Composite Indicators of Research Excellence

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of the fully fledged composite indicator on research excellence The pillars in this framework explain a greater share of variance in the data and each variable contributes to pillar scores in a more balanced way than in Framework 1 At the same time the contribution of each pillar to the composite index is intrinsically more balanced

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European Commission,Joint Research Centre, Institute for the Protection and Security of the Citizen. Contact information,Forename Surname, Address Joint Research Centre Via Enrico Fermi 2749 TP 361 21027 Ispra VA Italy. E mail stefano tarantola jrc ec europa eu,Tel 39 0332 78 9928. Fax 39 0332 78 5733,http ipsc jrc ec europa eu,http www jrc ec europa eu. Legal Notice, Neither the European Commission nor any person acting on behalf of the Commission.
is responsible for the use which might be made of this publication. Europe Direct is a service to help you find answers to your questions about the European Union. Freephone number 00 800 6 7 8 9 10 11, Certain mobile telephone operators do not allow access to 00 800 numbers or these calls may be billed. A great deal of additional information on the European Union is available on the Internet. It can be accessed through the Europa server http europa eu. EUR 25488 EN,ISBN 978 92 79 26260 9,ISSN 1831 9424. doi 10 2788 45492, Luxembourg Publications Office of the European Union 2012. European Union 2012, Reproduction is authorised provided the source is acknowledged. Printed in Italy,EXECUTIVE SUMMARY, This report on Research Excellence is the deliverable of the third work package WP3 of the.
feasibility study ERA MONITORING financed by DG RTD The objective of the work. package was to explore the possibility to develop a composite indicator of research. excellence in Europe in coherence with the orientations of the EU 2020 strategy and the. Innovation Union initiative, The study built on the theoretical framework proposed by the 2011 report of the Expert. Group on the Measurement of Innovation Indicators of Research Excellence co authored. by R mi Barr CNAM France Hugo Hollanders UNU MERIT The Netherlands and. Ammon Salter Imperial College UK from now on identified as the Expert Group report. The report identified a scoreboard of indicators to describe research excellence in the. context of a research and innovation system The proposed indicators characterize. knowledge production as well as the institutional arrangements and interactions through. which research activities take place and refer to basic research actors industrial. innovation actors and societal and political actors. We considered the quality profile of 22 indicators for 41 countries and performed multivariate. analyses We concluded that 16 indicators can be used for aggregation into a composite. indicator some only after the treatment of outliers and imputation of missing values We also. found that the indicators could be computed for all EU Member States most EFTA countries. Candidate countries and the main international competitors of the European Union United. States Japan and China However given that some indicators are meaningless for non. ERA countries we concluded that modified setups would be required for global country. comparisons, We proposed three alternative conceptual frameworks of research excellence with different. underlying indicator structures and tested their statistical coherence In the first theoretical. framework we aimed to follow as closely as possible the Expert Group recommendation of 6. dimensions In the second framework we tried to consider only two dimensions basic and. applied science also based on the Expert Group report The third framework was derived. from the data and three dimensions were identified directly from a principal component. First we tested the 6 dimensional conceptual framework originally proposed by the expert. group Framework 1 The multivariate statistical analysis suggested that the framework only. partially holds We decided to remove some indicators from each dimension so that this. better expresses a distinct aspect of research excellence We identified four dimensions. given the no data were available on indicators of societal relevance which consisted of a. total of 13 indicators In sum we found that, dimension 1a would obtain greater statistical coherence if it were narrowed down to. include only five indicators Publications 1a1 Share of highly cited publications. 1a2 Share of 250 top scientific Universities 1a4 Share of ERC grants 1a5 and. Specialisation in Grand Societal Challenges publications 1a9 as defined in section. dimension 1b is a statistically coherent pillar composed by 4 indicators as long as. indicator Share of international co publications 1b1 is replaced by another. International Collaboration Index 1b1 collind, dimension 2a needs to be reduced to three indicators Patent applications by the. public sector 2a1 Patent applications by industry 2a4 and Patenting in Key. Enabling Technologies 2a8 for a statistically coherent pillar. dimension 2b could only be represented by indicator Public private co publications. 2b1 given the negative correlation between the only two indicators available. We found that the dimensions were populated by different numbers of indicators each pillar. captured one single latent dimension that explained at least 55 of variance in the data In. addition the factors loadings for pillar 2a were rather unbalanced. Second we tested the two dimensional framework distinguishing basic and applied research. Framework 2 The multivariate analysis showed that basic research can only be captured. in three distinct conceptually heterogeneous dimensions while the applied research pillar. is relatively sound and consists of three indicators 2a1 2a4 and 2b1 In summary this. second framework was found weak because of the existence of three basic research. pillars for which the statistical profile was not matched with any theoretical underpinning. Thirdly aiming to achieve a framework which is both statistically sound and rich in indicators. we analysed by principal components the whole set of 22 indicators starting from Framework. 1 and testing alternative specifications In this third attempt we considered a modified. indicator 2b3 gdp to measure financial flows from business to public research In. Framework 3 we found three coherent and statistically sound pillars. 1 excellence of public research 6 indicators,2 interactions collaborations 4 indicators.
