He may use retrospective data, but these bring little certainty since nobody is using them the way he suggests.
The authors are entirely responsible for the facts and accuracy of the data presented. 1 Foreword:
Project fact-sheets drafted with data based on interviews and desk research (one per project analysed) Telephone interviews with project lead partners
in particular, through analytical studies and EU-wide data and statistics. The overall objective of the programme is to foster a business-friendly environment for SMES with a view to ensuring
and represent the demand for data to support policy development. Therefore, these projects are not about GPS,
but about data and case studies. Specific knowledge available from ESPON can help managing authorities including regional authorities to improve their policies.
INTERREG IVC project partners could include these data when defining their work programme, identifying GPS and analysing their conditions of transferability.
These three networking programme have a wealth of data relevant to regional policy improvement, especially for URBACT II and ESPON;
A capitalisation tool allowing easy access to these data would be beneficial to the future INTERREG EUROPE project partners.
and personnel to provide professional advice could include data from these networks. Another way to improve synergies would be for the programme to require a benchmark analysis of the GPS that exist
including those based on massive volumes of data or processing, to SMES with limited resources. 73 DISTRICT+focus on‘transfer of good practices and policies improved'65 Main conclusions and recommendations:
The statistical data for Israel are supplied by and under the responsibility of the relevant Israeli authorities.
The use of such data by the OECD is without prejudice to the status of the Golan heights, East Jerusalem and Israeli settlements in the West bank under the terms of international law.
48 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 discovery process.
OECD-TIP enquiry in governance for smart specialisation Designing a specialisation strategy at the regional level requires an intelligent use of data
another important element is the use 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 potential of emerging activities
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.
Interesting insights can also result from studying relations between scientific, technological and economic specialisations, which can be mapped using conversion tables (see for example Callaert et al.,
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 underlying fields,
ECOOM-Centre for Research & development Monitoring at Leuven University 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 attention in the future.
For example, the ongoing OECD work on global value chains is building national 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
'In addition to quantitative data, diagnostic tools can be particularly useful to identify these promising‘activities'not captured by existing empirical material
During the last 15 years the so-called SFINNO project has identified nearly 5 000 innovations and collected data on them.
Data and indicators to measure specialisation in science technology and employment may help policy-makers in diagnosing apparent strengths,
prospective data and analysis. Selecting and engaging key actors, necessary for their expertise and knowledge, is an increasingly difficult task due to the cross-border, multi-disciplinary and cross-sectoral dimensions of emerging activities.
It includes performance data such as publications, critical size, collaborative projects etc. The Monitoring helps to fine-tune the Strategy...
Collection of data is undertaken based on a random sample of approximately 9 000 businesses. The sample was stratified by industry and an employment-based size indicator.
Data from the survey is used to monitor trends in farm innovation, evaluate impacts on agricultural productivity
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 broader skills
Metrics are evaluated currently against qualitative data gathered from interactions with industry and by gauging community
Qualitative data, in the form of real life success stories help demonstrate to SMES, the value of networks, like SEMIP in supporting regional specialisation.
Data from the Australian Bureau of Statistics demonstrates the concentration of advanced manufacturing and high tech firms in the region:
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 mid-1990s.
Impact of data and diagnostic tools: Lower Austria made positive learning experiences with the establishment of these tools among others,
Tekes Empirical data-on how to articulate regional choices in terms of the national strategy-were collected in a series of 18 regional workshops,
During the last 15 years the so-called SFINNO project has identified nearly 5 000 innovations and collected data on them.
iii) Malopolska Social policy Observatory which monitors and collects the data from the area of social policy;
This type of tools is mostly based on data from the past and present. The analysis can be used by policy makers as the evidence base to support certain domains or clusters.
While the participating policy makers were provided with this data-set for the OECD exercise, it is too early to comment on how it is used by them.
THE ROLE OF SMART SPECIALISATION OECD 2013 147 Evaluation and monitoring While good progress has been made to collect data
The current state of the art for baseline data profiling for policy prioritisation is developed much more than that for ongoing monitoring.
