Research and development (R&D) (rd)

1.1. Contact organisation

Directorate General of Education and Science Statistics (DGEEC) | Direção Geral de Estatísticas da Educação e Ciência

1.2. Contact organisation unit

Directorate for Science and Technology Statistics and Information Society Services
(DSECTSI - Direção de Serviços de Estatística da Ciência e Tecnologia e da Sociedade de Informação)

1.3. Contact name

Restricted from publication

1.4. Contact person function

Restricted from publication

1.5. Contact mail address

Av. 24 de Julho, 134
1399-054 Lisboa, PORTUGAL

1.6. Contact email address

Restricted from publication

1.7. Contact phone number

Restricted from publication

1.8. Contact fax number

Not required.

2.1. Metadata last certified

2 October 2025

2.2. Metadata last posted

2 October 2025

2.3. Metadata last update

2 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	GOV sector includes the units, established in Portugal, comprised in the central, regional and local public administration, units mainly financed and/or controlled by the government, public hospitals and other public health facilities, with the exclusion of those units included in the Higher Education Sector (HES).
Hospitals and clinics	All public hospitals and other public health facilities, including university hospitals and clinics. (Private hospitals and clinics are included in BE sector).
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	In accordance with FM (2015: 2.122), R&D management and other R&D support activities are considered and reported as part of the unit R&D activities.
External R&D personnel	In accordance with FM (2015); covered.
Clinical trials: compliance with the recommendations in FM §2.61.	Clinic trials are mentioned as an example of R&D activities (according to FM 2015: 2.61), in the R&D survey. If applicable, the R&D related to clinical trials is to be reported among all the R&D performed by the unit. It is not requested detailed information whether they were included in the response or not.

3.3.4. International R&D transactions

Receipts from rest of the world by sector - availability

Statistics on international R&D transaction regarding receipts from the rest of the world are available, according to FM (2015: table 4.3). Data by sources of funds for R&D, namely funding from the “Rest of the world”, were classified as follows: European Union (EU), Other international organizations, Foreign governments (GOV), Foreign private non-profit (PNP) institutions, Foreign business enterprises (BE), Foreign higher education institutions. These data are displayed as aggregated figures, as “Foreign Funds”.

Payments to rest of the world by sector - availability

Statistics on international R&D transaction regarding payments to the rest of the world are available. To what concerns the distribution by providers and recipients of extramural funds (for exchange R&D and transfer R&D), R&D data coverage regarding the rest of the world were classified as follows: Foreign GOV institutions, Foreign HE institutions, Foreign PNP institutions, Foreign BE, technological centres / interface institutions with enterprises and Other foreign institutions.

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	To separate extramural R&D expenditure from intramural R&D expenditure, there are two distinct sections in the form: the section IV: only for ‘Intramural R&D Expenditure’, and the section V: only for ‘Extramural R&D Expenditure’. Both concepts are also explained in the annexes (see point 10.6.), explanatory notes, and in the FAQ that are provided with the survey (in the online platform). The extramural R&D expenditures are compiled separating the transfer funds for R&D from exchange funds for R&D, and both are disaggregated by type of institution (GOV, HES, PNP institutions; enterprises, technological centres/interface institutions related to enterprises, and other institutions) and geographic location (Portugal or rest of the world).
Difficulties to distinguish intramural from extramural R&D expenditure	Some units still have difficulty in distinguishing both concepts. The main difficulty encountered with the coverage of extramural funds was specifically related with the fact that, for the purchase of R&D, some respondents still struggled to distinguish intramural from extramural R&D expenditure, namely distinguishing acquiring R&D services within the scope of their own R&D activities and contracting R&D services from third parties. Having this in mind, the definition of both concepts is provided in the explanatory notes and annexes (see point 10.6.). Furthermore, during the data collection, DGEEC clarifies any doubt on this matter, whenever requested. Moreover, all along the validation process, the values reported for intramural and extramural expenses are compared and, in case of suspicion of duplicated information, or of misunderstanding, the units are contacted (email or telephone) for clarification and, if necessary, for data corrections.

3.4. Statistical concepts and definitions

See below

3.4.1. R&D expenditure

Coverage of years	Calendar year
Source of funds	In accordance with FM (2015)
Type of R&D	In accordance with FM (2015)
Type of costs	In accordance with FM (2015)
Defence R&D - method for obtaining data on R&D expenditure	Defence R&D expenditure is calculated according to the percentage reported in socio-economic objective (SEO) "Defence". In Portuguese R&D form, the unit must report and distribute the percentage of their R&D activities according to their socio-economic objective/s (distribution of 100% in as many SEO applicable).

3.4.2. R&D personnel

See below

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

Coverage of years	Calendar year
Function	The R&D form is composed by two main modules: the first module collets information on intramural and extramural R&D expenditures (type of intramural R&D costs, sources of funds, type of R&D, SEO, etc.). The second module is an individual form which collects detailed information about each person with tertiary level of education (=> ISCED 5) performing R&D activities in the unit, namely the percentage of time spent in R&D. In this individual form, there is a question about the main R&D function performed in the reference year. For R&D personnel with no tertiary education (< ISCDE 5), the function is reported in the first module, in a table (section III of the form), breakdown by sex, HC and FTE.
Qualification	In the individual form (explained above), the qualification is requested (mandatory). The respondent should report the highest degree obtain until the end of the reference year.
Age	In the individual form (explained above), the date of birth is requested (optional). Because, it is only requested for personnel with ISCED => level 5, and it is not a mandatory question, the breakdown by this variable may be underestimated.
Citizenship	In the individual form (explain above), country of nationality is requested (optional). Because, it is only requested for personnel with ISCED => level 5, and it is not a mandatory question, the breakdown by this variable may be underestimated.

