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.

Dataset about research projects funded under the programme Horizon 2020, from 2014 to 2020. Each row corresponds to the participation of a specific organisation in a specific research project.

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

The file 'cordis-h2020projects.csv' 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).

The participating organizations are listed in the file 'cordis-h2020organizations.csv' which includes: project Record Control Number (RCN), project ID, project acronym, organization role, organization ID, organization name, organization short name, organization type, participation ended (true/false), EC contribution, organization country.

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

https://data.europa.eu/euodp/en/data/dataset/cordisH2020projects

© European Union, 1994-2018

CORDIS, http://cordis.europa.eu/

Dataset for CO2 utilisation/valorisation options. Excel file consists of H2020 projects, grouped by field of CO2 utilisation (chemical production, fuels, algae, etc)

The metadata of interdisciplinary (IDR) and transdisciplinary (TDR) projects conducted under the European Union framework programs (FP7 & Horizon 2020) were collected from the Cordis database (https://cordis.europa.eu/). SHAPE-ID research team used periodic data dumps, stored in EU open data portal (https://data.europa.eu/euodp/en/data/dataset/cordisfp7projects and https://data.europa.eu/euodp/en/data/dataset/cordisH2020projects).

The data dump from May 2019 was used, so the FP7 database is complete while H2020 projects were still being added periodically.

CORDIS files were subsequently queried for interdisciplinar* or transdicsiplinar*, matched against title or abstract (“objective”). This procedure allowed for creating two subsets:

FP7_projects_May2019_IDR_TDR.csv 1750 FP7 projects. Out of 1699 IDR projects, interdisciplinar* featured in 40 titles and 1679 abstracts. Out of 56 TDR projects transdisciplinar* featured in 2 project titles and 54 abstracts.

1912 H2020 projects (as of May 2019). Out of 1837 IDR projects, interdisciplinar* featured in 57 titles and 1820 abstracts. Out of 85 TDR projects transdisciplinar* featured in 2 project titles and 85 abstracts.

Description of the files

CSV files contain the same fields as CORDIS database data dumps: id, acronym, status, programme, topics, framework Programme, title, startDate, endDate, projectUrl, objective, totalCost, ecMaxContribution, call, fundingScheme, coordinator, coordinatorCountry, participants, participantCountries, subjects.

Additional fields:

IDR - project features interdiciplinary research (1 = yes, 0 = no)

TDR - project features transdiciplinary research (1 = yes, 0 = no)

Title_Interdisciplinar* - frequency of “interdisciplinar*” in the project title

Objective_interdisciplinar*- frequency of “interdisciplinar*” in the project objective

Title_transdisciplinar* - frequency of “interdisciplinar*” in the project title

Obj_transdisiplinar* - frequency of “interdisciplinar*” in the project objective

Reference data (countries, funding schemes/types of action, subjects (SIC codes)) can be found in this dataset: https://data.europa.eu/euodp/en/data/dataset/cordisref-data

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.

Database : Substances mapping and database documentation. Database used for mapping PM(T) substances, i.e., creating connections, associations, or representations between substances for analysis, classification, modeling, or data visualization. The results of the mapping are presented within deliverable 5.1 of the Horizon 2020 funded project PROMISCES. Deliverable 5.1 is available here Preventing Recalcitrant Organic Mobile Industrial chemicalS for Circular Economy in the Soil-sediment-water system | PROMISCES | Project | Results | H2020 | CORDIS | European Commission (europa.eu)

This dataset includes detailed information about all European Union-funded research and innovation projects initiated between 1st January 2021 and 31st December 2024 in which the University of Jaén (UJA) is participating. The dataset includes projects referenced on CORDIS (Community Research and Development Information Service), mainly from Horizon 2020 and Horizon Europe, projects from the Erasmus+ programme, covering KA1 and KA2 projects, among others. Each entry includes publicly available information, such as project title and reference, description, dates, funding program, status, budget, number of participants, etc. It also indicates UJA’s role in each project and the corresponding EU funding program and action.

