This is an application programming interface (API) that opens up core EU legislative data for further use. The interface uses JSON, meaning that you have easy to use machine-readable access to meta data on European Union legislation. It will be useful if you want to use or analyze European Union legislative data in a way that the official databases are not originally build for. The API extracts, organize and connects data from various official sources.

The API is based on the most important official EU-databases (EUR-Lex, PreLex and Council public votes).

EudraGMDP is the name for the Union database referred to in article 111(6) of Directive 2001/83/EC and article 80(6) of Directive 2001/82/EC.

It contains the following information:

• Manufacturing and import authorisations
• Good Manufacturing Practice (GMP) certificates.
• Statements of non-compliance with GMP
• GMP inspection planning in third countries
• Wholesale Distribution Authorisations
• Good Distribution Certificates (GDP)
• Statements of non-compliance with GDP
• Registration of manufacturers, importers and distributors of active substances for human use located in the EEA

The database provides information on all EU Geographical Indications (GI) for agri-food products, wine and spirit drinks registered and protected in the European Union. It includes status (applied, published or registered), product specification, and a direct link to the legal basis when they are officially protected.

Region-industry trade flow data provide useful information for policy makers and constitute necessary inputs for dynamic spatial general equilibrium modellers. EU official databases only provide data at the national-sectoral or regional-only level. Regional Trade Data for Europe are compiled at the regional level with sectoral detail and are intended for being used in dynamic spatial general equilibrium modelling and social-economic analysis for answering a wide-range of policy questions, including policies related to investments in innovation, defence, human capital, green infrastructure and SDGs. EU Economic Modelling System (EU-EMS).

Full edition for public use. The REMINDER Integrated Multilevel Database on Migration in the EU brings together cross-national public opinion data and statistics related to immigration and EU mobility from multiple sources. The archived material offers complete replication code and auxiliary files to assist researchers in reconstructing and expanding the database for their own analyses. Please note that replication requires users to access the original survey data separately. The integrated database consists of 184400 observations and 160 variables, 61 of which are at the country level (28 EU plus Norway and Switzerland). We harmonize existing and newly collected survey data between 2002 and 2017, matched with country level data on the welfare impacts of immigration as well as stocks and flows of immigrant populations.

The EU’s Global Engagement database was developed by a research team composed of Ulrich Krotz, Katerina Wright and Danilo Di Mauro within the Europe in the World programme of the Global Governance Programme. It provides a comprehensive overview of EU military operations and civilian missions under the Common Security and Defence Policy (CSDP). The primary purpose of the database is to fill the gap in existing empirical knowledge by providing the first centralized, comprehensive, and accurate database on the EU’s military operations and civilian missions worldwide. The database also provides some indicators of the level of the EU’s engagement globally. The version 2.0 of the database contains detailed information on all of the 35 military operations and civilian missions initiated from the first CSDP operation in January 2003 to December 2017. All of the 73 variables recorded for each of the 35 (completed or ongoing) operations have been updated through the end of December 2017. Select variables include: the number and percentage of EU member states involved, the duration of deployment, the number of troops or personnel deployed by each EU member state, the goals of each operation and mission, the geographic area of deployment, the type and intensity of the conflict in the area of intervention, the costs, and a combined index of EU engagement. Within the Codebook, in addition to variable descriptions and statistics, we also include fact-sheets for every mission and operation, along with 92 figures describing the findings.

This database was prepared in the context of the EFSA mandate on plant pest surveillance (M-2020-0114), at the request of the European Commission. Its purpose is to guide the Member States in preparing data and information for designing statistically sound and risk-based surveys of non-EU tephritid fruit flies (Diptera: Tephritidae) regulated as Union quarantine pests. This database provides information on taxonomy, distribution, biology, host range, and detection and identification of 254 species of non-EU Tephritidae belonging to the 75 taxa listed in Commission Implementing Regulation (EU) 2019/2072. The database summarizes the information included in the eight crop-specific EFSA pest survey cards on non-EU Tephritidae, and is part of a package that includes eight crop-based survey cards and a guide for selecting the appropriate card for preparing surveys (EFSA et al., 2023).

