Research and development (R&D) (rd)

See below.

1.1. Contact organisation

Statistical Office of the Republic of Slovenia (SURS).

1.2. Contact organisation unit

Demography and Social Statistics Division, Social Services Statistics Section

1.3. Contact name

Restricted from publication

1.4. Contact person function

Restricted from publication

1.5. Contact mail address

Litostrojska cesta 54, 1000 Ljubljana, Slovenija

1.6. Contact email address

Restricted from publication

1.7. Contact phone number

Restricted from publication

1.8. Contact fax number

Restricted from publication

31 July 2025

2.1. Metadata last certified

31 July 2025

2.2. Metadata last posted

31 July 2025

2.3. Metadata last update

31 July 2025

See below.

3.1. Data description

Statistics on Business enterprise R&D (BERD) measure research and experimental development (R&D) performed in the business enterprise 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 business enterprise sector consists of all R&D performing enterprises (including all R&D performers – occasional and continuous, known and unknown - in all branches and size classes) belonging to this sector. The “enterprise” is defined in Council Regulation (EEC) No 1993/696 of 15 March 1993. The results are related to the population of all R&D performing enterprises classified in Sections A to U of the common statistical classification of economic activities as established by Regulation (EC) No 1893/2006 of the European Parliament and of the Council (NACE Rev.2).

The main concepts and definitions used for the production of R&D statistics are given by 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 Eurostat’s 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) 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 distribution of principal economic activity and by industry orientation are based on Statistical classification of economic activities in the European Community (NACE Rev. 2);
The local unit for the statistics are compiled at regional level according to NUTS 2 – Nomenclature of Territorial Units for Statistics;
The distribution by socioeconomic objectives (SEO) are 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

Business enterprise sector (BES)	The business enterprise sector is defined according to the Frascati Manual (FM) and is in line with SNA standards. The target population consists of known and assumed R&D-performing units within this sector.
Hospitals and clinics	University hospitals and medical centres associated with higher education institutions are included in HES, other hospitals and medical centres are included in the GOV.
Inclusion of units that primarily do not belong to BES and the borderline cases.	In the BES sector are not included units that primery not belong to it.

3.3.3. R&D variable coverage

R&D administration and other support activities	Management and administration support: Specific R&D management and administration support: Specific R&D management and administration supports, which are closely associated with R&D projects, are included in R&D personnel and in R&D current expenditure. Indirect R&D management and administration: Indirect R&D management and administration both are not included in R&D personnel, but their corresponding costs are included in other current expenditure as overheads. Library: Unit specific libraries: The purchase of books, magazines for unit specific libraries is included in other current expenditure. The purchase of buildings is included in capital expenditure. The personnel employed in these libraries are included in other R&D personnel. Their labour costs are included in current R&D expenditure. Central libraries: Central libraries are included in R&D. Computing departments: Unit-specific computing departments: Computer services related directly to R&D are included in R&D. Corresponding personnel is included in other R&D personnel, their labour costs are included in current R&D expenditure. Central computing departments: Central computing departments are not included in R&D. Other ancillary services: Other ancillary services (security, maintenance, cleaning, etc.) are included in other current expenditure as overheads.
External R&D personnel	The coverage of external R&D personnel is in line with FM recommendations. Self-employed consultants, employees of other units hired as R&D consultants, doctoral/master`s but only if they are on the university payroll or if they are employed as university assistants or as other scientific staff with the main purpose of working in research projects.
Clinical trials: compliance with the recommendations in FM §2.61.	Clinical trials phases 1, 2 and 3 are treated as R&D activities, while phase 4 of clinical trials is not. Phase 4 of clinical trials is not included in R&D, except in cases that contribute to further scientific of technological advances. However, in the methodological guidelines for reporting units there are no special instructions about it.

R&D administration and other support activities

Management and administration support:

Specific R&D management and administration support: Specific R&D management and administration supports, which are closely associated with R&D projects, are included in R&D personnel and in R&D current expenditure.
Indirect R&D management and administration: Indirect R&D management and administration both are not included in R&D personnel, but their corresponding costs are included in other current expenditure as overheads.

Library:

Unit specific libraries: The purchase of books, magazines for unit specific libraries is included in other current expenditure. The purchase of buildings is included in capital expenditure. The personnel employed in these libraries are included in other R&D personnel. Their labour costs are included in current R&D expenditure.
Central libraries: Central libraries are included in R&D.

Computing departments:

Unit-specific computing departments: Computer services related directly to R&D are included in R&D. Corresponding personnel is included in other R&D personnel, their labour costs are included in current R&D expenditure.
Central computing departments: Central computing departments are not included in R&D.
Other ancillary services: Other ancillary services (security, maintenance, cleaning, etc.) are included in other current expenditure as overheads.

External R&D personnel

The coverage of external R&D personnel is in line with FM recommendations. Self-employed consultants, employees of other units hired as R&D consultants, doctoral/master`s but only if they are on the university payroll or if they are employed as university assistants or as other scientific staff with the main purpose of working in research projects.

Clinical trials: compliance with the recommendations in FM §2.61.

Clinical trials phases 1, 2 and 3 are treated as R&D activities, while phase 4 of clinical trials is not. Phase 4 of clinical trials is not included in R&D, except in cases that contribute to further scientific of technological advances. However, in the methodological guidelines for reporting units there are no special instructions about it.

3.3.4. International R&D transactions

Receipts from rest of the world by sector - availability	Receipts and payments from abroad (i.e. Rest of the World) by sector are available.
Payments to rest of the world by sector - availability	Payments to abroad by sector are available. Extramural R&D expenditures are inquired about and can be distinguished for institutions abroad by the following categories: to foreign affiliates, to other enterprises, to foreign universities and research institutions of HES, to other PNP research organisations, to international organisations and to others.
Intramural R&D expenditure in foreign-controlled enterprises – coverage	R&D expenditures of foreign affiliates are not covered, except in cases if foreign affiliates are funded nationally.

Receipts from rest of the world by sector - availability

Receipts and payments from abroad (i.e. Rest of the World) by sector are available.

Payments to rest of the world by sector - availability

Payments to abroad by sector are available.

Extramural R&D expenditures are inquired about and can be distinguished for institutions abroad by the following categories: to foreign affiliates, to other enterprises, to foreign universities and research institutions of HES, to other PNP research organisations, to international organisations and to others.

Intramural R&D expenditure in foreign-controlled enterprises – coverage

R&D expenditures of foreign affiliates are not covered, except in cases if foreign affiliates are funded nationally.

3.3.5. Extramural R&D expenditures

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

Data collection on extramural R&D expenditure (Yes/No)	Yes. Data on extramural R&D expenditures are available and can be distinguished according to following categories: domestic: to small enterprises, to medium-sized enterprises, to large enterprises, to public research institutions (without institutions of HES), public higher education institutions, others, foreign: (i.e. institutions abroad): to foreign affiliates, to other enterprises, to foreign univerities and research institutions of HES, to other private-non profit research organisations, to international organisations, to others.
Method for separating extramural R&D expenditure from intramural R&D expenditure	The questionnaire includes a separate question/table on extramural R&D expenditure, along with additional clarifications to assist reporting units.
Difficulties to distinguish intramural from extramural R&D expenditure	Some difficulties were detected, mainly for the borderline cases.

