This dataset contains information about projects and their results funded by the European Union under the Horizon 2020 framework programme for research and innovation from 2014 to 2020.

The dataset is composed of six (6) different sub-set (in different formats):

• H2020 projects – which includes participating organisations, legal basis information, topic information, project URLs and classification with the European Science Vocabulary (EuroSciVoc)
• H2020 project IPRs (Intellectual Property Rights) [N.B.: This dataset only includes patent data for awarded patents available in the database of the European Patent Office (EPO)]
• H2020 project deliverables (meta-data and links to deliverables included since May 2019)
• H2020 project publications (meta-data and links to publications included since May 2019)
• H2020 report summaries (periodic or final publishable summaries included since September 2018)
• Principal Investigators in Horizon 2020 ERC projects

Reference data (programmes, topics, topic keywords funding schemes (types of action), organisation types and countries) can be found in this dataset: https://data.europa.eu/euodp/en/data/dataset/cordisref-data

EuroSciVoc is available here: https://data.europa.eu/data/datasets/euroscivoc-the-european-science-vocabulary

CORDIS datasets are produced monthly. Therefore, inconsistencies may occur between what is presented on the CORDIS live website and the datasets.

The EURIO (EUropean Research Information Ontology) Knowledge Graph is the knowledge graph containing CORDIS data about research projects funded by the H2020 and FP7 framework programmes. The EURIO Knowledge Graph can be accessed via its SPARQL endpoint at this link: https://cordis.europa.eu/datalab/sparql-endpoint/en. This dataset provides both a database dump of the EURIO Knowledge Graph and subsets of the EURIO Knowledge Graph in the form of named graphs.

The schema defining the structure of the named graphs is the EURIO ontology, available at https://op.europa.eu/en/web/eu-vocabularies/eurio. All files are available in the following formats: RDF, TTL, N-Quads, JSONLD, and N-Triples. For other formats (xlsx,csv etc ;…), please refer to these links: https://data.europa.eu/data/datasets/cordish2020projects and https://data.europa.eu/data/datasets/cordisfp7projects

The file EURIO Knowledge Graph contains a database dump of all CORDIS data about research projects funded under the H2020 and FP7 framework programmes. The file Project contains all projects funded under the H2020 and FP7 framework programmes. The file Organisation contains all organisations funded under the H2020 and FP7 framework programmes.

Reference data (countries, funding schemes/types of action, etc....) can be found in this dataset https://data.europa.eu/euodp/en/data/dataset/cordisref-data, while the EuroSciVoc taxonomy can be freely downloaded or browsed on the EuVocabularies website at this link: https://op.europa.eu/en/web/eu-vocabularies/dataset/-/resource?uri=http://publications.europa.eu/resource/dataset/euroscivoc

Analysis of ‘CORDIS - EU research projects under Horizon 2020 (2014-2020)’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from http://data.europa.eu/88u/dataset/cordish2020projects on 08 January 2022.

--- Dataset description provided by original source is as follows ---

This dataset contains projects and related organisations funded by the European Union under the Horizon 2020 framework programme for research and innovation from 2014 to 2020.

The file 'H2020 Projects' contains the public grant information for each project, including the following information: Record Control Number (RCN), project ID (grant agreement number), project acronym, project status, funding programme, topic, project title, project start date, project end date, project objective, project total cost, EC max contribution (commitment), call ID, funding scheme (type of action), coordinator, coordinator country, participants (ordered in a semi-colon separated list), participant countries (ordered in a semi-colon separated list).

In the individual XML files of the projects you'll find, in addition, their classification with the newly introduced EuroSciVoc taxonomy (fields of science) as well as links to related editorial articles such as news or Results in Brief.

The participating organisations are listed in the file 'H2020 Organisations' which includes: project Record Control Number (RCN), project ID, project acronym, organisation role, organisation ID, organisation name, organisation short name, organisation type, participation ended (true/false), EC contribution, organisation country.

The periodic or final report summaries (or publishable summaries) from the projects have been included since September 2018.