EU-Hydro is a dataset for all EEA38 countries and the United Kingdom providing photo-interpreted river network, consistent of surface interpretation of water bodies (lakes and wide rivers), and a drainage model (also called Drainage Network), derived from EU-DEM, with catchments and drainage lines and nodes. The EU-Hydro dataset is distributed in separate files (river network and drainage network) for each of the 35 major basins of the EEA38 + UK area, in GDB and GPKG formats. The production of EU-Hydro and the derived layers was coordinated by the European Environment Agency in the frame of the EU Copernicus programme.

The European Union Visitor Visa Database contains statistics on short-stay visa issuing practices. It is based on official administrative data, cleaned-up to provide a consistent time-series from 2005 to 2022.

Background As a non-immigrant visa, a visitor visa is typically valid for a visit of up to 3 months and grants access to the entire Schengen area (for the reporting states that are full members of Schengen). Short-stay visas are an important component of border control practices, providing a mechanism for screening visitors before they arrive at the physical borders.

The statistics are reported in the original administrative data on a per consulate level. A reporting state will typically be a member of the European Union (EU) and the Schengen free travel area. The dataset does include, however, statistics reported by states in the process of becoming Schengen members. It also includes data from European countries that are a part of the Schengen but not members of the EU, such as Norway.

The dataset includes a column with the refusal rate calculated as the share of visas not issued as a total of the number of visas issued and not issued. Note that visas issued includes both explicit refusals as well as lapsed or otherwise discontinued applications.

The dataset made available here includes application statistics. It should be noted that these cover only one albeit important component of the common visa policy. Other major elements include the common list of countries subject to a visa requirement in the first place as well as consular cooperation on visa issuing.

The code for creating the dataset, as well as further details on sources, can be found in the Github repository.

Use cases The dataset can be used to probe questions on the state and evolution of EU cooperation in the area of borders and migration control. Problems that can be investigated with the data include for example: - Patterns of liberal and restrictive border practices and their determinants. - The degree of harmonization, convergent and divergent visa practices, between EU states

Acknowledgements As detailed in the repository, the raw data is processed (cleaned-up) as evidenced in the source code. The data for 2005-2012 have been imported relying on earlier data clean-up done in connection with the construction of the European Visa Database (see background section). The country classification (income group and regions) are sourced from The World Bank: World Bank Country and Lending Groups: Country classification dataset

A number of layers for soil properties have been created based on data from the European Soil Database in combination with data from the Harmonized World Soil Database (HWSD) and Soil-Terrain Database (SOTER).

The EUPOL dataset includes virtually all information contained in the European Commission’s online database PreLex. The mission of PreLex is to monitor the inter-institutional decision-making process of the EU, providing information about various formal events and institutional actors involved in policy-making, as well as cross-references to documents contained in other online databases. In combination with its long-term coverage since the mid 1970s, PreLex is a useful database for studies of EU politics. The EUPOL dataset provides the complete information contained in PreLex in a standardized and machine-readable format.

About

Overview from FAQ:

The Market Access Database is an important operational tool of the European Union's Market Access Strategy, supporting a continuous three-way exchange of information between the EU institutions, Member States and European business. The Market Access Strategy is a key pillar of the EU's Trade Policy which aims to reduce the obstacles faced by European exporters of goods and services. The Market Access Database is a free, interactive, easy to use service providing: Information about Market Access conditions in non-EU countries.

• A systematic way for the European Commission to follow up complaints from businesses about barriers to trade in non-EU countries.
• A means of ensuring that our trading partners are abiding by their international commitments.
• Better input for defining the EU's trade policy objectives on further trade liberalisation in the framework of the World Trade Organisation (e.g. Doha Development Agenda) and new free trade agreements between the EU and preferential partners (e.g. EU - MERCOSUR).