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

Coverage of years	Calendar year
Function	Same procedure for HC (see above)
Qualification	Same procedure for HC (see above)
Age	Same procedure for HC (see above)
Citizenship	Same procedure for HC (see above)

3.4.2.3. FTE calculation

For R&D personnel with tertiary level of education (=> ISCED 5), the FTE calculation is based on the information provided in the individual form, regarding the percentage of time dedicated to R&D activities.
Although a person may perform R&D in more than one unit, due to the fact that there is an individual form, it is possible to identify if the same person is performing R&D in other units. If they exceeded 100%, the percentage is adjusted accordingly to the number of times that the person is identify and according to the percentage of time in R&D activities that was reported in each unit, assuring that no one is counted for more than 1.0 FTE.
For R&D personnel without tertiary education (< ISCED 5), the FTE is reported by the respondent unit as aggregated data (by gender and function) and considered as such, after the validation process (where the data is compared with previous years and/or questioned if needed).

3.5. Statistical unit

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

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	Units having scientific and technological potential for performing R&D activities, established in Portugal, encompassed in the GOV sector (only potential R&D performers, regular and occasional R&D performers): central, regional and local public administration, units mainly financed and/or controlled by the government, and all public hospitals and other public health facilities (including university hospitals and clinics) as well as state oncology institutes. The State Laboratories (Laboratórios do Estado, in Portuguese) are included in the GOV sector, they are public research institutions that were created with the explicit purpose of pursuing the scientific and technological policy’s goals, adopted by the State through the development of R&D activities and other scientific and technical activities. These laboratories are formally consulted by the government on the definition of the national programmes and of the scientific and technological policy’s tools It is considered as potential R&D performers the units that had receive public R&D funding for these activities, either in the form of subsidies for R&D projects, research grants, other forms of hiring researchers and other fundings; and/or private R&D funding in the form of payment of R&D contract services or other. Also, are included units that, although hadn’t received specifically R&D funding, they had allocated part or all of their annual budget for R&D activities (in the form of payment of human resources salaries and other current and capital expenditures) and units that had host individuals with R&D employment contracts and R&D grant holders (including those paid or financed by other units). In each year, it is also considered to inquiry units that, if they do not meet the criteria indicated above, had reported R&D at least once in the last 3 years. In addition to the criteria previously described, it was approved, in 2009, new legislation on the medical and nursing careers (Decree-Law Nr. 177/2009 of August 4th; Decree-Law Nr. 248/2009 of September 22th) which behold, as an official employment function, performing and coordinating research activities, ensuring thus that any hospital facility (and corresponding hospital services), that had on their service one doctor or one nurse, be considered as a potential R&D performer. The Directory of Institutions of the National Scientific and Technological System is updated considering the information reported in previous R&D surveys, and administrative data from other sources (see point 18.1.3).
Estimation of the target population size	Not applicable

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	All the institutional units classified by the National Accounts are included in the general Government, with the exclusion of those units included in the HES.
Methods and data sources used for identifying a unit as known or supposed R&D performer	For identifying units as R&D performers, DGEEC had previously identified those which had received public or private R&D funding, those which had allocated part or all of their annual budget for R&D activities and, also, those units that had host individuals with R&D employment contracts or R&D grant holders (even paid or financed by other units). Public Hospitals and other public health facilities (and corresponding hospital services) are also considered as potential R&D performers, once the legislation (from 2009) of Medical and Nurses Careers points out that R&D should be part of their activities. (see point 3.6.1.) Main data sources used (see also point 18.1.3): DGEEC’s Institutions Directory of the National Scientific and Technological System (yearly updated), List of contracts for teaching and/or R&D in institutions covered in the Observatory of Scientific and Teaching Employment (OECD, acronym in Portuguese); List R&D Units, and their list of R&D personnel, that are financed by Foundation for Science and Technology (FCT); List R&D individual grants (PhD), that are financed by Foundation for Science and Technology (FCT); Government’s websites.
Inclusion of units that primarily do not belong to the frame population	Not applicable.
Systematic exclusion of units from the process of updating the target population	If the response in 3 consecutive years is that the Unit does not perform, or finance or contract, R&D, then it’s no longer surveyed. However, its inclusion back in the directory may be evaluated according to the main admission criteria: receiving R&D funding; and/or allocating part of its budget to R&D; and/or host individuals for R&D activities.
Estimation of the frame population	Not applicable.

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.

Reference year.

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. 

6.1.2. National legislation

Existence of R&D specific statistical legislation	Production of national R&D statistics is governed by the general national statistical legislation: Law Nr. 22/2008 of May 13th.
Are respondents obliged by the national law to provide raw and administrative data:	Yes: Law Nr. 22/2008 of May 13th.

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: 

a)       Confidentiality protection required by law:

DGEEC proceeds according to the National Statistical System (Law Nr. 22/2008 of May 13th) that regulates statistical confidentiality (Article 6).

 

b)       Confidentiality commitments of survey staff:

The staff working directly with statistical production must sign commitment document, which ensures the acknowledge of the confidentiality issues and data protection law.

7.2. Confidentiality - data treatment

R&D data is checked in order to assure confidentiality. Monitoring and control of the data is made before it is published, assuring no confidential information is released. If applicable, checking any cell with less than 3 population units, and properly modifying the table to avoid also secondary disclosure is applied.

For public institutions, according to the Law Nr. 22/2008 of May 13th (article 6, point 3), individual statistical data on public administration are not covered by statistical confidentiality, unless otherwise provided by law.

8.1. Release calendar

The calendars of statistical operations and statistical publications are publicly available (in January) on the DGEEC's website.