Data collection on extramural R&D expenditure (Yes/No)

Yes.

Data on extramural R&D expenditures are available and can be distinguished according to following categories:

domestic: to small enterprises, to medium-sized enterprises, to large enterprises, to public research institutions (without institutions of HES), public higher education institutions, others,
foreign: (i.e. institutions abroad): to foreign affiliates, to other enterprises, to foreign univerities and research institutions of HES, to other private-non profit research organisations, to international organisations, to others.

Method for separating extramural R&D expenditure from intramural R&D expenditure

The questionnaire includes a separate question/table on extramural R&D expenditure, along with additional clarifications to assist reporting units.

Difficulties to distinguish intramural from extramural R&D expenditure

Some difficulties were detected, mainly for the borderline cases.

3.4. Statistical concepts and definitions

See below.

3.4.1. R&D expenditure

Coverage of years	Calendar year.
Source of funds	R&D expenditures are classified by source of funds into five sectors: business enterprise, government, higher education, private non-profit and abroad. All these categories are broken down into sub-categories.
Type of R&D	All three types of R&D (basic research, applied research and experimental development) are included.
Type of costs	In line with FM 2015 four types of costs are distinguished: labour costs, other current costs and capital expenditures (land and buildings, instruments and equipments, capitalised computer software and other intellectual property products). All these categories are broken down into sub-categories.
Economic activity of the unit	Units are classified according to the NACE Rev. 2 and ISIC classifications.
Economic activity of industry served (for enterprises in ISIC/NACE 72)	Units are classified according to the NACE Rev. 2 and ISIC classifications.
Product field	Not used.
Defence R&D - method for obtaining data on R&D expenditure	It is covered.

3.4.2. R&D personnel

See below.

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

Coverage of years	Calendar year.
Function	Data on R&D personnel by occupation group (researcher, technicians and equivalent staff, other supporting staff) in head counts (HC) and sex are available.
Qualification	Data on R&D personnel by qualification (level) (doctoral or equivalent, short cycle tertiary, bachelor, master or equivalent, other level of education) in head counts (HC) and sex are available for all occupation groups.
Age	Data on R&D personnel by age (group) in head counts (HC) are available only for researchers.
Citizenship	Data on R&D personnel by citizenship (group) in head counts (HC) are available only for researchers.

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

Coverage of years	Calendar year.
Function	Data on R&D personnel by occupation (group) (researcher, technicians and equivalent staff, other supporting staff) in full time equivalents (FTE) and sex are available.
Qualification	Data on R&D personnel by qualification in full time equivalents (FTE) are not available.
Age	Data on R&D personnel by age (group) in full time equivalents (FTE) are not available.
Citizenship	Data on R&D personnel by citizenship (group) in full time equivalents (FTE) are not available.

3.4.2.3. FTE calculation

The following formula is used for calculating the FTE:

FTE = N × T × M

Where:

N = number of persons
T = proportion of time spent on R&D
M = proportion of the year worked (months/12)

The following are examples used for calculating Full-Time Equivalents (FTE):

1 researcher working full-time (100%) in R&D all year:
1 × 1 × 1 = 1.0 FTE
3 researchers working half-time (50%) in R&D all year:
3 × 0.5 × 1 = 1.5 FTE
2 researchers working 20% of their time in R&D throughout the year:
2 × 0.2 × 1 = 0.4 FTE
1 researcher working full-time (100%) for half the year:
1 × 1 × (6/12) = 0.5 FTE
2 researchers working 25% of their time in R&D for 8 months:
2 × 0.25 × (8/12) = 0.33 FTE

3.5. Statistical unit

The statistical unit for BERD is the enterprise as defined by Council Regulation (EEC) No 1993/696 of 15 March 1993, if there are deviations please explain.

3.6. Statistical population

See below.

3.6.1. National target population

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 Business Enterprise Sector should consist of all R&D performing enterprises (including all R&D performers – occasional and continuous, known and unknown - in all branches and size classes) belonging to this sector. In practice however, countries in their R&D surveys might exclude some enterprises for which R&D activities are deemed to be non-existent or negligible, in order to limit the response burden or due to budgetary constraints.

	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	National target population includes all potential R&D performing units (in all branches and size classes) in the Republic of Slovenia belonging to business enterprise sector.	Not applicable.
Estimation of the target population size	Regular and occasional R&D performers both are included.	Not applicable.
Size cut-off point	All size classes are included.	Not applicable.
Size classes covered (and if different for some industries/services)	Size classes are covered in line with FM 2015 recommendations.	Not applicable.
NACE/ISIC classes covered	NACE/ISIC classes are covered in line with FM 2015 recommendations.	Not applicable.

3.6.2. Frame population – Description

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.

Method used to define the frame population	Data sources used for identifying (known or supposed) R&D performers are: Statistical Business Register (Statistical Office of the Republic of Slovenia) - business entities, their subsidiaries and other divisions of business entities, registered for performing R&D activities (as covered by NACE Rev. 2 Division 72); List of recipients of state aid for investment in R&D (Ministry of Finance); List of business entities liable to general and regional tax incentives for R&D investments (Financial Administration of the Republic of Slovenia); The Community Innovation Survey (CIS) (Statistical Office of the Republic of Slovenia); Slovenian Current Research Information System (SICRIS) (Slovenian Research Agency).
Methods and data sources used for identifying a unit as known or supposed R&D performer	There is no any special method applied for inclusions R&D performers not known and not supposed to perform R&D.
Inclusion of units that primarily do not belong to the frame population	Units that primery do not belong in the BES sector are not included.
Frequency and the methods applied for inclusion R&D performers not known and not supposed to perform R&D	No specific method was applied to identify R&D performers that are not known or not assumed to perform R&D. It is assumed that all R&D-performing units are included in the data sources used for identification, and that any unknown or missed performers are few and their contribution to total R&D activity is negligible.
Number of “new”¹⁾ R&D enterprises that have been identified and included in the target population	The initial (gross) sample for the BES sector varies between approximately 2,000 and 2,100 units on an annual basis, with the term 'initial (gross) sample' referring to all units selected for the survey, including both eligible and ineligible entities.
Systematic exclusion of units from the process of updating the target population	Within the process of updating the target population certain units are (systematically) excluded: units operating regularly, but were not R&D active for three consecutive years; ineligible units (i.e. units deleted from the Business Register; units registered for performing R&D activities (NACE Rev. 72) with fewer than 2 persons in paid employment and were not among the recipients of state aid for R&D investments) or were not liable to any tax incentives for R&D investments).
Estimation of the frame population	2045 (BES sector initial sample)

1) i.e. enterprises previously not known or not supposed to perform R&D

3.7. Reference area

Not requested. R&D statistics cover national and regional data.

3.8. Coverage - Time

Not requested, see concept 12.3.3. (data availability).

3.9. Base period

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 this report, data from the calendar year 2023 was used as the reference period.

