******* was the European country with the highest share of graduates in 2024, with almost **** of those aged between 15 and 64 having a degree. On the contrary, only ** percent of the population aged 15 to 64 in ********************** hold a tertiary education title.
Ireland and Luxembourg were the European countries with the highest share of graduates aged 30 to 34 in 2024, with two thirds of people in this age group having a degree. Countries such as Italy, Bosnia, and Romania had the lowest share of graduates in this age group at 30.7, 28.2, and 23.6 percent respectively.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The folder 'population by educational attainment level (edat1)' presents data on the highest level of education successfully completed by the individuals of a given population.
The folder 'transition from education to work (edatt)' covers data on young people neither in employment nor in education and training – NEET, early leavers from education and training and the labour status of young people by years since completion of highest level of education.
The data shown are calculated as annual averages of quarterly EU Labour Force Survey data (EU-LFS).
Up to the reference year 2008, the data source (EU-LFS) is, where necessary, adjusted and enriched in various ways, in accordance with the specificities of an indicator, including the following:
Details on the adjustments are available in CIRCABC.
The adjustments are applied in the following online tables:
- Population by educational attainment level, sex and age (%) - main indicators (edat_lfse_03)
- Population by educational attainment level, sex and NUTS 2 regions (%) (edat_lfse_04)
(Other tables shown in the folder 'population by educational attainment level (edat1)' are not adjusted and therefore the results in these tables might differ).
LFS ad-hoc module data available in the folder 'transition from education to work (edatt)' are not adjusted.
The folder 'young people by educational and labour status (incl. neither in employment nor in education and training - NEET) (edatt0)' also presents one table with quarterly NEET data (lfsi_neet_q). Deviating from the NEET indicator calculation as provided in 3.4, the denominator in this table with quarterly data is the total population of the same age group and sex which explains differences in results. For further information, see the ESMS on 'LFS main indicators'.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
This repository contains a dataset of higher education institutions in France. This includes 349 higher education institutions in France, including universities, universities of applied sciences and Higher Institutes as Higher Institute of Engineering, Higher Institute of biotechnologies and few others. This dataset was compiled in response to a cybersecurity investigation of France higher education institutions' websites [1]. The data is being made publicly available to promote open science principles [2].
The data includes the following fields for each institution:
The methodology for creating the dataset involved obtaining data from two sources: The European Higher Education Sector Observatory (ETER)[3]. The data was collected on December 26, 2024, the Eurostat for NUTS - Nomenclature of territorial units for statistics 2013-16[4] and 2021[5].
This section outlines the methodology used to create the dataset for Higher Education Institutions (HEIs) in France. The dataset consolidates information from various sources, processes the data, and enriches it to provide accurate and reliable insights.
Data Sources
eter-export-2021-FR.xlsx
NUTS2013-NUTS2016.xlsx
NUTS2021.xlsx
Data Cleaning and Preprocessing Column Renaming Columns in the raw dataset were renamed for consistency and readability. Examples include:
ETER ID
→ ETER_ID
Institution Name
→ Name
Legal status
→ Category
Value Replacement
Category
column was cleaned, with government-dependent institutions classified as "public."Handling Missing or Incorrect Data
ETER_ID
. For instance:
FR0333
(updated to www.icam.fr
)FR0906
(updated to epss.fr
)FR0104
(updated to www.ensa-nancy.fr
)FR0466
(updated to www.clermont-auvergne-inp.fr
)FR0907
(updated to insp.gouv.fr
) - This universety also changed your name for Institut national du service public
FR0129
and FR0944
due to insufficient or invalid information.Regional Data Integration
Final Dataset The final dataset was saved as a CSV file: france-heis.csv
, encoded in UTF-8 for compatibility. It includes detailed information about HEIs in France, their categories, regional affiliations, and membership in European alliances.
Summary This methodology ensures that the dataset is accurate, consistent, and enriched with valuable regional and institutional details. The final dataset is intended to serve as a reliable resource for analyzing French HEIs.
This data is available under the Creative Commons Zero (CC0) license and can be used for any purpose, including academic research purposes. We encourage the sharing of knowledge and the advancement of research in this field by adhering to open science principles [2].
If you use this data in your research, please cite the source and include a link to this repository. To properly attribute this data, please use the following DOI: 10.5281/zenodo.7614862
If you have any updates or corrections to the data, please feel free to open a pull request or contact us directly. Let's work together to keep this data accurate and up-to-date.