3 excellence in industrial actors 3 indicators, The framework was found to accommodate 13 indicators similarly to Framework 1 with. each pillar capturing one single latent dimension which explains at least 63 of variance in. the data The factors loadings were overall rather balanced. Composite indicators were computed for each of the three frameworks using geometric. aggregation across pillars Each pillar was an arithmetic average of its indicators normalized. between 0 and 100 using the min max method and taking into consideration the two years. simultaneously Initially the geometric aggregation was computed using equal weights. which were adjusted in light of the global sensitivity analysis results carried out at the pillar. level This improved the balance between the pillars in all three cases. For Framework 1 the composite indicator shows a clear North West vs South East divide. with centers of excellence in the Nordic and North Sea countries Almost all countries have. improved their excellence between 2005 and 2009 The considerable spread of scores at the. pillar level provides useful insights to research excellence performance high and low scores. are detected for pillars 1b and 2b respectively, For Framework 2 the pillars of the resulting composite indicator do not contribute equally to. the overall composite indicator A re adjustment of weights could improve the framework. imbalances but leaves the conceptual difficulties of the theoretical framework unresolved. According to Framework 3 three countries are clearly distinguished as the leaders in. research excellence Switzerland Israel and the Netherlands all with a score of 70 or above. They are followed by countries of North Western Europe with scores exceeding the EU27. score and Southern and Eastern member states and Associate Countries below the EU27. score Of the countries with the largest population United Kingdom and Germany are neck. and neck ahead of France and Italy Three countries trail the list with single digit scores. Romania Lithuania and Turkey, The scores resulting from the frameworks with adjusted weights are shown in Figure 1 for. 2009 Frameworks 1 and 3 are closely correlated Pearson correlation coefficient 0 97. while Framework 2 scores show greater variance,80 Framework 1. 70 Framework 2,60 Framework 3, Figure 1 Research excellence composite scores comparison of 3 conceptual frameworks.
adjusted weights 2009, We tested the composite indicator of Framework 3 against other established composite. indicators of the research and innovation system We found that the research excellence. composite scores correlate strongly with the Innovation Union Scoreboard 2011 s Summary. Innovation Index Comparing the scores with GERD figures we also found that composite. score changes over time of around 20 30 are associated with R D investments of at least. 1 5 of GDP, Our final recommendation is to consider Framework 3 as the basis for the development. of the fully fledged composite indicator on research excellence The pillars in this framework. explain a greater share of variance in the data and each variable contributes to pillar scores. in a more balanced way than in Framework 1 At the same time the contribution of each. pillar to the composite index is intrinsically more balanced. Introduction and Objectives, The EU2020 strategy contains a blueprint for transforming Europe into an Innovation Union. by 2020 The Innovation Union flagship initiative COM 2010 546 final October 6th 2010. commits the EU to boosting investment in research and making Europe an attractive place to. develop innovative products Consequently national governments will have to reform their. innovation systems to boost cooperation between industry and universities ensure a. modernization of framework conditions for enterprises and a number of other measures to. enhance cross border cooperation and to embrace joint programming All these innovation. aspects need to be carefully monitored by policy makers in the European institutions and. Member states, This feasibility study entitled ERA monitoring focuses on monitoring the progress of. Europe towards the completion of the European Research Area ERA towards the. structural change of national and supra national innovation systems and towards the. modernization of higher education institutions, The project addresses the feasibility to develop three conceptual frameworks organised in.
