success rate of projects are missing.
or impact Evidence of outcomes based on evaluation and other evidence No data is available about the number of applications. 16 projects were selected,
Do's and Don'ts No data is available about the number of applications, thus the success can not be judged.
Regional data, information on funding resources and studies are areavailable on CD. One can also visit the website of the Agency for information.
Integration of these data into the countrywide information system. 2. Evaluation and registration of innovation centres, incubator houses and technology centres. 3. Information provision about funding opportunities for innovative SMES,
It also helps the SMES of the region in getting access to financial resources provided in the framework of various Hungary or EU financed programmes. 32 Appendix D Statistical data Indicator Közép--Magyarország
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