We would like to acknowledge the support of the Norte Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF), within the project "Cybers SeC IP" (NORTE-01-0145-FEDER-000044). This study was also developed as part of the Master in Cybersecurity Program at the Instituto Politécnico de Viana do Castelo, Portugal.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This domain covers statistics and indicators on key aspects of the education systems across Europe. The data show entrants and enrolments in education levels, education personnel and the cost and type of resources dedicated to education.
For a general technical description of the UOE Data Collection see UNESCO OECD Eurostat (UOE) joint data collection – methodology - Statistics Explained (europa.eu).
The standards on international statistics on education and training systems are set by the three international organisations jointly administering the annual UOE data collection:
The following topics are covered:
Data on enrolments in education are disseminated in absolute numbers, with breakdowns available for the following dimensions:
Additionally, the following types of indicators on enrolments are calculated (all indicators using population data use Eurostat’s population database (demo_pjan)):
Data on entrants in education are disseminated in absolute numbers, with breakdowns available for the following dimensions:
Additionally the following indicator on entrants is calculated:
Data on learning mobility is available for degree mobile students, degree mobile graduates and credit mobile graduates. Degree mobility means that students/graduates are/were enrolled as regular students in any semester/term of a programme taught in the country of destination with the intention of graduating from it in the country of destination. Credit mobility is defined as temporary tertiary education or/and study-related traineeship abroad within the framework of enrolment in a tertiary education programme at a "home institution" (usually) for the purpose of gaining academic credit (i.e. credit that will be recognised in that home institution). Further definitions are in Section 2.8 of the UOE manual.
Degree mobile students are referred to as just ‘mobile students’ in UOE learning mobility tables. Data is disseminated for degree mobile students and degree mobile graduates in absolute numbers with breakdowns available for the following dimensions:
Additionally the following types of indicators on degree mobile students and degree mobile graduates are calculated ((all indicators using population data use Eurostat’s population database (demo_pjan)):
For credit mobile graduates, data are disseminated in absolute numbers, with breakdowns available for the following dimensions:
Data on personnel in education are available for classroom teachers/academic staff, teacher aides and school-management personnel. Teachers are employed in a professional capacity to guide and direct the learning experiences of students, irrespective of their training, qualifications or delivery mechanism. Teacher aides support teachers in providing instruction to students. Academic staff are personnel employed at the tertiary level of education whose primary assignment is instruction and/or research. School management personnel covers professional personnel who are responsible for school management/administration (ISCED 0-4) or whose primary or major responsibility is the management of the institution, or a recognised department or subdivision of the institution (tertiary levels). Full definitions of these statistical units are in Section 3.5 of the UOE manual.
Data are disseminated on teachers and academic staff in absolute numbers, with breakdowns available for the following dimensions:
Around ** percent of Europeans held an upper secondary school title in 2024. Figures ranged from ** percent of people residing in Czechia to only ** percent of Spaniards. About ********* of EU citizens had a primary school title only, while this was the case for ************** of the Turkish population. As far as tertiary education, ** percent of the Irish population held a bachelor's or higher degree, compared to only ** percent of those living in Bosnia and Herzegovina.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Percentage of students in tertiary education who are female (%) in European Union was reported at 54.04 % in 2018, according to the World Bank collection of development indicators, compiled from officially recognized sources. European Union - Percentage of students in tertiary education who are female - actual values, historical data, forecasts and projections were sourced from the World Bank on October of 2025.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
As part of the EOSC project family the FAIRsFAIR - Fostering Fair Data Practices in Europe - project aims to supply practical solutions for the use of the FAIR data principles throughout the research data life cycle. The FAIRsFAIR project runs from March 2019-February 2022.
FAIRsFAIR Work Package 7 “FAIR Data Science and Professionalisation” aims to develop resources and build communities that support the uptake of RDM and FAIR practice within higher education curricula.
The data published here stems from a both a web-based questionnaire with 90 responses conducted within FAIRsFAIR WP7 between 19 September and 15 November 2019.
The questionnaire covered several dimensions of research data management at HEIs relevant for the implementation of FAIRsFAIR WP7, as well as WP3 “FAIR Data Policy Practice” and WP6 “FAIR Competence Centre”. These dimensions included:
Institutional research data management policies
Support services for research data management
Competence development of students and graduates
Universities and EOSC
FAIRsFAIR support for universities
The data resulting from the survey has been used as the basis for D7.1 FAIR in European Higher Education.
