Research and development (R&D) (rd)

1.1. Contact organisation

National Documentation Centre (EKT)

1.2. Contact organisation unit

RDI Metrics and Services Department

1.3. Contact name

Restricted from publication

1.4. Contact person function

Restricted from publication

1.5. Contact mail address

56, Zefyrou, GR-17564, P. Faliro

1.6. Contact email address

Restricted from publication

1.7. Contact phone number

Restricted from publication

1.8. Contact fax number

Not required.

29 October 2025

2.1. Metadata last certified

29 October 2025

2.2. Metadata last posted

29 October 2025

2.3. Metadata last update

29 October 2025

3.1. Data description

Statistics on Government R&D (GOVERD) measure research and experimental development (R&D) performed in the Government sector, i.e. R&D expenditure and R&D personnel. In line with this objective the target population for the national R&D survey of the Government sector should consist of all R&D performing units (including all R&D performers – occasional and continuous, known and unknown - in all branches and size classes) belonging to this sector.

Main concepts and definitions used for the production of R&D statistics are given by the OECD (2015), Frascati Manual 2015: Guidelines for Collecting and Reporting Data on Research and Experimental Development, The Measurement of Scientific, Technological and Innovation Activities, which is the internationally recognised standard methodology for collecting R&D statistics and by the European Business Statistics Methodological Manual on R&D Statistics (EBS Methodological Manual on R&D Statistics). 

The guiding document to preparing the quality reports is the European Statistical System (ESS)  Handbook for Quality and Metadata Reports — re-edition 2021.

Since the beginning of 2021, the collection of R&D statistics is based on Commission Implementing Regulation (EU) No 2020/1197 of 30 July 2020. The Regulation sets the framework for the collection of R&D statistics and specifies the main variables of interest and their breakdowns at predefined level of detail.

3.2. Classification system

• The local units for the statistics are compiled at regional level according to NUTS 2 – Nomenclature of Territorial Units for Statistics;
• The distribution by socioeconomic objectives (SEO) is based on Nomenclature for the Analysis and Comparisons of Scientific Programmes and Budgets (NABS);
• The fields of research and development are based on Classification and distribution by Fields of Research and Development (FORD).
• The R&D personnel and researchers by educational attainment are classified by the International Standard Classification of Education ISCED 2011

3.3. Coverage - sector

See below.

3.3.1. General coverage

Definition of R&D

R&D comprise creative and systematic work undertaken in order to increase the stock of knowledge - including knowledge of humankind, culture and society - and to devise new applications of available knowledge.

3.3.2. Sector institutional coverage

Government sector	Coverage of GOV is in line with the FM recommendations and ESA 13 classification. It covers public institutions administered or/and financed by Ministries (public research centers, archaeological and cultural institutions, public hospitals, agricultural institutions, etc.), as well as Greek Public Independent Authorities.
Hospitals and clinics	University hospitals are included in the higher education sector (HES). Private and PNP hospitals are included in the BES and PNP sector respectively. Government hospitals and Military hospitals are included in the GOV sector since 2012 (for reference year 2011 and onwards).
Inclusion of units that primarily do not belong to GOV and the borderline cases.	Not applicable

3.3.3. R&D variable coverage

R&D administration and other support activities	Included, according to FM
External R&D personnel	Since reference year 2011, the reported total R&D personnel included both internal and external personnel, as required by the FM 2015. However, no detailed data were available for each category and information on breakdowns (such as gender) was missing. Recently, five distinct R&D personnel categories based on the most common types of employment in Greek R&D institutional units were defined. More specifically, in the questionnaire Question B.1 asks respondents to indicate whether they employ individuals (Researchers and/or Other R&D personnel) under the following five employment status categories: B1.1. Internal permanent personnel engaged in R&D activities This category involves all persons with employment contracts of indeterminate duration with the statistical unit. In the GOV sector, the personnel costs for this category are covered by the ordinary budget.      B1.2 Internal temporary personnel engaged in R&D activities This category includes individuals who work in R&D activities under the instructions of the statistical unit and have a regular interaction with it (regular physical presence or remote work, regular work meetings, etc.). The category refers to fixed-term employment contracts (full-time or part-time) and civil contracts covered by par. 9 of art 39 of Greek law Νo.4387/2016. B1.3 External contributors engaged in R&D activities This category includes individuals who work on R&D under the instructions of the statistical unit but without a regular interaction with it. It refers to contracts for the provision of services or the assignment of work to natural persons, experts, emeritus professors and researchers who receive remuneration, etc. This type of contracts mainly concerns independent/self-employed individuals. The social security contributions for their remuneration are paid by the individuals themselves, and not by the institution as in category B1.2. B1.4. Personnel of Greek HEIs engaged in R&D activities This category includes the (active) Universities’ personnel, such as Professors, Associate Professors, laboratory personnel etc., who work as external experts in R&D activities of statistical units in the GOV sector.   B1.5. Other external personnel engaged in R&D activities This category includes individuals who work on intramural R&D activities under the instructions of the statistical unit (with or without a regular interaction with it), and they are: paid by another institution/enterprise, or seconded from another institution, or paid for their R&D activities through external R&D grants such as the State Scholarships Foundation (IKY), the Onassis Foundation, the EU Marie Skłodowska-Curie Actions, etc.
Clinical trials: compliance with the recommendations in FM §2.61.	Clinical trials (phases 1, 2, 3 and occasionally 4) undertaken by pharmaceutical companies are covered.

3.3.4. International R&D transactions

Receipts from rest of the world by sector - availability	Funding from abroad is covered by all sectors and is broken down into: European Commission (e.g. Horizon Europe, Horizon 2020 and other EU Programs), Foreign Business enterprises, International Organizations, Other sources.  For the BES category ‘foreign business enterprises’ is further broken down into ‘foreign enterprises within the same group’ and ‘other foreign enterprises’.
Payments to rest of the world by sector - availability	Since the 2013 survey, an additional section on extramural expenditure has been added to GOV questionnaire, including information on extramural expenditure to abroad (enterprises and other organizations separately). However, it should be noted that data are collected only from R&D Performers and do not cover the total national payments to abroad.

3.3.5. Extramural R&D expenditures

According to the Frascati Manual (FM), expenditure on extramural R&D (i.e. R&D performed outside the statistical unit) is not included in intramural R&D performance totals (FM, §4.12).

Data collection  on extramural R&D expenditure (Yes/No)	Yes
Method for separating extramural R&D expenditure from intramural R&D expenditure	Since the 2013 survey, an additional section on extramural expenditure has been added to the questionnaire, including information on extramural expenditure to abroad (enterprises and other organisations separately). However, it should be noted that data are collected only from R&D Performers and do not cover the total national payments to abroad.
Difficulties to distinguish intramural from extramural R&D expenditure	No particular difficulties reported.

3.4. Statistical concepts and definitions

See below.

3.4.1. R&D expenditure

Coverage of years	Calendar year.
Source of funds	No divergence from the Frascati Manual recommendations. Since the reference year 2011, in order to address national requirements, government funding has been further categorised to separately indicate R&D funding from European Structural Investment Frameworks, such as the Greek Partnership Agreement ESPA 2014-2020 and ESPA 2021-2027. These subcategories are specified during each survey round.   For the reference year 2023, the GOV questionnaire covered the following sources of funding (question C2): Government: Ordinary Budget Public Investment Budget (National Development Programme, Regions, Municipalities, Special Funds, etc.) Partnership Agreement ESPA 2014-2020 Partnership Agreement ESPA 2021-2027 Recovery and Resilience Fund (RRF) Own funds / Self-financing Business enterprises sector: Greek enterprises within the same group Other private Greek enterprises Other public enterprises Higher Education Sector Private non-profit institutions Rest of the World: European Commission (e.g. Horizon Europe, Horizon 2020, other EU programmes) Foreign enterprises within the same group Other foreign enterprises International Organisations (United Nations, etc.) Other foreign organisations Additional analysis is conducted to offer further breakdowns regarding internal and external funds as well as transfer and exchange funds.  More specifically, the ‘Own funds / Self-financing’ variable is utilized to compute the ‘internal’ component, whereas the remaining source of funds (other sub categories of Government, Business enterprise sector, Higher Education Sector, Private non-profit institutions, and Rest of the World) yield the ‘external component’. In order to determine the breakdown between Exchange and Transfer funds within external R&D funding, survey participants are specifically asked to report whether they received relevant funding for research and development under a contractual agreement which involves providing R&D services or results directly to the funding institution. By identifying these contractual arrangements, it is possible to clearly distinguish Exchange funds from other forms of funding. Once the Exchange funds for each R&D performing unit have been collected, calculating the Transfer component of external funding becomes a straightforward process.
Type of R&D	Since 2012 (reference year 2011 onwards) breakdowns regarding type of R&D are available for the total intramural R&D expenditure.
Type of costs	Since reference year 2011 onwards, the available breakdowns regarding type of costs included: Current expenditure Current - labour cost Current - other expenditure Capital expenditure Capital - land and buildings Capital - instruments and equipment. Further breakdowns for type of costs according to Eurostat’s guidelines. The following list presents the categories by type of cost: Current costs Labour costs for internal R&D personnel Other current costs Other current costs / External R&D personnel Other current costs / Other costs Capital costs Land and buildings Machinery and equipment Capitalized computer software Other intellectual property products
Defence R&D - method for obtaining data on R&D expenditure	Information about defence R&D is separately available for the GOV sector only (NABS classification).

3.4.2. R&D personnel

See below.

3.4.2.1. R&D personnel – Head Counts (HC)

Coverage of years	Calendar year.
Function	Information about the two occupational categories (researchers and other R&D personnel) is collected. Since 2012 (reference period 2011 onwards) information about all occupations is also available by sex, educational level (and sex), by major field of science (and sex) and by region (and sex).
Qualification	Qualification is available for all occupational categories and sex. Data are separately available for ISCED 2011 level 8, ISCED 2011 levels 5, 6 and 7 and ‘other qualification’ in line with the new classification that has been introduced with the Com. Reg. 995/2012
Age	Since 2012 (reference year 2011 onwards) information about age (and sex) of the researchers has been collected in head counts.
Citizenship	Since 2012 (reference year 2011 onwards) information about citizenship of the researchers has been collected in head counts.

