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.

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.

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/

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)

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

Records relating to the EU Life Project funding. LIFE is the EU's financial instrument supporting environmental, nature conservation and climate action projects throughout the EU.

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

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

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.

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.

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

This project has received funding from the H2020 innovation and research program of the European Commission under the Marie Sklodowska-Curie grant no: 846077, entitled “Quality of Service for the Internet Things in Smart Cities via Predictive Networks".

Each file consists of time series data which are the number of bits at each sampling.

• Purpose of the data: These data are provided to aid researchers who aim to develop methods to process IoT sensor traffic data.
• Time and date of creation and availability: These data were collected as part of the QoSIoTSmartCities project in the years 2019 – 2021 and made available on this site.
• Data file size: The data file size appears next to the data file.
• Data Units: All of the units of these data are “bits”

The data produced in the project is useable by third parties with the disclaimer that the Coordinator, the funding agency, and the host institution bear no responsibility whatsoever, legal or otherwise, that result from the re-use of these data sets.

This dataset contains projects funded by the European Union under the first framework programme for research and technological development (FP1) from 1984 to 1987.

The file 'FP1 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).

The participating organisations are listed in the file 'FP1 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 dataset has been updated to match the structure of more recent datasets - some fields may not be populated

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

Plant‑Soil Chemistry Dataset (Raja 2019 Field Campaign)

## 1. Overview

This repository contains the **final, cleaned chemistry data** that were produced from the 2019 Raja field campaign.
The data combine:

* Plant tissue concentrations (leaf, bark, needles, …) for a set of selected elements.
* Corresponding soil‑till depth, point location, lithology and basic tree information.
* Element‑specific relative‑standard‑deviation (RSD) uncertainties that were calculated from laboratory‑derived uncertainty parameters.

All files are provided in **CSV** format (UTF‑8, `,` separator) and/or the R programming language binary format RData.

*The exact set of tissue files depends on the species/plant‑parts that were sampled; the naming convention is `pl` + lower‑case abbreviation of the tissue (generated by `abbreviate(Plant, minlength = 2)` + `PlantPart`).*

---

## 2. Column description (common to all tables)

| Column | Meaning | Type |
|--------|---------|------|
| `PointID` | Unique identifier for the sampling point (e.g., `NEXT‑2019‑257`). | character |
| `X` / `Y` | Projected coordinates (Easting / Northing, EPSG 3067). | numeric |
| `Plant` | Species name (full). | character |
| `PlantPart` | Plant part sampled (`Leaf`, `Bark`, `Fruit`, …). | character |
| `Tissue` | Short code: `

### 2.1. Concentration vs. Uncertainty tables

* **`Plant_all_final.csv`** – contains **concentrations** (units as reported by the laboratory, typically mg kg⁻¹).
* **`Plant_uncensored_raw.RData`** – contains the very original, untreated data.
* **`*_uncertainty*.csv`** – the element columns have been **replaced by their relative standard deviation (RSD)**, i.e. a unit‑less proportion (`0.12` = 12 % RSD).

If you need both concentration **and** uncertainty for a given point, use the two files together (join on `PointID`).

---

## 3. Usage notes

* **Joining concentration & uncertainty** – the two CSVs 'plant' and 'plant_uncertainty' share the same column order and can be merged on `PointID`.
* **Missing values** – `NA` indicates either a non‑detected element or that no uncertainty parameter was available for that element.
* **Spatial reference** – coordinates are in **ETRS89 / Lantmäteriet 3006 (EPSG 3067)**, suitable for Swedish national mapping.
* **Element selection** – in the subdatasets not every element is present in every tissue file; only the elements that passed the QC selection criteria are kept.

The European Copernicus Coastal Flood Awareness System (ECFAS) project aimed at contributing 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 provides 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 ran from January 2021 to December 2022. The ECFAS project was 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 was 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.

Reference literature:

Souto-Ceccon, P. E., Montes, J., Duo, E., Ciavola, P., Fernández-Montblanc, T., and Armaroli, C.: A European database of resources on coastal storm impacts, Earth Syst. Sci. Data, 17, 1041–1054, https://doi.org/10.5194/essd-17-1041-2025, 2025.