The data has been used in the project RURALIZATION which has been funded (grant agreement number 817642) by the European Union (EU) as part of the Horizon 2020 research and innovation programme. Outcomes of the RURALIZATION project reflect only the author’s view. The Agency and Commission are not responsible for any use that may be made of information.

This data sets includes a README.TXT and three data files:

1.T53DATA.csv
2.A2LPRACTICES.CSV
3. LANDNUTS3.csv

T53DATA.csv
This data is based on a survey among project members of RURALIZATION leading contributions in a task to ‘confront’ case studies of promising practices with other regions to consider potential for uptake. Practice abstracts of the case studies can be found at the EIP-AGRI website: https://ec.europa.eu/eip/agriculture/en/find-connect/projects/ruralization-opening-rural-areas-renew-rural. The case studies are in ‘D5.2 30 Case studies on rural newcomers, new entrants to farming and successors’ at https://ruralization.eu/deliverables/ and will become available at https://cordis.europa.eu/project/id/817642/results

A2LPRACTICES.CSV
This data is the inventory underlying the report ‘D6.1 – Typology of actions based on an analysis of current innovative actions and discussion with stakeholders’ which is currently available at at https://ruralization.eu/deliverables/ and will become available at https://cordis.europa.eu/project/id/817642/results

This inventory of 64 land practices, from training programmes for individual farmers, to attempts to influence national policy impacting land use and land transfers, have been gathered by partners in the RURALIZATION project consortium.
LandsNUTS3.csv: a collection of data to analyse rural land markets

nextGEMS is a collaborative European project. Funded by the EU’s Horizon 2020 programme, it will tap expertise from fourteen European Nations to develop two next generation (storm-resolving) Earth-system Models. Through breakthroughs in simulation realism, these models will allow us to understand and reliably quantify how the climate will change on a global and regional scale, and how the weather, including its extreme events, will look like in the future. See further details at https://nextgems-h2020.eu/ and https://cordis.europa.eu/project/id/101003470.

This dataset provides an overview of EU-funded projects involving the Stefan cel Mare University from Suceava from 2021 to mid-2025, including completed and ongoing projects. The dataset includes projects referenced on CORDIS, mainly from Horizon 2020 and Horizon Europe and projects from the Erasmus+ Project Results Platform, covering KA1 and KA2 projects. Each entry includes the following publicly available information: project title, description, dates, funding program, call topic (if applicable), status, budget, and number of participants.

This dataset contains the data that supports the following paper: Féret, R. and Cros, M., 2019. The embedded research librarian: a project partner. LIBER Quarterly, 29(1), pp.1–20. DOI: 10.18352/lq.10304

The dataset contains 3 files related to the bibliographic metadata of the publications of the 7 H2020 projects supported by the University Library of Lille and a general file providing the data for the table, figure 2 and 3 and for the data on H2020 projects coordinators:

figures: this file contains the information related to the projects supported by the Library, including the data presented in the figure 2 (tab 1), the figure 3 (tab 2), the table 1 (tab 3) and the data on 2020 project coordinators (tab 4).

wos_publications : the data extracted from the Web of Science for 106 publications (.txt, UTF-8, Windows), searched on the base of the 7 H2020 projects Cordis number.

refined_wos_publications : the same data after having been transformed into a .xlsx format in the tool OpenRefine.

processed_publications : contains the main bibliographic data (authors, article title, source title, DOI, date of publication) and their open status.

Abstract of the paper This paper presents new services developed by the Lille University Library for European and National research project coordinators. This is a specific audience that libraries are not used to target, with a widely recognised institutional status and academic background. Supporting them in their coordination activities is an opportunity to gain a new role for libraries, which starts from the design of research at the submission stage and lasts several years after, during the project lifetime. These services help coordinators to meet their funders’ expectations on open access and research data management. It is also a way to develop new collaborations with research units and some university services, such as the Grant Office. The Lille University Library has already supported the writing of forty grant proposals since 2017, including about thirty since early 2019. The Library currently follows twelve projects on open access, research data management or both. This second figure is likely to increase in 2020 due to the number of projects supported at submission stage since the beginning of 2019. The paper describes our set of services and the lessons we learned from our approach.