3.4.2.2. R&D personnel – Full Time Equivalent (FTE)

Coverage of years	Calendar year.
Function	Information about the two occupational categories (researchers and other R&D personnel) is collected. Since 2012 (reference period 2011 onwards) information about all occupations is also available by sex, educational level (and sex), by major field of science (and sex) and by region (and sex).
Qualification	Qualification is available all qualification categories and sex. Data are separately available for ISCED 2011 level 8, ISCED 2011 levels 5, 6 and 7 and ‘other qualification’ in line with the new classification that has been introduced with the Com. Reg. 995/2012.
Age	Not available / not collected.
Citizenship	Not available / not collected.

3.4.2.3. FTE calculation

Reporting units made the calculation of FTEs following the questionnaire guidelines that have been drafted in line with FM recommendations (§ 333). Information about how calculations were performed has been provided by respondents in the metadata chapter of the questionnaire. Note that since 2017, FTEs less than 10% are not reported as R&D activities.

The majority of the institutions in the government sector have reported that they calculated FTE using the internal time-sheets kept by the institutions or by applying coefficients as reported by directors / heads of the institutions. Combination of the two has also been reported. To a lesser extent, institutions have also reported the use of other methods, such as the application of different coefficients on occupation or type of contract, the implementation of survey to the staff, etc. R&D coefficients, derived from a time use survey realized by EKT in 2015, were applied for the calculation of the R&D share (and FTEs) in the Public Hospitals.

 

3.5. Statistical unit

The statistical unit is the institutional unit as defined by Council Regulation (EEC) No 1993/696 of 15 March 1993.

Government institutions as listed in the statistical Register of General Government Entities (S13) that is maintained by ELSTAT (Hellenic Statistical Authority). Merges/ abolitions of institutions are regularly checked and statistical units are modified accordingly.

3.6. Statistical population

See below.

3.6.1. National target population

The target population is the population for which inferences are made. The frame (or frames, as sometimes several frames are used) is a device that permits access to population units. The frame population is the set of population units which can be accessed through the frame and the survey data really refer to this population of institutional units.

The objective of the European R&D statistics is to cover all intramural R&D activities. In line with this objective, the target population for the national R&D survey of the Government Sector should consist of all R&D performing units (including known R&D performers or assumed to perform R&D). In practise however, countries in their R&D surveys might have difficulty in identifying R&D activities at the municipality level. 

 

	Target population when sample/census survey is used for collection of raw data	Target population when administrative data or pre-compiled statistics are used
Definition of the national target population	The target population is based on the GOV R&D Directory which is developed by EKT and includes those institutions of the general government (ESA S13) that are known to regularly perform R&D (core institutions) or to occasionally perform R&D (perimeter institutions), with the exception of higher education institutions and public enterprises. The Directory is regularly updated. It is also checked against the statistical Register of General Government Entities that is maintained by ELSTAT (the Hellenic Statistical Authority) which is updated annually to reflect any recent changes in the perimeter of the Greek General Government (mergers/ abolitions, e.tc.). Both core and perimeter institutions are covered by a census survey.	Administrative data are collected as supplementary data for a part of the target population of the census survey, namely public hospitals, archaeological and cultural institutions. These data are used to provide direct government funding information and to cross-check data collected from the census surveys.
Estimation of the target population size	Regular (core) and occasional (perimeter) R&D performers: 259	Regular (core) and occasional (perimeter) R&D performers: 259

3.6.2. Frame population – Description

In ESS countries, the frame population for GOV R&D statistics is defined as the list of all the institutional units classified by the national accounts (ESA) as included in the General government (S.13), with the exclusion of those units included in the Higher education sector (HES).

 

Method used to define the frame population	The survey frame comprises institutions included in the statistical Register of General Government Entities (S13) that is maintained by ELSTAT (Hellenic Statistical Authority) with the exclusion of those units belonging to the Higher Education Sector. A few public enterprises listed in S13 are also excluded.
Methods and data sources used for identifying a unit as known or supposed R&D performer	The target population is based on the GOV R&D Directory at EKT and includes those institutions of the general government (ESA S13) that are known to perform or are very likely to perform R&D, with the exception of higher education institutions and public enterprises. To this end, the R&D survey frame for GOV sector is the GOV R&D directory (which is a subset of the statistical Register of General Government Entities (S13)) and includes government research centers (100% R&D performers) as well as other government institutions that perform R&D along with other activities, on regular or occasional basis. The development of GOV R&D Directory started with a screening exercise which was conducted on all GOV potential R&D performers during the first year of the implementation of the survey by EKT (in 2012-2013 with reference to 2011 data). During the second round (reference year 2013), the directory has been updated based on the answers from the first round, the institutions organizational changes (e.g. merges or splits of institutions), the inclusion of R&D performers not previously known, that have been identified as new from the GBARD survey or from information retrieved from administrative sources (e.g. Monitoring Information System (M.I.S.) of “NSRF 2014-2020”, eCORDA database containing information about R&D projects financed by EU research programs (Horizon 2020, Horizon Europe). Below is a description of the GOV R&D Directory at EKT: A) All Research Centers hat are supervised by the General Secretariat for Research and Innovation (GSRI) (Resarch centers in alphabetic order in Greek): the National Observatory of Athens, the National Hellenic Research Foundation, The Centre for Research and Technology (including the Center for Research and Technology, Thessaly), the National Center for Scientific Research DEMOKRITOS, the Hellenic Centre for Marine Research, the National Centre for Social Research, the Biomedical Research Foundation Academy of Athens the Hellenic Pasteur Institute, the Alexander Fleming Biomedical Sciences Research Center, the Athena-Research and Innovation Center in Information, Communication and Knowledge Technologies, the Foundation for Research & Technology Hellas. Moreover, the technological bodies that are supervised by the GSRI: the Greek Atomic Energy Commission the Patras Science Park and the Thessaloniki Science Center & Technology Museum NOESIS). B) Other Public Research Institutions supervised by different Ministries (indicative and non-exhaustive list of GOV institutions is the following:the Academy of Athens, , the Hellenic Agricultural Organization DEMETRA, the Benaki Phytopathological Institute, the Center for Renewable Energy Sources and Saving, the Mediterranean Agronomic Institute of Chania, the Computer Technology Institute and Press Diophantus, etc.). C) Entities supervised by the Ministry of Culture: Ephorates of Antiquities, Ephorate of Palaeoanthropology and Speleology, Ephorate of Underwater Antiquities, Management of the National Archive of Monuments, Acropolis Restoration Service, archaeological sites and museums, Cultural heritage organizations, etc. D) Public hospitals E) Public independent authorities, other government organizations, etc. The Directory is regularly updated against the statistical Register of General Government Entities (S13) that is maintained by ELSTAT (for any mergers/abolitions). It is also enriched with government institutions belonging to S13 list, in cases of a clear evidence for the performance of R&D activities (information from GBARD surveys, eCORDA, NSRF national development programs etc.).
Inclusion of units that primarily do not belong to the frame population	No
Systematic exclusion of units from the process of updating the target population	No

3.7. Reference area

Not requested.

3.8. Coverage - Time

Not requested, see concept 12.3.3 (Data availability).

3.9. Base period

The base year for the unit Purchasing Power Standard (PPS) and PPS per inhabitant at constant prices is currently 2005. All calculations of non-basic unit (national currencies) are done by Eurostat.

R&D expenditure is published in the following units:  Euro (MIO_EUR) and Euro per inhabitant (EUR_HAB); data are available in the following units: basic unit National currency (MIO_NAC); Purchasing Power Standard (MIO_PPS); Purchasing Power Standard at 2005 prices (MIO_PPS_KP05); Purchasing Power Standard per inhabitant at constant 2005 prices (PPS_HAB_KP05); Percentage of gross domestic product (PC_GDP); and Percentage of total R&D expenditure (PC_TOT - for the breakdown by source of funds).

R&D personnel data are published in full-time equivalent (FTE), in head count (HC), as a percentage of total employment and as a percentage of active population.

For personnel: HC, FTE

For costs and funding: MIO_NAC (Millions of National Currency)

Reference year: 2023.

6.1. Institutional Mandate - legal acts and other agreements

See below.

6.1.1. European legislation

Legal acts / agreements:

Since the beginning of 2021, the collection of R&D statistics is based on Commission Implementing Regulation (EU) No 2020/1197 of 30 July 2020 laying down technical specifications and arrangements pursuant to Regulation (EU) 2019/2152 of the European Parliament and of the Council on European business statistics repealing 10 legal acts in the field of business statistics. The Regulation sets the framework for the collection of R&D statistics and specifies the main variables of interest and their breakdowns at predefined level of detail. The transmission of R&D data is mandatory for Member States and EEA countries.

The Commission Implementing Regulation (EU) No 2012/995 concerning the production and development of Community statistics on science and technology was in force until the end of 2020. 

EKT is an agency and a national authority of the Hellenic Statistical System (ELSS), responsible for the production of national statistics for Research, Development and Innovation (RDI) (see relevant decisions Hellenic Statistical Authority). EKT is engaged in the production of RDI statistics since 2012, taking the responsibility from the General Secretariat for Research and Innovation (relevant decision Government Gazette (FEK) 1359/Β/ 25 April 2012). From the beginning of its mandate and onwards, EKT is in close collaboration with EL.STAT. More specifically, EKT and ELSTAT are cooperating in the field of science and technology statistics in accordance with the relevant mutually signed MoUs (dated 28 January 2014, 04 June 2015, 15 December 2020 and 26 May 2022) EKT has recently participated as an ONA in the third round of ESS peer reviews and its compliance with the principles of the European Statistics Code of Practice was positively assessed.