8.2. Release calendar access

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

For National this is: Release calndar estatistica

8.3. Release policy - user access

R&D data, by sectors of performance, is available to all users on the DGEEC’s website.
When data/publications are released in DGEEC website, the units surveyed in the reference year, regardless the type of response (performing R&D or not), are also informed by email.
The Chief of Staff of the Minister of Science, Technology and Higher Education, 24 hours before the scheduled of release, can receive information under embargo, as it is publicly described in the European Statistics Code of Practice and in accordance with point 15, chapter B, of Statistics Portugal (INE).

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

At national level is also 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	N
Ad-hoc releases	N

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	National R&D Statistical Yearbook for the GOV sector. Link: National Statistial Yearbook
Specific paper publication (e.g. sectoral provided to enterprises)	Y	Highlights of provisional data on R&D Expenditure and R&D Personnel (includes GOV sector): Link: Provisional data  Highlights of final data on R&D Expenditure and R&D Personnel (includes GOV sector): Link: Final data Publication of the R&D activities in Hospitals Institutions  (expenditure and personnel): Link: Dgeec Publication

1) Y – Yes, N - No 

10.3. Dissemination format - online database

A list of the R&D units is provided in DGEEC’s website, which contains the Unit’s name, general contacts, and the FORD of each unit that in the reference year performed R&D.
Link: List of R&D units

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	Under the Cooperation Protocol between Statistics Portugal (INE), DGEEC and the Foundation for Science and Technology (FCT), R&D microdata can be acceded only by researchers and for scientific purposes. DGEEC is the entity that certifies researchers for the use of microdata, and only after that process of certification, INE provide the access to it.
Access cost policy	Free of charge.
Micro-data anonymisation rules	Applied by Statistics Portugal (INE).

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	The National R&D Statistical Yearbook for the GOV sector contains the main indicators and variables collected in the IPCTN Survey, and it’s available online to all users in XLS/ODS format. National Statistical Yearbook
Data prepared for individual ad hoc requests	Y	Micro-data and Aggregate figures	Other statistical demands for specific data, that are not available on DGEEC’s website, can be provided under specific request. Micro-data confidentiality is guaranteed by law and anonymization rules are in place.
Other	N

1) Y – Yes, N - No 

10.6. Documentation on methodology

List of national descriptive text and/or references to methodological documents available to the R&D statistical process:

• IPCTN form – Institutional Sector (includes GOV, HE and PNP sectors); available: Dgeec.methodology
• IPCTN Methodological Document (DGEEC, INE); available:
  • Dgeec mehodological document and at
  • INE’s website: Ine's Documentacao Metodologica
• Validation Handbook (internal working document / DGEEC),
• Handbook for questionnaire non- response cases (internal working document / DGEEC).

IPCTN form, for 2023 reference year, had 5 annexes which provide useful information for a correct filling of the questionnaire:

• Annexe I – Concepts and examples of R&D activities,
• Annexe II - Intramural and extramural R&D expenses,
• Annexe III – Human resources performing R&D activities,
• Annexe IV – SEO according to Eurostat (NABS, 2007),
• Annexe V – National priorities according to R&D National Strategy for an Intelligent Specialisation (ENEI 2030),
• Annexe VI – Fields of R&D Classification (FORD, 2015).

The IPCTN Survey’s Methodological Document provides all information related to this national statistical operation. In general, it describes the needs, the goals and the funding of this statistical operation; it also provides a general characterisation of the statistical operation (type, source of information used, periodicity, geographic scope, breaks in time series, information available to users and its dissemination means) and contains methodological information on target population, data collecting, data treatment, data dissemination, and more. It’s the official methodological document approved by INE for registering this statistical operation in the NSS.

Data validation rules are defined in the Validation Handbook.

Rules for questionnaire non- response cases were defined in the Handbook (included uncompleted questionnaires), as well as for units that had submitted their questionnaire as non-R&D performer although being funded by the Foundation for Science and Technology (see point 18.1.3.).

All these documents are updated on a yearly basis, for each statistical operation.

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.)	Along with each publication, it is always provided detail information on data collection and metadata. FAQ are also frequently updated and displayed online regarding the R&D survey.
Requests on further clarification, most problematic issues	No requests on further clarification on this subject 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).

The Code of Practice available at Code of Practice

DGEEC, as the institution responsible for producing official statistics, must respect and be governed by national and international statistical quality standards, in accordance with article 7 of Law Nr. 22/2008 of May 13, and by the European Statistics Code of Practice. In the case of the R&D statistics, DGEEC also follows Eurostat's and OECD methodological recommendations.

Several data validation processes take place before the R&D indicators are released. These validation procedures have been updated over the years that, complemented with the use of new database management tools, have resulted in more efficient and effective data management.