This dataset is the result of a mapping exercise of the online database containing relevant information on microbiome-related policies and strategies, funding programmes, research projects and organisations. This included collecting research programmes and projects from (1) the full H2020 database on Cordis, (2) a database with research projects funded via ERA-NETs and Joint Programming Initiatives, (3) COST Action research networks, (4) European Molecular Biology Organization projects, (5) the Horizon Frontier Science Programme, (6) the Bill and Melinda Gates Foundation, and (7) the Gordon and Betty Moore Foundation as well as relevant new policies, research strategies and infrastructures and knowledge platforms. The database is accessible on the project website: LINK

Dataset contendo a listagem dos projetos investigação financiados pelo programa H2020 (Horizon 2020 - European Commission). Este dataset foi feito em colaboração com European Comission.

Dos 31 129 projetos listados, 16 743 apresentam um URL para um site ou uma página de projeto, dos quais 379 são repetidos. Assim, existem 16 364 URLs únicos para recolher o que é cerca de 53.79% dos projectos agregados ao H2020. De forma a preservar o conteúdo deste projeto, foi executada uma abordagem semelhante à descrita no paper por “D.Bicho, D. Gomes (2016) - Preserving Websites Of Research & Development Projects”, em que foi executado a heurística: “+Acronym +Title -Cordis -EC +Common-Terms” (i.e., foram feitas queries ao bing search api com o acrónimo do projecto, o titulo retiramos dos restulados os sites cordis.europa.eu, ec.europa.eu e adicionamos um termo adicional). Por exemplo, MARmaED MARine MAnagement and Ecosystem Dynamics under climate change project -site:cordis.europa.eu -site:ec.europa.eu.

Contem as seguintes informações: rcn, id, acronym, status, programme, topics, frameworkProgramme, title, startDate, endDate, projectUrl, objective, totalCost, ecMaxContribution, call, fundingScheme, coordinator, coordinatorCountry, participants, participantCountries, subjects, URLsBingSearch, ArchivedProjectURLs. Adicionalmente ao dataset disponibilizado European Comission foi adicionado a coluna URLsBingSearch que contem os top 10 resultados para as queries sobre o bing search api, apenas quando não existe um URL para o projecto de investigação e a coluna ArchivedProjectURLs com o link para a versão persevado no Arquivo.pt.

Esta listagem requer revisão, pois os sites mudam mais depressa do que as instituições que os publicam. O dataset foi descarregado em Dezembro de 2020.

Background: Despite the substantial societal impact of prevalent endocrine diseases like obesity, diabetes, infertility, and thyroid disorders, plus over 440 rare endocrine conditions, it remains unclear whether endocrine science receives adequate research funding to address present and future health challenges.

Methods: We analysed the funding for endocrine science under the EU Research Framework Programme Horizon 2020 (2014-2020) using the EU CORDIS database. Through keyword searches and European Science Vocabulary Classification Codes, we identified relevant projects and analysed total funding, distribution across endocrine areas, funding mechanisms (top-down vs bottom-up), and geographical allocation. We also conducted a preliminary analysis of the ongoing Horizon Europe (2021-2027) program.

Results: Horizon 2020 funded 331 endocrine research projects totalling €61 M, representing 3.9% of biomedical and health research funding. Nearly 70% was allocated to diabetes and obesity, with an additional 17.4% to environmental factors affecting endocrine health, predominantly through top-down funding schemes reflecting European Commission priorities. All other endocrinology areas combined received just 13.6% of endocrine funding, primarily through smaller bottom-up grants. Geographical analysis revealed significant disparities, with EU Widening Countries receiving only 4% of funding. Preliminary Horizon Europe data (€57.7 M) shows similar distribution patterns and persistent geographical inequities.