The lists of publications and deliverables from the projects have been included since May 2019.

Reference data (programmes topics, funding schemes (types of action), organisation types and countries) can be found in this dataset: https://data.europa.eu/euodp/en/data/dataset/cordisref-data

CORDIS datasets are produced monthly. Therefore, inconsistencies may occur between what is presented on the CORDIS live website and the datasets.

--- Original source retains full ownership of the source dataset ---

This dataset is the combined research data of the MyWave project. It consists of of several data bundles. Each data bundle contains the research data of one ESR (combined, not per publication). Each data bundle also contains a dedicated readme.

In Horizon 2020 the Commission committed itself to running a flexible pilot on open research data (ORD Pilot). The ORD pilot aims to improve and maximise access to and re-use of research data generated by Horizon 2020 projects. It takes into account the need to balance openness and protection of scientific information, commercialisation and IPR, privacy concerns, security as well as data management and preservation questions. This ORD pilot comprises various selected areas of Horizon 2020 ('core areas' ). Projects not covered by the scope of the pilot can participate on an individual and voluntary project-by-project basis ('opt-in'). Projects may also decide not to participate in the pilot ('opt-out') at any stage of the project lifecycle. As of the Work Programme 2017 the ORD pilot scope is extended to cover all thematic areas of Horizon 2020 so as to make open research data the default, but retaining opt-out possibilities – however, this does not yet apply to the datasets analysed below. The ORD pilot applies primarily to the data needed to validate the results presented in scientific publications. Other data can also be provided by the beneficiaries on a voluntary basis, as stated in their Data Management Plans (DMP). Costs associated with data management, including the creation of a data management plan, can be claimed as eligible costs in any Horizon 2020 grant. It should be noted that the potential participation in the pilot is not part of the evaluation of proposals: in other words, proposals are not evaluated more favourably because they are part of the ORD pilot and are not penalised for opting out of the ORD pilot. The legal requirements for projects participating in this pilot are contained in article 29.3 of the Model Grant Agreement. This file does not contain research data generated by Horizon 2020 projects themselves. Rather it provides an overview of the take-up of the Commission's Open Research Data Pilot (ORD Pilot) It gives statistics by call about proposals: - Opting out of the Pilot on Open Access Research data in H2020 - Participating in the Pilot on Open Access Research data in H2020 on a voluntary bases (opt-in). This overview encompasses two finalised datasets obtained from CORDA: 2014-2015 and 2015-2016. Data obtained from CORDA. the following instruments are excluded: SME instrument, cofund, and prizes. ERC grants are also not included for the 2015-2016 sample. These datasets have been cleaned in order to reduce overlap and replace previous datasets. In this period, 68% of the funded projects in the core areas (CA) participate in the ORD. Correspondingly, the average opt-out rate in signed grant agreements is 32%. Outside the core areas, 9% of projects make use of the voluntary opt-in possibility.

Collection of EU Research projects in soils during the last forty years (n = 1101 projects) funded by the successive European Commission Framework Programs (FP) for research and innovation (from FP1 to H2020)

This dataset provides an overview of EU-funded projects involving the University of Tours from 2021 to the present (mid 2025). The database lists projects active as of January 1, 2021 or later, which are either still ongoing or completed. It includes projects referenced on CORDIS (mainly Horizon 2020, Horizon Europe, and some EIT actions) and the Erasmus+ Project Results Platform (covering KA1, KA2, and Jean Monnet projects). It also identifies COST Actions. Each entry includes publicly available information: project title, description, dates, funding programme, call topic (if applicable), status, budget, and number of participants.

The MEDIATIZED EU project aims to study how the media discourses are constructed to foster or hamper the European project and how they resonate among the public by focusing on the elite-media-public triangle. The research was conducted in seven target countries: Ireland, Belgium, Estonia, Spain, Portugal, Hungary and Georgia.