Access

Access to material via search interfaces, including:

• Complaint register
• Applied Tariff Database
• Trade Barriers Database
• SPS Database
• Statistical Database

Openness

Free to be re-used as long as attribution is given. The Copyright notice on the European Commission website states:

Reproduction is authorised, provided the source is acknowledged, save where otherwise stated.

Where prior permission must be obtained for the reproduction or use of textual and multimedia information (sound, images, software, etc.), such permission shall cancel the above-mentioned general permission and shall clearly indicate any restrictions on use.

Access to the Exporter's Guide and Applied Tariffs sections is limited to those within EU countries:

Access to the Sectoral and Trade Barriers Database, SPS Database, Statistics and Studies sections is free. However, information in the Exporter's Guide and Applied Tariffs sections is restricted to users in the Member States of the European Union and Acceding or Candidate Countries. From a technical point of view, if the computer on which your browser is running is not directly connected to the internet via an Internet Service Provider located in one of those countries, then you are prohibited from viewing the Exporter's Guide and Applied Tariffs data for any purpose.

This database (2006) is a set of raster data sets that have been derived from the European soil Database v2, for most attributes. The values for the attributes are categorized (non-continuous). These rasters are an interpretation of the data that are contained in the ESDB v2.0

This statistic shows the frequency mid-market businesses update their databases in Europe in 2016. The majority of respondents updated their databases every month with a total of ** percent.

The online database of collections (registry) provides an abundance of useful information on the most exciting collections and treasures of cultural opposition for the purposes of network building, learning and research.

EFSA is regularly evaluating pesticide occurrence data in food generated under the official monitoring programs of Member States with respect to consumer exposure and risk assessment. Most of these data refer to raw commodities (RAC) because maximum residue levels established under European legislation reflect pesticide residues only in the RAC. However, food processing operations can have decisive effects on pesticide residue levels and therefore consumer exposure. This database has been developed to compile validated processing factors for pesticide residues in food in line with the EFSA food classification and description system (FoodEx2).

The database is complemented by the following publications:

• Background Document on the EU Database of Processing Factors for Pesticide Residues
• Compendium of Representative Processing Techniques Investigated in Regulatory Studies for Pesticides
• Linking Processed Foods and Processing Techniques to the FoodEx2 Coding System

Abstract

EU-SILC has become the EU reference source for comparative statistics on income distribution and social exclusion at European level, particularly in the context of the "Program of Community action to encourage cooperation between Member States to combat social exclusion" and for producing structural indicators on social cohesion for the annual spring report to the European Council. The first priority is to be given to the delivery of comparable, timely and high quality cross-sectional data.

There are two types of datasets: 1) Cross-sectional data pertaining to fixed time periods, with variables on income, poverty, social exclusion and living conditions. 2) Longitudinal data pertaining to individual-level changes over time, observed periodically - usually over four years.

Longitudinal data is limited to income information and a limited set of critical qualitative, non-monetary variables of deprivation, aimed at identifying the incidence and dynamic processes of persistence of poverty and social exclusion among subgroups in the population. The longitudinal component is also more limited in sample size compared to the primary, cross-sectional component. Furthermore, for any given set of individuals, microlevel changes are followed up only for a limited duration, such as a period of four years. For both the cross-sectional and longitudinal components, all household and personal data are linkable. Furthermore, modules providing updated information in the field of social exclusion is included starting from 2005.

Social exclusion and housing-condition information is collected at household level. Income at a detailed component level is collected at personal level, with some components included in the "Household" section. Labour, education and health observations only apply to persons 16 and older. EU-SILC was established to provide data on structural indicators of social cohesion (at-risk-of-poverty rate, S80/S20 and gender pay gap) and to provide relevant data for the two 'open methods of coordination' in the field of social inclusion and pensions in Europe.