Conclusions: The high prevalence of endocrine disorders warrants greater research funding allocation toward endocrine science. To address this funding gap, the European Society of Endocrinology and the European Society of Paediatric Endocrinology, together with partner societies and individual experts, have created the EndoCompass roadmap project—a research roadmap for better hormone health.

This repository contains the protein-protein interactions inferred by mimicINT (https://github.com/TAGC-NetworkBiology/mimicINT) between the proteins of seven human coronaviruses (HCoV-229E, HCoV-HKU1, HCoV-NL63, HCoV-OC43, MERS-CoV, SARS-CoV and SARS-CoV-2) and substantial fraction of the human proteome. This dataset was generated in the context of the RiPCoN project (H2020-SC1-PHE-CORONAVIRUS-2020, https://cordis.europa.eu/project/id/101003633).

O Programa-Quadro de Pesquisa e Inovação Horizonte 2020 (H2020), implementado pela Comissão Europeia a partir de 2014, financiou milhares de projetos (31 116 projetos, dados de dezembro de 2020). Destes, apenas 16 744 (46 %) mencionaram um Website relacionado com o projeto. O Arquivo.pt utilizou a informação disponibilizada no portal CORDIS (https://cordis.europa.eu/projects) para identificar, recolher e disponibilizar para fins de investigação os Websites e outros conteúdos relativos aos projetos. Além disso, o Arquivo.pt prosseguiu com a identificação de Websites relativos aos projetos que não mencionaram endereços Web. As atividades, os resultados e outras publicações relativas a projetos encontram-se publicadas na Web, mesmo que os seus autores não as refiram. Através de uma metodologia automática, aplicada em 2016 aos Programas-Quadro, foram identificados novos conteúdos Web do H2020 e recolhidos no primeiro trimestre de 2021.

This dataset contains the data related to the pXRF analyses conducted on copper objects from the Congo Basin curated at the Museum of Anthropology and Archaeology (MAA), University of Cambridge in December 2020. The study has been done in the framework of the H2020-MSCA-IF-2019 Project Number 890896 ‘An Archaeology of Exchange Networks in Central Africa. The Cases of the Copperbelt and Niari Basin Copper Deposits’ (ArCAN). https://cordis.europa.eu/project/id/890896 All information about the dataset can be found in the readme file.