Description of the product

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.

This ECFAS Database is made available under the Open Database License: http://opendatacommons.org/licenses/odbl/1.0/. Any rights in individual contents of the database are licensed under the Open Database License: http://opendatacommons.org/licenses/dbcl/1.0/.

This Report is made available under the Creative Commons Attribution 4.0 International License.

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.

This project has received funding from the Horizon 2020 research and innovation programme under grant agreement No. 101004211

Detailed information on the implementation of investment projects of European Union funds for 2014-2020 is published (contracts of the projects, monitoring indicators, budget of the contract projects, contract measures, financing forms, objectives, activities, project payment requests, refunds, project procurement plans, reports after the end of funding, etc.).

Detailed information on the 2014-2020 European Union fund investment projects applications (sources of funding for the eligible costs of the application projects, budget of the project applications, activities, objectives, monitoring indicators, etc.) and project evaluation is published.

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

Data Description

The H2020 CAPTOR project deployed three testbeds in Spain, Italy and Austria with low-cost sensors for the measurement of tropospheric ozone (O3). The aim of the H2020 CAPTOR project was to raise public awareness in a project focused on citizen science. Each testbed was supported by an NGO in charge of deciding how to raise citizen awareness according to the needs of each country. The data presented in this document correspond to the raw data captured by the sensor nodes in the Spanish testbed using SGX Sensortech MICS 2614 metal-oxide sensors.

The Spanish testbed consisted of the deployment of twenty-five nodes. Each sensor node included four SGX Sensortech MICS 2614 ozone sensors, one temperature sensor and one relative humidity sensor. Each node underwent a calibration process by:

• Co-located the node at an EU reference air quality monitoring station for two to three weeks
• Co-located at three sub-urban reference stations near the final deployment site for two to three weeks.
• Deployed in volunteers' homes for about two months
• Co-located again at the sub-urban reference stations for two weeks for final calibration and assessment of potential drifts.

All data presented in this paper are raw data taken by the sensors that can be used for scientific purposes such as calibration studies using machine learning algorithms, or once the concentration values of the nodes are obtained, they can be used to create tropospheric ozone pollution maps with heterogeneous data sources (reference stations and low-cost sensors). The ground truth reference data on O3 concentration is downloaded from a public database.

Value of the Data

• The sensor data complement the data provided by the AQMN (Air Quality Monitoring Network) reference stations deployed by governmental organisations. The spatial density of AQM reference stations is typically low, therefore data from nodes with low-cost sensors complements the AQM reference network. The data are raw, meaning that the data are as measured by a real sensor in the field, without being calibrated.
• As the nodes are deployed over a wide area of about 30Kmx25Km, many different studies can be carried out in various research fields: calibration, data fusion, sensor networks, interpolation of calibrated ozone concentrations, among others. Therefore, the major beneficiaries of these data are researchers in air pollution monitoring networks using low-cost sensors.
• The data can be used by researchers in several fields: i) researchers interested in building maps with ozone concentrations in areas where AQM reference stations are not deployed, ii) researchers interested in testing machine learning algorithms for low-cost sensor calibration, iii) researchers interested in studying network of heterogeneous data sources including reference stations and low-cost sensor nodes.
• Each node has up to four O3 metal-oxide sensors mounted on it. As the deployment has twenty-five nodes, it adds up to one hundred low-cost sensors. In addition, some nodes were left in place at reference stations throughout the summer to have a large part of the dataset in the same place as the reference data, while other nodes were moved to volunteers' homes. This allows calibration-only studies with a large number of sensors, or research of sensors forming a network.

This data set includes: - Stakeholders active with the SOC technology (either SOEC, SOFC or rSOC). - National and EU regional funding programme supporting SOC technology. - European project supporting rSOC/SOEC technology - List of demonstration plants for energy storage through power-to-X. The data have been gather within the H2020 project BALANCE and they might not be exhaustive. https://www.balance-project.org/ This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 731224.