Major improvements were obtained using technology and information systems, through a wider range of administrative databases, through more efficient communication between organizations, but also due to the expertise staff involved in these statistical operations, who greatly contributed to the quality of the survey responses. The activities carried out by the technicians are highly complex and require in-depth knowledge of the concepts and methodologies inherent to this survey, in the field of statistics, as well as high computer skills, especially in programs that allow data management and calculation - for example, SQL, SAS and SPSS. In addition, communication skills and contact with respondents are also privileged, both in the validation phase and in the phase of obtaining responses, which is why it is necessary to guarantee continuous training for all those who contribute to this census. Training has been given to technicians in these areas, as well as complementing training in areas related to database management and making information available (data scientist, PowerBI, etc.). Internal manuals are updated annually, including a validation handbook, and a detailed description of the entire final validation process, which takes place in SQL. A thorough validation procedure of data collected is carried out, consisting in finding and correcting internal inconsistencies among the sections and questions in survey and by comparing with data from previous years or with other data sources. All efforts are made to reduce errors, to identify and correct them. Assistance/helpdesk is provided to respondents during data collection. During the validation process, entities are contacted for further clarifications or for correcting errors. For all questionnaires, the following procedures are carried out: The electronic form includes validations that allow checking the consistency of the information (it may be necessary to contact the entity, if incoherence is found). Inconsistencies of the "Error" type must be resolved before registration is accepted. Once the data registration is concluded, the information is analyzed and processed, namely the analysis of the consistency of the year's data, and comparison of values with the previous year for quality control. Some data are confronted with information from other administrative sources considered relevant. DGEEC had also implemented a Quality Management System for improving the quality by measuring its services, processes and procedures. As part of this system, procedures are included in matters such as document management, resource management, and human resources skills improvement on statistical production. The Quality Manual, as well as the commitment to quality could be also noticed in DGEEC’s annual programs that are publicly available on its website.

11.2. Quality management - assessment

The Portuguese R&D survey (IPCTN) is part of the National Statistical System, and DGEEC, as responsible for these official statistics, is legally obliged to respect the national and international statistical quality standards (Law for the National Statistical System, European Statistics Code of Practice).

The IPCTN survey has been implemented for almost 4 decades, with continuous adaptation, improvement, and ongoing monitoring to assure that the survey is according to FM.
The quality is considered very good, mainly because of the intensive follow-up activities with the respondents, the administrative databases that complement the survey, which contributes for the data validation, as well as the high response rates over the years.

See below

12.1. Relevance - User Needs

See below

12.1.1. Needs at national level

Users’ class1)	Description of users	Users’ needs
1- Institutions	European Commission	Eurostat R&D questionnaires.
1- Institutions	OECD	OECD R&D Questionnaires; Biotech and Nanotech Questionnaire.
1- Institutions	RICYT – Red Iberoamericana de Indicadores de Ciencia y Tecnología	Questionnaire “El Estado de la Ciencia. Principales Indicadores de Ciencia y Tecnología Iberoamericanos / Interamericanos.
1- Institutions	Portuguese Ministries	Data on national R&D expenditure and R&D human resources for policy-making.
1 - Institutions	Statistical Portugal (INE)	Structural R&D indicators, statistical yearbooks and other statistical outputs.
3 - Media	National Media	Main R&D data displayed on DGEE’s website.
4 - Researchers and students	Researchers and students	Ad hoc requests
6 - Other	Other institutions	Ad hoc requests

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	A user satisfaction survey is sent to all individual ad hoc requests.
User satisfaction survey specific for R&D statistics	No specific survey satisfaction for R&D statistics, but in the R&D survey the units can give feedback in the additional field that is provided in the survey.
Short description of the feedback received	So far, this information has not been regularly treated, thus a short description of the feedback received can’t be provided.

12.3. Completeness

See below

12.3.1. Data completeness - rate

See below

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	Not applicable.
Obligatory data on R&D expenditure	Not applicable.
Optional data on R&D expenditure	Not applicable.
Obligatory data on R&D personnel	Not applicable.
Optional data on R&D personnel	Not applicable.
Regional data on R&D expenditure and R&D personnel	Not applicable.

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-1982	1982-1992 (Every two years) 1995-2007 (Every two years) 2008 onwards (Yearly)	1994
Type of R&D	Y-1982	1982-1992 (Every two years) 1995-2007 (Every two years) 2008 onwards (Yearly)	1994
Type of costs	Y-1982	1982-1992 (Every two years) 1995-2007 (Every two years) 2008 onwards (Yearly)	1994
Socioeconomic objective	Y-1997	1997-2007 (Every two years) 2008 onwards (Yearly)
Region	Y - 1995	1995-2007 (Every two years) 2008 onwards (Yearly)		Data compiled at regional level according to NUTS 2002.	2003	NUTS 2002 was introduced for compiling data at regional level.
FORD	Y-1982	1982-1992 (Every two years) 1995-2007 (Every two years) 2008 onwards (Yearly)	1994	Changes in the classifications by field of science.	2005 2007 2016	1982 to 2004: Data available only for GOV, HE and PNP sectors. Until 2003 a 2-digit level national classification on fields of science was used allowing for a distribution of R&D expenditure and personnel on 30 fields of science, which can be aggregated to the 6 major FOS. 2005: introduced the FOS classification at 2 digit-level to classify R&D expenditure, researchers and total R&D. This variable was included in BES. 2007: it was adopted the revised classification of fields of science and technology (FOS 2007). The revision was only at 2 -digit level, which considered emerging and interdisciplinary fields. 2016 onwards: it was adopted the FORD classification (2015).
Type of institution	Y-1995	1995-2007 (Every two years) 2008 onwards (Yearly)		Data for public Hospitals collected separately.	1995	Possibility to provide separately data for public hospitals

