Synopsis: Ict: Data: Data:

The statistical data for Israel are supplied by and under the responsibility of the relevant Israeli

The use of such data by the OECD is without prejudice to the status of the Golan heights, East

Box 3. 1. Advantages and limitations of patent data as a proxy indicator for technological innovation...

In addition to quantitative indicators, qualitative data such as SWOT analyses, surveys workshops and interviews with regional stakeholders are also important in the priority setting and

Designing a specialisation strategy at the regional level requires an intelligent use of data in order

of quantitative and qualitative data to situate the region, country or emerging †activities†in a larger picture

what data and tools are needed †and available †to support policy makers to assess the

Thus, data and indicators are necessary to track progress, assess structural transformations and compare strategies.

and export data per economic sector For countries, sufficiently detailed, internationally comparable economic data is available from OECD (www. oecd

-ilibrary. org/industry. Unfortunately, on a regional level, it is difficult to find sufficiently detailed, internationally

comparable economic data. The most appropriate data appear to be OECD€ s regional labour market statistics

By comparing specialisation indicators over time, changes in scientific, technological or economic specialisations can be analysed.

In addition to publications, patents and economic performance indicators, other data are relevant for assessing a country†s or a region†s STIE potential.

Unfortunately, it is very difficult to find regional data that are sufficiently detailed in terms of relevant

Additional limitations to data analyses arise when considering that regional internationally comparable data †especially on economic specialisation †are underdeveloped.

A number of indicators for innovation, research and development commitments, complementary investments in related industries early stage market transactions as well as for interregional and international collaboration deserve more

indicators based on the new data available to measure trade in value-added terms: the OECD ICIO model

and ORBIS firm-level data. It could be interesting to explore if regional indicators can be developed to

In addition to quantitative data, diagnostic tools can be particularly useful to identify these promising †activities††not captured by existing empirical material â€

identified nearly 5 000 innovations and collected data on them. This database makes it possible to make versatile

Data and indicators to measure specialisation in science, technology and employment may help policy-makers in diagnosing apparent strengths, weaknesses, fits and misfits in terms of scientific

strategy formation process, prospective data and analysis •Selecting and engaging key actors, necessary for their expertise and knowledge, is an

It includes performance data such as publications, critical size, collaborative projects etc The Monitoring helps to â€oefine-tune†the Strategy...

Collection of data is undertaken based on a random sample of approximately 9 000 businesses. The sample was

Data from the survey is used to monitor trends in farm innovation, evaluate impacts on agricultural productivity

Furthermore, the data allows the grain sector to develop its own benchmarks for innovation to ensure agriculture does not lag behind the national push to develop

evaluated against qualitative data gathered from interactions with industry and by gauging community and industry support for the organisation through event attendance and brand recognition.

Qualitative data, in the form of â€oereal life†success stories help demonstrate to SMES, the value of networks, like SEMIP in

Data from the Australian Bureau of Statistics demonstrates the concentration of advanced manufacturing and high tech

•Use of data and diagnostic tools: The region†s innovation strategy is based on both qualitative

and quantitative data and takes into account local and external conditions. Lower Austria has gone through extensive prioritisation processes thanks to several strategic exercises since the

•Impact of data and diagnostic tools: Lower Austria made positive learning experiences with the

Empirical data-on how to articulate regional choices in terms of the national strategy-were collected in a series of 18 regional workshops,

identified nearly 5 000 innovations and collected data on them. This database makes it possible to make

collects the data from the area of social policy; and iv) Labour market and Education Observatory of

This type of tools is mostly based on data from the past and present. The analysis can be used by

makers were provided with this data-set for the OECD exercise, it is too early to comment on how it is

While good progress has been made to collect data and develop indicators to monitor the innovation performance of regions and countries, there is still a challenge to develop appropriate evaluation

The current state of the art for baseline data profiling for policy prioritisation is developed much more than that for ongoing monitoring.