6.1.2. National legislation

Existence of R&D specific statistical legislation	The production of national R&D statistics is governed by general national statistical legislation.
Are respondents obliged by the national law to provide raw and administrative data:	The production of national R&D statistics is governed by general national statistical legislation.

6.1.3. Standards and manuals

• Frascati Manual 2015, Guidelines for Collecting and Reporting Data on Research and Experimental Development
• European Business Statistics Methodological Manual on R&D Statistics

6.2. Institutional Mandate - data sharing

Not requested.

7.1. Confidentiality - policy

A property of data indicating the extent to which their unauthorised disclosure could be prejudicial or harmful to the interest of the source or other relevant parties.

At the level of the ESS the EU regulation 223/2009 on European statistics defines confidential data as data which allows statistical units (respondents) to be identified, either directly - by formal identifiers such as respondents’ names, addresses, identification numbers - or indirectly - by using a combination of variables or characteristics such as age, gender, education - thereby disclosing individual information (see Article 2(1)(e) of regulation 223/2009).

At national level: 

• Confidentiality protection required by law:

Confidentiality issues are clearly defined in the provisions on statistical confidentiality of the Greek statistical law (No. 3832/2010, as amended and in force), and are further specified in the Regulation on the Statistical Obligations of the Agencies of the ELSS.

As a National Authority Agency of the ELSS, EKT fully implements the above law and regulation as well as the European Statistics Code of Practice (principle 5 and relevant indicators). To this end, EKT has developed and published its Statistical Confidentiality Policy ( Statistical Confidentiality Policy ).

• Confidentiality commitments of survey staff:

The internal personnel employed in the RDI statistics unit at EKT, the external statistical correspondents used for the collection and checking of primary data of its statistical surveys, as well as the external experts providing EKT with technical support or being assigned to carry out statistical works on account of EKT, commit themselves to the observance of statistical confidentiality of the data to which they have access or which they handle and sign a statistical confidentiality declaration.

7.2. Confidentiality - data treatment

Concerning the Procedures to identify confidential cells in data delivered to Eurostat, no confidential suppression/protection was applied on GOV data.

8.1. Release calendar

Every year, during the first week of December EKT publishes a calendar of R&D Statistics press releases for the following year.

8.2. Release calendar access

For Eurostat this is: Release calendar - Eurostat (europa.eu)

The calendar is accessible by all users at the following link: Release Calendar

8.3. Release policy - user access

EKT provides equal and simultaneous access to its statistical products to all users, as mentioned in the Dissemination Policy it applies

(EKT_Policy_Dissemination_1.1_en.pdf ).

EKT is fully complying with the relevant principles and regulations of the Statistical Confidentiality Policy. The main source of information for all R&D statistics derived by EKT, accessible to all users, is the following page: R&D Data Collection by ECB

The frequency of R&D data dissemination at Eurostat level is yearly for provisional and final data.

10.1. Dissemination format - News release

See below.

10.1.1. Availability of the releases

	Availability (Y/N)1)	Links
Regular releases	Y	Each R&D data publication is accompanied with press releases, which are sent to all media in Greece as well as social media (Twitter, Facebook and LinkedIn) and are published in EKT’ s website. For 2023, the publications can be found at the following sites: Key R&D Indicators (provisional R&D results for 2023) Key Final R&D Indicators (final R&D results for 2023).
Ad-hoc releases	Y	At regular intervals, the organization issues ad-hoc publications, such as reports on regional data, on women's participation in R&D etc: ECB R&D Publications

1) Y - Yes, N – No

10.2. Dissemination format - Publications

See below.

10.2.1. Availability of means of dissemination

Means of dissemination	Availability (Y/N)1)	Links
General publication/article	Y	EKT operates a website dedicated to the dissemination and promotion of its statistical data: R&D Statistical Authority, recognisable by its “metrics” logo. This portal serves as the primary access point for EKT’s statistical information, providing unrestricted access to all users. The metrics site is also available via EKT’s main website, which reported approximately 170,000 unique users and roughly 420,000 page views in 2023. R&D data from EKT is available in several formats: 1) Publications (ECB Publications): These documents present key findings from R&D surveys, along with additional publications that offer in-depth analysis of specific topics. Most of these publications are also accessible in English. 2) Data Brief Reports (R&D Online Database): Concise publications that provide focused analyses of results on specific subjects. 3) EKT Biweekly Electronic Newsletter Articles: Sent to over 55,000 recipients, this newsletter includes articles covering current developments. 4) Social Media Releases: Updates are shared via EKT's accounts on X, Facebook, and LinkedIn, with the follower base exceeding 56,000 in 2023. 5) DATAHub@EKT Interactive Platform: EKT has introduced DATAHub@EKT, an integrated digital infrastructure designed to enhance the dissemination and analysis of its statistical data. This platform facilitates ease of access, comprehension, and application of EKT’s statistical resources, catering to policy makers, researchers, businesses, and other stakeholders. DATAHub@EKT supports the simplification, analysis, and effective utilisation of EKT’s statistical data and indicators.
Specific paper publication (e.g. sectoral provided to enterprises)	Y	Final R&D results for 2023: Final R&D Data

1) Y – Yes, N - No 

10.3. Dissemination format - online database

Data tables R&D Indicators

DATAHub@EKT Interactive Platform

(available only in Greek language).

 

10.3.1. Data tables - consultations

Not requested.

10.4. Dissemination format - microdata access

As Eurostat receives no R&D micro-data from the reporting countries, users should contact directly the respective national statistical institute (NSI) for access to the micro-data.

10.4.1. Provisions affecting the access

Access rights to the micro-data	Microdata access is not provided to users outside EKT. Upon user requests, we produce more detailed analysis compared to the analysis of data requested and transmitted to Eurostat. This analysis is still in aggregated form. Data are protected for confidentiality and aggregations are produced in such way as not to reveal the identity of the enterprises/institution.
Access cost policy	No charges
Micro-data anonymisation rules	Microdata access is not provided to users outside EKT. Upon user requests, we produce more detailed analysis compared to the analysis of data requested and transmitted to Eurostat. This analysis is still in aggregated form. Data are protected for confidentiality and aggregations are produced in such way as not to reveal the identity of the enterprises/institution.

10.5. Dissemination format - other

See below.

10.5.1. Metadata - consultations

Not requested.

10.5.2. Availability of other dissemination means

Dissemination means	Availability (Y/N)1)	Micro-data / Aggregate figures	Comments
Internet: main results available on the national statistical authority’s website	Y	Aggregate/ figures	R&D Indicators DATAHub@EKT Interactive Platform
Data prepared for individual ad hoc requests	Y	Aggregate/ figures	Upon request from NSRF and RIS monitoring authorities, policy makers, expert group meetings, etc.
Other	Y	Aggregate/ figures	Data presented in the form of short articles: ECB Datahub Data presented in conferences organised by EKT and targeting various audiences: Businesses, Researchers, academia, public e.tc. Conferences presentations can be accessed here: ECB Events

1) Y – Yes, N - No 

10.6. Documentation on methodology

The production of R&D statistics follows the FM 2015 concepts, definitions and methodology as well as Eurostat "FM2015 Implementation, Harmonization EU Guidelines" as updated. A detailed handbook on R&D collection processes has been developed (internal) for GOV sector and is continuously enriched and improved.

National metadata (SIMS v2.0, in Greek) are made available to all users in the dedicated EKT website:

National Metadata

10.6.1. Metadata completeness - rate

Not requested.

10.7. Quality management - documentation

See below.

10.7.1. Documentation and users’ requests

Type(s) of data accompanying information available (metadata, graphs, quality reports, etc.)

A glossary is available online to explain all the R&D related concepts to users of these statistics: Online Glossary  Reference material is also available online in the main page of the R&D statistics portal (English version: Main R&D Indicators). This page contains information about the aim of the survey, links to reference documents  (Commission Regulation, FM, etc.), all related publications and datatables and the link for the online R&D questionnaire. Access to the online questionnaire requires username and password, which details are sent to respondents along with the (email) survey invitation. Online helpdesk is also available for authorized users (i.e. respondents). However, the FAQ page is open to the public (Online Helpdesk). National metadata (SIMS v2.0, in Greek) are published in the dedicated EKT website: Online R&D Metadata Publication with graphs, tables, maps, etc. are also made available, containing also methodological notes about the survey. Finally, a detailed handbook on the production of GOV R&D statistics, coupled with methodological annexes, has been developed and is continuously enriched and improved.

Requests on further clarification, most problematic issues

No further requests for clarifications have been received.

11.1. Quality assurance

At Eurostat level, the common quality framework of the European Statistical System (ESS) is composed of the European Statistics Code of Practice, the Quality Assurance Framework of the ESS, and the general quality management principles (such as continuous interaction with users, continuous improvement, integration, and harmonisation).

EKT is an Agency of the Hellenic Statistical System (ELSS) and a National Authority, and as such it fully complies to the European and international standards concerning statistical methodologies, organizational procedures and IT infrastructure. EKT also complies strictly with the national and European legislative framework about statistics. EKT's quality policy is publicly available Quality Policy of ECB .

EKT follows the Generic Statistical Business Process Model (GSBPM) for the production of RDI statistics. Accordingly, the workflow of a typical GOV R&D collection follows all level 1 phases of the GSBPM model and level 2 sub processes, modified to meet the specific sector and data collection requirements. A detailed handbook on the production of GOV R&D statistics, coupled with methodological annexes, has been developed and is continuously enriched and improved.

The quality of the data that EKT collects is controlled through a carefully implemented procedure that guarantees the production of meaningful statistics. In particular, the following practices are in place to enhance data quality:

Designing of the statistical process: Before the collection begins, a thorough investigation of the actions needed to ensure the quality of the data is conducted. This includes a) registry updates, b) questionnaire updates, c) preparation of the relevant infrastructure, d) preparation of a calendar program, and e) the employment of external statistical correspondents to assist the collection.