The following files are available:
Codebook including original questionnaire
Dataset
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This domain covers statistics and indicators on key aspects of the education systems across Europe. The data show entrants and enrolments in education levels, education personnel and the cost and type of resources dedicated to education.
For a general technical description of the UOE Data Collection see UNESCO OECD Eurostat (UOE) joint data collection – methodology - Statistics Explained (europa.eu).
The standards on international statistics on education and training systems are set by the three international organisations jointly administering the annual UOE data collection:
The following topics are covered:
Data on enrolments in education are disseminated in absolute numbers, with breakdowns available for the following dimensions:
Additionally, the following types of indicators on enrolments are calculated (all indicators using population data use Eurostat’s population database (demo_pjan)):
Data on entrants in education are disseminated in absolute numbers, with breakdowns available for the following dimensions:
Additionally the following indicator on entrants is calculated:
Data on learning mobility is available for degree mobile students, degree mobile graduates and credit mobile graduates. Degree mobility means that students/graduates are/were enrolled as regular students in any semester/term of a programme taught in the country of destination with the intention of graduating from it in the country of destination. Credit mobility is defined as temporary tertiary education or/and study-related traineeship abroad within the framework of enrolment in a tertiary education programme at a "home institution" (usually) for the purpose of gaining academic credit (i.e. credit that will be recognised in that home institution). Further definitions are in Section 2.8 of the UOE manual.
Degree mobile students are referred to as just ‘mobile students’ in UOE learning mobility tables. Data is disseminated for degree mobile students and degree mobile graduates in absolute numbers with breakdowns available for the following dimensions:
Additionally the following types of indicators on degree mobile students and degree mobile graduates are calculated ((all indicators using population data use Eurostat’s population database (demo_pjan)):
For credit mobile graduates, data are disseminated in absolute numbers, with breakdowns available for the following dimensions:
Data on personnel in education are available for classroom teachers/academic staff, teacher aides and school-management personnel. Teachers are employed in a professional capacity to guide and direct the learning experiences of students, irrespective of their training, qualifications or delivery mechanism. Teacher aides support teachers in providing instruction to students. Academic staff are personnel employed at the tertiary level of education whose primary assignment is instruction and/or research. School management personnel covers professional personnel who are responsible for school management/administration (ISCED 0-4) or whose primary or major responsibility is the management of the institution, or a recognised department or subdivision of the institution (tertiary levels). Full definitions of these statistical units are in Section 3.5 of the UOE manual.
Data are disseminated on teachers and academic staff in absolute numbers, with breakdowns available for the following dimensions:
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Since 1999, the EUA Trends reports have consistently mapped developments in the European higher education landscape, by presenting comparative data from the perspective of higher education institutions. In the ninth edition of the European University Association’s long-running series, the Trends 2024 report provides an overview of how European higher education institutions have experienced changes over the past five years, due to higher education reforms, and in the wider context of societal, political, economic and technological changes, marked among others by the implications of Covid-19 pandemic and Russia’s war against Ukraine.
Trends 2024 is based on survey data collected in April to July 2023.
Responses were gathered from 489 higher education institutions in 46 European higher education systems. The survey was open to all higher education institutions in the European Higher Education Area (EHEA) that provide study programmes in at least one of the three degree cycles (bachelor’s, master’s, doctoral). One response per institution was collected.
The survey addressed the higher education institutions’ perspectives and strategies regarding:
· The institution and its context
· The student life cycle and experience
· Learning, teaching and teachers
· Inclusion, equity and diversity
· Engagement and outreach with society and community
· Internationalisation
Results of the survey are published in “Trends 2024 - European higher education institutions in times of transition”.
The following files are available:
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
School enrollment, tertiary (% gross) in European Union was reported at 79.73 % in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. European Union - School enrollment, tertiary (% gross) - actual values, historical data, forecasts and projections were sourced from the World Bank on October of 2025.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This domain covers statistics and indicators on key aspects of the education systems across Europe. The data show entrants and enrolments in education levels, education personnel and the cost and type of resources dedicated to education.
For a general technical description of the UOE Data Collection see UNESCO OECD Eurostat (UOE) joint data collection – methodology - Statistics Explained (europa.eu).