See below.

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 the 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. Regulation No 2020/1197 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.

6.1.2. National legislation

Existence of R&D specific statistical legislation	There is no legislation specific to R&D statistics. However, the collection of R&D data is conducted under the National Statistical Act, which provides the legal basis for all official statistical surveys.
Are respondents obliged by the national law to provide raw and administrative data:	Respondents are obliged under the National Statistics Act to complete and submit statistical questionnaires, including those related to R&D. Administrative data is typically not collected directly from respondents, but rather obtained from relevant public records and institutions.

6.1.3. Standards and manuals

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

6.2. Institutional Mandate - data sharing

Not requested.

See below.

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: The National Statistics Act requires that all data collected for statistical purposes be strictly confidential and used exclusively for statistical analysis. The Act prohibits the disclosure of individual data and ensures that no information can be traced back to a specific reporting unit.
Confidentiality commitments of survey staff: All staff involved in statistical data collection, processing, and dissemination are legally bound by confidentiality obligations under the National Statistics Act.

7.2. Confidentiality - data treatment

All R&D data collected are treated as confidential and are used only for statistical purposes. By following general statistical confidentiality framework used by the Statistical Office of the Republic of Slovenia (SURS), statistics can be published only in aggregate form, i.e. in a manner that does not allow recognition of the unit to which data relate. Identifiable information can be published only exceptionally in cases where the unit gives its written consent to publish it. More information on statistical confidentiality is available on the official website under the section Statistical confidentiality.

See below.

8.1. Release calendar

Release calendar is publicly accessible.

8.2. Release calendar access

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

8.3. Release policy - user access

All data and metadata information are published and are accessible to users through various channels; among them is the most important website. The information on the website is available free of charge and is also available at English, for the widest possible use that is actively promoted.

The release policy deternines the dissemination of statistical data to all users at the same time.

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

See below.

10.1. Dissemination format - News release

See below.

10.1.1. Availability of the releases

	Availability (Y/N)¹⁾	Links
Regular releases	Y	R&D data are disseminated annually through one preliminary and one final release. The preliminary and final release are published on the Official Website of the Statistical Office. The final data are also made available in the SI-STAT Database. The same data that are published nationally are also transmitted to Eurostat, ensuring full consistency. Press releases (in the form of article) YES (Language: ENG, SI) Press conferences NO Public database (final data) YES (Language: ENG, SI) Eurostat transmission YES Paid or restricted access NO
Ad-hoc releases	N

Availability (Y/N)¹⁾

Links

Regular releases

R&D data are disseminated annually through one preliminary and one final release. The preliminary and final release are published on the Official Website of the Statistical Office. The final data are also made available in the SI-STAT Database. The same data that are published nationally are also transmitted to Eurostat, ensuring full consistency.

Press releases (in the form of article) YES (Language: ENG, SI)
Press conferences NO
Public database (final data) YES (Language: ENG, SI)
Eurostat transmission YES
Paid or restricted access NO

Ad-hoc releases

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	Final data are released together with a short accompanying text on the official website of the Statistical Office.
Specific paper publication (e.g. sectoral provided to enterprises)	N

1) Y – Yes, N - No

10.3. Dissemination format - online database

The disseminated data are available in the official database of the Statistical Office, namely the SI-STAT Database. The data are accessible in both Slovenian and English.

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	The statistical office enables researchers to access data for the purpose of research. Access to micro-level data must be requested; more information is available on the official website.
Access cost policy	Free of charge.
Micro-data anonymisation rules	Micro-data are anonymised to ensure that individual respondents cannot be identified. All direct and indirect identifiers are removed or masked before data access is granted, in compliance with the National Statistics Act requirements.

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	Data on R&D are published in the First Release and at a more detailed level in the SiStat database.
Data prepared for individual ad hoc requests	Y	Aggregate figures
Other	N

1) Y – Yes, N - No

10.6. Documentation on methodology

Methodological materials are available on the official website under the section Questionnaires, Methodological Explanations, Quality Reports.

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.)	With each annual release of final data, the methodological explanations and the quality report are published to ensure transparency and data reliability.
Requests on further clarification, most problematic issues	To date, no significant requests for further clarification or issues have been reported.

See below.

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).

11.2. Quality management - assessment

Overall quality of R&D statistics is good.

The coverage of reporting units is full. R&D statistics domain follow general quality management activities used in SURS (including the European Statistics Code of Practice and the Fundamental Principles of Official Statistics). Detailed methodological instructions for completing questionnaire are available. Data validation is performed in collaboration with reporting units. Discussion of results, substantive matters and key issues are points on the agenda or the subjects under discussion of the Research and Development, and Technology Statistics Advisory Committee.

However, there are still some aspects to be improved at R&D statistics. Despite the available methodological guidelines and instructions reporting units still have some problems with recognizing their R&D performance, understanding the R&D definitions, identifying an capturing the real/proper R&D content of activities and corresponding items. Most of the reporting units do not have records tailored to survey reporting, so they often make use of estimates without considering the substantive relevance between the items.

In the R&D statistics domain’s quality assurance activities are guaranteed through:

clear and well-structured survey questionnaire with detailed methodological instructions for its completion;
single point for communicating with business entities regarding the submission of data (i.e. Contact Center);
good competences of Call Center staff and personnel responsible for data editing (training before the questionnaires are sent to the reporting units);
good cooperation with the reporting units during data collection phase;
computer control programs for input data;
feedback from key reporting units and data users;

continuous updating and improvement of methodological instructions in the light of past experience.

See below.

12.1. Relevance - User Needs

See below.

12.1.1. Needs at national level

Users’ class¹⁾	Description of users	Users’ needs
1-International organizations	OECD
1-National level	Ministries, UMAR (The Institute of Macroeconomic Analysis and Development)

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	The Statistical Office of the Republic of Slovenia (SURS) measured general user satisfaction in 2024. Overall satisfaction with SURS’s products and services reached an average score of 8.4, trust in the institution 8.8, and trust in the data 8.7 (on a scale from 1 – disagree completely to 10 – agree completely).
User satisfaction survey specific for R&D statistics	A dedicated user satisfaction survey focusing exclusively on R&D statistics is not currently conducted.
Short description of the feedback received	R&D statistics falls within the scope of the Statistical Advisory Committee on Research and Development Activities and Technologies. More information on the operation of the Committe is available on the following website Statistical Advisory Community on R&D (in Slovene only).

12.3. Completeness

See below.

12.3.1. Data completeness - rate

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.

	Reasons for missing cells
Preliminary variables	All required data were submitted, and voluntary data were provided where available.
Obligatory data on R&D expenditure	All required data have been transmitted.
Optional data on R&D expenditure	Optional data have been transmitted where available.
Obligatory data on R&D personnel	All required data have been transmitted.
Optional data on R&D personnel	Optional data have been transmitted where available.
Regional data on R&D expenditure and R&D personnel	All required data have been transmitted.

12.3.3. Data availability

See below.