OSMOSE WP1 DATASET This dataset has been compiled within the OSMOSE project, from the European Union’s Horizon 2020 research and innovation program, to support adequacy studies performed in Work-Package 1. Original data originate from two main sources : Plan4Res EU project and ENTSOE Pan European Common Database. ## Content The dataset contains 35 weather years (1982-2016) of data for 33 EU countries. General data granularity is country level. Some RES data are provided at the granularity of the 99-clusters of the e-Highway2050 project. - non-thermosensitive load profile (1 profile per country). Profiles sum to 1. (Source: Plan4Res and OSMOSE) - electric heating profiles (1 profile per country, 1 file per weather year). Profiles sum to 1 on average but not individually. (Source: Plan4Res and OSMOSE) - electric vehicles profiles (1 profile per country, 1 file per weather year). Profiles sum to slightly more than 1, depending on the weather scenario used. The difference to 1 corresponds to the thermo-sensitive effect due to the heating and the air-conditioning necessary for the well-functioning of the motor and the comfort of the passengers in this weather scenario. Its varies from country to country. (Source : OSMOSE, JRC for daily profiles, CS3 for weather and annual vehicle usage profiles) - onshore wind power-factor profiles (1 profile per country, 1 file per weather year and 1 profile per cluster, 1 file per weather year). (Source: PECD) - offshore wind power-factor profiles (1 profile per country per weather year and 1 profile per cluster per weather year). (Source: PECD) - solar pv power-factor profiles (1 profile per country, 1 file per weather year and 1 profile per cluster, 1 file per weather year). (Source: PECD) - hydro data (installed capacities (Run-of-River - ror, reservoir, Pump Storage Plants - PSP), volumes of the reservoirs and PSP, annual energies (ror and reservoir), per country and per cluster. Source: (OSMOSE based on MAF2018 and MAF2019) - hydro energies in GWh (ror - daily, reservoir - weekly, per country, 1 file per weather year). (Source: OSMOSE based on PECD) Full details of data processing performed by OSMOSE WP1 can be found in appendix B of OSMOSE deliverable D1.3 (available at https://www.osmose-h2020.eu/resource-center). ## AntaresSimulator studies The dataset also contains 2 study skeletons (country and cluster granulariry) and R scripts allowing to build studies to be run with AntaresSimulator (https://antares-simulator.org). To run these studies, unzip the archives "OSMOSE_DATASET" (which actually contains the dataset) and "ANTARES_R" (which contains R scripts) and follow the instructions in "ANTARES_R/README.md". ## Forecast data The dataset also comprises 10 weather years (1982-1991) of AntaresSimulator imput time-series corresponding to day-ahead forecast data for demand, solar and wind for 2030 and 2050. These forecast data have been computed based on the installed capacities defined in OSMOSE CGA scenario. Details of the computation process can be found in the report included in this distribution. ## OSeMOSYS dataset This file contains the OSeMOSYS parameter values (costs, demand, potentials, emission limits...) used in the study "Comparing the relative impacts of investment constraints and temporal detail on the outcomes of capacity expansion models applied to power systems". ## Licences Data is published under the terms of the "Creative Commons Attribution 4.0 International" licence (https://creativecommons.org/licenses/by/4.0) R code is published under the terms of the "MIT" licence (https://opensource.org/licenses/MIT) ## Acknowledgements The OSMOSE project(https://www.osmose-h2020.eu) received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 773406. Plan4Res EU project (https://zenodo.org/record/3802550) C3S (https://cds.climate.copernicus.eu) ENTSOE Pan European Common Database (https://zenodo.org/record/3702418 and https://zenodo.org/record/3985078) and MAF (https://www.entsoe.eu/outlooks/midterm/previous-maf-versions) e-Highway2050 project (https://cordis.europa.eu/project/id/308908/reporting)

As policies, good practices and funder mandates on research data management evolve, more emphasis has been put on the licencing of data. Licencing information allow potential re-users to quickly identify what they can do with the data in question and is therefore an important component to ensure the reusability of research.

In my research I analyse a pre-existing collection of 840 Horizon 2020 public data management plans (DMPs) available on the repository of the University of Vienna, Phaidra,, to determine which ones mention creative commons licences and among those who do, what licences are being used.

This excel file contains the data underlying the publication "Uncommon Commons? Creative Commons licencing in Horizon 2020 Data Management Plans ".

Sheet 1 contains the data collected in the previous "Data Re-Use" project: 840 DMPs downloaded from CORDIS and vetted to ensure they are public documents and not copyrighted

Sheet 2 contains the same data as sheet 1, with columns D to Q not visible (for better reading) but an added column R which now contains the CC licening information (where available)

Sheet 3 is filtered so that only the projects containing CC BY relevant licencing are shown

Sheet 4 is filtered so that only the projects containing CC-BY-SA relevant licencing are shown

Sheet 5 is filtered so that only the projects containing CC-BY-NC relevant licencing are shown

Sheet 6 is filtered so that only the projects containing CC-BY-ND relevant licencing are shown

Sheet 7 is filtered so that only the projects containing Cc-BY-NC-ND relevant licencing are shown

Sheet 8 is filtered so that only the projects containing CC-BY-NC-SA relevant licencing are shown

Sheet 9 is filtered so that only the projects containing CC0 relevant information are shown

Sheet 10 provides an overview table of the relevant licences (manual entry)

Sheet 11 and 12 contain graphic visulations of the data as used in the article