The standards on international statistics on education and training systems are set by the three international organisations jointly administering the annual UOE data collection:
The following topics are covered:
Data on enrolments in education are disseminated in absolute numbers, with breakdowns available for the following dimensions:
Additionally, the following types of indicators on enrolments are calculated (all indicators using population data use Eurostat’s population database (demo_pjan)):
Data on entrants in education are disseminated in absolute numbers, with breakdowns available for the following dimensions:
Additionally the following indicator on entrants is calculated:
Data on learning mobility is available for degree mobile students, degree mobile graduates and credit mobile graduates. Degree mobility means that students/graduates are/were enrolled as regular students in any semester/term of a programme taught in the country of destination with the intention of graduating from it in the country of destination. Credit mobility is defined as temporary tertiary education or/and study-related traineeship abroad within the framework of enrolment in a tertiary education programme at a "home institution" (usually) for the purpose of gaining academic credit (i.e. credit that will be recognised in that home institution). Further definitions are in Section 2.8 of the UOE manual.
Degree mobile students are referred to as just ‘mobile students’ in UOE learning mobility tables. Data is disseminated for degree mobile students and degree mobile graduates in absolute numbers with breakdowns available for the following dimensions:
Additionally the following types of indicators on degree mobile students and degree mobile graduates are calculated ((all indicators using population data use Eurostat’s population database (demo_pjan)):
For credit mobile graduates, data are disseminated in absolute numbers, with breakdowns available for the following dimensions:
Data on personnel in education are available for classroom teachers/academic staff, teacher aides and school-management personnel. Teachers are employed in a professional capacity to guide and direct the learning experiences of students, irrespective of their training, qualifications or delivery mechanism. Teacher aides support teachers in providing instruction to students. Academic staff are personnel employed at the tertiary level of education whose primary assignment is instruction and/or research. School management personnel covers professional personnel who are responsible for school management/administration (ISCED 0-4) or whose primary or major responsibility is the management of the institution, or a recognised department or subdivision of the institution (tertiary levels). Full definitions of these statistical units are in Section 3.5 of the UOE manual.
Data are disseminated on teachers and academic staff in absolute numbers, with breakdowns available for the following dimensions:
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This domain covers statistics and indicators on key aspects of the education systems across Europe. The data show entrants and enrolments in education levels, education personnel and the cost and type of resources dedicated to education.
For a general technical description of the UOE Data Collection see UNESCO OECD Eurostat (UOE) joint data collection – methodology - Statistics Explained (europa.eu).
The standards on international statistics on education and training systems are set by the three international organisations jointly administering the annual UOE data collection:
The following topics are covered:
Data on enrolments in education are disseminated in absolute numbers, with breakdowns available for the following dimensions:
Additionally, the following types of indicators on enrolments are calculated (all indicators using population data use Eurostat’s population database (demo_pjan)):
Data on entrants in education are disseminated in absolute numbers, with breakdowns available for the following dimensions:
Additionally the following indicator on entrants is calculated:
Data on learning mobility is available for degree mobile students, degree mobile graduates and credit mobile graduates. Degree mobility means that students/graduates are/were enrolled as regular students in any semester/term of a programme taught in the country of destination with the intention of graduating from it in the country of destination. Credit mobility is defined as temporary tertiary education or/and study-related traineeship abroad within the framework of enrolment in a tertiary education programme at a "home institution" (usually) for the purpose of gaining academic credit (i.e. credit that will be recognised in that home institution). Further definitions are in Section 2.8 of the UOE manual.
Degree mobile students are referred to as just ‘mobile students’ in UOE learning mobility tables. Data is disseminated for degree mobile students and degree mobile graduates in absolute numbers with breakdowns available for the following dimensions:
Additionally the following types of indicators on degree mobile students and degree mobile graduates are calculated ((all indicators using population data use Eurostat’s population database (demo_pjan)):
For credit mobile graduates, data are disseminated in absolute numbers, with breakdowns available for the following dimensions:
Data on personnel in education are available for classroom teachers/academic staff, teacher aides and school-management personnel. Teachers are employed in a professional capacity to guide and direct the learning experiences of students, irrespective of their training, qualifications or delivery mechanism. Teacher aides support teachers in providing instruction to students. Academic staff are personnel employed at the tertiary level of education whose primary assignment is instruction and/or research. School management personnel covers professional personnel who are responsible for school management/administration (ISCED 0-4) or whose primary or major responsibility is the management of the institution, or a recognised department or subdivision of the institution (tertiary levels). Full definitions of these statistical units are in Section 3.5 of the UOE manual.