three work packages WPs and the potential to further aggregate the underlying. components into composite indicators to measure, progress in the construction and integration of a European Research Area ERA to. monitor the overall performance of the Science and Technology system. structural change to monitor the increase towards a more knowledge intensive. economy in Europe coherently with the orientations of the EU 2020 strategy and the. Innovation Union initiative, research excellence in Europe meaning the effects of European and National. policies on the modernization of research institutions the vitality of the research. environment and the quality of research outputs in both basic and applied research. The present deliverable represents the outcome of WP 3 of the project. The objective of this work package is to test the feasibility to develop a composite indicator. to measure the excellence of the research systems of all EU Member States most EFTA. countries Candidate countries and the main international competitors of the European Union. United States Japan and China The aim of the study is to propose alternative conceptual. frameworks of research excellence and to test their statistical coherence in order to identify. feasible composite indicators, In this WP as well as in WP1 and WP2 the steps mentioned in the OECD JRC Handbook1. have been followed, step1 Development of theoretical frameworks for the measurement of research excellence. The proposed frameworks were derived by the report entitled Indicators of Research. Excellence co authored by R mi Barr Hugo Hollanders and Ammon Salter of the. Expert Group from now on identified as the Expert Group on the Measurement of. Innovation finalized on 8 Oct 2011, The first theoretical framework consisting of 6 dimensions was proposed by the.
Expert Group The relevant data sources were collected at country level and for as. many years as possible for all EU27 Member States most EFTA countries. Candidate countries and the main international competitors of the European Union. United States Japan and China Another framework consisting of two dimensions. basic and applied science was extracted from the Expert Group report and tested. Finally an alternative framework in which the indicators were combined according to. three dimensions deriving from a principal component analysis was proposed and. step2 Multivariate statistical tools have been used to assess the suitability of the data set. and to ease the understanding of the implications of the methodological choices e g. weighting and aggregation during the construction phase of the composite indicator. Statistical analysis has been used for imputing missing data detecting outliers and. to suggest suitable transformations of indicators due to skewness or kurtosis. Principal components analysis has been used to verify whether the structure of the. underlying data is consistent with the proposed conceptual framework and therefore. is appropriate to describe the phenomenon Note that principal component analysis. has not been used as a weighting method, step3 Construction of composite indicators The composite indicator has been calculated. by considering geometric aggregations of the pillars using both equal and adjusted. weights The composite scores for each pillar have been calculated by taking the. arithmetic averages of the underlying indicators, step4 Sensitivity analysis was conducted to appreciate the relative importance of the pillars. on the overall composite The results show how balanced the composite structure is. Nardo M Saisana M Saltelli A Tarantola S Hoffman A Giovannini E 2008 Handbook on constructing. composite indicators methodology and user guide OECD publishing. http www oecdbookshop org oecd display asp CID LANG en SF1 DI ST1 5KZN79PVDJ5J. in its components and suggest the adoption of adjusted weights in case the degree of. balance has to be increased, Theoretical Framework proposed by the Expert Group. The main aim of the Expert Group Report was to recommend a short list of indicators and a. method of assessment to describe the progress to excellence of European research In an. initial step the Report interprets the measurement of excellence at the country level. According to the Report three stages of extension translate excellent pieces of research. validated by the peer review process to research excellence measured at the country level. First having a sufficient number of scientific articles and research projects that are. considered excellent define an excellent researcher Second research units laboratories. university departments and even research institutes or universities are considered as. excellent by a sufficient proportion of excellent researchers Third regions and countries. are excellent if a sufficient proportion of their research institutes and universities are. considered excellent, Why and how does research excellence matter The main reason as stated in the Report. for governments to be concerned about research excellence and a better functioning. national research and innovation system is the need to maximize efficiency when allocating. resources to research organizations through various schemes Three contexts of. engagement are identified, research engagement with actors in the academic context with issues of scientific.