This dataset is part of the integration of the MEDIATIZED EU project research data into the EU’s Open Research Data Pilot. In accordance with the Data Management Plan, public opinion survey data were deemed suitable for being openly shared through ORDP to be accessible and of use to other academic researchers in Europe and worldwide. Quantitative data derived from surveys was deemed suitable, with the only concerns being the heterogeneous nature of some of the survey questions in each target country.

The aim of the population surveys was to investigate public opinion about the media and elites in their country and the EU and how they interpret elite and media discourses on Europeanisation and European integration. The merged database allows the project participants and other researchers to compare their national research results with phenomena in other participating countries.

This dataset contains a subset of integrated survey data including those survey questions where comparative data was available. The final deliverable contains this subsection of the survey data which has been weighted and cleaned, in .SAV and .XLS formats, and provides the requisite codebook for the dataset.

For more on the MEDIATIZED EU project, visit our website at mediatized.eu or view our CORDIS profile at: https://cordis.europa.eu/project/id/101004534

This project has received funding from the European Union’s Horizon 2020 Research and Innovation programme under grant agreement no 101004534. Views and opinions expressed are however those of the authors only and do not necessarily reflect those of the European Union or European Research Executive Agency. Neither the European Union nor the granting authority can be held responsible for them.

The EU Horizon 2020 project DiverIMPACTS aims to promote the realisation of the full potential of crop diversification through rotation, multicropping and intercropping by demonstrating technical, economic and environmental benefits for famers, along the value chain and for society at large, and by providing innovations that can remove existing barriers and lock-ins of practical diffusion.

DiverIMPACTS does so by combining findings from several participatory case studies with a set of field experiments across Europe, and translating these into strategies, recommendations and fit-for-purpose tools developed with and for farmers, advisors and other actors along the value chain.

To first gain a good overview of the current situation, i.e. the existing success stories and challenges of crop diversification in Europe, Work Package 1 (WP 1) identified and analysed factors of success and failure associated with a variety of crop diversification experiences (CDEs) outside those already represented in the consortium (see Deliverable 1.1). WP 1 thus makes sure that the rich experience with crop diversification initiatives across Europe (e.g. from other Horizon 2020 projects) is taken into account for developing strategies, recommendations and tools.

Deliverable 1.1 provided i) a list of key drivers (ex ante occurrence of market opportunities, environmental constraints, availability of enabling advisory services, land and workforce availability etc.) to be further considered in WP3, and WP5; and ii) a comprehensive and exhaustive description of the links between key factors and CDE types. This analysis is the basis for consolidating or updating the tentative typology of crop diversification situations used for setting up DiverIMPACTS (case studies), and was used for selecting experiences for more detailed investigations in T1.2. It also complements the identification and characterisation of lock-ins and barriers to crop diversification, and serves their overcoming. During the process of collecting, cleaning and analysing the survey data, a Database of European diversification experiences was created.

All together 128 valid responses from 15 European countries – mainly from the project countries Belgium, France, Germany, Hungary, Italy, the Netherlands, Poland, Romania, Sweden, Switzerland, and UK, but also from Denmark, Finland, Luxemburg and Spain were received in T1.1, and were included in the database.

The database is stored in original and back-up form in a tabular ='.csv'= format that can be opened in Excel on the Sharepoint system of the project and now on Zenodo, under restricted WP1 area. A further ='.csv'= file was created to store the metadata of the database. This file helps to have a better overview of the questions and sub-questions that were asked in the survey and the type of answer that could be provided to each of them (e.g. factor, Yes-No selection or character).

Using the meta data and the database, a selection of personal data fields has been made (e.g. email addresses and names of people) that cannot be published with open access, and needs special attention and data handling. These variables were removed from the original database, and a public version of the database was created that can be shared with third parties. Links to the data files will be shared here after.

Developing a Shiny(c) application in R was chosen as a solution to visualize the public data, and make it possible for Partners and all interested parties to interactively view the survey results. The Shiny application is shared as an R-package and are freely accessible on the internet. The users have the possibility to download application and public data in order to visualize them on their own computer. A remote solution, facilitating the consultation of the data, will be installed in CRA-W, where the open data analyses module will be hosted. A short user guide and tutorial is part of this deliverable for helping interested parties to use the Shiny interface.