Data and indicators about smart specialisation are necessary to make those processes and their impact

metrics, indicators and regular data collections, smart specialisation strategic opportunities will not be discernible and policy makers will be unable to track progress,

One of the most accepted and widely used data sources for the analysis of scientific specialisations is

and data handling by Thomson Reuters the multidisciplinarity of the database, its selectivity based on quantitative criteria, the completeness of the

one of the most appropriate data sources for bibliometric analyses. In addition to SCIE, the Web of Science

scientific specialisations of countries, regionalisation of publication data has made it possible to develop the same indicators on a regional basis. They then represent the scientific specialisations of a specific

As the SCIE data do not contain regional identifiers such as NUTS2 or NUTS3 codes, regionalisation of publication data currently requires

text mining and programming procedures. Regionalization of the Scopus data is even more cumbersome given the lower quality of the address information in this database

The successful application of the Activity Index and of RCR by scientific field strongly depends on

The data indicate that the country has a persistent relative specialisation in geosciences and space sciences (G), mathematics (H), and biology

publication data for this country can shed more light on these dynamics INNOVATION-DRIVEN GROWTH IN REGIONS:

The most widely used indicators for technological activities make use of patent data. Despite several

Box 3. 1. Advantages and limitations of patent data as a proxy indicator for technological innovation

The advantages of patent data as a proxy indicator for technological innovation •Patents cover virtually every field of technology useful for the analysis of the diffusion of key

•The statistical processing of data is largely free of errors, because patent documents are legal

•Accessibility and electronic availability of patent data has eased greatly their use The limitations of patent data as a proxy indicator for technological innovation

•Firms differ in their propensities to patent(#patents per unit of expenditure on R&d or just#of patent

Just as with publication data, one needs to be careful in interpreting low count data. Regions with very

Data on these European patents are available from the European Patent office EPO). ) Data from the U s. patent system is available from the United states Patent and Trademark Office

USPTO). ) One important way in which patent systems differ is in their publishing and granting procedures

as well as about national patent systems data for about 100 countries worldwide. Access to the PATSTAT database is obtained through a license agreement with EPO

The choice of this benchmark group will often be determined by the patent data source used. When using USPTO,

use EPO patent data to compare the specialisation profile of Sweden with that of all Scandinavian

noted that the regionalization of patent data, based on inventor and applicant addresses, is not available in

The data show a relatively stable specialisation profile, with relative INNOVATION-DRIVEN GROWTH IN REGIONS:

This indicator is calculated typically with export data (Balassa 1965), but other economic indicators such as employment, Gross domestic product (GDP), number of

internationally comparable data is necessary on a relatively fine-grained classification level For countries, sufficiently detailed, internationally comparable economic data is available from OECD

www. oecd-ilibrary. org/industry. The OECD Statistics on Measuring Globalisation database, the OECD databases on Structural and Demographic Business Statistics and the OECD Structural Analysis Statistics

Benchmark data can be obtained by summing up sectoral data over all countries in these OECD database (or over a smaller group of

benchmark countries if desired. Also Eurostat publishes ample economic data on a sufficiently detailed sectoral level.

The limitation of Eurostat data compared to OECD data is that the benchmarking group pertains to the whole (or a selection) of European countries, making worldwide comparisons impossible

Unfortunately, on a regional level, it is difficult to find sufficiently detailed, internationally comparable economic data.

The most appropriate data appear to be OECD€ s regional labour market statistics (e g. number of establishments or number of employees per TL2 region),

which are available for a selection of countries and regions and are aggregated in 37 industries.

Due to limited data availability for some sectors in multiple regions and countries, only 32 industries can be used in comparative analyses.

limitation of these data is that not all industries represented. In a case a region would like to use other

indicators for its regional economic specialisation indicator, it can collect its own data and compare this to

this case, special care needs to be taken regarding data collection methodology in order to obtain internationally comparable statistics.

In Flanders for example, export data are calculated without quasi -transits, while OECD data include quasi-transits,

making international benchmarking difficult An example Figure 3 below shows the RCANS for an anonymous region in 32 industries according to OECD€ s

The data show a relative specialisation in Manufacture of Coke and Refined Petroleum Products, Manufacture of Chemicals and Chemical Products, and Manufacture of

publication and patent data can point to opportunities in technology development. In particular, the use of

patent data. These promising scientific and technological domains can and should then be discussed with economic actors in order to assess potential economic use and impact

Data on co-applications need to be interpreted with caution. The location (and hence the region or country) of the application can differ

In addition to publications, patents and economic performance indicators, other data are relevant for assessing a country†s or a region†s potential.