Data collection – start of the collection period: At the beginning of the collection period, a request to complete the questionnaire is forwarded electronically to all respondents, through an online questionnaire completion tool (LimeSurvey). The request is accompanied by an official letter by EKT’s Director, detailed instructions on how to complete the questionnaire, as well as instructions on how to request guidance regarding the completion process. For this purpose, EKT operates an electronic Help Desk which provides definitions, glossaries, and completion instructions with representative examples for each questionnaire. In addition, respondents can electronically submit questions and comments in the system which are, in turn, monitored by EKT members who are responsible for providing the relevant feedback. It is important to note that LimeSurvey provides statistics that assist the monitoring of the collection process. For administrative data, separate requests are sent via emails to the corresponding government entities.

Data Processing: After the end of the collection period, the micro-data are passed through several, and more sophisticated, validation layers. For the analysis process for R&D statistics, a Data Management System (DMS) is in place, along with peripheral analytics tools such as Python and R libraries. The validation process includes tests with respect to: a) logical rules not provided in the online questionnaire, b) the time-series component, c) ratios (e.g., expenditure over the number of FTEs, etc.), d) cross-testing with data reported from other countries cross-testing with administrative data from external (to EKT) sources, and e) statistical tests (e.g., identification of outliers).

The indicators’ production is automatically implemented via a combination of the EKT’s DMS (Data Management System) and R/Python libraries. Indicators are monitored for their validity through a second layer of tests based on the aggregated data. The validation process includes basic logical tests, time series tests as well as distribution tests (e.g., R&D activities by region). Further, depending on their economic content, statistical outputs are additionally evaluated by EKT members with expertise on the field from other departments. The final SDMX file is tested and automatically corrected for rounding errors, through specific Python libraries.

The 3rd round of Peer Review on the Hellenic Statistical System, conducted and published by Eurostat , has confirmed the high standards maintained by the National Documentation Centre (EKT) in its statistical operations. The review specifically highlighted EKT’s strict adherence to the principles established in the European Statistics Code of Practice. As a National Authority responsible for Research, Development, and Innovation (RDI) European statistics, EKT actively participated in the peer review process. The assessment recognized EKT’s exemplary performance and its overall excellence in fulfilling its statistical responsibilities within the European framework.

11.2. Quality management - assessment

The guiding document to preparing the quality reports is the European Statistical System (ESS)  for Quality and Metadata Reports — re-edition 2021.

The overall quality of the GOV R&D statistical outputs is very good. The methodology has been designed in line with the FM recommendations, the relevant Commission Regulation and Eurostat guidelines. The continuous improvement is a key goal set by EKT and is implemented alongside the phases of the GSBPM model. Firstly, requirements of national users were met (such as the Hellenic Statistical Authority, the central /regional Monitoring Committees of the national development projects (NSRF projects) etc.).

The overall quality of the GOV R&D statistical outputs is very good. In 2015, EKT realized detailed case studies in 23 GOV institutions coming from all GOV R&D registry categories: Research Centers that are supervised by the General Secretariat for Research and Innovation (GSRI), Other Public Research Institutions supervised by different Ministries, Entities supervised by the Ministry of Culture (Ephorates of Antiquities, museums, etc.), Public hospitals, and Special Accounts of Research Funds operating at regional health directorates. The case studies were performed through site-visits and interviews with respondents, the following topics were investigated:

• the data collection methodology and the systems used by the institutions,
• the problems faced as well as probable measurement errors,
• best practices in data collection, and
• motives for respondents to participate in the survey.

Moreover, any comments made by the respondents in the relevant section of the R&D questionnaire, regarding the questionnaire’s structure or the clarity of the guidelines provided, were considered. Based on the results of the case studies as well as the respondents’ input, the structure of the online questionnaires was improved and the guidelines available to respondents through the RDI e-helpdesk operating at EKT, were enriched. For the RD survey round with reference year 2017, it is to be noted that the new methodological guidelines regarding the implementation of the FM 2015 were fully incorporated.

Overall, the respondents in 2023 GOV survey declared a satisfaction rate above 95%. 

EKT’s R&D Information System is based on relevant international standards, such as CERIF and SDMX, robust technologies and best practices. The R&D Statistics Information System serves the objectives of: a) R&D micro-data collection, b) Workflow-based statistical analysis, c) Validation of data, d) R&D indicators production, e) Benchmarking analysis with third party datasets, f) Dissemination of R&D statistics.

The desired functionality is achieved by four subsystems, namely the Organisation Registry (OR), the Online Data Collection System (ODCS), the DMS and the SDMX Reference Implementation.

It is important to note that several peripheral Python packages were, additionally, developed to support the DMS, for certain data processing and statistical needs:

• Monitoring: libraries and visualization tools to track the survey response process, monitoring both daily submission rates and the evolution of key R&D indicators.
• Additional layers of data validation:
  • Microdata level: a) cross-validation tests with respect to other sources (administrative data), b) time-series analyses using historical data from the R&D Survey, c) statistical tests (e.g., outlier detection and correlations between variables), d) logical and correctness tests.
  • Aggregate level: a) cross-validation tests with other countries’ data, b) logical and correctness tests (e.g., the total is equal to the sum of the components for each breakdown).
• Imputation and estimation tools: a) outlier corrections, b) strata imputation, c) variable estimation based on historical rates and strata rates (using linear programming techniques).   
• Calculation of statistical indicators: libraries to calculate all statistical indicators, including automated tools that correct for rounding errors (based on linear programming techniques).
• Interactive dashboard reporting: interactive visualization (e.g., bar charts) of the indicators (and their breakdowns) in absolute values and percentages and interactive comparison with data provided by other countries.

Relevance is the degree to which statistics meet current and potential users’ needs. It includes the production of all needed statistics and the extent to which concepts used (definitions, classifications etc.) reflect user needs. The aim is to describe the extent to which the statistics are useful to, and used by, the broadest array of users. For this purpose, statisticians need to compile information, firstly about their users (who they are, how many they are, how important is each one of them), secondly on their needs, and finally to assess how far these needs are met.

12.1. Relevance - User Needs

See below.

12.1.1. Needs at national level

Users’ class1)	Description of users	Users’ needs
1	Eurostat	Production of European statistics Data dissemination in Eurobase Eurostat's Online Database and in various publications Eurostat's STI Publications
1	European Commission, other European agencies	Policy making for R&D and Innovation. Especially the R&D intensity indicator is one of the longstanding indicators for R&D in Europe as well as one of the auxiliary indicators of the MIP Scoreboard. Moreover, SDG 9 goal includes RD intensity and RD personnel among its target indicators. EKT provides the national indicators on gender equality and was statistical correspondent for EC publication. See figures 2023.
1	OECD	Policy making for R&D and Innovation Publications and studies (Science, Technology and Industry Scoreboard, STI Outlook, etc.) with country comparisons and presentation of country profiles.
1	Hellenic Statistical Authority	Compilation of National Accounts in line with the revised European System of National and Regional Accounts (ESA 2010) (Commission Reg. 549/2013)
1	Greek Government	R&D Intensity is one of the indicators of the National Reform Program.
1	Ministry of Education, Religious Affairs and athletics, General Secretariat for Research and Innovation, other Ministries Ministry of Development, Regional Authorities, Central /regional Monitoring Committees of the NSRF national development projects etc.	Policy making and national strategic planning for R&D and Innovation, Monitoring of EU strategic targets (e.g. EU2020), Monitoring and evaluation of NSRF National Development Frameworks (the current “Partnership Agreement for the Development Framework 2014-2020” and the “Partnership Agreement for the Development Framework 2021-2027”), the Recovery and Resilience Fund (RRF) and of the Regional smart specialization policies (RIS) at national, regional and sectoral level
1	National Council for Research, Technology and Innovation (NCRTI)	Benchmarking, monitoring country's performance in Science and Technology and Innovation, monitoring GOV performance in Research, Technology and Innovation, evaluation and assessment of research outputs.
3	Media	Country performance in relation to other European countries, publication of main policy R&D indicators
4	Researchers, students	Analysis, subject-specific studies and/or regional studies, etc.

1)       Users' class codification

1- Institutions:

• European level: Commission (DGs, Secretariat General), Council, European Parliament, ECB, other European agencies etc.
• in Member States, at the national or regional level: Ministries of Economy or Finance, other ministries (for sectoral comparisons), National Statistical Institutes and other statistical agencies (norms, training, etc.), and
• International organisations: OECD, UN, IMF, ILO, etc.

2- Social actors: Employers’ associations, trade unions, lobbies, among others, at the European, national or regional level.

3- Media: International or regional media – specialized or for the general public – interested both in figures and analyses or comments. The media are the main channels of statistics to the general public.

4- Researchers and students (Researchers and students need statistics, analyses, ad hoc services, access to specific data.)

5- Enterprises or businesses (Either for their own market analysis, their marketing strategy (large enterprises) or because they offer consultancy services)

6- Other (User class defined for national purposes, different from the previous classes.)

12.2. Relevance - User Satisfaction

To evaluate if users' needs have been satisfied, the best way is to use user satisfaction surveys.