12.3.3.1. Data availability - R&D Expenditure

	Availability¹⁾	Frequency of data collection
Source of funds	Y	Annual
Type of R&D	Y	Annual
Type of costs	Y	Annual
Socioeconomic objective	N	Does not apply
Region	Y	Annual
FORD	Y	Annual
Type of institution	N	Does not apply

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

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

	Availability¹⁾	Frequency of data collection
Sex	Y	Annual
Function	Y	Annual
Qualification	Y	Annual
Age	Y (only for researchers)	Annual
Citizenship	Y (only for researchers)	Annual
Region	Y	Annual
FORD	Y	Annual
Type of institution	N	Does not apply
Economic activity	Y	Annual
Product field	N	Does not apply
Employment size class	Y	Annual

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

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

	Availability¹⁾	Frequency of data collection
Sex	Y	Annual
Function	Y	Annual
Qualification	N	Does not apply
Age	N	Does not apply
Citizenship	N	Does not apply
Region	Y	Annual
FORD	Y	Annual
Type of institution	N	Does not apply
Economic activity	Y	Annual
Product field	N	Does not apply
Employment size class	Y	Annual

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
Does not apply.

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'), if R&D data for BES are collected for additional breakdowns or/and at more detailed level than requested.

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
Does not apply.

See below.

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⁾
	Sampling errors¹⁾	Coverage errors	Measurement errors	Processing errors	Non response errors	Model-assumption Errors¹⁾	Perceived direction of the error²⁾
Total intramural R&D expenditure	:					Does not apply.
Total R&D personnel in FTE	:					Does not apply.
Researchers in FTE	:					Does not apply.

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 (BES R&D). 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 key variables by NACE

	Industry sector¹⁾	Services sector²⁾	TOTAL
R&D expenditure	Does not apply.	Does not apply.	Does not apply.
R&D personnel (FTE)	Does not apply.	Does not apply.	Does not apply.

1) Industry sector (NACE Rev. 2: 01-03, 05-09, 10-33, 35, 36-39, 41-43)

2) Services sector (NACE Rev 2.: 45-47, 49-53, 55-56, 58-63, 64-66, 68, 69-75, 77-82, 84, 85, 86-88, 90-93, 94-96, 97-98, 99)

13.2.1.3. Confidence interval for key variables by Size Class

	0-9 employees and self-employed persons (optional)	10-49 employees and self-employed persons	50-249 employees and self-employed persons	250- and more employees and self-employed persons	TOTAL
R&D expenditure	Does not apply.	Does not apply.	Does not apply.	Does not apply.	Does not apply.
R&D personnel (FTE)	Does not apply.	Does not apply.	Does not apply.	Does not apply.	Does not apply.

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 (or frame 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: All known institutions are included in the survey. Participation in the survey is mandatory. Coverage error is not expected, as the target population and the surveyed units are identical. It is assumed that all hunits are captured in the sample. In the unlikely event that any unit was omitted, its contribution to total R&D expenditure and employment would be minor and negligible.
Measures taken to reduce their effect: Does not apply.

13.3.1.1. Over-coverage - rate

Not requested.

13.3.1.2. Common units - proportion

Not requested.

13.3.1.3. Frame misclassification rate

Misclassification rate measures the percentage of enterprises that changed stratum between the time the frame was last updated and the time the survey was carried out. It is defined as the number of enterprises that changed stratum divided by the number of enterprises which belong to the stratum, according to the frame. The rate can be estimated based on the characteristics of the surveyed enterprises.

Not applicable

By size class for the Industry Sector (NACE Rev. 2: 01-03, 05-09, 10-33, 35, 36-39, 41-43)	0-9 employees and self-employed persons (optional)	10-49 employees and self-employed persons	50-249 employees and self-employed persons	250-and more employees and self-employed persons	TOTAL
Number or surveyed enterprises in the stratum (according to frame)
Number of surveyed enterprises that have changed stratum (after inspection of their characteristics)
Misclassification rate
By size class for the Services Sector (NACE Rev 2.: 45-47, 49-53, 55-56, 58-63, 64-66 68, 69-75, 77-82, 84, 85, 86-88, 90-93, 94-96, 97-98, 99)	0-9 employees and self-employed persons (optional)	10-49 employees and self-employed persons	50-249 employees and self-employed persons	250-and more employees and self-employed persons	TOTAL
Number or surveyed enterprises in the stratum (according to frame)
Number of surveyed enterprises that have changed stratum (after inspection of their characteristics)
Misclassification rate

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: Measurement errors in the survey may arise when the questionnaire is completed by multiple individuals or organizational units, or by someone who lacks detailed knowledge of R&D activities. Additional sources of error include non-compliance with methodological instructions and the reliance on subjective assessments. These factors can result in inconsistent or unreliable responses.
Measures taken to reduce their effect: The web questionnaire includes built-in validation and consistency checks to ensure logical and complete responses. Responding units are recontacted if anomalies are detected in the data.

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 satisfying by computing the weighted and un-weighted response rate.

Definition:

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

Definition:

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
Weighted Unit Non- Response Rate = [1 - (Total weighted responding units) / (Total weighted number of eligible / unknown eligibility units in the sample)] * 100

13.3.3.1.1. Unit non-response rates by Size Class

	0-9 employees and self-employed persons (optional)	10-49 employees and self-employed persons	50-249 employees and self-employed persons	250-and more employees and self-employed persons	TOTAL
Number of units with a response in the realised sample	749	662	498	216	2170
Total number of units in the sample*	946	732	528	226	2432
Unit Non-response rate (un-weighted)	16%	10%	6%	4%	11%
Unit Non-response rate (weighted)	Does not apply.	Does not apply.	Does not apply.	Does not apply.	Does not apply.

Data are only available for the overall R&D survey and cannot be provided separately for the individual sectors (BES, GOV, HES, and PNP).

*The initial (grosse) sample in 2023 included 2,454 units. On yearly basis about 1% of units are uneligible. The sample consists of Legal Units.

13.3.3.1.2. Unit non-response rates by NACE

	Industry¹⁾	Services²⁾	TOTAL
Number of units with a response in the realised sample	824	1346	2170
Total number of units in the sample*	902	1530	2432
Unit Non-response rate (un-weighted)	9%	12%	11%
Unit Non-response rate (weighted)	Does not apply.	Does not apply.	Does not apply.

1) Industry (NACE Rev. 2: 01-03, 05-09,10-33,35,36-39,41-43)

2) Services (NACE Rev 2.: 45-47, 49-53, 55-56, 58-63, 64-66 68, 69-75, 77-82, 84, 85, 86-88, 90-93, 94-96, 97-98, 99)

Data are only available for the overall R&D survey and cannot be provided separately for the individual sectors (BES, GOV, HES, and PNP).

*The initial (grosse) sample in 2023 included 2,454 units. On yearly basis about 1% of units are uneligible. The sample consists of Legal Units.

13.3.3.1.3. Recalls/Reminders description

Units that did not submit data on time are reminded by a reminder.