Data are disseminated on teachers and academic staff in absolute numbers, with breakdowns available for the following dimensions:
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
European Union - Tertiary educational attainment, age group 30-34 was 44.70% in December of 2024, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for European Union - Tertiary educational attainment, age group 30-34 - last updated from the EUROSTAT on October of 2025. Historically, European Union - Tertiary educational attainment, age group 30-34 reached a record high of 44.70% in December of 2024 and a record low of 27.20% in December of 2005.
This dataset shows the proportion of the European population aged 30-34 with a tertiary educational attainment during the 2011-2013 period at regional level. A well-educated workforce is key to prosperity. There tends to be a strong correlation between the educational attainment of a region’s workforce and median earnings in the region. In addition, attaining a relatively high education level tends to mean less risk of being unemployed. The Europe 2020 strategy is aimed at increasing the share of the population aged 30–34 with tertiary education to 40% by 2020. Member States have set national targets for this varying from 26% (in Italy) to 60% (in Ireland). In the EU-27, the share increased significantly between 2008 and 2012 from 31% to 36%, suggesting that the Union-wide target of 40% should be achievable without much difficulty. % of population aged 30-34 EU-28 = 35.7; Source: Eurostat, DG REGIO
In 2019, a Statista study on labor shortages showed that in 2020, ** percent of the workforce of the European Union working in occupations that required higher education, with this share increasing to ** percent by 2030.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
Empowering’ university policies improve our economies, states the recent report of Empower European Universities called The State of University Policy for progress in Europe. This report assesses the contribution of higher education policies to higher education performance and economic innovation. The main findings are summarized in a policy report, the technical report explains the data we have used and method, the country reports provide a snapshot of each one of the 32 countries.Higher education contributes to economic innovation. This study measures and compares the extent to which national governments’ policies foster this contribution across Europe. The study stresses the relevance of policies which are ‘empowering’ for higher education institutions, or in other words provide them with appropriate resources and regulatory environments.The assessment relies on quantitative scores, based on the contribution of policies regarding funding and autonomy to higher education performance in education, research and economic innovation, using non-arbitrary weights and eighteen policy indicators across 32 European countries. A large number of countries belong to a ‘middle group’ in our overall assessment, indicating a relative cohesion in Europe. Yet, substantial variations exist in terms of higher education policy in Europe, each European country having room for policy improvement.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The average for 2022 based on 26 countries was 80.28 percent. The highest value was in Greece: 166.67 percent and the lowest value was in Luxembourg: 21.03 percent. The indicator is available from 1970 to 2023. Below is a chart for all countries where data are available.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset provides values for ENROLMENT IN TERTIARY EDUCATION PER 100 000 INHABITANTS MALE WB DATA.HTML reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.
Abstract copyright UK Data Service and data collection copyright owner. There are currently over 35 million students within Europe and yet there is no clear understanding of the extent to which understandings of ‘the student’ are shared. Thus, a central aim of this project was to investigate how the contemporary higher education (HE) student is conceptualised and the extent to which this differs both within nation-states and across them. This is significant in terms of implicit (and sometimes explicit) assumptions that are made about common understandings of ‘the student’ across Europe – underpinning, for example, initiatives to increase cross-border educational mobility and the wider development of a European Higher Education Area. It is also significant in relation to exploring the extent to which understandings are shared within a single nation and, particularly, the degree to which there is congruence between the ways in which students are conceptualised within policy texts and by policymakers, and the understandings of other key social actors such as the media, higher education institutions and students themselves. The empirical project was guided by four main research questions: (i) How are understandings of the higher education student produced, shaped and disseminated by (a) policymakers, (b) the media and (c) higher education institutions? (ii) To what extent do these understandings differ within and across European nations? (iii) How do students of different national and social backgrounds understand the role of the higher education student? (iv) To what extent are their understandings consonant with those produced, shaped and disseminated by policymakers, the media and higher education institutions? To answer these questions, data were collected from six different European countries – Denmark, England, Ireland, Germany, Poland and Spain – and through four strands of work, each of which focuses on a different social actor i.e. policymakers, the media, higher education institutions and students themselves. Main Topics: Higher Education, Students, Europe Purposive selection/case studies Face-to-face interview Face-to-face focus group
******* was the European country with the highest share of graduates in 2024, with almost **** of those aged between 15 and 64 having a degree. On the contrary, only ** percent of the population aged 15 to 64 in ********************** hold a tertiary education title.