relevance and scientific quality, innovation engagement with actors in a socio economic context with issues of socio. economic relevance in particular related to firms or how efficiently to convert R D. investment into value and, society engagement with the citizens the general public stakeholders and. concerned groups as well as the political and public authorities through issues of public. policies quality of life sustainability with attention to issues of risks and ethics in the. political context defining political relevance, In each of these three contexts the production of knowledge as well as the institutional. arrangements and interaction schemes in which knowledge activities take place matter for. excellence The reason for focusing not only on the end result of knowledge production but. also on the mechanisms through which knowledge is produced is the time lag between the. activity and the impact, In addition to measuring the existence and size of excellent research activities further. measures of excellence include impact openness and attractiveness of the research and. innovation system Impact is more closely associated with knowledge production while. openness and attractiveness are more closely associated with institutional arrangements. and interaction schemes, The Expert Group Report concludes that the measurement of research excellence should.
consider six types of activities or dimensions which are presented in a matrix in Table 1. taken over from the Report The issues at stake are both the excellence of each dimension. as well as the balance of the portfolio, As words of caution the Report points out that excellence should not be seen as an absolute. term and that one need to appreciate the various dimensions and their relative weights in. context It also points out potential problems with taking into consideration sectoral and. disciplinary diversity and life cycle dynamics of research actors. Table 1 Research Excellence Dimensions of Analysis. Issues Impact Openness attractiveness,Institutional arrangements. Context of engagement Knowledge production,interaction schemes. 1a Coordination networks, Research actors Production of generic knowledge Collaborative schemes infrastructures. Scientific publications instruments open to the scientific. 2a Industrial and professional partnerships, Industrial innovation Knowledge and expertise and collaborative schemes in particular.
actors orientated towards industrial in the context of clusters. innovation Public research industry linkages,consulting. Knowledge and expertise 3b,Societal and political, orientated towards societal Civil society and public policies. concerns and policy regulations partnerships and collaborative schemes. S T diffusion and culture,Source Expert Group Report Table 1 p 7. Potential indicators and data treatment, Table 1 reports the indicators proposed by the Expert Group which are robust and currently. available Table 8 of the EG Report As it can be noted no indicators are currently available. for the societal dimensions 3a and 3b, Table 1 available and reliable indicators proposed by the Expert Group for the assessment of.
research excellence, 1a Engagement with research actors Knowledge production impact. 1a1 Publications per 1000 researchers in public research. 1a2 of Highly cited publications publications,1a3 Average of relative citations ARC. 1a5 EU ERC and or Marie Curie grantees EU public RD spending HERD GOVERD. 1a9 Specialisation in publications in the fields of the Grand societal challenges. 1a10 Specialisation in publications in the fields of the Key enabling technologies KETs. 1b Engagement with research actors Institutional arrangements. interaction schemes openness attractiveness,1b2 Collaboration index with emerging countries. 1b5 Foreigners in doctoral programmes, 1b7 EU Coordination position in FP projects EU participation in FP projects. 2a Engagement with industrial innovation actors,Knowledge production impact.