12.2.1. National Surveys and feedback

Conduction of a user satisfaction survey or any other type of monitoring user satisfaction	Users’ workshops/meetings are organized with key stakeholders and policy makers (General Secretariat for Research and Innovation, Ministry of Education, Religious Affairs and athletics, Ministry of Development and Investment, central /regional Monitoring Committees of the NSRF national development projects e.tc.) on a systematic base, at least twice a year. Feedback is taken into consideration in the R&D survey design. Furthermore, in the dedicated website of metrics.ekt.gr, users can also add their feedback and ask questions (Online Feedback Form). Also, this feedback is considered for future improvements and proposal of additional indicators. A wide user satisfaction survey was conducted in 2015. The survey consisted of two parts: a) electronic questionnaire, and b) interviews with most important/ key users (e.g. officials from the General Secretariat for Research and Innovation, key researchers). An additional real time source of information used by EKT is social media platforms. EKT monitors regularly comments across platforms like Facebook, Twitter, or Instagram to gather user feedback and measure satisfaction through direct user engagement. For instance, EKT identifies recurring themes in user comments, such as requests for new data requirements or additional clarifications.
User satisfaction survey specific for R&D statistics	The users’ workshops are focused on R&D statistics: the main results are presented and explained with additional information and breakdowns relevant to the national environment. As regards the user survey, the questionnaire provided separate questions for each set of RDI statistics: R&D, GBARD and Innovation statistics.
Short description of the feedback received	Users are overall very satisfied with the quality of the statistics produced. As a result of the workshops, some additional breakdowns have been added to the R&D questionnaires (for example data collection on HCs / FTEs of R&D personnel working in projects financed by the National Development Framework). At a wider audience, user survey results showed that R&D indicators are used at least once every three months and they are considered very important.

12.3. Completeness

See below.

12.3.1. Data completeness - rate

Mandatory variables: 100%

12.3.2. Completeness - overview

Completeness is assessed via comparison of the data delivered against the requirements of Commission Implementing Regulation (EU) No 2020/1197 of 30 July 2020. The Regulation (EU) stipulates periodicity of variables that should be provided, breakdowns and if they should be provided mandatory or on voluntary basis.

 

	Reasons for missing cells
Preliminary variables	Very Good
Obligatory data on R&D expenditure	Very Good
Optional data on R&D expenditure	Very Good
Obligatory data on R&D personnel	Very Good
Optional data on R&D personnel	Very Good
Regional data on R&D expenditure and R&D personnel	Very Good

12.3.3. Data availability

See below.

12.3.3.1. Data availability - R&D Expenditure

	Availability1)	Frequency of data collection	Gap years – years with missing data	Changes - Description	Changes - Year of introduction	Changes - Reasons
Source of funds	Y	Annual	2007	Additional break downs (internal / external, transfer exchange)	2020	2020_EL_RDI project Module 2.2
Type of R&D	Y-2011	Biennial		Annual frequency	2020
Type of costs	Y	Biennial	2007, 2009	Annual frequency Additional break downs (Other current costs / External R&D personnel, Other current costs / Other costs, Capitalized computer software, Other intellectual property products)	2020	2020_EL_RDI project Module 2.2
Socioeconomic objective	Y-2011	Biennial		Annual frequency	2020
Region	Y-2011	Biennial		Annual frequency	2020
FORD	Y-2011	Biennial		Annual frequency	2020
Type of institution	Y-2011	Annual		Additional break downs (Central government, Regional (or state) government, Local (or municipal government, Non-profit institutions controlled by government)	2020	2020_EL_RDI project Module 2.2

1) Y-start year, N – data not available

12.3.3.2. Data availability - R&D Personnel (HC)

	Availability1)	Frequency of data collection	Gap years – years with missing data	Changes - Description	Changes - Year of introduction	Changes - Reasons
Sex	Y-1999	Biennial	2007, 2009	Annual frequency	2011
Function	Y-1993	Biennial	2007, 2009	Annual frequency	2011
Qualification	Y-1993	Biennial	2007, 2009	Annual frequency	2011
Age	Y-2011	Biennial		Available for researchers only. Annual frequency after 2020	2011,2020
Citizenship	Y-2011	Biennial		Available for researchers only. Annual frequency after 2020	2011,2020
Region	Y-2011	Biennial		Annual frequency after 2020	2020
FORD	Y-2011	Biennial		Annual frequency after 2020	2020
Type of institution	Y-2011	Annual

1) Y-start year, N – data not available

12.3.3.3. Data availability - R&D Personnel (FTE)

	Availability1)	Frequency of data collection	Gap years – years with missing data	Changes - Description	Changes - Year of introduction	Changes - Reasons
Sex	Y-1999	Biennial	2009	Annual frequency	2011
Function	Y-1993	Biennial	2009	Annual frequency	2011
Qualification	Y-1993	Biennial	2009	Annual frequency	2011
Age	N
Citizenship	N
Region	Y-2011	Biennial		Annual frequency	2020
FORD	Y – 2011	Biennial		Annual frequency	2020
Type of institution	Y-2011	Annual		Annual frequency	2020

1) Y-start year, N – data not available

12.3.3.4. Data availability - other

Additional dimension/variable available at national level1)	Availability2)	Frequency of data collection	Breakdown variables	Combinations of breakdown variables	Level of detail
R&D Expenditure funded by GOV	Y-2011	Annual	a) Funds from the Ordinary Government Budget, b) Funds from the NSRF National Development Framework and Recovery and Resilience Fund (RRF), c) Public Investment Program (PIP) other than ESPA, d) Other (Regional Authorities, Municipalities, Special accounts, etc.)
Intramural R&D expenditure in specific fields of interest (and percentage financed by the government)	Y-2017	Annual	Fields of Research and Innovation Strategy for Smart Specialisation (RIS 3) in the following eight fields: Agri-food, Health – medicines, ICT, Energy, Environment and sustainable development, Transport, Materials – construction, Tourism – Culture – Creative industries.
Extramural R&D expenditure	Y-2013	Annual	Type of organization undertaken the R&D activity (private /public, national / abroad): a) Domestic enterprises (excl. banks and state-owned enterprises), b) Domestic banks, c) Domestic enterprises of the public sector, d) Domestic non-profit Institutions, e) Domestic other institutions of the public sector, f) Foreign enterprises, g) Other foreign institutions

1) This question is optional. It refers to variables and breakdowns NOT asked by the Commission Implementing Regulation (EU) No 2020/1197 (neither as 'optional').

2) Y-start year

12.3.3.5. R&D personnel - Cross-classification by function and qualification (if available in FTE and HC)

Cross-classification	Unit	Frequency
Yes	Both	Every year

13.1. Accuracy - overall

Accuracy in the statistical sense denotes the closeness of computations or estimates to the exact or true values. Statistics are not equal with the true values because of variability (the statistics change from implementation to implementation of the survey due to random effects) and bias (the average of the possible values of the statistics from implementation to implementation is not equal to the true value due to systematic effects).

Several types of statistical errors occur during the survey process. The following typology of errors has been adopted:

1. Sampling errors. These only affect sample surveys. They are due to the fact that only a subset of the population, usually randomly selected, is enumerated.

2. Non-sampling errors. Non-sampling errors affect sample surveys and complete enumerations alike and comprise:

a) Coverage errors,

b) Measurement errors,

c) Non response errors and

d) Processing errors.

Model assumption errors should be treated under the heading of the respective error they are trying to reduce.

13.1.1. Accuracy - Overall by 'Types of Error'

	Sampling errors1)	Non-sampling errors1)				Model-assumption Errors1)	Perceived direction of the error2)
		Coverage errors	Measurement errors	Processing errors	Non response errors
Total intramural R&D expenditure	-	3	1	4	3		+/-
Total R&D personnel in FTE	-	3	1	4	3		+/-
Researchers in FTE	-	3	1	4	3		+/-

1)  Ranking of the type(s) of errors that result in over/under-estimation, from the most important source of error (1) to the least important source of error (6). If errors of a particular type do not exist, the sign ‘:‘ is used.

2)  The perceived direction of the ‘overall’ error using the signs “+” for over estimation, “-” for under estimation and “+/-” when assumption of the direction of the error cannot be made for R&D.

13.1.2. Assessment of the accuracy with regard to the main indicators

Indicators	5 (Very Good)1)	4 (Good)2)	3 (Satisfactory)3)	2 (Poor)4)	1 (Very poor)5)
Total intramural R&D expenditure	x
Total R&D personnel in FTE	x
Researchers in FTE	x

1) 'Very Good' = High level of coverage (annual rate of substitution in the target population lower than 5%). High average rates of response (>80%) in census and sample surveys. Full data consistency with reference to totals and relationships between variables in the dataset sent to Eurostat.  

2) 'Good' = If at least one out of the three criteria described above is not fully met.

3) 'Satisfactory' = If the average rate of response is lower than 60%, even by meeting the two remaining criteria.

4) 'Poor' = If the average rate of response is lower than 60% and at least one of the two remaining criteria is not met.

5) 'Very Poor' = If all the three criteria are not met.

13.2. Sampling error

That part of the difference between a population value and an estimate thereof, derived from a random sample, which is due to the fact that only a subset of the population is enumerated.

13.2.1. Sampling error - indicators

See below. 

13.2.1.1. Variance Estimation Method

Not applicable. 

13.2.1.2. Confidence interval for R&D expenditure by source of funds

Source of funds	R&D expenditure
Business enterprise	Not applicable
Government	Not applicable
Higher education	Not applicable
Private non-profit	Not applicable
Rest of the world	Not applicable
Total	Not applicable

13.2.1.3. Confidence interval for R&D personnel by occupation and qualification

		R&D personnel (FTE)
Occupation	Researchers	Not applicable
	Technicians	Not applicable
	other support staff	Not applicable
Qualification	ISCED 8	Not applicable
	ISCED 5-7	Not applicable
	ISCED 4 and below	Not applicable

13.3. Non-sampling error

Non-sampling errors occur in all phases of a survey. They add to the sampling errors (if present) and contribute to decreasing overall accuracy. It is important to assess their relative weight in the total error and devote appropriate resources for their control and assessment.

13.3.1. Coverage error

Coverage errors are due to divergences between the target population and the frame population. The frame population is the set of target population members that has a chance to be selected into the survey sample. It is a listing of all items in the population from which the sample is drawn that contains contact details as well as sufficient information to perform stratification and sampling.

•  Description/assessment of coverage errors :There are minor divergences between target and frame population.

• Measures taken to reduce their effect: Not applicable.

• Share of PNP (if PNP is included in GOV): PNP is not included in GOV.

13.3.1.1. Over-coverage - rate

Not requested.