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	1999-2007 (Every two years) 2008 onwards (Yearly)		Extend the variables collection	2001	Data on sex variable for total R&D personnel (before, only for researchers).
Function	Y-1982	1982-1992 (Every two years) 1995-2007 (Every two years) 2008 onwards (Yearly)	1994	R&D personnel classification by occupation revised. Researcher concept was enlarged. Revision of the occupation categories for R&D personnel. based on ISCO classification.	1992 1995 2013	1992: R&D personnel classification by occupation was revised for the 1995 R&D survey and retrospectively back to 1992. From 1992 onwards, data for RSE and technicians are not comparable with those for previous years. 1995: Researcher concept started to include all university diplomates (ISCED level 5B included) performing R&D activities. 2013: Occupation categories breakdown for R&D personnel: researcher, technicians and other support staff were defined based on the main functions performed by each individual within its R&D activities rather than on the academic qualification level. This modification made in accordance with the criteria established on ISCO classification).
Qualification	Y-1999	1999-2007 (Every two years) 2008 onwards (Yearly)
Age	Y-1999	1999-2007 (Every two years) 2008 onwards (Yearly)		Extend the variables collection	2013	Data on age variable available only for tertiary education graduated personnel. Until 2013, these data were only available for researchers.
Citizenship	Y-1999	1999-2007 (Every two years) 2008 onwards (Yearly)		Extend the variables collection	2013	Data on citizenship variable available only for tertiary education graduated personnel. Until 2013, these data were only available for researchers.
Region	Y-1995	1995-2007 (Every two years) 2008 onwards (Yearly)		Data compiled at regional level according to NUTS 2002.	2003	NUTS 2002 was introduced for compiling data at regional level.
FORD	Y-1982	1982-2007 (Every two years) 2008 onwards (Yearly)	1994	Changes in the classifications by field of science.	2005 2007 2016	1982 to 2004: Data available only for GOV, HE and PNP sectors. Until 2003 a 2-digit level national classification on fields of science was used allowing for a distribution of R&D expenditure and personnel on 30 fields of science, which can be aggregated to the 6 major FOS.  2005: introduced the FOS classification at 2 digit-level to classify R&D expenditure, researchers and total R&D. This variable was included in BES.  2007: it was adopted the revised classification of fields of science and technology (FOS 2007). The revision was only at 2 -digit level, which considered emerging and interdisciplinary fields.  2016 onwards: it was adopted the FORD classification (2015).
Type of institution	Y-1995	1995-2007 (Every two years) 2008 onwards (Yearly)

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	1999-2007 (Every two years) 2008 onwards (Yearly)		Extending data collection.	2001	Data on sex variable for total R&D personnel (before, only for researchers).
Function	Y-1982	1982-1992 (Every two years) 1995-2007 (Every two years) 2008 onwards (Yearly)	1994	R&D personnel classification by occupation revised. Researcher concept was enlarged. Revision of the occupation categories for R&D personnel based on ISCO classification.	1992 1995 2013	1992: R&D personnel classification by occupation was revised for the 1995 R&D survey and retrospectively back to 1992. From 1992 onwards, data for RSE and technicians are not comparable with those for previous years. 1995: Researcher concept started to include all university diplomates (ISCED level 5B included) performing R&D activities. 2013: Occupation categories breakdown for R&D personnel: researcher, technical and other support staff were defined based on the main functions performed by each individual within its R&D activities rather than on the academic qualification level. This modification made in accordance with the criteria established on ISCO classification).
Qualification	Y-1999	1999-2007 (Every two years) 2008 onwards (Yearly)
Age	Y-1999	1999-2007 (Every two years) 2008 onwards (Yearly)		Collect more indicators on R&D personnel	2013	Data on age variable available only for tertiary education graduated personnel. Since 1999, these data were only available for researchers.
Citizenship	Y-1999	1999-2007 (Every two years) 2008 onwards (Yearly)		Collect more indicators on R&D personnel	2013	Data on citizenship variable available only for tertiary education graduated personnel. Since 1999, these data were only available for researchers.
Region	Y-1995	1995-2007 (Every two years) 2008 onwards (Yearly)		Data compiled at regional level according to NUTS 2002.	2003	NUTS 2002 was introduced for compiling data at regional level.
FORD	Y-1982	1982-1992 (Every two years) 1995-2007 (Every two years) 2008 onwards (Yearly)	1994	Changes in classifications by field of science	2005 2007 2016	1982 to 2004: Data available only for GOV, HE and PNP sectors. Until 2003 a 2-digit level national classification on fields of science was used allowing for a distribution of R&D expenditure and personnel on 30 fields of science, which can be aggregated to the 6 major FOS.  2005: introduced the FOS classification at 2 digit-level to classify R&D expenditure, researchers and total R&D. This variable was included in BES.  2007: it was adopted the revised classification of fields of science and technology (FOS 2007). The revision was only at 2 -digit level, which considered emerging and interdisciplinary fields.  2016 onwards: it was adopted the FORD classification (2015).
Type of institution	Y-1995	1995-2007 (Every two years) 2008 onwards (Yearly)		Data for public Hospitals collected separately.	1995	Possibility to separate data for public hospitals.

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
No information was given.	No information was given.	No information was given.	No information was given.	No information was given.	No information was given.

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	FTE and HC	Every year

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)
		Coverage errors	Measurement errors	Processing errors	Non response errors
Total intramural R&D expenditure	Not applicable	Not applicable	Not applicable	Not applicable	Not applicable	Not applicable	Not applicable
Total R&D personnel in FTE	Not applicable	Not applicable	Not applicable	Not applicable	Not applicable	Not applicable	Not applicable
Researchers in FTE	Not applicable	Not applicable	Not applicable	Not applicable	Not applicable	Not applicable	Not applicable

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

Not applicable

13.2.1.1. Variance Estimation Method

Not applicable; Census survey

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.

 

a)       Description/assessment of coverage errors :

Not applicable

 

b)      Measures taken to reduce their effect:

Not applicable

 

c)       Share of PNP (if PNP is included in GOV):

Not applicable

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.

