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

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)

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 ---

H2020 SUNSHINE - eNanoMapper database - aggregated data from H2020 SUNSHINE and other projects

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 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.

H2020 RiskGone - eNanoMapper database - aggregated data from H2020 RiskGone and other projects

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 ---

Analysis of ‘Number of distinct organisations participating in H2020 ICT projects for the first time’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from http://data.europa.eu/88u/dataset/rtpubqnennjlg4zjsu9aq on 10 January 2022.

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

Organisations participating for the first time in H2020 ICT calls, and which have not participated in FP7 ICT calls during 2007-2013 period.

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 ---

H2020 caLIBRAte - eNanoMapper database - aggregated data from H2020 caLIBRAte and other projects

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

Results of Pilots from H2020 project Zerobrine, technical reports to be found on zerobrine.eu

GenTree is a European Union project financed under the Horizon 2020 framework. The goal of GenTree was to improve the status and use of European in-situ and ex-situ forest genetic resource (FGR) collections, support acquisition, conservation, characterization, evaluation and use of relevant FGR in breeding and forestry practice and policy, will seek to harmonize, rationalize and improve management of existing collections and databases, and will strengthen the EU strategy for cooperation on FGR research and innovation. The major outputs of GenTree included: new scientific knowledge on phenotypic and genotypic diversity across environmental gradients in Europe, improved genotyping and phenotyping monitoring tools for practitioners, updated and refined data for information systems of in-situ and ex-situ FGR collections, innovative strategies for conservation, breeding and exchanging and using diversified forest reproductive material, novel outreach and science-policy support tools to better integrate FGR concerns into forest management and better implement relevant international commitments in Europe. Here, we report SPET and exome capture data from over 4700 trees from 12 species sampled in 36 sites across Europe.

The data is extracted from the TRIMIS dataset of projects and contains research and innovation projects with urban mobility and logistics in their scope. The list of projects contains H2020 and other European projects (e.g. Interreg) which have started since the year 2014. The file contains all the data used in JRC Science for Policy Report: "Research and Innovation in Urban Mobility and Logistics in Europe. An assessment based on the Transport Research and Innovation Monitoring and Information System (TRIMIS)".

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.

Data collected during the lab-in-the-field experiment under EU H2020 project VISIONARY

This document, D7.6 Data Management Plan Update, is a deliverable of the A-LEAF Project, which is funded by the European Union’s H2020 Programme under Grant Agreement No.732840. The A-LEAF project participates in the H2020 Open Research Data Pilot. This updated version of the Data Management Plan provides an analysis of the main elements of the data management policy that will be used by the members of the Consortium with regard to the data generated through the life of the project.