13.3.1.2. Common units - proportion

Not requested.

13.3.2. Measurement error

Measurement errors occur during data collection and generate bias by recording values different than the true ones (e.g. difficulty to distinguish intramural from extramural R&D Expenditure). The survey questionnaire used for data collection may have led to the recording of wrong values, or there may be respondent or interviewer bias.

• Description/assessment of measurement errors: The main difficulties that have been reported by respondents concerned a) the separation of R&D from other activities, b) the separation of in-house R&D performance from outsourcing activities, c) the breakdown of labour cost in all kinds of personnel.
• Measures taken to reduce their effect:
  • Guidelines have been included in the questionnaire and both electronic and telephone helpdesk was operating throughout the collection period to respond to enquiries by the respondents.
  • Moreover, in cases where measurement errors have been detected during the validation phase (e.g. very small R&D performance in relation to the enterprises turnover, inconsistencies between the personnel and expenditure data), enterprises have been contacted by experienced staff to clarify misunderstandings, etc.
  • In the electronic questioner a set of validation rules is added in order to help the respondents to complete the questioner. Also, a set of further information, guidelines and examples added in the electronic questioner in order to explain more the questions.
  • A detailed question with the breakdown of the personnel is added in order to allow respondents to clearly report all the categories of personnel (external, internal, full-time, part-time, etc) and its breakdowns HCs, FTEs, Education level, Age group, Nationality.
  • A detailed question about the labour costs of all personnel categories as explained above, which are then compared to the respective FTEs to assure the consistency of the reported figures.
  • A mandatory question relevant to R&D activities that can be answered as 'Yes/No' in order to proceed to the next section. The answers to these questions help respondents understand the concept of R&D and leads to the identification of R&D activities in their organization / enterprise.
  • Regional analysis is also separated by type of personnel (researchers and other staff) for HCs / FTEs as also R&D expenditures by region. Users have to report except the R&D expenditures per region also the HCs and FTEs separated by sex.

13.3.3. Non response error

Non-response occurs when a survey failed to collect data on all survey variables from all the population units designated for data collection in a sample or complete enumeration.

There are two elements of non-response:

• Unit non-response which occurs when no data (or so little as to be unusable) are collected on a designated population unit.
• Item non-response which occurs when data only on some, but not all survey variables are collected on a designated population unit.

The extent of response (and accordingly of non response) is also measured with response rates. 

13.3.3.1. Unit non-response - rate

The main interest is to judge if the response from the target population was satisfactory by computing the un-weighted response rate.

Definition: Eligible are the survey units which indeed belong to the target population. Frame imperfections always leave the possibility that some units may not belong to the target population. Moreover, when there is no contact with certain units and no other way to establish their eligibility they are characterised as ‘unknown eligibility units’.

Un-weighted Unit Non- Response Rate = [1 - (Number of units with a response) / (Total number of eligible and unknown eligibility units in the survey)] * 100

13.3.3.1.1. Un-weighted unit non-response rate

Number of units with a response in the survey	Total number of units in the survey	Unit non-response rate (Un-weighted)
250	259	3.47%  (All of the non-responding units belong to the perimeter of the GOV R&D Directory. The core GOV institutions with systematic R&D had a 100% response rate.)

13.3.3.2. Item non-response - rate

Definition:
Un-weighted Item Non-Response Rate (%) = [1-(Number of units with a response for the item) / (Total number of eligible, for the item, units in the sample)] * 100

13.3.3.2.1. Un-weighted item non-response rate

	R&D Expenditure	R&D Personnel (FTE)	Researchers (FTE)
Item non-response rate (un-weighted) (%)	0%	0%	0%
Comments

13.3.4. Processing error

Between data collection and the beginning of statistical analysis, data must undergo a certain processing: coding, data entry, data editing, imputation, etc. Errors introduced at these stages are called processing errors. Data editing identifies inconsistencies or errors in the data.

13.3.4.1. Identification of the main processing errors

Data entry method applied	No data entry errors since the online questionnaire has been used by all respondents.
Estimates of data entry errors	Not applicable.
Variables for which coding was performed	Not applicable.
Estimates of coding errors	Not applicable.
Editing process and method	Validation checks were embedded into the online questionnaire to inform users, in real time, about the occurrence of errors (check totals, sub-totals, totals between questions, no of FTEs vs no of HCs). In addition, extra controls were applied on the submitted data, using statistical software to cover other types of errors. Identified errors have been corrected as described below.
Procedure used to correct errors	In cases of 'important' errors respondents have been contacted by phone for correction/verification. In cases of less 'important' errors, values have been corrected with logical assumptions and imputation.

13.3.5. Model assumption error

Not requested.

14.1. Timeliness

Timeliness and punctuality refer to time and dates, but in a different manner: the timeliness of statistics reflects the length of time between their availability and the event or phenomenon they describe. Punctuality refers to the time lag between the release date of the data and the target date on which they should have been delivered, with reference to dates announced in the official release calendar.

14.1.1. Time lag - first result

Time lag between the end of reference period and the release date of the results:
Indicator: (Release date of provisional/ first results) - (Date of reference for the data)

• End of reference period: December 2023 (T)
• Date of first release of national data: October 2024 (T+10)
• Lag (days): 10 months (300 days)

14.1.2. Time lag - final result

• End of reference period: December 2023 (T)
• Date of first release of national data: June 2025 (T+18)
• Lag (days): 540 (18 months)

14.2. Punctuality

Punctuality refers to the time lag between the release date of data and the target date on which they were scheduled for release as announced officially.

14.2.1. Punctuality - delivery and publication

Punctuality of time schedule of data release = (Actual date of the data release) - (Scheduled date of the data release)

14.2.1.1. Deadline and date of data transmission

	Transmission of provisional data	Transmission of final data
Legally defined deadline of data transmission (T+_ months)	10	18
Actual date of transmission of the data (T+x months)	10	18
Delay (days)	0	0
Reasoning for delay	0	0

15.1. Comparability - geographical

See below.

15.1.1. Asymmetry for mirror flow statistics - coefficient

Not requested.

15.1.2. General issues of comparability

No deviations from FM recommendations and classifications. Therefore, R&D data for Greece are considered to be comparable with international R&D data.

15.1.3. Survey Concepts Issues

The following table lists a number of key survey concepts and conceptual issues; it gives reference to the Commission Implementing Regulation (EU) No 2020/1197, Frascati manual (FM) and EBS Methodological Manual on R&D Statistics paragraphs with recommendations about these concepts / issues.

 

Concept / Issues	Reference to recommendations	Deviation from recommendations	Comments on national definition / Treatment – deviations from recommendations
R&D personnel	FM2015 Chapter 5 (mainly sub-chapter 5.2).	No deviation.
Researcher	FM2015, § 5.35-5.39.	No deviation.
Approach to obtaining Headcount (HC) data	FM2015, § 5.58-5.61 (in combination with  Eurostat's EBS Methodological Manual on R&D Statistics).	No deviation.
Approach to obtaining FTE data	FM2015, § 5.49-5.57 (in combination with Eurostat's EBS Methodological Manual on R&D Statistics).	No deviation.	Starting from the 2017 survey, we provide detailed guidelines to R&D performing units to exclude personnel with less than 0.1 FTE of R&D activity. We also implement additional validation rules in the online questionnaire to ensure that these persons are not recorded.
Reporting data according to formula: Total R&D personnel = Internal R&D personnel + External R&D personnel	FM2015, §5.25	No deviation.	Total R&D personnel is divided into internal and external personnel. In the questionnaire we implement a more detailed division of R&D personnel into five groups, of which the first two groups (a and b) represent the internal personnel: a) regular personnel, b) temporary personnel, c) external associates, d) Greek University personnel and e) external associates who are paid by another organization/enterprise.   This detailed breakdown also improves the understanding of respondents.
Intramural R&D expenditure	FM2015, Chapter 4 (mainly sub-chapter 4.2).	No deviation.
Statistical unit	FM2015, § 8.64-8.65 (in combination with Eurostat's EBS Methodological Manual on R&D Statistics).	No deviation.
Target population	FM2015, § 8.63 (in combination with Eurostat's EBS Methodological Manual on R&D Statistics).	No deviation.
Sector coverage	FM2015, § 8.2-8.13 (in combination with Eurostat's EBS Methodological Manual on R&D Statistics).	No deviation.
Hospitals and clinics	FM2015, § 8.22 and 8.34	No deviation.
Borderline research institutions	FM2015, § 8.14-8.23 (in combination with Eurostat's EBS Methodological Manual on R&D Statistics).	No deviation.
Fields of research & development coverage and breakdown	Reg. 2020/1197 : Annex 1, Table 18	No deviation.
Socioeconomic objectives coverage and breakdown	Reg. 2020/1197 : Annex 1, Table 18	No deviation.
Reference period	Reg. 2020/1197 : Annex 1, Table 18	No deviation.

15.1.4. Deviations from recommendations

The following table lists a number of key methodological issues, which may affect the international comparability of national R&D statistics. The table gives the references in the Frascati manual (FM), where related recommendations are made. Countries are asked to report on the existence of any deviations from existing recommendations and comment upon.

Methodological issues	Reference to recommendations	Deviation from recommendations	Comments on national treatment / treatment deviations from recommendations
Data collection method	FM2015 Chapter 8 (mainly sub-chapter 8.5).	No deviation.
Survey questionnaire / data collection form	FM2015 Chapter 8 (mainly sub-chapter 8.5).	No deviation.
Cooperation with respondents	FM2015 Chapter (mainly sub-chapter 8.5).	No deviation.
Data processing methods	FM2015 Chapter 8 (mainly sub-chapters 8.5-8.6).	No deviation.
Treatment of non-response	FM2015 Chapter 8 (mainly sub-chapter 8.5).	No deviation.
Variance estimation	FM2015 Chapter 6 (mainly sub-chapter 6.7).		Not applicable
Data compilation of final and preliminary data	Reg. 2020/1197 : Annex 1, Table 18	No deviation.