 

a)       Description/assessment of measurement errors:

Not applicable

b)      Measures taken to reduce their effect:

Not applicable

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)
294	295	0,34

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) (%)	Not applicable	Not applicable	Not applicable
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	Responses through electronic online questionnaires. The data is saved directly into a SQL Database
Estimates of data entry errors	Not available
Variables for which coding was performed	Most variables have an underlying code, excepting the open-ended questions such as R&D expenditures or the number of R&D personnel. Variables coded: region (NUTS), country, FORD, SEO, type of costs, source of funds, ISCED, type of R&D, sex, carers.
Estimates of coding errors	Not available
Editing process and method	Automatic validation procedures: the online platform for data collection had validated units’ responses while filling in the questionnaire, minimizing the item non-response and ensuring logical coherence of the information provided. For the remaining responses, when necessary, DGEEC requests clarifications to the units. A macro level validation is also considered. During validation procedure, the data reported by the units were compared with those given in previous years; also, key variables were contrasted with data available in other information sources. Data was processed using platform functionalities (ASP.net 2.0 or 3.0 - Active Server Pages – technologies to interact with Microsoft SQL Server) and other standard software applications, such as Microsoft Office ACCESS.
Procedure used to correct errors	In case of data discrepancies or wrong information, the survey staff contacts the units for corrections. Reopening the questionnaire, in order to the Unit make their corrections, is an option, the corrections can be made DGEEC according to the unit information. The Unit as always access to the final response: accessing the survey with their credentials, where they can see the information, and download a PDF with the response.

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)

 

a) End of reference period: 31 December 2023

b) Date of first release of national data: 23 December 2024

c) Lag (days): 205

14.1.2. Time lag - final result

a) End of reference period: 31 December 2023

b) Date of first release of national data: 20 December 2024

c) Lag (days): 355

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	15
Delay (days)	0	0
Reasoning for delay	Not applicable	Not applicable

See below

15.1. Comparability - geographical

See below.

15.1.1. Asymmetry for mirror flow statistics - coefficient

Not requested.

15.1.2. General issues of comparability

The R&D statistics are according to FM (2015) and harmonized with OECD’s criteria, therefore international comparability is ensured. The R&D survey methodology is applied in same procedures in all national territory (no differences between mainland and islands).

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
Researcher	FM2015, § 5.35-5.39.	No
Approach to obtaining Headcount (HC) data	FM2015, § 5.58-5.61 (in combination with  Eurostat's EBS Methodological Manual on R&D Statistics).	No
Approach to obtaining FTE data	FM2015, § 5.49-5.57 (in combination with Eurostat's EBS Methodological Manual on R&D Statistics).	No
Reporting data according to formula: Total R&D personnel = Internal R&D personnel + External R&D personnel	FM2015, §5.25	No
Intramural R&D expenditure	FM2015, Chapter 4 (mainly sub-chapter 4.2).	No
Statistical unit	FM2015, § 8.64-8.65 (in combination with Eurostat's EBS Methodological Manual on R&D Statistics).	No
Target population	FM2015, § 8.63 (in combination with Eurostat's EBS Methodological Manual on R&D Statistics).	No
Sector coverage	FM2015, § 8.2-8.13 (in combination with Eurostat's EBS Methodological Manual on R&D Statistics).	No
Hospitals and clinics	FM2015, § 8.22 and 8.34	No
Borderline research institutions	FM2015, § 8.14-8.23 (in combination with Eurostat's EBS Methodological Manual on R&D Statistics).	No
Fields of research & development coverage and breakdown	Reg. 2020/1197 : Annex 1, Table 18	No
Socioeconomic objectives coverage and breakdown	Reg. 2020/1197 : Annex 1, Table 18	No
Reference period	Reg. 2020/1197 : Annex 1, Table 18	No

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
Survey questionnaire / data collection form	FM2015 Chapter 8 (mainly sub-chapter 8.5).	No
Cooperation with respondents	FM2015 Chapter (mainly sub-chapter 8.5).	No
Data processing methods	FM2015 Chapter 8 (mainly sub-chapters 8.5-8.6).	No
Treatment of non-response	FM2015 Chapter 8 (mainly sub-chapter 8.5).	No
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

 

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)
Function	1982-1992 1995-2012 2013 onwards	1995 2013	1995: Following the revision of the existing methodology undertaken in 1997 (data revised back to 1995), the concept of Researcher was enlarged to include all university graduates performing R&D activities (including ISCED level 5B). 2013: Revision of the occupation categories of R&D personnel (researcher, technical and other supporting staff) took place in accordance with the criteria based on ISCO classification of occupations; therefore, occupations were defined according to the main functions performed by each individual within its R&D activities, rather than exclusively defined by the level of academic qualification.
Qualification	1982 onwards
R&D personnel (FTE)
Function	Same as for HC (see above).	Same as for HC (see above).	Same as for HC (see above).
Qualification	Same as for HC (see above).	Same as for HC (see above).	Same as for HC (see above).
R&D expenditure
Source of funds
Type of costs	1982-2015 2016 onwards	2016	Labour costs and Other current costs were identified as breaks in time series due to the redeployment to Other current costs of the external R&D personnel costs. Nevertheless, these breaks in time series don’t affect the annual comparability of the total national R&D expenditure
Type of R&D
Other	1995 onwards	1995	Reclassification of units according to the nomenclature of territorial units (NUTS 2002); until 1995 the reclassification by NUTS it is not feasible.

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

The survey is annual since 2008; data have been produced in the same way in 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

SNA classifications are used to classify R&D units in their institutional sector.