13.3.3.1.4. Unit non-response survey

Conduction of a non-response survey	So far we have not conducted any non-response survey at R&D statistics.
Selection of the sample of non-respondents	Not applicable
Data collection method employed	Not applicable
Response rate of this type of survey	Not applicable
The main reasons of non-response identified	Main reason of non-response is that reporting unit did not carry out R&D activities in the reference period.

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%
Imputation (Y/N)	N	N	N
If imputed, describe method used, mentioning which auxiliary information or stratification is used	Does not apply.	Does not apply.	Does not apply.

13.3.3.3. Magnitude of errors due to non-response

	Magnitude of error (%) due to non-response
Total intramural R&D expenditure	Not available
Total R&D personnel in FTE	Not available
Researchers in FTE	Not available

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	Data collection is conducted through an online questionnaire deployed via eSTAT, the official web-based data collection platform of the Statistical Office used for all surveys. The questionnaire includes a comprehensive set of built-in validation and consistency checks designed to minimize measurement errors, prevent logical inconsistencies, and ensure completeness at the point of entry. This approach supports the collection of high-quality, reliable data from the outset.
Estimates of data entry errors	Does not apply.
Variables for which coding was performed	Does not apply.
Estimates of coding errors	Does not apply.
Editing process and method	Does not apply.
Procedure used to correct errors	Once the questionnaire is submitted, the data undergo additional automated validation procedures (referred to as logical controls). Any anomalies or inconsistencies identified during this phase are systematically verified through recontact with the reporting units. No further data editing is performed beyond these follow-ups, ensuring the integrity and transparency of the data collection process.

13.3.5. Model assumption error

Not requested.

See below.

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: 31 December 2023
Date of first release of national data: 5 November 2024
Lag (days): 305

14.1.2. Time lag - final result

End of reference period: 31 December 2023
Date of first release of national data: 5 March 2025
Lag (days): 425

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

See below.

15.1. Comparability - geographical

This sub-concept refers to the geographical comparability of data among the 27 Member States and the EFTA and Candidate Countries.

15.1.1. Asymmetry for mirror flow statistics - coefficient

Not requested.

15.1.2. General issues of comparability

No issues have been identified. National R&D statistics are produced in accordance with the Frascati Manual methodology.

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 or 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
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 Full-time equivalence (FTE) data	FM2015, §5.49-5.57 (in combination with Eurostat’s EBS Methodological Manual on R&D Statistics).	No deviation
Reporting data according to formula: Total R&D personnel = Internal R&D personnel + External R&D personnel	FM2015, §5.25	No deviation
Intramural R&D expenditure	FM2015 Chapter 4 (mainly sub-chapter 4.2).	No deviation
Special treatment for NACE 72 enterprises	FM2015, § 7.59.	No deviation
Statistical unit	FM2015 Chapter 7 (mainly paragraphs 7.3 and 7.7 in combination with Eurostat's EBS Methodological Manual on R&D Statistics).	No deviation
Target population	FM2015 Chapter 7 (mainly sub-chapter 7.7 in combination with Eurostat's EBS Methodological Manual on R&D Statistics).	No deviation
Identification of not known R&D performing or supposed to perform R&D enterprises	FM2015 Chapter 7 (mainly sub-chapter 7.7 in combination with Eurostat's EBS Methodological Manual on R&D Statistics).	No deviation
Sector coverage	FM2015 Chapter 3 (mainly sub-chapter 3.5) in combination with Eurostat's EBS Methodological Manual on R&D Statistics).	No deviation
NACE coverage and breakdown	Reg. 2020/1197 : Annex 1, Table 18	No deviation
Enterprise size coverage and breakdown	Reg. 2020/1197 : Annex 1, Table 18	No deviation
Reference period for the main data	Reg. 2020/1197 : Annex 1, Table 18	No deviation
Reference period for all data	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
Data collection preparation activities	FM2015 Chapter 7 (mainly sub-chapter 7.7).	No deviation
Data collection method	FM2015 Chapter 7 (mainly sub-chapter 7.7).	No deviation
Cooperation with respondents	FM2015 Chapter 7 (mainly sub-chapter 7.7).	No deviation
Follow-up of non-respondents	FM2015 Chapter 7 (mainly sub-chapter 7.7).	No deviation
Data processing methods	FM2015 Chapter 6 (mainly sub-chapter 6.7).	No deviation
Treatment of non-response	FM2015 Chapter 6 (mainly sub-chapter 6.7).	No deviation
Data weighting	FM2015 Chapter 7 (mainly sub-chapter 7.7).	No deviation
Variance estimation	FM2015 Chapter 6 (mainly sub-chapter 6.9).	No deviation
Data compilation of final and preliminary data	Reg. 2020/1197 : Annex 1, Table 18	No deviation
Survey type	FM2015 Chapter 6 (mainly sub-chapter 6.4).	No deviation
Sample design	FM2015 Chapter 6 (mainly sub-chapter 6.4).	No deviation
Survey questionnaire	FM2015 Chapter 6 (mainly sub-chapter 6.4).	No deviation

15.2. Comparability - over time

For more information related to the break years and the nature of the breaks, see the following sub-concepts in the full metadata view.

15.2.1. Length of comparable time series

See below.