This is the 4th release of 2008 Longitudinal Dataset, as published by Eurostat in March 2012.

Geographic coverage

The survey covers following countries: Austria, Belgium, Bulgaria, Czech Republic, Denmark, Estonia, Greece, Spain, France, Ireland, Italy, Cyprus, Latvia, Lithuania, Luxembourg, Hungary, Netherlands, Poland, Portugal, Romania, Slovenia, Slovakia, Finland, Sweden, United Kingdom, Iceland, Norway.

Small parts of the national territory amounting to no more than 2% of the national population and the national territories listed below may be excluded from EU-SILC: France - French Overseas Departments and territories; Netherlands - The West Frisian Islands with the exception of Texel; Ireland - All offshore islands with the exception of Achill, Bull, Cruit, Gorumna, Inishnee, Lettermore, Lettermullan and Valentia; United kingdom - Scotland north of the Caledonian Canal, the Scilly Islands.

Analysis unit

• Households;
• Individuals 16 years and older.

Universe

The survey covered all household members over 16 years old. Persons living in collective households and in institutions are generally excluded from the target population.

Kind of data

Sample survey data [ssd]

Sampling procedure

On the basis of various statistical and practical considerations and the precision requirements for the most critical variables, the minimum effective sample sizes to be achieved were defined. Sample size for the longitudinal component refers, for any pair of consecutive years, to the number of households successfully interviewed in the first year in which all or at least a majority of the household members aged 16 or over are successfully interviewed in both the years.

For the cross-sectional component, the plans are to achieve the minimum effective sample size of around 131.000 households in the EU as a whole (137.000 including Iceland and Norway). The allocation of the EU sample among countries represents a compromise between two objectives: the production of results at the level of individual countries, and production for the EU as a whole. Requirements for the longitudinal data will be less important. For this component, an effective sample size of around 98.000 households (103.000 including Iceland and Norway) is planned.

Member States using registers for income and other data may use a sample of persons (selected respondents) rather than a sample of complete households in the interview survey. The minimum effective sample size in terms of the number of persons aged 16 or over to be interviewed in detail is in this case taken as 75 % of the figures shown in columns 3 and 4 of the table I, for the cross-sectional and longitudinal components respectively.

The reference is to the effective sample size, which is the size required if the survey were based on simple random sampling (design effect in relation to the 'risk of poverty rate' variable = 1.0). The actual sample sizes will have to be larger to the extent that the design effects exceed 1.0 and to compensate for all kinds of non-response. Furthermore, the sample size refers to the number of valid households which are households for which, and for all members of which, all or nearly all the required information has been obtained. For countries with a sample of persons design, information on income and other data shall be collected for the household of each selected respondent and for all its members.

At the beginning, a cross-sectional representative sample of households is selected. It is divided into say 4 sub-samples, each by itself representative of the whole population and similar in structure to the whole sample. One sub-sample is purely cross-sectional and is not followed up after the first round. Respondents in the second sub-sample are requested to participate in the panel for 2 years, in the third sub-sample for 3 years, and in the fourth for 4 years. From year 2 onwards, one new panel is introduced each year, with request for participation for 4 years. In any one year, the sample consists of 4 sub-samples, which together constitute the cross-sectional sample. In year 1 they are all new samples; in all subsequent years, only one is new sample. In year 2, three are panels in the second year; in year 3, one is a panel in the second year and two in the third year; in subsequent years, one is a panel for the second year, one for the third year, and one for the fourth (final) year.