2a1 Patent applications by HEIs PROs per 1000 researchers. 2a7 Specialisation in patenting in the fields of Grand social challenges. 2a8 Specialisation in patenting in the Key enabling technologies KETs. 2b Engagement with industrial innovation actors, Institutional arrangements interaction schemes openness attractiveness. 2b1 Public private co publications per million population. 2b3 national HERD GOVERD financed by business RD financed by business. 2b4 national of industry funded HEIs PROs budget, 3a Engagement with societal and political actors Knowledge production impact. 3b Engagement with societal and political actors Institutional arrangements. interaction schemes openness attractiveness, Table 7 of the Expert Group report provides additional available indicators with some. problems of reliability robustness and comparability We could collect reliable data for 7. indicators These are listed in Table 2 using the language of the Expert Group report. Table 2 Additional available indicators with some problems of reliability robustness and. comparability proposed by the Expert Group, 1a4 EU 250 top scientific universities EU public RD spending HERD GOVERD. 1a6 EU ERC and or Marie Curies grantees EU of HE researchers government RD. personnel in FTE,1a7 women among researchers,1a8 EU Scientific prizes EU HEI PRO spending.
1b1 International collaborations index, 2a3 national innovative firms that use HEIs PROs as a source for their knowledge for innovation. 2a4 Patent applications by industry per 1000 researchers and or relative to BERD. List of indicators used, We have collected data for the indicators provided in Tables 1 and 2 and for some additional. indicators which are not in these lists The 22 indicators used in this WP are defined below. some of which may not coincide with the indicators proposed by the Expert Group because. of data availability, Note that indicators 1a5 1a6 1b7 and 2a3 defined below were not meaningful beyond the. ERA e g research institutes in the US or Japan are not receiving ERC grants These. indicators could therefore not be considered for any global comparison. 1a1 Publications per 1000 researchers, Definition Total number of publications by country divided by 1000 researchers. In the EG Report the denominator is defined as 1000 researchers in public research. However since the set of publications in the numerator covers all publications including. those with authors in the private sector the denominator was adjusted to similarly cover all. sectors for consistency reasons,Sources and notes, Numerator Science Metrix Scopus data on the total number of publications by country full.
counting method based on Scopus 2011 bibliometric data due to incomplete coverage for. 2009 2008 figures shown as latest year available, Denominator Eurostat OECD and UNESCO data on R D personnel and researchers by. sectors of performance Occupation based definition applied figures in full time equivalents. FTEs Data extrapolated for missing years for GR FI HR US and interpolated for CH. 2005 and 2008 values used, 1a2 Highly cited publications as a share of total publications. Definition Total number of publications within the top 10 most cited publications as a. share of all publications by country, Sources and notes Science Metrix based on Scopus data computation using Relative. Citation indices see explanation for indicator 1a3 below full counting method applied co. authored publications shown for each author s country Since a 4 year citation window was. applied reference year 3 years 2007 was the latest reference year available. 1a3 Average of relative citations ARC, Definition Relative citation indices are computed by dividing the citation count of a. publication by the average citation count of all publications of the corresponding document. type reviews benchmarked against reviews articles against articles published in the same. year in the same scientific subfield The ARC is obtained by computing the average of such. type and field normalized citation scores A value above 1 indicates that an entity is cited. more frequently than the world average, Sources and notes Science Metrix based on Scopus data computation a citation window.
includes the three years following the year of publication i e 2005 scores cover the period. of 2005 2008 however 2007 scores refer only to a window of 2007 2009 due to the. incompleteness of reference year 2010 at the time of the analysis. 1a4 Share in Top 250 scientific universities public R D spending HERD GOVERD. Definition Number of universities in a country included in the list of the world s top 250. universities based on scientific impact divided by public R D spending of the higher. education and government research institutes,Sources and notes. Numerator The Leiden Ranking CWTS Leiden University ranking for 2008 and 2010. based on CWTS computations of size independent and field normalized average impact In. order to measure global excellence and to be able to benchmark against non European. countries world top 250 ranking was used, Denominator Eurostat and OECD data on Total intramural R D expenditure GERD by. sectors of performance and source of funds HERD GOVERD calculated using constant. 2000 PPPs IL 2009 values extrapolated Previous year s figures were used i e 2007 and. 2009 in the numerator, Note that the indicator does not take into account the position in the top 250 which was not. seen as a problem as it would refer to less than the top 10 universities a recent EUMIDA. study2 identified some 2500 higher education institutes in Europe alone. 1a5 Amount of ERC grants received by country public RD spending HERD. Definition The total amount of European Research Council ERC grants by country of host. organization spread over duration of project divided by HERD GOVERD. Sources and notes, Numerator DG RTD data on ERC grants retrieved 18 May 2011 The total amount of ERC. grant funding received by the country of the host organization spread equally over a. project s years of duration Includes both starting grants and advanced grants first year. available is 2008 I e 1 million EUR grant responding to a call in 2007 for a project starting. in 2008 and ending in 2011 will be counted as 250 thousand EUR for the years 2008 2009. 2010 and 2011, Denominator Eurostat and OECD Total intramural R D expenditure GERD by sectors of.