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)	203 380,2	2 751,6	1 820,5
Final data (delivered T+18)	206 864,8	2 764,2	1 821,7
Difference (of final data)	3 484,6	12,6	1,2

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)	Internal R&D Personnel expenditure / Internal R&D Personnel FTE = 44 327 € per year	Grant holders paid by the unit or host institution are included in the internal R&D personnel, according to the European Business Statistics Methodological Manual for R&D statistics (2023 edition)  (see 2.4.5. topic 5).
Consistency between FTEs of external R&D personnel and other current costs for external R&D personnel (2)	External R&D Personnel expenditure / External R&D Personnel FTE = 21 023 € per year

(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

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)	294 (of 295 surveyed units)	Number of completed and submitted answers.
Average Time required to complete the questionnaire in hours (T)1)	Units that performed R&D activities: 11 hours and 14 minutes Units without R&D activities (intramural or extramural): 9 minutes Units with only extramural R&D activities: 2 hours and 11 mimutes	In the section ‘Additional information’ there is a question about time spent on completing the questionnaire/survey. Based on this report, we calculate the average time breakdown by sector and situation according to R&D activities.
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.

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

National Scientific and Technological Potential Survey (IPCTN, Portuguese acronym) – Institutional Sectors (includes GOV, HE and PNP sectors) is a census survey.
There is no combination of sample survey and census data or of dedicated R&D and other survey(s).
The variables the survey contributes to are R&D expenditures by: type of expenditure; sources of funds; SEO; FORD; NABS; Region (NUTS II); type of R&D.
The survey is launched in March (T+15). Data collection period is extended until November of the same year. Along with data collection is also implemented the data validation processes, which involve contacts with the units (if needed).
In the last two months of the year the final validation, in SQL, is implemented to produce final results.

18.1.2. Sample/census survey information

Sampling unit	Not applicable
Stratification variables (if any - for sample surveys only)	Not applicable
Stratification variable classes	Not applicable
Population size	Not applicable
Planned sample size	Not applicable
Sample selection mechanism (for sample surveys only)	Not applicable
Survey frame	Not applicable
Sample design	Not applicable
Sample size	Not applicable
Survey frame quality	Not applicable
Variables the survey contributes to	Not applicable

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

Source	Directorate General of Education and Science Statistics (DGEEC): Observatory of Scientific and Teaching Employment (OECD, acronym in Portuguese); includes Public Higher Education Employment Survey (IEESP, acronym in Portuguese) Scientific and Teaching Employment in Higher Education Survey (IECDES, acronym in Portuguese) National Register of Doctoral Thesis (RENATES, acronym in Portuguese) Foundation for Science and Technology (FCT, acronym in Portuguese), is the national public agency supporting research in science, technology and innovation in all areas of knowledge. It is a special regime public institute under the supervision and oversight of the Ministry of Science, Technology and Higher Education. Public Hospitals
Description of collected data / statistics	Observatory of Scientific and Teaching Employment (OECD; website) includes: IEESP: data collection on human resources: qualification, employment contract, activities performed. IEC: data on all contracts signed by R&D institutions with doctoral graduates who carried out R&D activities or management and communication of science and technolog. activities, as well as workers in any of the scientific research career’s category. OECD-PNC: mandatory registration of all scientific and teaching employment contracts within 30 days of their entry into force by all R&D institutions or their host institution (public and PNP), as well as all higher education institutions. RENATES: data on doctoral theses in progress, doctorates completed in Portugal, equivalences awarded by Portuguese universities, records of doctoral degrees communicated by the Directorate-General for Higher Education (DGES) and master's degrees completed. FCT: data on R&D units and institutions receiving public R&D funds (Pluriannual R&D funding program); data on the individuals that are directly financed by FCT with R&D grants; List R&D Units and R&D personnel List R&D individual grants (PhD) Public Hospitals: data on expenditure and human resources (total) of the Public Hospitals – data requested by DGEEC, by an official-letter, where these institutions provide the annual expenditure, by type of expenditure, in order to complement the R&D survey responses.
Reference period, in relation to the variables the administrative source contributes to	Reference year.
Variables the administrative source contributes to	HC; FTE; qualification; intramural expenditures.

18.2. Frequency of data collection

See below

18.3. Data collection

See below

18.3.1. Data collection overview

Information provider	The survey is addressed to the director of the unit or to the respondent of the last R&D survey (if applicable).
Description of collected information	The information collected with references to the R&D variables requested by EU Regulation 2020/1197, namely: GOV R&D expenditure, by ministries and regional governments, type of entity and: type of expenditure, sources of funds, R&D type, FORD, SEO, NUTS GOV R&D personnel (FTE and HC) by type of entity, and: function and sex, level of education and sex, FORD and sex, NUTS II and sex, FORD, function and sex, NUTS III, function and sex, GOV R&D Researchers (FTE and HC) by type of entity, and: level of education and sex, FORD and sex, NUTS II and sex, nationality, age, level of education and sex, professional situation (career) and sex.
Data collection method	The IPCTN Survey is part of the national official statistics and the response is mandatory. It is an online survey, where each unit has their own credentials for the platform. Some questions are pre-filled, namely general information about the unit (e.g., name of the Unit, address, etc.), as well as information that was reported in other administrative sources and can be use in the R&D survey, in the individual form (FCT and OECD (see point 18.1.3.). The units can update and/or correct the information that was pre-filled, if necessary. For the launch of the survey it is sent, by email, a formal notice to each unit, explaining the importance of the data, the deadline for the response, the link to the FAQs, the direct contact (email and phone) of the staff that is responsible to monitor the unit's response, if they have any doubts filling the questionnaire. Each staff is responsible for a group of units, that includes tracking the responses, to clarify unit’s questions, and validate their responses.
Time-use surveys for the calculation of R&D coefficients	Not applicable
Realised sample size (per stratum)	Not applicable
Mode of data collection (face-to-face interviews; telephone interviews; postal surveys, etc.)	Electronic survey on an online platform:
Incentives used for increasing response	Official-letters are sent, explaining the importance of the survey, its uses and to which Organizations the data is provided. In addition, contacts by telephone and email (reminders, or other type of notification) in order to increase the response rate.
Follow-up of non-respondents	Four letters of formal notice are sent: the first one is when the statistical operation is launched and, at the most, 3 reminders can be sent for non-responders. Furthermore, telephone and email contacts were made in order to follow-up the non-respondent units.
Replacement of non-respondents (e.g. if proxy interviewing is employed)	Not applicable
Response rate (ratio of completed "interviews" over total number of eligible enterprises or enterprises of unknown eligibility)	99,7%
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:	ipctn23i_Formulario_ENG
R&D national questionnaire and explanatory notes in the national language:	ipctn23i_Formulario
Other relevant documentation of national methodology in English:	Not available
Other relevant documentation of national methodology in the national language:	IPCTN23i_DMET_vfinal (IPCTN Survey's Methodological Document