THE ROLE OF SMART SPECIALISATION 152 OECD 2013 Observing and measuring smart specialisation Data and indicators about smart specialisation are necessary to make those processes
Without metrics, indicators and regular data collections, smart specialisation strategic opportunities will not be discernible and policy makers will be unable to track progress,
Databases One of the most accepted and widely used data sources for the analysis of scientific specialisations is the Science Citation Index Expanded (SCIE
and data handling by Thomson Reuters, the multidisciplinarity of the database, its selectivity based on quantitative criteria, the completeness of the INNOVATION-DRIVEN GROWTH IN REGIONS:
THE ROLE OF SMART SPECIALISATION OECD 2013 155 address information for all authors, the inclusion of all references and the electronic availability make it one of the most appropriate data sources for bibliometric analyses.
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 region vis-à-vis the specialisations of the world's scientific activities.
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 given even more cumbersome 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 underlying subject classification system,
The data indicate that the country has a persistent relative specialisation in geosciences and space sciences (G), mathematics (H),
Further analysis of publication data for this country can shed more light on these dynamics.
Baseline indicators for technological specialisations Indicators The most widely used indicators for technological activities make use of patent data.
THE ROLE OF SMART SPECIALISATION OECD 2013 157 Box 3. 1. Advantages and limitations of patent data as a proxy indicator for technological innovation The advantages of patent data
The statistical processing of data is largely free of errors, because patent documents are legal documents in
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 applications;
Technology fields differ in their propensity to patent; Countries differ in their propensity to patent:
and a negative value representing a relative disadvantage compared to the average country or region in the benchmark group. Just as with publication data,
one needs to be careful in interpreting low count data. Regions with very low patent numbers may be specialized relatively in a specific technology domain.
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. In the USPTO system e g.,
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,
one can use EPO patent data to compare the specialisation profile of Sweden with that of all Scandinavian countries,
It should be noted that the regionalization of patent data, based on inventor and applicant addresses, is not available in patent databases.
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 newly established firms,
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 database contain many different sector-specific
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.
A 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 worldwide indicators (e g. the sum of nationally available statistics over all OECD countries).
However, in 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 regional labour market statistics.
The data show a relative specialisation in Manufacture of Coke and Refined Petroleum Products, Manufacture of Chemicals and Chemical Products,
more advanced analyses of publication and patent data can point to opportunities in technology development.
Similar approaches can be envisaged for the detection of promising new technological domains using patent data.
Data on co-applications need to be interpreted with caution. The location (and hence the region or country) of the application can differ from the location of the invention
Mapping the broader picture 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,
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 of specialisation profiles.
For the mapping of human capital educational data, such as the number of students enrolled in different educational programs could be of relevance.
However, this data should be rather detailed in order to provide insights in potential future specialisations or strengths.
For example, it does not seem enough to know the number of engineering students in a country or region without knowing their specific field of study.
regional internationally comparable data especially on economic specialisations is underdeveloped. In addition, a number of indicators for innovation and research and development commitments, complementary investments in related industries and early stage market transactions,
and licensing data, report for the European commission, Brussels. Schmoch, U. 2008), Concept of a Technology Classification for Country Comparisons, final report to the World Intellectual Property Organisation (WIPO), http://www. wipo
Often hard data give surprising results and are useful for policy-making; There are no mechanisms to assess technological/economic SWOT on a regular basis,
It includes performance data such as publications, critical size, collaborative projects etc. The Monitoring helps to fine-tune the Strategy...
and captured by 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 efforts towards future opportunities through instilling more radical trajectory changes.
and prospective data and analysis will be particularly important to mobilise. The generic arguments for the necessity of good
and licensing data. 41 Extract from Polish questionnaire: The Ministry of Economy does not want to prioritise sectors.
Questionnaires and interviews 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.
although it remains difficult 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). 4. 0 Results
New technologies also bring opportunities for integrating data for journey planning and electronic ticketing, and smart cards to facilitate interoperability between public transport modes.