For example, sectoral data from the European Innovation Survey and R&d Survey can be used to construct relative specialisation indices

benchmark group. Unfortunately, it is very difficult to find reliable regional data on these topics. Most

regional innovation and R&d data does not contain sector specific information needed for the construction

For the mapping of human capital, educational data, such as the number of students enrolled in

However, this data should be rather detailed in order to provide insights in potential future specialisations or strengths.

economic development have been developed, regional internationally comparable data †especially on economic specialisations †is underdeveloped. In addition, a number of indicators for innovation and

•â€oeoften hard data give surprising results and are useful for policy-making†•â€oethere are no mechanisms to assess technological/economic SWOT on a regular basis, further

It includes performance data such as publications, critical size, collaborative projects etc. The Monitoring helps to â€oefine-tune†the

existing data or stakeholder action. Actually, the responses to the enquiry suggest that the approach followed puts much more weight on reinforcing existing strengths than on directing

and prospective data and analysis will be particularly important to mobilise The generic arguments for the necessity of good, robust and policy-oriented monitoring and

and licensing data. †41 Extract from Polish questionnaire: â€oethe Ministry of Economy does not want to prioritise sectors.

were used to solicit for relevant data. Collected data was presented and analysed using tables, bar charts and pie charts as extracted from Statistical Packages for Social sciences (SPSS). The

hypothesis test was conducted using the SPSS package. On the findings, innovation was found as one of the major attributes which aid SMES to remain competitive.

to asses the true nature of SME failure due to lack of accurate data on this phenomena.

Data was collected mainly using structured interviews and questionnaires and analysed using Statistical Packages for Social Studies (SPSS

bring opportunities for integrating data for journey planning and electronic ticketing, and smart cards to facilitate interoperability between public transport

has funded various projects on data collection monitoring and analysis of modal effects and ON ITS for integrated traffic management

transport data from all over Europe by means of common mechanisms, standard rules, and protocols. This easy to install

data on vehicles as well as an online calculator for lifetime costs of vehicles, as required by the

and integrate freight data in urban mobility statistics 22 INNOVATION IN URBAN MOBILITY-POLICY MAKING AND PLANNING

data were not fully available for each case. From 1980 to 1987, ANVAR changed its administrative

error due to the confidential nature of the data and the variance among participating firms (Dess & Robinson, 1983.

Annex 3. Statistical data...44 Figures Figure 1: main concepts explaining innovation...2 Figure 2:

Data is triangulated from three sources: semi-structured interviews, survey and secondary data Data collection was based on a detailed case study protocol.

I was supported by a research assistant for translation, transcription, administration and logistics. 42 semi-structured

interviews were conducted, comprising 27 firms, 3 experts, 11 major players of the local innovation system and one global buyer.

as the data received proved unreliable Innovation creates economic rents, especially relational and product rents. They can be

own data. Firms in Yogyakarta didn†t fit the bill, as subcontracting makes it hard to control

The analysis is based on qualitative data Capacity of non-firm actors and research incentives Interaction with non-firm actors plays a secondary role in innovation.

adjusted, but as a result the data on the bottom-end subcontractors must be treated with

and interpreting innovation data. Paris: OECD publications OECD 2006. Comnmunity Innovation Statistics. From today†s community innovation surveys to better surveys tomorrow

data collection IHS Working Paper 27.2013. Innovation in SMES. The case of home accessories in Yogyakarta, Indonesia 42

Annex 3. Statistical data Table 1: association of acquisition indicators (V-Cramer/significance Travel Language Access to

Annex 3. Statistical data

In the natural world there is n o w aste D etritu s fro m

Using data from Germany, BASF factored together energy costs and consumption, purchasing costs, and other environmental and

human genes, the status of the data bases built up in functional genomics and the scope of patent claims on

resources (health data, family histories blood samples, etc. legitimately be obtained? is informed consent of the

companies and stored in private data bases? Is it legitimate to reserve exclusive access to data bases for just

•With respect to gene sequence data there is a growing consensus that these data be disclosed and made

freely available to all scientists. Are there reasons to apply that policy to data bases in functional genomics

Empirical data suggests that small firms file for less patents abroad than do large firms (e g.