18.4. Data validation

A thorough validation procedure of data collected is carried out, that is implemented along with the data collection, and increased when then response rate is high (in the first months the main efforts are conducted to obtain the maximum number of responses, for the provisional results).
In general, the validation process can be described in three main levels:

• 1st: Validation of the online platform, when the units are filling the questionnaire. The survey’s electronic template form cross-checks the information consistency: "Error" type inconsistencies are checked out otherwise the platform don’t allow the questionnaire submission.
• 2nd: Considering the guidelines of the Validation Handbook, for the data collection, a validation procedure of the information gathered is carried out, regarding:
  • Coherence - analysis of data inconsistencies among the sections and the questions of the units’ questionnaire
  • Comparison - analysis of the data, compared with responses from with previous years (if available).
  • Cross-check - analysis of the data, compared with other sources: administrative databases (DGEEC’s or other entities)
• 3rd: parallel with the previous phases, DGEEC calculates estimations on Current and Capital expenditures on R&D activities in the reference year. This information is provided to the Units during the validation process, in order to compare it to what was reported in the survey.

Calculation on personnel costs, is made by considering the FTE and the career of R&D personnel that was reported by the units. Considering the information provided in the individual form (=> ISCED 5), as well in the section of the form for the personnel without tertiary education (< ISCED 5), and having the National Pay Scale System for Public Administration as the starting point, it is estimated an average salary for each person reported by the unit. The aggregate amount of these salaries is compared with the personnel expenditure reported by the Unit, compared also with the response of the previous year (when available), and analysed by the IPCTN survey staff.
Calculation on average salaries, considering only the report expenditure by the units are made, in order to validate the amount that was reported. if the average salary is too low or too high, units are contacted to provide clarifications.
In GOV sector, calculations of Capital cost are made only for the Hospitals, by considering the FTE of the R&D personnel, the HC of the human resources and the expenditures Hospitals.

During all validation process, if inconsistencies, or major variations, are detected, units are contacted for further clarification and, if needed, for correcting errors.

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)

18.5.2. 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	According to the levels given by the Nomenclature of Territorial Units for Statistics (NUTS) and the location of the R&D Unit (obtained by the District in the form).
Coefficients used for estimation of the R&D share of more general expenditure items	Not applicable
Inclusion or exclusion of VAT and provisions for depreciation in the measurement of expenditures	In accordance with FM (2015); the exclusion of VAT and provisions for depreciation is in the R&D form explanatory notes.

18.5.4. Weighting and estimation methods

Description of weighting method	Not applicable
Description of the estimation method	Not applicable

18.6. Adjustment

Not requested.

18.6.1. Seasonal adjustment

Not requested.

Brief historical notes on the IPCTN Survey (all sectors included):

• The IPCTN survey started to be administrated in 1982 (every two years; even years), however in 1994 was a gap year (missing data). For the years that the IPCTN survey was not administrated, data were based in simple averages between the surveyed years.
• For 1993 and 1994, the GERD were estimated by applying the annual average growth rate of the period 1992-1995. By sector of performance, the value was distributed in terms of their weight (%) in the GERD, as it was observed in 1992.
• For the 1999 IPCTN survey, special attention was given to the public hospital and clinics: a special survey was launched based on R&D undertaken projects (project approach).
• From 2001 onwards: DGEEC has started to undertake electronic Survey administration and also postal survey (when required by the units). In 1997 and 1999: Floppy disk and postal survey. Until 1995: postal survey.
• From 2008 onwards, the IPCTN Survey started to be administrated yearly.
• In the 2009 IPCTN Survey, it was made a new revision of the hospitals’ core model questionnaire, and, from 2011 onwards, hospitals and health facilities were surveyed along with other units (in the institutional sector).
• From 2008 to 2010, phases 1, 2 and 3 of clinical trials were surveyed in R&D core model questionnaire for public and university hospitals.
• From years 2009 to 2011, DGEEC had reviewed data according to the following: i) removed all master students doing thesis from R&D personnel data that had been added to specific institutions (universities, colleges and polytechnic institutes) in the years 2009, 2010 and 2011 (that were estimated by DGEEC); ii) added postgraduate students at the PhD level with an individual R&D grant, financed by FCT, that weren’t included in the R&D personnel data of IPCTN surveys from 2009 to 2011.
• In 2010, it was introduced a new section in the IPCTN Survey for the BE sector: Section VI – Biotechnology R&D activities.
• In 2012, it was introduced the Section VI – Biotechnology R&D activities in the IPCTN Survey for the PNP, GOV and HE sectors. These data collection was interrupted from 2015 to 2017, and it was put back on in the 2018 survey.

IPCTN23i_Formulario
IPCTN23i_Formulario_ENG
R&D Survey’s Methodological Document (IPCTN23i)

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.

2 October 2025

See below

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

See below

Not requested.

Reference year.

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.

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.

At national level is also 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.