The chosen approach, linking R scripts, R packages and data files, will be useful in the future in order to continiously complete the data base and to update the application (new graphs, new functions regarding the demand of the main users). The release of the application will be shared using modern technologies of information and communication : project website, newsletter, blogs, twitter and other social networks.

The main deliverable (D1.2) which is public, is available here : 10.5281/zenodo.3966852

Analysis of ‘Total EC funding to participants in H2020 ICT projects’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from http://data.europa.eu/88u/dataset/xn4qxz0bmutu8bpd6z2eew on 08 January 2022.

--- Dataset description provided by original source is as follows ---

Value of European Commission funding committed through grant agreements signed, during the reference year, with participants in ICT research projects under Horizon 2020 (LEIT ICT, Excellent Science, Societal Challenges 1, 6 and 7). Projects under negotiation are not included.

Original source

Common Research Data Warehouse:

http://webcorda.rtd.cec.eu.int/index.cfm?page=index

Parent dataset

This dataset is part of of another dataset:

http://digital-agenda-data.eu/datasets/digital_agenda_scoreboard_key_indicators

--- Original source retains full ownership of the source dataset ---

Analysis of ‘Open Research Data (ORD) - the uptake in Horizon 2020’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from http://data.europa.eu/88u/dataset/open-research-data-the-uptake-of-the-pilot-in-the-first-calls-of-horizon-2020 on 10 January 2022.

--- Dataset description provided by original source is as follows ---

In Horizon 2020 the Commission committed itself to running a flexible pilot on open research data (ORD Pilot). The ORD pilot aims to improve and maximise access to and re-use of research data generated by Horizon 2020 projects. It takes into account the need to balance openness and protection of scientific information, commercialisation and IPR, privacy concerns, security as well as data management and preservation questions.

This ORD pilot comprises various selected areas of Horizon 2020 ('core areas' ). Projects not covered by the scope of the pilot can participate on an individual and voluntary project-by-project basis ('opt-in'). Projects may also decide not to participate in the pilot ('opt-out') at any stage of the project lifecycle.

As of the Work Programme 2017 the ORD pilot scope is extended to cover all thematic areas of Horizon 2020 so as to make open research data the default, but retaining opt-out possibilities – however, this does not yet apply to the datasets analysed below.

The ORD pilot applies primarily to the data needed to validate the results presented in scientific publications. Other data can also be provided by the beneficiaries on a voluntary basis, as stated in their Data Management Plans (DMP). Costs associated with data management, including the creation of a data management plan, can be claimed as eligible costs in any Horizon 2020 grant.

It should be noted that the potential participation in the pilot is not part of the evaluation of proposals: in other words, proposals are not evaluated more favourably because they are part of the ORD pilot and are not penalised for opting out of the ORD pilot.

The legal requirements for projects participating in this pilot are contained in article 29.3 of the Model Grant Agreement.

This file does not contain research data generated by Horizon 2020 projects themselves. Rather it provides an overview of the take-up of the Commission's Open Research Data Pilot (ORD Pilot) It gives statistics by call about proposals: - Opting out of the Pilot on Open Access Research data in H2020 - Participating in the Pilot on Open Access Research data in H2020 on a voluntary bases (opt-in).

This overview encompasses two finalised datasets obtained from CORDA: 2014-2015 and 2015-2016. Data obtained from CORDA. the following instruments are excluded: SME instrument, cofund, and prizes. ERC grants are also not included for the 2015-2016 sample. These datasets have been cleaned in order to reduce overlap and replace previous datasets. In this period, 68% of the funded projects in the core areas (CA) participate in the ORD. Correspondingly, the average opt-out rate in signed grant agreements is 32%. Outside the core areas, 9% of projects make use of the voluntary opt-in possibility.