Cataloguing data can be found at the end of this publication Luxembourg: Publications Office of the European union, 2011

and travel data...pp. 8†12 Action area 2: Continuity of traffic and freight management ITS services

integration †by linking all sources of data to produce valuable information for transport users and operators

traffic and travel data Many ITS applications rely on an accurate knowledge of the road network and of traffic regulations like one-way streets

Optimal use of data will also facilitate multimodal journey planning pages 13†16 >Action area 2:

The handling of data †notably personal and financial †in ITS applications raises a number of issues as citizens†data

-protection rights are at stake. Data integrity and confidentiality must be ensured for all parties involved, especially citizens

The provision and use of ITS applications also create additional requirements in terms of liability. These issues could be a major

Given advances in data-collection technology and with growing demand for more precise and real-time information

the need for more †and better †data is increasing all the time. Yet differences between national policies on traveller

sectors as well as rules for cooperation on data exchange content and service provision >AIMS >make private, especially safety-related, traffic

-and travel-related data >promote public†private cooperation to improve traffic and travel information >increase data quality and improve multimodal

cooperation >encourage (cross-border) data exchange >TASKS AND ACHIE VEMENTS The European commission in 2011 completed a study on

traffic and travel data access, with a view to analysing the status quo in the EU and producing draft policy options

Specifications and procedures should be established for the use of public data; data availability, formats, exchange

and (cross-border) procedures; and legal issues (contracts agreements, licences, liability. Harmonisation should make it easier to develop Europe-wide traffic

and travel information services Definition of procedures for the provision of EU-wide real-time traffic and travel

•provision of traffic regulation data by the transport authorities •guaranteed access by public authorities to safety-related information collected

•guaranteed access by private companies to relevant public data DGMOVE brochure ITS A4 indd 8 11/05/11 15:

Accurate road data is needed for in-car navigation devices as well as for travel planners and all kinds of traffic-management

However, data shortcomings are restricting the ability of in-car systems to consider traffic-management plans

countries on the collection of road and traffic-regulation data have been uneven and often completely lacking.

and data formats for the collection of road data and traffic-regulation data in all EU Member States

>establish common minimum requirements and standards regarding the timely and coordinated updating of this data in all EU Member States

>establish common minimum requirements attributes and data formats for recommended routes, in particular for heavy goods vehicles

data for digital maps (Action 1. 3), the European commission will launch a study to analyse the status quo concerning road-data

collection and the provision and reuse of traffic circulation plans traffic regulations and recommended routes in the EU. Looking

road data. road data Optimisation of the collection and provision of road data and traffic circulation plans

traffic regulations and recommended routes (in particular for heavy goods vehicles Optimised collection and provision of road

traffic and travel data DGMOVE brochure ITS A4 indd 9 11/05/11 15: 15t105146 cee. pdf 11t105146 cee. pdf 11 20/06/11 13: 5020/06/11 13:50

The problem has been that the road data needed to produce them is not always available, accurate or

data for use in digital maps in the EU >define procedures for ensuring fair, simple and

transparent access to this road data for digital map providers >identify common minimum requirements regarding

road-data collection for digital maps, and of the technical and standardisation needs, is ongoing.

and existing or planned national and European spatial data infrastructures, the ongoing study will try to provide

designed to ensure timely data dissemination >>For further information on the topi ht p://ec. europ. eu/tran port/its/road

of availability of accurate public data forof availability of accurate public data forof availability of accurate public data for

Definition of procedures for ensuring the availability of accurate public data for digital maps and their timely updating through cooperation between the relevant public

Availability of accurate public data for digital maps DGMOVE brochure ITS A4 indd 10 11/05/11 15:

Definition of specifications for data and procedures for the free provision of minimum universal traffic information services (including definition of the repository of

>address issues of data availability, data sharing formats) and data quality >move from national systems to a true European

door-to-door information system and multimodal journey planner >TASKS AND ACHIE VEMENTS The ITS Directive foresees the development of functional

exchange of traffic data and information across borders, regions and urban/interurban interfaces enabling door-to-door and truly multimodal travel

data exchange for traffic management and travel information) specifications >finalise the adoption of required specifications for

and travel data exchangeand developed as a traffic and travel data exchange mechanism by a European task force set up to mechanism by a European task force set up to mechanism by a European task force set up to

confidentiality and secure handling of data, including personal and financial details, and show that citizens†rights are fully

of data in ITS applications and services and propose measures in full compliance with EU legislation

Cataloguing data can be found at the end of this publication Luxembourg: Publications Office of the European union, 2010

CCTV) security systems to more advanced applications integrating live data and feedback from aâ variety of information sources (e g. parking guidance, weather information

•Various forms of wireless communication for both short-range and long-range data exchange UHF, VHF, Wimax, GSM, etc

data (from devices such as radar, RFID readers, infrared-and visible-band cameras) and infrastructure-based data (from similar devices,

as well as inductive or pressure sensors installed or embedded in and around the road To meet the challenges of achieving virtually accident-free, clean and efficient mobility

and travel data •continuity of traffic and freight management ITS services in European transport corridors and

detailed GPS navigation and road/traffic data, including local roadworks. The in-vehicle technologies needed 3g telecom

computerised data, to enable vehicles to †understand†the environment around them. They facilitate control, accident

•Speed alert †using satellite navigation data to signal thatâ aâ vehicle is travelling too quickly when approaching

and growing range of available data sources and types, the impact of potential information overload on the primary task

Centralised processing of data on the natural and infrastructure conditions of aâ road network makes it possible to generate alerts,

be combined with data from moving vehicles to provide operators, maintenance authorities and road users with

real-time data to aâ central server, where it can be analysed byâ sophisticated prediction and decision-making models

†Closing the loop by using the vehicles themselves to send data back to traffic control centres

so that they can exchange data with roadside infrastructure, display information to the drivers (or passengers on public transport) and communicate

which the data can be managed, will greatly increase the quality and reliability of personalised information available to

The same data can also be used to extend the functionality of in-vehicle safety systems †for example, by constructing

and context-specific data, trusted travel assistants will be able to plan each journey and guide travellers throughout

accessibility, based on data provided via RTTI services Forâ passenger transport, the envisaged systems embrace all

-time data for pre-trip planning and on-the spot response to changing needs or conditions

data for individual bus stops or rail stations, so that DRT could be fully coordinated with the fixed line services †which

personalised data Existing systems for journey planning and route guidance tend to be limited to single forms of transport or even single

systems will integrate data from vehicles, to provide dynamic, predictive and adaptive control of traffic flows

data collection and information exchange via mushrooming social networking websites C H A p T E R 8

and transport data from various sources with an emphasis on quality, standardisation and cost-efficiency

s and the most recent data was released by the CSO on 19 february 2013. This survey examines R&d activities performed

s survey data is represented in the following charts by a perforated line If you require further information about this survey please contact

Where data for 2011 was unavailable the next closest year was used 0. 16 %0. 16 %0. 17

Comparing 2011 data from Figure 12 and 13 shows the occupations spending most of their time on R&d (as determined

In this section data gathered on the number of R&d-active companies and the levels of R&d

of doing business for a wide range of data providers, and restrictions on cloud provider

â€oeinternet of Things, †data analytics and big data, IT-powered robotics, intelligent agents mobile commerce, improved self-serve kiosks, 3d printing, location awareness, and

OECD data show that from 1985 to 2010, ICT capital contributed 0. 53 percentage points to the average annual GDP growth rate in the United states and 0. 56 percentage points in

Internet access and standardized data exchange with trading partners contributed to significant increases in labor productivity. 60 Similarly, Koellinger finds that firms in the EU