performance and source of funds data used to computed HERD GOVERD with current. prices in millions of EUR PPPs, Note that the indicator is only applicable for European Research Area countries. 1a6 Amount of ERC starting grants researchers by country number of researchers. in institutes of higher education and public research institutes in FTE. Definition The total number of ERC starting grant receivers by country of principle. investigator divided by the total number of researchers in HEI and PROs in full time. equivalents FTEs The indicator aims at measuring the excellence of young researchers in. a country in receiving ERC funding,Sources and notes. European Commission 2010 Feasibility Study for Creating a European University Data Collection. Final Study Report DG RTD URL ec europa eu research era docs en eumida final report pdf. Numerator DG RTD data on ERC grants retrieved 18 May 2011 The total number of ERC. grants projects awarded to a country of the principle investigator by year of grant call ERC. Starting grants are aimed at offering young researchers with 2 12 years of experience. opportunities to develop independent careers First year of grant calls was 2007. subsequently grants were advertised from 2009 onwards 2009 and 2010 figures averaged. in order to avoid fluctuations, Denominator Eurostat Total R D personnel by sectors of performance occupation and sex. data occupation based definition sum of full time equivalents computed for Higher. education and public research organizations, Note that the indicator is only applicable for European Research Area countries. 1a7 Share of women among researchers, Definition The number of women intramural researchers divided by the total number of.
intramural researchers computed in terms of headcount. Sources and notes UNESCO OECD Eurostat data on R D personnel by sector of. employment and sex occupation based definition including all sectors of employment Data. of US differs in definition and refers to all persons with bachelor s or higher degrees in. science or engineering S E as published by the National Science Foundation. 1a8 Number of highly valued scientific prizes by HEI and PRO R D spending. Definition The number of Nobel prizes in natural sciences and economics plus Field Medals. by country divided by HEI and PRO R D spending,Sources and notes. Numerator The total number of Nobel prizes in chemistry medicine physics and. economics and Fields Medal in mathematics awarded to researchers by country of. affiliation within the 5 most recent years i e 2005 values refer to 2001 2005. Note that the distribution of these prizes is highly skewed 0 values found for over 77 of. the countries within our scope and highly concentrated to one country US which accounts. for 61 and 45 of all prizes in 2005 and 2010 respectively. Denominator HERD GOVERD same as 1a4, 1a9 Specialisation in publications in the fields associated with Grand Societal. Challenges, Definition A specialization index number of a country s publications within FP7 thematic. priorities classified as Grand Societal Challenges GSC divided by the total number of. publications in a country over the share of GSC publications in the world. Sources and notes, Numerator Science Metrix based on Scopus data data the total number of publications by. country published in journals classified in any of the following FP7 thematic priorities 1. Health 2a Food Agriculture and Fisheries 5 Energy or 6 Environment incl Climate. Change over the total number of publications by country fractional counting method to. avoid duplications, Denominator The share of GSC publications in the world.