According to the Commission Regulation on sampling and tracing rules, the selection of the sample will be drawn according to the following requirements:

1. For all components of EU-SILC (whether survey or register based), the cross-sectional and longitudinal (initial sample) data shall be based on a nationally representative probability sample of the population residing in private households within the country, irrespective of language, nationality or legal residence status. All private households and all persons aged 16 and over within the household are eligible for the operation.
2. Representative probability samples shall be achieved both for households, which form the basic units of sampling, data collection and data analysis, and for individual persons in the target population.
3. The sampling frame and methods of sample selection shall ensure that every individual and household in the target population is assigned a known and non-zero probability of selection.
4. By way of exception, paragraphs 1 to 3 shall apply in Germany exclusively to the part of the sample based on probability sampling according to Article 8 of the Regulation of the European Parliament and of the Council (EC) No 1177/2003 concerning

Community Statistics on Income and Living Conditions. Article 8 of the EU-SILC Regulation of the European Parliament and of the Council mentions: 1. The cross-sectional and longitudinal data shall be based on nationally representative probability samples. 2. By way of exception to paragraph 1, Germany shall supply cross-sectional data based on a nationally representative probability sample for the first time for the year 2008. For the year 2005, Germany shall supply data for one fourth based on probability sampling and for three fourths based on quota samples, the latter to be progressively replaced by random selection so as to achieve fully representative probability sampling by 2008. For the longitudinal component, Germany shall supply for the year 2006 one third of longitudinal data (data for year 2005 and 2006) based on probability sampling and two thirds based on quota samples. For the year 2007, half of the longitudinal data relating to years 2005, 2006 and 2007 shall be based on probability sampling and half on quota sample. After 2007 all of the longitudinal data shall be based on probability sampling.

Detailed information about sampling is available in Quality Reports in Documentation.

Mode of data collection

Mixed

Abstract

The dataset files contain a data on the EU Standards Database for agricultural products and textiles/clothing. The EU Standards Database collates European standards for agricultural products and textiles/clothing over the period 1995-2003, and maps them to the Harmonized System. For each product-year combination, counts are given both of the number of standards and of the number of pages of standards. In general, rapid growth is observed both in the number and average length of standards.

Kind of data

Aggregate data [agg]

Mode of data collection

Other [oth]

eCertis (https://ec.europa.eu/tools/ecertis) is the information system that helps you identify different certificates requested in procurement procedures across the EU. If you are a European company wishing to participate in a public procurement procedure, or if you are a public buyer that has to evaluate bids received from various Member States, eCertis can help you understand what evidence is requested or provided by the other party. Just enter the description of the document used for proving the fulfilment of the exclusion or selection criteria in a given procedure. The search function is supported in any of the EU languages.

Please note that eCertis is a reference tool and not a service of legal advice. It does not guarantee that the information resulting from a query will be recognised as valid by a contracting authority. It is just an information tool which helps you identify and recognise the certificates and attestations that are most commonly requested in the context of procurement procedures of different Member States. The IT system was developed by the European Commission however the information contained in the database is provided by the national authorities and updated on a regular basis.

The complete data about criteria, evidence and issuers can be extracted from the home page as an EXCEL export.

The BABEL Polish Database is a speech database that was produced by a research consortium funded by the European Union under the COPERNICUS programme (COPERNICUS Project 1304). The project began in March 1995 and was completed in December 1998. The objective was to create a database of languages of Central and Eastern Europe in parallel to the EUROM1 databases produced by the SAM Project (funded by the ESPRIT programme).

The BABEL consortium included six partners from Central and Eastern Europe (who had the major responsibility of planning and carrying out the recording and labelling) and six from Western Europe (whose role was mainly to advise and in some cases to act as host to BABEL researchers). The five databases collected within the project concern the Bulgarian, Estonian, Hungarian, Polish, and Romanian languages.

The Polish database consists of the basic "common" set which is: • The Many Talker Set: 30 males, 30 females; each to read 100 numbers, 3 connected passages and 5 “filler” sentences (or 4 passages if no fillers needed). • The Few Talker Set: 5 males, 5 females, normally selected from the above group: each to read 5 blocks of 100 numbers, 15 passages and 25 filler sentences ( or 20 passages if fillers not needed), and 5 lists of syllables. • The Very Few Talker Set: 1 male, 1 female, selected from many-talker set: 5 blocks of syllables, with and without carrier sentences.