--- Original source retains full ownership of the source dataset ---

2025.05.26 Update

Updated the Research Projects csv with renamed columns from 'title' and 'abstract' to 'grant_title' and 'grant_abstact'.

The data download from EPMC already contained a 'title' column, refering to the awardee title (e.g., Professor) so after the final column harmonisation step some EPMC entries in the original file had the wrong information (i.e., "Professor", "Dr", etc) instead of project titles.

_

This Zenodo entry provides integrated and harmonised datasets of research grants and associated awardees from multiple funding databases, specifically designed to facilitate research funding analyses. The dataset is one of the most comprehensive openly accessible compilations of research project funding information, containing over 320,000 harmonised entries from major UK and European funding databases. While predominantly UK-focused, the dataset also includes significant international coverage from European Commission programmes and international funders captured in Europe PMC.

This dataset will be updated several times per year to include new data and refinements

The datasets consolidate grant information from four key sources: Europe PMC (EPMC), UKRI Gateway to Research, NIHR Funding and Awards, and the European Commission's Horizon 2020 and Horizon Europe programmes. My sincere thanks go to all those involved in creating and maintaining this essential open data infrastructure.

Two datasets are included:

1. Research projects.csv: This dataset includes harmonised grant details such as grant IDs, titles, abstracts, funding organisations, lead institutions (including available identifiers), country of origin, project start/end dates, and funding amounts (in original currencies).

2. Research projects awardees.csv: This dataset contains information about researchers and their institutional affiliations associated with each project. It includes researcher names, identifiers (ORCID, person IDs), affiliated organisations, their roles within projects, and associated grant IDs.

Research projects data coverage (Total: >320,000 entries):

• UKRI Gateway to Research: >160,000 entries

• Europe PMC: >90,000 entries

• European Commission: >50,000 entries

• NIHR Funding and Awards: >10,000 entries

Data harmonisation involved standardisation of formats, handling missing values, deduplication (prioritising completeness of records), and consistent assignment of country information using various methods appropriate to each data source.

Limitations include:

• Single-institution representation for multi-institutional EPMC grants.

• Country assignments based on inferred information where direct data was limited.

• Original currencies are retained without conversions.

• Inconsistent availability of organisational and researcher identifiers across data sources.

• Focus on project grant information - coverage of infrastructure investment from major UK funders is limited at the moment.

This entry also contains the processing code developed for reproducibility and transparency purposes, hosted in a Google Colab notebook. Detailed methodology, known limitations, and usage instructions are documented to support reproducibility and transparency in data processing.

Future work:

• Expanding to include additional national and international funding bodies.

• Collaborating with charity partners to incorporate charity-specific funding data.

• Linking datasets to other open-access resources, such as the Research Organization Registry (ROR), and liaising with other organisations doing similar work, to avoid duplication of efforts.

• Performing "live analyses" on datasets as they are updated, including advanced methods such as topic modelling.

Citation guidance:

If you use this dataset in your work, please cite it as follows:

Gómez Magenti, J. (2025). Harmonised datasets of research project grants from UK and European funders [Data set]. Zenodo. https://doi.org/10.5281/zenodo.15479411

This dataset is published in 2017 by the OpenAIRE project and the FAIR Data Expert Group.

It contains two survey data files, two pdf-files summarising the results in a report and an infographic, and a Readme.txt file.

The OpenAIRE project supports the open science ambitions of the European Commission. The project and in particular the Research Data Management team provide support, training and information on the Open Research Data Pilot. In this context, a survey was carried out to collect feedback on the Horizon 2020 template for Data Management Plans (DMPs). The team collaborated with the FAIR data expert group, which is providing recommendations to the European Commission on turning FAIR data into reality. One of the specific tasks of the Expert Group is contributing to an evaluation of the Horizon 2020 approach to DMPs, including future revisions of the template and the development of additional sector/ discipline-specific guidance. The aim of the survey was to collect experiences of researchers and DMP reviewers with the DMP template and guidelines on FAIR data management in Horizon 2020. The survey assesses the usefulness of the guidelines and any aspects that are confusing and unclear to determine what improvements can be made.