15.2.2. Breaks in time series

	Break years¹⁾	Nature of the breaks
R&D personnel (HC)	2011, 2017	With the data for 2011 new administrative sources were introduced in the survey on R&D, which enabled additional identification of (potential) R&D performers and thus improved sample unit coverage. At the same time, weighting adjustment for non-response was also introduced in the survey on R&D. By both reasons values of R&D activity in all sectors of performance increased. With data for 2017 some methodological changes were introduced in the R&D survey as a result of the Frascati methodology harmonisation and at the same time statistical data protection was also introduced to the R&D survey. Following methodological changes were introduced: the extended definition of the higher education sector (in addition to higher education institutions, higher vocational institutions are included) is applied, private researchers are involved in a part of the BES (previously part of the PNP), non-profit institutions providing services for households (S.15) are involved in a part of the PNP (previously part of the BES), in the presentation of R&D personnel in the head counts (HC), both internal and external R&D personnel are included (previously only internal R&D personnel), data on the occupation of R&D personnel have three categories (researchers, technicians and equivalent staff, other supporting staff), while in previous years occupation referred to five categories (researchers, professional staff, technical staff, management personnel, other supporting staff).
Function	2011, 2017	With the data for 2011 new administrative sources were introduced in the survey on R&D, which enabled additional identification of (potential) R&D performers and thus improved sample unit coverage. At the same time, weighting adjustment for non-response was also introduced in the survey on R&D. By both reasons values of R&D activity in all sectors of performance increased. With data for 2017 some methodological changes were introduced in the R&D survey as a result of the Frascati methodology harmonisation and at the same time statistical data protection was also introduced to the R&D survey. Following methodological changes were introduced: the extended definition of the higher education sector (in addition to higher education institutions, higher vocational institutions are included) is applied, private researchers are involved in a part of the BES (previously part of the PNP), non-profit institutions providing services for households (S.15) are involved in a part of the PNP (previously part of the BES), in the presentation of R&D personnel in the head counts (HC), both internal and external R&D personnel are included (previously only internal R&D personnel), data on the occupation of R&D personnel have three categories (researchers, technicians and equivalent staff, other supporting staff), while in previous years occupation referred to five categories (researchers, professional staff, technical staff, management personnel, other supporting staff).
Qualification	2011, 2017	With the data for 2011 new administrative sources were introduced in the survey on R&D, which enabled additional identification of (potential) R&D performers and thus improved sample unit coverage. At the same time, weighting adjustment for non-response was also introduced in the survey on R&D. By both reasons values of R&D activity in all sectors of performance increased. With data for 2017 some methodological changes were introduced in the R&D survey as a result of the Frascati methodology harmonisation and at the same time statistical data protection was also introduced to the R&D survey. Following methodological changes were introduced: the extended definition of the higher education sector (in addition to higher education institutions, higher vocational institutions are included) is applied, private researchers are involved in a part of the BES (previously part of the PNP), non-profit institutions providing services for households (S.15) are involved in a part of the PNP (previously part of the BES), in the presentation of R&D personnel in the head counts (HC), both internal and external R&D personnel are included (previously only internal R&D personnel), data on the occupation of R&D personnel have three categories (researchers, technicians and equivalent staff, other supporting staff), while in previous years occupation referred to five categories (researchers, professional staff, technical staff, management personnel, other supporting staff).
R&D personnel (FTE)	1994, 2011, 2017	With the data for 2011 new administrative sources were introduced in the survey on R&D, which enabled additional identification of (potential) R&D performers and thus improved sample unit coverage. At the same time, weighting adjustment for non-response was also introduced in the survey on R&D. By both reasons values of R&D activity in all sectors of performance increased. With data for 2017 some methodological changes were introduced in the R&D survey as a result of the Frascati methodology harmonisation and at the same time statistical data protection was also introduced to the R&D survey. Following methodological changes were introduced: the extended definition of the higher education sector (in addition to higher education institutions, higher vocational institutions are included) is applied, private researchers are involved in a part of the BES (previously part of the PNP), non-profit institutions providing services for households (S.15) are involved in a part of the PNP (previously part of the BES), in the presentation of R&D personnel in the head counts (HC), both internal and external R&D personnel are included (previously only internal R&D personnel), data on the occupation of R&D personnel have three categories (researchers, technicians and equivalent staff, other supporting staff), while in previous years occupation referred to five categories (researchers, professional staff, technical staff, management personnel, other supporting staff).
Function	1993-1995, 2011, 2017	With the data for 2011 new administrative sources were introduced in the survey on R&D, which enabled additional identification of (potential) R&D performers and thus improved sample unit coverage. At the same time, weighting adjustment for non-response was also introduced in the survey on R&D. By both reasons values of R&D activity in all sectors of performance increased. With data for 2017 some methodological changes were introduced in the R&D survey as a result of the Frascati methodology harmonisation and at the same time statistical data protection was also introduced to the R&D survey. Following methodological changes were introduced: the extended definition of the higher education sector (in addition to higher education institutions, higher vocational institutions are included) is applied, private researchers are involved in a part of the BES (previously part of the PNP), non-profit institutions providing services for households (S.15) are involved in a part of the PNP (previously part of the BES), in the presentation of R&D personnel in the head counts (HC), both internal and external R&D personnel are included (previously only internal R&D personnel), data on the occupation of R&D personnel have three categories (researchers, technicians and equivalent staff, other supporting staff), while in previous years occupation referred to five categories (researchers, professional staff, technical staff, management personnel, other supporting staff).
Qualification	2011, 2017	With the data for 2011 new administrative sources were introduced in the survey on R&D, which enabled additional identification of (potential) R&D performers and thus improved sample unit coverage. At the same time, weighting adjustment for non-response was also introduced in the survey on R&D. By both reasons values of R&D activity in all sectors of performance increased. With data for 2017 some methodological changes were introduced in the R&D survey as a result of the Frascati methodology harmonisation and at the same time statistical data protection was also introduced to the R&D survey. Following methodological changes were introduced: the extended definition of the higher education sector (in addition to higher education institutions, higher vocational institutions are included) is applied, private researchers are involved in a part of the BES (previously part of the PNP), non-profit institutions providing services for households (S.15) are involved in a part of the PNP (previously part of the BES), in the presentation of R&D personnel in the head counts (HC), both internal and external R&D personnel are included (previously only internal R&D personnel), data on the occupation of R&D personnel have three categories (researchers, technicians and equivalent staff, other supporting staff), while in previous years occupation referred to five categories (researchers, professional staff, technical staff, management personnel, other supporting staff).
R&D expenditure	2011, 2017	With the data for 2011 new administrative sources were introduced in the survey on R&D, which enabled additional identification of (potential) R&D performers and thus improved sample unit coverage. At the same time, weighting adjustment for non-response was also introduced in the survey on R&D. By both reasons values of R&D activity in all sectors of performance increased. With data for 2017 some methodological changes were introduced in the R&D survey as a result of the Frascati methodology harmonisation and at the same time statistical data protection was also introduced to the R&D survey. Following methodological changes were introduced: the extended definition of the higher education sector (in addition to higher education institutions, higher vocational institutions are included) is applied, private researchers are involved in a part of the BES (previously part of the PNP), non-profit institutions providing services for households (S.15) are involved in a part of the PNP (previously part of the BES), in the presentation of R&D personnel in the head counts (HC), both internal and external R&D personnel are included (previously only internal R&D personnel), data on the occupation of R&D personnel have three categories (researchers, technicians and equivalent staff, other supporting staff), while in previous years occupation referred to five categories (researchers, professional staff, technical staff, management personnel, other supporting staff).
Source of funds	2011, 2017	With the data for 2011 new administrative sources were introduced in the survey on R&D, which enabled additional identification of (potential) R&D performers and thus improved sample unit coverage. At the same time, weighting adjustment for non-response was also introduced in the survey on R&D. By both reasons values of R&D activity in all sectors of performance increased. With data for 2017 some methodological changes were introduced in the R&D survey as a result of the Frascati methodology harmonisation and at the same time statistical data protection was also introduced to the R&D survey. Following methodological changes were introduced: the extended definition of the higher education sector (in addition to higher education institutions, higher vocational institutions are included) is applied, private researchers are involved in a part of the BES (previously part of the PNP), non-profit institutions providing services for households (S.15) are involved in a part of the PNP (previously part of the BES), in the presentation of R&D personnel in the head counts (HC), both internal and external R&D personnel are included (previously only internal R&D personnel), data on the occupation of R&D personnel have three categories (researchers, technicians and equivalent staff, other supporting staff), while in previous years occupation referred to five categories (researchers, professional staff, technical staff, management personnel, other supporting staff).
Type of costs	2011, 2017	With the data for 2011 new administrative sources were introduced in the survey on R&D, which enabled additional identification of (potential) R&D performers and thus improved sample unit coverage. At the same time, weighting adjustment for non-response was also introduced in the survey on R&D. By both reasons values of R&D activity in all sectors of performance increased. With data for 2017 some methodological changes were introduced in the R&D survey as a result of the Frascati methodology harmonisation and at the same time statistical data protection was also introduced to the R&D survey. Following methodological changes were introduced: the extended definition of the higher education sector (in addition to higher education institutions, higher vocational institutions are included) is applied, private researchers are involved in a part of the BES (previously part of the PNP), non-profit institutions providing services for households (S.15) are involved in a part of the PNP (previously part of the BES), in the presentation of R&D personnel in the head counts (HC), both internal and external R&D personnel are included (previously only internal R&D personnel), data on the occupation of R&D personnel have three categories (researchers, technicians and equivalent staff, other supporting staff), while in previous years occupation referred to five categories (researchers, professional staff, technical staff, management personnel, other supporting staff).
Type of R&D	2011, 2017	With the data for 2011 new administrative sources were introduced in the survey on R&D, which enabled additional identification of (potential) R&D performers and thus improved sample unit coverage. At the same time, weighting adjustment for non-response was also introduced in the survey on R&D. By both reasons values of R&D activity in all sectors of performance increased. With data for 2017 some methodological changes were introduced in the R&D survey as a result of the Frascati methodology harmonisation and at the same time statistical data protection was also introduced to the R&D survey. Following methodological changes were introduced: the extended definition of the higher education sector (in addition to higher education institutions, higher vocational institutions are included) is applied, private researchers are involved in a part of the BES (previously part of the PNP), non-profit institutions providing services for households (S.15) are involved in a part of the PNP (previously part of the BES), in the presentation of R&D personnel in the head counts (HC), both internal and external R&D personnel are included (previously only internal R&D personnel), data on the occupation of R&D personnel have three categories (researchers, technicians and equivalent staff, other supporting staff), while in previous years occupation referred to five categories (researchers, professional staff, technical staff, management personnel, other supporting staff).
Other	does not apply	does not apply