15.2. Comparability - over time

See below.

15.2.1. Length of comparable time series

See below.

15.2.2. Breaks in time series

	Length of comparable time series	Break years1)	Nature of the breaks
R&D personnel (HC)	13 consequent years, starting from 2011.	2011,1983	2011: Coverage of GOV has been extended to also cover public hospitals as well as all institutions administered by the Ministry of Culture (mainly archaeological and cultural institutions). 1983: The methodology for identifying R&D personnel was brought into line with the recommendations of the FΜ, resulting in changes to personnel cost.
Function
Qualification
R&D personnel (FTE)	13 consequent years, starting from 2011.	2011,1983	2011: Coverage of GOV has been extended to also cover public hospitals as well as all institutions administered by the Ministry of Culture (archaeological and cultural institutions). 1983: The methodology for identifying R&D personnel was brought into line with the recommendations of the Frascati Manual, resulting in changes to personnel cost.
Function
Qualification
R&D expenditure	13 consequent years, starting from 2011.	2011	2011: Coverage of GOV has been extended to also cover public hospitals as well as all institutions administered by the Ministry of Culture (archaeological and cultural institutions).
Source of funds
Type of costs
Type of R&D
Other

1)       Breaks years are years for which data are not fully comparable to the previous period.

15.2.3. Collection of data in the even years

All data for R&D personnel (HC, FTE) and Expenditure are collected annually (odd and even years).

15.3. Coherence - cross domain

This part deals with any national coherence assessments which may have been undertaken. It reports results for variables which are the same or relevant to R&D statistics, from other national surveys and / or administrative sources and explains and comments on their degree of agreement with R&D statistics.

15.3.1. Coherence - sub annual and annual statistics

Not requested.

15.3.2. Coherence - National Accounts

Based on the MOU between ELSTAT and EKT, microdata are sent annually to ELSTAT for inclusion in the National Accounts.

15.4. Coherence - internal

See below.

15.4.1. Comparison between preliminary and final data

This part compares key R&D variables as preliminary and final data.

 

	Total R&D expenditure – GOVERD (in 1000 of national currency)	Total R&D personnel (in FTEs)	Total number of researchers(in FTEs)
Preliminary data (delivered at T+10)	705,416.81	16,990.78	9,837.31
Final data (delivered T+18)	707,860.14	16,948.44	9,855.14
Difference (of final data)	2,443.33	-42,34	17,83

Comments: No comments.

15.4.2. Consistency between R&D personnel and expenditure

	Average remuneration per year (cost in national currency)	Explanations of consistency issues, if any
Consistency between FTEs of internal R&D personnel and R&D labour costs (1)	26,394.34
Consistency between FTEs of external R&D personnel and other current costs for external R&D personnel (2)	16,838.88

(1)    Calculate the average remuneration (cost) of individuals belonging to the internal R&D personnel, excluding those who are only formally ‘employees’ (university students, grant holders, etc.).

(2)    Calculate the average remuneration (cost) of individuals belonging to the external R&D personnel (FTEs/other current R&D costs for external R&D personnel).

The assessment of costs associated with a statistical product is a rather complicated task since there must exist a mechanism for appointing portions of shared costs (for instance shared IT resources and dissemination channels) and overheads (office space, utility bills etc). The assessment must become detailed and clear enough so that international comparisons among agencies of different structures are feasible. 

16.1. Costs summary

	Costs for the statistical authority (in national currency)	Cost for the NSI in time use/person/day
Staff costs	Not available	Not available
Data collection costs	Not available	Not available
Other costs	Not available	Not available
Total costs	Not available	Not available

1)       The shares of the figures given in the first column that are accounted for by payments to private firms or other Government agencies.

Comments on costs:

16.2. Components of burden and description of how these estimates were reached

	Value	Computation method
Number of Respondents (R)	2.3	Information has been retrieved from a relevant question that is included in the questionnaire. Number of Respondents is calculated as the average persons per unit.
Average Time required to complete the questionnaire in hours (T)1)	12.4	Information has been retrieved from a relevant question that is included in the questionnaire. Average time is calculated as the average amount of hours needed to complete the survey, as reported by all responding units.
Average hourly cost (in national currency) of a respondent (C)	Not Available
Total cost	Not Available

1)        T = the time required to provide the information, including time spent assembling information prior to completing a form or taking part in interview and the time taken up by any subsequent contacts after receipt of the questionnaire (‘Re-contact time’)

17.1. Data revision - policy

Not requested.

17.2. Data revision - practice

Not requested.

17.2.1. Data revision - average size

Not requested.

18.1. Source data

Several separate activities are used for the collection of raw data or pre-compiled administrative data and statistics related to R&D. This section collects information on the type of data collection instruments used as well as methodological information for each data collection instrument. Depending on the type of data collection instrument used, only the sections corresponding to that data collection instrument are filled in.

18.1.1. Data source – general information

Survey name	GOV R&D survey – Personnel engaged and Expenditure spent on R&D activities
Type of survey	Census to all known or potential R&D performing units in the GOV.
Combination of sample survey and census data	Not applicable
Combination of dedicated R&D and other survey(s)	Direct census survey has been used for almost all GOV entities Especially for the entities supervised by the Ministry of Culture as well as public hospitals, with continuous and systematic R&D activities, a combination of census survey and administrative data collection from the Ministry of Culture and the Ministry of Health was used. Administrative data refer to the institutional funding by the Ordinary Budget allocated to the above entities. R&D activities funded by all other sources of funds (i.e. R&D projects financed by NSRF national programs, by EU, by companies, etc.), were provided through the direct census survey by the entities supervised by the Ministry of Culture and by the Special Accounts of Research Funds operating at regional health directorates (public hospitals).  Additional administrative sources (MIS information, eCORDA,) as well GBARD data were used for validation /imputation purposes.
Sub-population A (covered by sampling)	Not applicable.
Sub-population B (covered by census)	165 core institutions with systematic R&D activities 94 institutions with potential or occasional R&D activities
Variables the survey contributes to	All R&D variables requested by the Commission Regulation No 2020/1197 and additional voluntary variables as requested by Eurostat.

18.1.2. Sample/census survey information

Sampling unit	Government institutions (public research centers, archaeological and cultural institutions, public hospitals, agricultural institutions, etc)
Stratification variables (if any - for sample surveys only)	No stratification – census survey
Stratification variable classes	Not applicable
Population size	259 government institutions
Planned sample size	Not applicable
Sample selection mechanism (for sample surveys only)	Not applicable
Survey frame	Survey frame comprises all GOV institutions that are included in the “Directory of Greek R&D organizations” developed by EKT. The directory comprises all gov institutions systematically performing R&D activities (e.g. Greek research centers) and also those that potentially or occasionally perform R&D. The Directory is regularly updated through the statistical Register of General Government Entities that is maintained by ELSTAT which is updated annually to reflect changes in the perimeter of General Government, such as the inclusion of new entities, which are classified into General Government according to the ESA95 criteria as well as with the deletion of entities that either are abolished or cease to fulfill the criteria for remaining in the General Government sector.
Sample design	Not applicable
Sample size	Not applicable
Survey frame quality	Overall assessment is very good.
Variables the survey contributes to	All R&D variables requested by the Commission Regulation No 2020/1197 and additional voluntary variables as requested by Eurostat.

18.1.3. Information on collection of administrative data or of pre-compiled statistics

Source	The following sources are used: a) Detailed administrative information at institution level for the institutions supervised by from the Ministry of Education, Religious Affairs and athletics the Ministry of Culture, and the Ministry of Health as well as GBARD detailed data, b) Monitoring Information System (M.I.S.) including information about projects co-financed under the NSRF, c) eCORDA database with information about signed grants/beneficiaries with regards to EU research programs such as Horizon 2020, d) information provided by units that administer research projects (ELKEA) inside the six Health Region Administrations that operate in Greece for monitoring and managing private funding of clinical trials (primarily coming from pharmaceutical companies) conducted in public hospitals.
Description of collected data / statistics	R&D expenditure, where available. Total expenditures and total personnel where coefficients are applied to isolate the R&D component
Reference period, in relation to the variables the administrative source contributes to	Administrative data is available for reference period 2023
Variables the administrative source contributes to	All R&D variables requested by the Commission Regulation No 2020/1197 and additional voluntary variables as requested by Eurostat.

18.2. Frequency of data collection

See 12.3.3.

18.3. Data collection

See below.