Feedback was sought from both researchers and research support staff. The survey was initially scheduled to run from 22 May to 21 June 2017. Several organisations were asked to help announce the survey, including OpenAIRE’s National Open Access Desks, the FAIR data expert group, FOSTER, LIBER, and the RDA Interest Group on Active DMPs. When the first survey responses showed only a small share of researchers, more stakeholders were contacted to specifically target this community. The European Research Area was approached, whose project officers circulated the survey call among award holders of EC projects. Early-career researchers were also informed through the YEAR network and EURODOC. This resulted in an extension of the survey to 21 July 2017.

At the close of the survey on 21 July 2017, a total number of 289 responses were reached. 50% of the respondents indicated that they were researchers, and 60% that they were (also) research support staff. OpenAIRE and the FAIR data expert group are very pleased with this balanced outcome and would like to thank all colleagues and organisations who promoted the survey, as well as everyone who took part in it.

Horizon 2020 programme supports access to and reuse of research data generated by Horizon 2020 projects through the Open Research Data Pilot (ORDP). To support the validation of scientific results, the pilot focuses on providing access to data needed to validate the scientific results. There are several types of such data, e.g. machine learning data sets, models, measurements, statistical results of experiments, survey outcomes, etc.

This deliverable summarizes the data that are expected to be collected in the course of the project and where and how they are stored. The aspect of providing open access to research data (as required by the European Commission’s Open Research Data Pilot, https://www.openaire.eu/what-is-the-open-research-data-pilot) is addressed in Section 3. Finally, in Section 4 we describe the data sets that were or are expected to be generated within the TRINITY projects and made freely available.

The European Copernicus Coastal Flood Awareness System (ECFAS) project will contribute to the evolution of the Copernicus Emergency Management Service (https://emergency.copernicus.eu/) by demonstrating the technical and operational feasibility of a European Coastal Flood Awareness System. Specifically, ECFAS will provide a much-needed solution to bolster coastal resilience to climate risk and reduce population and infrastructure exposure by monitoring and supporting disaster preparedness, two factors that are fundamental to damage prevention and recovery if a storm hits.

The ECFAS Proof-of-Concept development will run from January 2021-December 2022. The ECFAS project is a collaboration between Scuola Universitaria Superiore IUSS di Pavia (Italy, ECFAS Coordinator), Mercator Ocean International (France), Planetek Hellas (Greece), Collecte Localisation Satellites (France), Consorzio Futuro in Ricerca (Italy), Universitat Politecnica de Valencia (Spain), University of the Aegean (Greece), and EurOcean (Portugal), and is funded by the European Commission H2020 Framework Programme within the call LC-SPACE-18-EO-2020 - Copernicus evolution: research activities in support of the evolution of the Copernicus services.

This project has received funding from the European Union’s Horizon 2020 programme

Description of the containing files inside the Dataset.

Deliverable 5.1 is a comprehensive inventory of extreme coastal events that produced flooding at different locations along the European coastline. It includes the collection and identification of events, locations and available information on the test cases.

The purpose of the ECFAS database is to provide a source of information on extreme coastal events and locations that experienced coastal flooding, considering both hazard and impact aspects. Thus, the database collects events, sites and available information to support further investigation on specific test cases. Test cases are defined here as specific sites where an extreme event that generated flooding and damage occurred. The time frame considered for the analysis is between 2010 and 2020 in order to use recent satellite imagery with good resolution and including, if possible, overlap with Sentinel missions.

The product includes three files: 1) an Excel file with the inventory; 2) an accompanying report that includes the guidelines to use the inventory, other relevant information on the method used to implement the inventory and the sources of information; 3) the test cases polygons in .geojson format.

Disclaimer:

ECFAS partners provide the data "as is" and "as available" without warranty of any kind. The ECFAS partners shall not be held liable resulting from the use of the information and data provided.

Geodata of the EU Horizon 2020 project mySMARTLife. Geodata of the EU Horizon 2020 project mySMARTLife.