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

Data are produced in the same way every year.

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. Intramural R&D expenditure (code 230101 in the Commission Implementing Regulation (EU) 2020/1197) and R&D personnel (code 230201) are surveyed also in foreign-controlled EU enterprises statistics (inward FATS).

The Community innovation survey also collects the R&D expenditure of enterprises that form the coverage of the CIS survey.

15.3.1. Coherence - sub annual and annual statistics

Not requested.

15.3.2. Coherence - National Accounts

Not available.

15.3.3. National Coherence Assessments

Variable name	R&D Statistics - Variable Value	Other national statistics - Variable value	Other national statistics - Source	Difference in values (of R&D statistics)	Explanation of / comments on difference
Not applicable	Not applicable	Not applicable	Not applicable	Not applicable	Not applicable

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 (in 1000 of national currency)	Total R&D personnel (in FTEs)	Total number of researchers (in FTEs)
Preliminary data (delivered at T+10)	938,471	11,268	6,688.5
Final data (delivered T+18)	938,471	11,268	6,688.5
Difference (of final data)	0	0	0

Comments :

15.4.2. Consistency between R&D personnel and expenditure

	Average remuneration per year (cost in national currency)	Explanation of consistency issues if any
Consistency between FTEs of internal R&D personnel and R&D labour costs (1)	Not available
Consistency between FTEs of external R&D personnel and other current costs for external R&D personnel (2)	Not available

(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 separately available.	Not separately available.
Data collection costs	Not separately available.	Not separately available.
Other costs	Not separately available.	Not separately available.
Total costs	Not separately available.	Not separately available.

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: Expenditure data are not disaggregated by sector of performance. The R&D survey is fully implemented by the Statistical Office of the Republic of Slovenia.

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

	Value	Computation method
Number of Respondents (R)
Average Time required to complete the questionnaire in hours (T)¹	Not separately available.
Average hourly cost (in national currency) of a respondent (C)	Not separately available.
Total cost	Not separately 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’)

See below.

17.1. Data revision - policy

Not requested.

17.2. Data revision - practice

Not requested.

17.2.1. Data revision - average size

Not requested.

See below.

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

R&D data for the Business Enterprise Sector (BES) sector are collected through the national survey Research and development activity by performers (eng.) - (the offical name in Slovenian language: Razvojno raziskovalna dejavnost pri izvajalcih). All known R&D performers are covered by the survey. The sample is constructed using administrative records to identify eligible units and ensure their inclusion. Given this approach, it is assumed that the entire population is fully captured. In the unlikely event that a unit is omitted, its impact on total R&D expenditure and employment estimates would be minor and negligible.

The survey is conducted annually and uses a single questionnaire to collect R&D data across all sectors, including BES. The survey does not rely on administrative data for the collection of R&D expenditure or personnel data—only direct reporting from units is used. Participation in the survey is mandatory for all reporting units, as required by the national statistical legislation. Units are formally invited in writing to participate and are required to complete the questionnaire independently—no interviewers are involved. Data are submitted via an online questionnaire, which includes detailed instructions and guidance for proper completion.

For additional support, a call center is available to assist with methodological questions, and technical assistance is offered to resolve any platform-related issues. If units do not submit their data on time, they receive automated reminders, followed by direct contact from the call center.

As part of the quality assurance process, submitted data are thoroughly checked for anomalies and inconsistencies. Units are recontacted if validation checks indicate potential issues. This verification process plays a key role in ensuring the accuracy and reliability of the collected R&D data.

18.1.2. Sample/census survey information

Sampling unit	Legal units in the BES sector. The BES sector included 1788 units (the number of valid responses obtained from the survey)
Stratification variables (if any - for sample surveys only)	Census survey
Stratification variable classes	Does not apply.
Population size
Planned sample size
Sample selection mechanism (for sample surveys only)	Census survey
Survey frame	Statistical Business Register (Statistical Office of the Republic of Slovenia) - business entities, their subsidiaries and other divisions of business entities, registered for performing R&D activities (as covered by NACE Rev. 2 Division 72), List of recipients of state aid for investment in R&D (Ministry of Finance), List of business entities liable to general and regional tax incentives for R&D investments (Financial Administration of the Republic of Slovenia), The Community Innovation Survey (CIS) (Statistical Office of the Republic of Slovenia), Slovenian Current Research Information System (SICRIS) (Slovenian Research Agency)
Sample design	Does not apply.
Sample size	Does not apply.
Survey frame quality	Does not apply.
Variables the survey contributes to	All variables on employement and expenditure.

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

Source	All data on employment and expenditure are collected directly through the survey; no administrative sources or pre-compiled statistics are used.
Description of collected data / statistics	Does not apply.
Reference period, in relation to the variables the administrative source contributes to	Does not apply.
Variables the administrative source contributes to	Does not apply.

18.2. Frequency of data collection

See 12.3.3.

18.3. Data collection

Please see the sub-concepts 18.3.1 and 18.3.2 in the full metadata view.

18.3.1. Data collection overview

Realised sample size (per stratum)
Mode of data collection	WEB questionnaire — no interviewers are involved, however a call center is available to assist with methodological questions.
Incentives used for increasing response	If units do not submit their data on time, they receive automated reminders.
Follow-up of non-respondents	If units do not submit their data on time, they receive automated reminders.
Replacement of non-respondents (e.g. if proxy interviewing is employed)	Does not apply.
Response rate (ratio of completed "interviews" over total number of eligible enterprises or enterprises of unknown eligibility)	88 % for BES
Non-response analysis (if applicable -- also see section 18.5.4 Data compilation - Weighting and Estimation methods)	Non-response analysis is not done.