18.3.1. Data collection overview

Information provider	1. GOV R&D survey R&D Expenditure and Personnel 2023: Data collection at micro level. Data were provided by GOV institutions which filled in the online questionnaires. 2. Detailed administrative information by the Ministry of Culture: Data collection at micro level. Data was provided, at institution level. 3.Survey to Special Accounts of Research Funds operating at regional health directorates: Data collection at micro level. Data was provided -via questionnaires by the Special Accounts of Research Funds operating at the seven regional health directorates of the country. Detailed administrative information: 4. Data collection at micro level. Data was provided, at institution level, by the Ministry of Health. 5. MIS / NSRF: Data collection at micro level. Data was provided at project /beneficiary level by the central Special Service for the MIS and by the NSRF monitoring service operating at the General Secretariat of Research and Innovation. 6. eCORDA: Data collection at micro level. EKT has access to eCORDA databases for downloads of raw data at project / beneficiary level.
Description of collected information	1. Information requested by the Regulation and additional/ more detailed breakdowns. 2. Detailed information, at institution level, for the personnel and expenditures funded by the Ordinary Budget (institutional funding) for the entities supervised by the Ministry of Culture. This data supplement the R&D data collected from the survey for these particular entities. 3. Administrative data collection. Detailed information, at institution level, for the personnel and expenditures funded by the Ordinary Budget (institutional funding) for the public hospitals that have systematic R&D activities. 4. Information about R&D projects financed by national development frameworks (ESPA 2014-2020, ESPA 2021-2027) and Recovery and Resilience Fund (RRF) at project /beneficiary level. The information has been used for validation / imputation purposes. 5. Information about R&D projects financed by EU research programs (Horizon Europe, Horizon 2020) at project /beneficiary level. The information has been used for validation / imputation purposes.
Data collection method	Data are collected with the use of online questionnaires filled out by the institutions. EKT has developed a special platform (LimeSurvey) for the implementation of the survey. Administrative data are collected for the institutions supervised by the Ministry of Education, Religious Affairs and athletics, the Ministry of Culture, and the Ministry of Health as well as GBAORD detailed. Administrative data are checked by the EKT before their use in statistical indices production.
Time-use surveys for the calculation of R&D coefficients	The latest time-use survey for the calculation of R&D coefficients of public hospitals took place in 2015.
Realised sample size (per stratum)
Mode of data collection (face-to-face interviews; telephone interviews; postal surveys, etc.)	Since 2012 (reference year 2011 onwards), this is an online survey. Every institution received, via e-mail, its ‘personal’ log-in details to access the online questionnaire. Institutions have the possibility to preview the questionnaire before completion. Frequently, EKT aids the institutions for the completion of the questionnaire via telephone interviews. Finally, several meetings have been realized with the directors of the institutions so as to further explain R&D concepts and variables in the questionnaire.
Incentives used for increasing response	Extensive communication with directors of institutions as well as official bodies (such as the Meetings of the Presidents of Research Centers). The survey is launched with an official letter, signed by the Director of EKT, that is attached to the e-mail invitations so as to explain the purpose and mandatory nature of the survey. The appropriate links to the online publications of EKT are also provided in the invitations to help respondents to better understand the use of the data they provide. Hard copies of the publications are also sent via post to the core group of systematic R&D performers.
Follow-up of non-respondents	Several email reminders. Systematic follow-up by phone and personal emails.
Replacement of non-respondents (e.g. if proxy interviewing is employed)	No replacement.
Response rate (ratio of completed "interviews" over total number of eligible enterprises or enterprises of unknown eligibility)	72% (2011) - Since this was the first time to run the survey after reference year 2005, our frame population covered exhaustively all government units that potentially have R&D activities. Most of the non-responding units (e.g. libraries) had no R&D activities and they are included in our GOV frame population as potential /occasional R&D performers. 98.3% for core institutions (2013) 100% for the core institutions (2015) 100% for the core institutions (2017) 100% for the core institutions (2019) 98.5% for the core institutions (2021) 100% for the core institutions (2023)
Non-response analysis (if applicable -- also see section 18.5.4 Data compilation - Weighting and Estimation methods)	Not applicable

18.3.2. Questionnaire and other documents

Annex	Name of the file
R&D national questionnaire and explanatory notes in English:	Not available
R&D national questionnaire and explanatory notes in the national language:	GOV_questionnaire_2023_EL.pdf
Other relevant documentation of national methodology in English:	Not available
Other relevant documentation of national methodology in the national language:

18.4. Data validation

Validation processes run throughout all phases of the R&D survey. All institutions belonging to the target population (GOV R&D Directory at EKT) are fully covered by a census survey. In order to eliminate any important missing information, an essential requirement of the R&D survey is to attain a 100% response rate by the core institutions of GOV R&D Directory, namely all GOV institutions which have a systematic R&D activity and contribute the major part of the final data (165 institutions). The administrative data that is used for the compilation of R&D data as well as for validation / imputation purposes come from official reliable sources at national (governmental / other authorities) or European level (eCORDA database). To ensure the validity of the data as completed by the respondents, validation checks are embedded into the online questionnaire to inform users, in real time, about the occurrence of errors (check totals, sub-totals, totals between questions, no of FTEs larger than no of HCs e.tc.). Any inconsistencies in the reported data are checked in each questionnaire received, namely at the institutional level, as for example FTEs of internal R&D personnel vs R&D labour costs considering the average remuneration cost for each sector, proportion of other current costs vs labour costs etc. Time series are also checked at the level of the each responding unit and item peaks are crosschecked both with respondents and administrative sources (for example a significant increase in EC funding for a reporting unit is checked with the eCORDA database and communicated and verified by the respondent). Thorough validation is carried out to check the coherence of the outputs produced. To this end, in addition to the extensive statistical checking, multiple official sources are used (as explained above, MIS data, eCORDA, etc.) to check the collected data against relevant data. The final outputs are interpreted using both tangible and tacit knowledge accumulated at EKT as well as sectoral studies produced by other national bodies.

18.5. Data compilation

See below.

18.5.1. Imputation - rate

Imputation is the method of creating plausible (but artificial) substitute values for all those missing.
Definition:
Imputation rate (for the variable x) % = (Number of imputed records for the variable x) * 100/ (Total number of possible records for x)

 

No imputation was used for GOV 2023.

18.5.2. Data compilation methods

Data compilation method - Final data	Not applicable – the R&D survey is conducted every year
Data compilation method - Preliminary data	Not applicable – the R&D survey is conducted every year

18.5.3. Measurement issues

Method of derivation of regional data	Questionnaires for all sectors included separate questions for the regional element of R&D Personnel and R&D expenditure. Respondents are asked to distribute total R&D personnel (headcounts and FTE by sex), Researchers (headcounts and FTE by sex) and total intramural expenditure into the 13 Greek regions (NUTS2).
Coefficients used for estimation of the R&D share of more general expenditure items	In the GOV sector and based on the information available, coefficients have been applied in some cases where R&D is part of the institutions activities funded by the ordinary budget. The purpose is to reduce response burden and at the same time increase data reliability. The data quality is very good. No R&D coefficients are applied for the estimation of R&D activities funded by other sources than the Ordinary Budget (such as EC, NSRF, etc.) for which data are collected directly by the responding GOV units.
Inclusion or exclusion of VAT and provisions for depreciation in the measurement of expenditures	In line with the FM, respondents were asked to exclude VAT and depreciation from R&D expenditures.

18.5.4. Weighting and estimation methods

Description of weighting method	No weighting has been applied in GOV.
Description of the estimation method	Estimations for unit non-response were made using data from official (administrative) sources.

18.6. Adjustment

Not requested.

18.6.1. Seasonal adjustment

Not requested.

GOV_questionnaire_2023_EL

Statistics on Government R&D (GOVERD) measure research and experimental development (R&D) performed in the Government sector, i.e. R&D expenditure and R&D personnel. In line with this objective the target population for the national R&D survey of the Government sector should consist of all R&D performing units (including all R&D performers – occasional and continuous, known and unknown - in all branches and size classes) belonging to this sector.

Main concepts and definitions used for the production of R&D statistics are given by the OECD (2015), Frascati Manual 2015: Guidelines for Collecting and Reporting Data on Research and Experimental Development, The Measurement of Scientific, Technological and Innovation Activities, which is the internationally recognised standard methodology for collecting R&D statistics and by the European Business Statistics Methodological Manual on R&D Statistics (EBS Methodological Manual on R&D Statistics). 

The guiding document to preparing the quality reports is the European Statistical System (ESS)  Handbook for Quality and Metadata Reports — re-edition 2021.

Since the beginning of 2021, the collection of R&D statistics is based on Commission Implementing Regulation (EU) No 2020/1197 of 30 July 2020. The Regulation sets the framework for the collection of R&D statistics and specifies the main variables of interest and their breakdowns at predefined level of detail.

29 October 2025

See below.

The statistical unit is the institutional unit as defined by Council Regulation (EEC) No 1993/696 of 15 March 1993.

Government institutions as listed in the statistical Register of General Government Entities (S13) that is maintained by ELSTAT (Hellenic Statistical Authority). Merges/ abolitions of institutions are regularly checked and statistical units are modified accordingly.

See below.

Not requested.

Reference year: 2023.

Accuracy in the statistical sense denotes the closeness of computations or estimates to the exact or true values. Statistics are not equal with the true values because of variability (the statistics change from implementation to implementation of the survey due to random effects) and bias (the average of the possible values of the statistics from implementation to implementation is not equal to the true value due to systematic effects).

Several types of statistical errors occur during the survey process. The following typology of errors has been adopted:

1. Sampling errors. These only affect sample surveys. They are due to the fact that only a subset of the population, usually randomly selected, is enumerated.

2. Non-sampling errors. Non-sampling errors affect sample surveys and complete enumerations alike and comprise:

a) Coverage errors,

b) Measurement errors,

c) Non response errors and

d) Processing errors.

Model assumption errors should be treated under the heading of the respective error they are trying to reduce.

R&D expenditure is published in the following units:  Euro (MIO_EUR) and Euro per inhabitant (EUR_HAB); data are available in the following units: basic unit National currency (MIO_NAC); Purchasing Power Standard (MIO_PPS); Purchasing Power Standard at 2005 prices (MIO_PPS_KP05); Purchasing Power Standard per inhabitant at constant 2005 prices (PPS_HAB_KP05); Percentage of gross domestic product (PC_GDP); and Percentage of total R&D expenditure (PC_TOT - for the breakdown by source of funds).

R&D personnel data are published in full-time equivalent (FTE), in head count (HC), as a percentage of total employment and as a percentage of active population.

For personnel: HC, FTE

For costs and funding: MIO_NAC (Millions of National Currency)

See below.

Several separate activities are used for the collection of raw data or pre-compiled administrative data and statistics related to R&D. This section collects information on the type of data collection instruments used as well as methodological information for each data collection instrument. Depending on the type of data collection instrument used, only the sections corresponding to that data collection instrument are filled in.

The frequency of R&D data dissemination at Eurostat level is yearly for provisional and final data.

Timeliness and punctuality refer to time and dates, but in a different manner: the timeliness of statistics reflects the length of time between their availability and the event or phenomenon they describe. Punctuality refers to the time lag between the release date of the data and the target date on which they should have been delivered, with reference to dates announced in the official release calendar.

See below.

See below.