1a10 Specialisation in publications in the fields associated with Key Enabling. Technologies, Definition A specialization index number of a country s publications within FP7 thematic. priorities classified as Key Enabling Technologies KET divided by the total number of. publications in a country over the share of KET publications in the world. Sources and notes, Numerator Science Metrix based on Scopus data data the total number of publications by. country published in journals classified in any of the following FP7 thematic priorities 2b. Biotechnology 3 Information and Communication Technologies 4a Nanosciences and. Nanotechnologies 4b Materials excl nanotechnologies or 4c New Production. Technologies over the total number of publications by country fractional counting method to. avoid duplications, Denominator The share of KET publications in the world. 1b1 collind International collaboration index, Definition The ratio between the predicted number of international co publications and the. observed number of co publications by country,Sources and notes.
Science Metrix calculations based on the overall number of publications in Scopus this is a. scale adjusted indicator of collaborations computed by adjusting for the power law. relationship between the number of publications and the number of co publications A value. above 1 means that a country produces more publications in collaboration with at least. another country than expected based on the size of its scientific production The. collaboration index CI was computed by log transforming the number of publications and. number of co publications and performing a log log linear regression to estimate the. constants a and k of the following equation, Expp M a M k where Expp expected number of co publications of a country M the. observed number of publications by a country3, As this indicator was only computed by Science Metrix for the entire period 2000 2009 a. non scale adjusted share of collaborations index was also considered see below 1b1. 1b1 Share of international co publications to total number of publications. Definition The ratio of international co publications to the total number of publications by. Sources and notes, Numerator Science Metrix based on Scopus data data on the number of co publications. from a country in which the co authors are from at least two different countries full counting. all fields, Denominator Science Metrix based on Scopus data data on the total number of. publications from a country full counting all fields. Note that this indicator is not scale adjusted c f indicator 1b1 collind. See detailed description on p 54 of Science Metrix Suite of Methods Methods Associated to. Report 2 3 1 to European Commission, 1b2 Share of international collaborations with non EU partners in total publications.
Definition The ratio of international co publications with at least one partner from a non EU. member state to the total number of publications by country. Sources and notes, Numerator Science Metrix based on Scopus data data on the number of co publications. from a country in which one of the co authors is from a non EU country other collaborator. may or may not be from an EU country fractional counting all fields. Denominator Science Metrix based on Scopus data data on the total number of. publications from a country full counting all fields. Note that this indicator is not scale adjusted c f indicator 1b1 The indicator is not as. originally intended a measure of co publication with emerging countries since co. publications with among others US JP CH NO IL could not be excluded. For non EU member states all international collaborations are counted The difference with. 1b1 is that this indicator uses fractional counting. 1b5 Share of foreigners in doctoral programmes, Definition Share of foreigners from other EU or non EU countries in doctoral programmes. within the total number of doctoral candidates in a country. Sources and notes Eurostat Education Statistics and MORE Survey Table D of MOB ST4. Number and share of doctoral candidates ISCED 6 with the citizenship of another EU27. member state in the reporting country in the EU27 and Number of doctoral candidates. ISCED 6 with another non EU27 citizenship per country in the EU27 Data for DE taken. from DESTATIS Statistik der Studenten Studierende Deutschland Semester Nationalit t. Geschlecht Angestrebte Abschlusspr fung, For the US National Science Foundation NSF S E and non S E foreign students. enrolled in U S higher education institutions by academic level 2006 09 table provides the. closest matching data however since it does not cover only science and engineering. students it was not considered, Note that data coverage is low no data is available for GR IE LU or NL or any non EU. country except for the US, 1b7 Share of coordination position in FP projects participation share in FP projects.
Definition A specialization index the share of coordination position by a country to the total. number of coordination positions of an FP6 or FP7 project divided by a country s share of. participation to the total number of FP6 and FP7 projects. Sources and notes, Special tabulations from CORDIS E Corda retrieved 12 Sep 2011 data for 2006 includes. all FP6 signed grant agreements by country over the period 2002 to 2006 data for 2011. includes the same for FP7 over the period 2007 2011. Numerator Number of FP projects coordinated by an entity from a given country divided by. the total number of FP projects, Denominator Number of FP project participation by an entity from a given country divided by. the total number of FP project participation of the country. Note that the indicator is only applicable for European Research Area countries.

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