18.3.2. Questionnaire and other documents

Annex	Name of the file
R&D national questionnaire and explanatory notes in English:	Questionnaire (only in Slovene) Methodological Explanation
R&D national questionnaire and explanatory notes in the national language:	Questionnaire (only in Slovene) Methodological Explanation explanation
Other relevant documentation of national methodology in English:	Does not apply.
Other relevant documentation of national methodology in the national language:	Does not apply.

Annexes:
The methodological explanations - Research and development activity by performers, Slovenia, 2023
Metodološko pojasnilo - Raziskovalno-razvojna dejavnost pri izvajalcih, 2023
Vprašalnik za statistično raziskovanje Raziskovalno-razvojna dejavnost pri izvajalcih, 2023

18.4. Data validation

Validation activities are: comparing the statistics with previous cycles, investigating inconsistencies in the statistics; performing micro data editing.

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)

18.5.1.1. Imputation rate by Size class

Does not apply.

Size class	R&D Expenditure		R&D personnel (FTE)
Size class	Unweighted	Weighted	Unweighted	Weighted
0-9 employees and self-employed persons (optional)
10-49 employees and self-employed persons
50-249 employees and self-employed persons
250-and more employees and self-employed persons
TOTAL

18.5.1.2. Imputation rate by NACE

Does not apply.

NACE	R&D Expenditure		R&D personnel (FTE)
NACE	Unweighted	Weighted	Unweighted	Weighted
Industry¹⁾
Services²⁾
TOTAL

1) Industry (NACE Rev. 2: 01-03, 05-09,10-33,35,36-39,41-43)

2) Services (NACE Rev 2.: 45-47, 49-53, 55-56, 58-63, 64-66 68, 69-75, 77-82, 84, 85, 86-88, 90-93, 94-96, 97-98, 99)

18.5.2. Data compilation methods

Data compilation method - Final data	Not applicable
Data compilation method - Preliminary data	Not applicable

18.5.3. Measurement issues

Method of derivation of regional data	R&D performers are classified by statistical and cohesion region based on the address information (i.e., municipality) recorded in the Statistical Business Register. In cases where a reporting unit provides data for the entire enterprise, the address of the headquarters is generally used for deriving regional data.
Coefficients used for estimation of the R&D share of more general expenditure items	Does not apply.
Inclusion or exclusion of VAT and provisions for depreciation in the measurement of expenditures	Depreciation and VAT are excluded from R&D expenditures.

18.5.4. Weighting and estimation methods

Weight calculation method	With the data for reference year 2011 weighting for unit non-response was introduced. The unit non-response is calculated by the ratio between the sample size and the sum of the responses and the ineligible units. Weights are calculated according to the strata, which are determined by the economic activity and the size of enterprise (considering the number of persons employed).
Data source used for deriving population totals (universe description)	The Statistical Business Register is used as a source for variables used for weighting.
Variables used for weighting	Economic activity, size of enterprise
Calibration method and the software used	Does not apply.
Estimation	Does not apply.

18.6. Adjustment

Not requested.

18.6.1. Seasonal adjustment

Not requested.

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

31 July 2025

See below.

The statistical unit for BERD is the enterprise as defined by Council Regulation (EEC) No 1993/696 of 15 March 1993, if there are deviations please explain.

See below.

Not requested. R&D statistics cover national and regional data.

For this report, data from the calendar year 2023 was used as the reference period.

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 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.

See below.

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

This sub-concept refers to the geographical comparability of data among the 27 Member States and the EFTA and Candidate Countries.

For more information related to the break years and the nature of the breaks, see the following sub-concepts in the full metadata view.

Research and development (R&D) (rd)

1. Contact accordion arrow down accordion arrow up

1.1. Contact organisation

1.2. Contact organisation unit

1.3. Contact name

1.4. Contact person function

1.5. Contact mail address

1.6. Contact email address

1.7. Contact phone number

1.8. Contact fax number

2. Metadata update accordion arrow down accordion arrow up

2.1. Metadata last certified

2.2. Metadata last posted

2.3. Metadata last update

3. Statistical presentation accordion arrow down accordion arrow up

3.1. Data description

3.2. Classification system

3.3. Coverage - sector

3.3.1. General coverage

3.3.2. Sector institutional coverage

3.3.3. R&D variable coverage

3.3.4. International R&D transactions

3.3.5. Extramural R&D expenditures

3.4. Statistical concepts and definitions

3.4.1. R&D expenditure

3.4.2. R&D personnel

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

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

3.4.2.3. FTE calculation

3.5. Statistical unit

3.6. Statistical population

3.6.1. National target population

3.6.2. Frame population – Description

3.7. Reference area

3.8. Coverage - Time

3.9. Base period

4. Unit of measure accordion arrow down accordion arrow up

5. Reference Period accordion arrow down accordion arrow up

6. Institutional Mandate accordion arrow down accordion arrow up

6.1. Institutional Mandate - legal acts and other agreements

6.1.1. European legislation

6.1.2. National legislation

6.1.3. Standards and manuals

6.2. Institutional Mandate - data sharing

7. Confidentiality accordion arrow down accordion arrow up

7.1. Confidentiality - policy

7.2. Confidentiality - data treatment

8. Release policy accordion arrow down accordion arrow up

8.1. Release calendar

8.2. Release calendar access

8.3. Release policy - user access

9. Frequency of dissemination accordion arrow down accordion arrow up

10. Accessibility and clarity accordion arrow down accordion arrow up

10.1. Dissemination format - News release

10.1.1. Availability of the releases

10.2. Dissemination format - Publications

10.2.1. Availability of means of dissemination

10.3. Dissemination format - online database

10.3.1. Data tables - consultations

10.4. Dissemination format - microdata access

10.4.1. Provisions affecting the access

10.5. Dissemination format - other

10.5.1. Metadata - consultations

10.5.2. Availability of other dissemination means

10.6. Documentation on methodology

10.6.1. Metadata completeness - rate

10.7. Quality management - documentation

10.7.1. Documentation and users’ requests

11. Quality management accordion arrow down accordion arrow up

11.1. Quality assurance

11.2. Quality management - assessment

12. Relevance accordion arrow down accordion arrow up

12.1. Relevance - User Needs

12.1.1. Needs at national level

12.2. Relevance - User Satisfaction

12.2.1. National Surveys and feedback

12.3. Completeness

12.3.1. Data completeness - rate

12.3.2. Completeness - overview

12.3.3. Data availability

1. Contact

2. Metadata update

3. Statistical presentation

4. Unit of measure

5. Reference Period

6. Institutional Mandate

7. Confidentiality

8. Release policy

9. Frequency of dissemination

10. Accessibility and clarity

11. Quality management

12. Relevance

13. Accuracy

14. Timeliness and punctuality