This database that can be used for macro-level analysis of road accidents on interurban roads in Europe. Through the variables it contains, road accidents can be explained using variables related to economic resources invested in roads, traffic, road network, socioeconomic characteristics, legislative measures and meteorology. This repository contains the data used for the analysis carried out in the papers:

1. Calvo-Poyo F., Navarro-Moreno J., de Oña J. (2020) Road Investment and Traffic Safety: An International Study. Sustainability 12:6332. https://doi.org/10.3390/su12166332

2. Navarro-Moreno J., Calvo-Poyo F., de Oña J. (2022) Influence of road investment and maintenance expenses on injured traffic crashes in European roads. Int J Sustain Transp 1–11. https://doi.org/10.1080/15568318.2022.2082344

3. Navarro-Moreno, J., Calvo-Poyo, F., de Oña, J. (2022) Investment in roads and traffic safety: linked to economic development? A European comparison. Environ. Sci. Pollut. Res. https://doi.org/10.1007/s11356-022-22567

The file with the database is available in excel.

DATA SOURCES

The database presents data from 1998 up to 2016 from 20 european countries: Austria, Belgium, Croatia, Czechia, Denmark, Estonia, Finland, France, Germany, Ireland, Italy, Latvia, Netherlands, Poland, Portugal, Slovakia, Slovenia, Spain, Sweden and United Kingdom. Crash data were obtained from the United Nations Economic Commission for Europe (UNECE) [2], which offers enough level of disaggregation between crashes occurring inside versus outside built-up areas.

With reference to the data on economic resources invested in roadways, deserving mention –given its extensive coverage—is the database of the Organisation for Economic Cooperation and Development (OECD), managed by the International Transport Forum (ITF) [1], which collects data on investment in the construction of roads and expenditure on their maintenance, following the definitions of the United Nations System of National Accounts (2008 SNA). Despite some data gaps, the time series present consistency from one country to the next. Moreover, to confirm the consistency and complete missing data, diverse additional sources, mainly the national Transport Ministries of the respective countries were consulted. All the monetary values were converted to constant prices in 2015 using the OECD price index.

To obtain the rest of the variables in the database, as well as to ensure consistency in the time series and complete missing data, the following national and international sources were consulted:

Eurostat [3]

Directorate-General for Mobility and Transport (DG MOVE). European Union [4]

The World Bank [5]

World Health Organization (WHO) [6]

European Transport Safety Council (ETSC) [7]

European Road Safety Observatory (ERSO) [8]

European Climatic Energy Mixes (ECEM) of the Copernicus Climate Change [9]

EU BestPoint-Project [10]

Ministerstvo dopravy, República Checa [11]

Bundesministerium für Verkehr und digitale Infrastruktur, Alemania [12]

Ministerie van Infrastructuur en Waterstaat, Países Bajos [13]

National Statistics Office, Malta [14]

Ministério da Economia e Transição Digital, Portugal [15]

Ministerio de Fomento, España [16]

Trafikverket, Suecia [17]

Ministère de l’environnement de l’énergie et de la mer, Francia [18]

Ministero delle Infrastrutture e dei Trasporti, Italia [19–25]

Statistisk sentralbyrå, Noruega [26-29]

Instituto Nacional de Estatística, Portugal [30]

Infraestruturas de Portugal S.A., Portugal [31–35]

Road Safety Authority (RSA), Ireland [36]

DATA BASE DESCRIPTION

The database was made trying to combine the longest possible time period with the maximum number of countries with complete dataset (some countries like Lithuania, Luxemburg, Malta and Norway were eliminated from the definitive dataset owing to a lack of data or breaks in the time series of records). Taking into account the above, the definitive database is made up of 19 variables, and contains data from 20 countries during the period between 1998 and 2016. Table 1 shows the coding of the variables, as well as their definition and unit of measure.