ICT investment shows up in survey data on ICT use as well. The 2013 and 2014 World

proposed data mining and data collection taxes, directed specifically at large internet companies such as Google and Facebook. 125 Higher taxes on ICT-producing companies

data collection would tax companies based on the number of users they collect data on apparently with no regard to the actual market value of the data

Another important channel through which tax policies influence investment is depreciation rates†the rates at which corporations can write off capital investments for tax purposes. 126

data providers This focus on the ICT-producing sector appears to be misplaced. Rohman finds that the

-border data flows) will be detrimental to the latter Yet, even if raising tariffs might lead to some offsetting production of the good or service in

usage, and data. They should allow companies to more rapidly depreciate ICT investments for tax purposes, including allowing firms to expense them in the first year

due to emerging â€oedata nationalism††the idea that data must be stored domestically in order to keep it secure.

Data nationalism is a â€oefalse promise†because it is unlikely to deliver the expected benefits of privacy and security,

down ICT-related growth. 182 Unfortunately, data nationalist policies are already a reality in some countries:

communication so that data never physically crosses the Atlantic. 184 By definition, the result of these kinds of policies will be to raise the costs of ICT services for firms in these

The responsible use of data can lead to productivity gains and innovation. However, overly stringent privacy rules limit the ability

-board. org/data/economydatabase/;/author calculations following Marcel P. Timmer et al. â€oeproductivity and Economic growth in Europe:

accessed April 2, 2014), http://www. conference-board. org/data/economydatabase /10. Ibid 11. Ibid 12.

Data unavailable for Croatia, Estonia, Latvia, and Slovenia 16. Ibid 17. Ibid. Data unavailable for Croatia, Estonia, Latvia and Slovenia;

Romania excluded because its extremely low initial productivity makes it an outlier 18. Robert D. Atkinson, â€oecompetitiveness, Innovation and Productivity:

-board. org/data/economydatabase/;/Timmer et al. â€oeproductivity and Economic growth in Europe. †Assuming 2. 8 percent productivity growth

Guidelines for Collecting and Interpreting Innovation Data (OECD 2005 29. Robert D. Atkinson, â€oecompetitiveness Innovation and Productivity:

http://www. worldklems. net/data/notes/jorgenson ho samuels. USPRODUCTIONACCOUNT. pdf 42. Ibid. 30; David M. Byrne, Stephen D. Oliner,

-Level Data on Developed and Developing Countries†(working paper, Center for Research on Information technology and Organizations, 2001;

Evidence from Firm-Level Data, †Electronic commerce Research 9, no. 3 (2009): 173-81 61.

-level evidence using data envelopment analysis and econometric estimations, †OECD Science, Technology and Industry Working papers, no. 2002/13 (September 2002), http://dx. doi. org/10.1787/101101136045

OECD, Country Statistical Profile 2012 (Investment Data and Shares of ICT Investment in Total Nonresidential GFCF;

2014), http://www. conference-board. org/data/economydatabase /85. National Science Foundation, Science and Engineering Indicators 2014 (Figure 6-7, ICT business and

Transmitting Data, Moving Commerce†(European Centre for International Political economy/U s Chamber of commerce, March 2013 https://www. uschamber. com/sites/default/files/legacy/reports/020508 economicimportance final revi

Data for the EU Member States, Iceland and Norway Luxembourg: European commission-eurostat, 2013 130. Lorin M. Hitt, D. J. Wu,

Daniel Castro, â€oethe False Promise of Data Nationalism†(Information technology and Innovation Foundation, December 2013), http://www2. itif. org/2013-false-promise-data-nationalism. pdf

183. See for example: â€oeprocessing of sensitive personal data in a cloud solution, †Datatilsynet, February 3 2011, http://www. datatilsynet. dk/english/processing-of-sensitive-personal data-in-a-cloud-solution/,and

David Jolly, â€oeeuropean Union Takes Steps Toward Protecting Data, †New york times, March 12, 2014 http://www. nytimes. com/2014/03/13/business/international/european-union-takes-steps-toward

-protecting-data. html 187. David Streitfeld, â€oeeuropean Court Lets Users Erase Records on Web, †New york times, May 13, 2014

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