The EU has funded various projects on data collection monitoring and analysis of modal effects, and ON ITS for integrated traffic management and multimodal information.
and authorities access to public transport data from all over Europe by means of common mechanisms, standard rules, and protocols.
The portal uses Europe's largest vehicle database and provides energy consumption and emission data on vehicles as well as an online calculator for lifetime costs of vehicles, as required by the Directive 2009/33/EC.
and integrate freight data in urban mobility statistics. 22 Innovation in urban mobilit y-polic y making
because data were not fully available for each case. From 1980 to 1987, ANVAR changed its administrative forms.
and represent a major source of measurement error due to the confidential nature of the data and the variance among participating firms (Dess & Robinson, 1983).
Using data from Germany, BASF factored together energy costs and consumption, purchasing costs, and other environmental and economic factors to develop guidelines on
How can access to human genetic resources (health data, family histories, blood samples, etc. legitimately be obtained?
With respect to gene sequence data, there is a growing consensus that these data be disclosed and made freely available to all scientists.
42 Annex 3. Statistical data...44 Figures Figure 1: main concepts explaining innovation...2figure 2:
Sampling 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 endogenous or exogenous (Kaplinsky and Morris 2000.
IKEA 2008,2010, own data. Firms in Yogyakarta didn't fit the bill, as subcontracting makes it hard to control standards,
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.
but as a result the data on the bottom-end subcontractors must be treated with caution.
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 2:
The case of home accessories in Yogyakarta, Indonesia 44 Annex 3. Statistical data Table 1:
Intelligent Transport Systems in action ACTION PLAN AND LEGAL FRAMEWORK FOR THE DEPLOYMENT OF INTELLIGENT TRANSPORT SYSTEMS (ITS) IN EUROPE Cataloguing data can be found at the end of this publication.
and travel data...pp. 8 12 Action area 2: Continuity of traffic and freight management ITS services on European transport corridors and in conurbations...
obstacles or modal integration by linking all sources of data to produce valuable information for transport users and operators.
and travel data Many ITS applications rely on an accurate knowledge of the road network and of traffic regulations like one-way streets and speed limits.
Optimal use of data will also facilitate multimodal journey planning. pages 13 16>Action area 2:
and liability issues The handling of data notably personal and financial in ITS applications raises a number of issues as citizens'dataprotection 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.
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.
A key issue is to define the roles of the public and private sectors as well as rules for cooperation on data exchange
traffic information available to public authorities>ensure fair and transparent access to public trafficand 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 ACHIEVEMENTS 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.
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 information services, addressing notably the following aspects:
provision of traffic information services by the private sector provision of traffic regulation data by the transport authorities guaranteed access by public authorities to safety-related information collected by private companies
guaranteed access by private companies to relevant public data 39>AC T ION 1. 2>A c T I O N 1. 2 I N t
I O N>THE CHALLENGE Accurate road data is needed for in-car navigation devices as well as for travel planners and all kinds of traffic-management applications.
data shortcomings are restricting the ability of in-car systems to consider traffic-management plans
Rules in EU countries on the collection of road and traffic-regulation data have been uneven and often completely lacking.
attributes 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>TASKS
AND ACHIEVEMENTS Building on the results of the actions on real-time traffic and travel information (Action 1. 1) and on the availability of accurate public 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,
>>Today many EU Member States have no nationally binding rules, procedures or format or updating of traffic management-related specifications regarding the provision, quality, 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 1 30 I N t E L L I G E N t t R A n s P O R T s Y S T E
The problem has been that the road data needed to produce them is not always available, accurate or reliable, with a lack of rules for timely updates.