Table. Database metadata

Code

Variable and unit

fatal_pc_km

Fatalities per billion passenger-km

fatal_mIn

Fatalities per million inhabitants

accid_adj_pc_km

Accidents per billion passenger-km

p_km

Billions of passenger-km

croad_inv_km

Investment in roads construction per kilometer, €/km (2015 constant prices)

croad_maint_km

Expenditure on roads maintenance per kilometer €/km (2015 constant prices)

prop_motorwa

Proportion of motorways over the total road network (%)

populat

Population, in millions of inhabitants

unemploy

Unemployment rate (%)

petro_car

Consumption of gasolina and petrol derivatives (tons), per tourism

alcohol

Alcohol consumption, in liters per capita (age > 15)

mot_index

Motorization index, in cars per 1,000 inhabitants

den_populat

Population density, inhabitants/km2

cgdp

Gross Domestic Product (GDP), in € (2015 constant prices)

cgdp_cap

GDP per capita, in € (2015 constant prices)

precipit

Average depth of rain water during a year (mm)

prop_elder

Proportion of people over 65 years (%)

dps

Demerit Point System, dummy variable (0: no; 1: yes)

freight

Freight transport, in billions of ton-km

ACKNOWLEDGEMENTS

This database was carried out in the framework of the project “Inversión en carreteras y seguridad vial: un análisis internacional (INCASE)”, financed by: FEDER/Ministerio de Ciencia, Innovación y Universidades–Agencia Estatal de Investigación/Proyecto RTI2018-101770-B-I00, within Spain´s National Program of R+D+i Oriented to Societal Challenges.

Moreover, the authors would like to express their gratitude to the Ministry of Transport, Mobility and Urban Agenda of Spain (MITMA), and the Federal Ministry of Transport and Digital Infrastructure of Germany (BMVI) for providing data for this study.

REFERENCES

1. International Transport Forum OECD iLibrary | Transport infrastructure investment and maintenance.

2. United Nations Economic Commission for Europe UNECE Statistical Database Available online: https://w3.unece.org/PXWeb2015/pxweb/en/STAT/STAT_40-TRTRANS/?rxid=18ad5d0d-bd5e-476f-ab7c-40545e802eeb (accessed on Apr 28, 2020).

3. European Commission Database - Eurostat Available online: https://ec.europa.eu/eurostat/data/database (accessed on Apr 28, 2021).

4. Directorate-General for Mobility and Transport. European Commission EU Transport in figures - Statistical Pocketbooks Available online: https://ec.europa.eu/transport/facts-fundings/statistics_en (accessed on Apr 28, 2021).

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Full edition for scientific use. The dataset comprises the data from 1468 young learners aged between 8 and 21, who stem from 17 European countries and Israel/Palestine and participated in science workshops offered by 19 museums and maker spaces. Data was collected in the realm of the H2020-funded SySTEM 2020 project by the means of a quantitative survey. The survey operationalised the approach of science learning ecologies to investigate the way young learners connect with science. The dataset includes information about the everyday activities, which might foster informal science learning, the social environment of the learners, their attitudes towards science in general as well as towards science lessons in school and further comprises socio-demographic information about the respondents. The survey data was collected longitudinally, with 736 participants answering the same survey twice within the period of one year. Additionally, the cross-sectional data of 732 participants, who were only reached once, is included in the data set.

Analysis of ‘Total cost of H2020 ICT projects’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from http://data.europa.eu/88u/dataset/wjmb8iur70eunyjjqh7f6w on 07 January 2022.

--- Dataset description provided by original source is as follows ---

Value of the total cost of the ICT research projects for which a grant agreement was signed in the reference year, under the Horizon 2020 LEIT ICT, Excellent Science, Societal Challenges 1, 6 and 7). Total cost of the project is the sum of participants' total costs.

Original source

Common Research Data Warehouse:

http://webcorda.rtd.cec.eu.int/index.cfm?page=index

Parent dataset

This dataset is part of of another dataset:

http://digital-agenda-data.eu/datasets/digital_agenda_scoreboard_key_indicators

--- Original source retains full ownership of the source dataset ---