>identify common minimum requirements of road 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 the timely updating of digital maps by digital map providers>TASKS AND ACHIEVEMENTS
A detailed assessment of the state-of-the-art concerning 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 orientation (s) regarding how a future system could be designed to ensure timely data dissemination.>>
>>For further information on the topi ht p://ec. europ. eu/tran port/its/road/topic of availability of accurate public data for digital maps:
http://europa. transport/action plan/public data en. htm Definition of procedures for ensuring the availability of accurate public data for digital maps
and their timely updating through cooperation between the relevant public bodies and digital map providers,
taking into account the results and recommendations of the esafety Digital Maps Working group Availability of accurate public data for digital maps 1 31 I N t E L L I G
Definition of specifications for data and procedures for the free provision of minimum universal traffic information services (including definition of the repository of messages to be provided) Traffic safety information services 1 32
or improved national journey planners in such a way that they can be connected>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 ACHIEVEMENTS The ITS Directive foresees the development of functional, technical,
and facilitate the electronic exchange of traffic data and information across borders, regions and urban/interurban interfaces enabling door-to-door
and DATEX II (data exchange for traffic management and travel information) specifications>finalise the adoption of required specifications for I2i,
and travel data exchange mechanism by a European task force set up to standardise between traffic control and information centres.
confidentiality and secure handling of data, including personal and financial details, and show that citizens'rights are protected fully.>
and personal data protection aspects related to the handling of data in ITS applications and services and propose measures in full compliance with EU legislation Data security
More information on the European union is available on the Internet (http://europa. eu). Cataloguing data can be found at the end of this publication.
from monitoring applications such as closed-circuit television (CCTV) security systems to more advanced applications integrating live data and feedback from a 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.;
Sensing technology employing sensors to feed control systems with both vehicle-based data (from devices such as radar, RFID readers, infrared-and visible-band cameras) and infrastructure-based data
and travel data; continuity of traffic and freight management ITS services in European transport corridors and conurbations;
and road/traffic data, including local roadworks. The in-vehicle technologies needed 3g telecommunications for the accuracy and speed of delivery to make services usable and useful
/2001 31/05/2004 Website http://www. transport-research. info/web/projects/Otherwise collectively described as Advanced Driver Assistance Systems (ADAS), these typically employ onboard sensors, together with digital maps and other computerised data,
Speed alert using satellite navigation data to signal that a vehicle is travelling too quickly when approaching a limited-speed road section.
'Improved human-machine interface It became apparent from an early stage that, given the large and growing range of available data sources and types,
Centralised processing of data on the natural and infrastructure conditions of a road network makes it possible to generate alerts,
and bridges can be combined with data from moving vehicles to provide operators, maintenance authorities and road users with rapid warning of emerging problems.
and transmits real-time data to a central server, where it can be analysed by sophisticated prediction and decision-making models.
‘Closing the loop by using the vehicles themselves to send data back to traffic control centres will bring great improvements in the efficiency of management and the safety of road users,
For interurban networks and secondary roads, greater reliance on in-car systems to provide‘floating car data,
so that they can exchange data with roadside infrastructure, display information to the drivers (or passengers on public transport) and communicate wirelessly with other vehicles and the infrastructure.
and the coordinated manner in which the data can be managed, will greatly increase the quality and reliability of personalised information available to drivers about their immediate environment and impending situations.
The same data can also be used to extend the functionality of in-vehicle safety systems for example,
Using real-time and context-specific data, trusted travel assistants will be able to plan each journey
based on data provided via RTTI services. For passenger transport, the envisaged systems embrace all types of mobility available to users buses, taxis, train, metro, walking, cycling, etc.
With increasing demand, especially in urban areas, it becomes more and more crucial to have ready access to accurate realtime data for pre-trip planning and on-the spot response to changing needs or conditions.
With the aid of cooperative systems, journey planners could ultimately provide real-time schedule data for individual bus stops or rail stations,
/2008 30/11/2010 Website www. access-to-all. eu WISETRIP Wide scale network of e-systems for multimodal journey planning and delivery of trip intelligent personalised data.
New generations of traffic management 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 Conclusions and the way forward I N t E L L
and transport data from various sources, with an emphasis on quality, standardisation and cost-efficiency;
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