Key results of the EOSC-hub Early Adopter Programme

Giuseppe La Rocca and Diego Scardaci update us on the main achievements of the EOSC-hub Early Adopter Programme

To facilitate the engagement of new research communities interested in exploring the latest state-of-art technologies and services, and contribute to drive the future evolution of the European Open Science Cloud, the EOSC-hub project promoted the selection of new research projects to allow research communities to scale up the in-house infrastructure and to access a richer set of resources. Overall, a total of 13 research projects, across different scientific disciplines, were selected with 2 calls opened in 2019.

One month before the end of the EOSC-hub project, with the following article, we update you about the status of the 5 research projects that reached a mature status.

Transitioning EMSO ERIC Data Management Platform to production (Earth Sciences)

To contribute to the establishment of a comprehensive and smart sensors system in water column, seafloor, and sub-seafloor environments as part of the integrated and sustainable organization EMSO ERIC, during the running programme the services of the EGI federation contributed to transitioning of the Data Management Platform (DMP) to full production. Thanks to the technical support provided by experts from the project, a federated authentication mechanism was also implemented for helping members of the ERIC to access the distributed infrastrastructure and analyse datasets collected from sensors. As a final result, the EMSO-ERIC Data Management Platform will be soon registered in the EOSC Portal.

Open AiiDALab platform for cloud computing in Materials Science (Physical Sciences)

This early adopter aims at providing an open AiiDALab instance for the EOSC users capable of supporting hundreds of concurrent users. Thanks to the programme organized by EOSC-hub the AiiDALab platform was extended to use the cloud resources of the EGI Federation that supports the deployment and operation of a new AiiDALab demo instance.  The technical support provided by the project has allowed the extension of AiiDALab to use federated authentication mechanisms to grant access to EOSC users to the service and the adaptation of the platform to use a managed Kubernetes service that facilitates the exploitation of the cloud resources.

Supporting FAIR data discoverability in clinical research: providing a global metadata repository (MDR) of clinical study object  (Health Sciences)

In recent years there has been a growing acceptance that to accurately assess the results of trials and other clinical research, and in particular to combine the results from different trials in meta-analyses, it is much better to have access to the original source data, as well as the result summaries found in published papers. As data and document sharing becomes more and more common, and the researcher is faced with a bewildering mosaic of possible source locations and access modalities, there is an urgent need to develop a central service that can catalogue all the diverse data and documents associated with a clinical study, and then make that information searchable by using a central web portal. To bridge this gap, the ECRIN MetaData Repository (MDR) was developed to make the data objects generated from clinical research easier to locate, and to describe how each of those data objects can be accessed, providing direct links to them where that is possible. In the context of the Programme the capability of the ECRIN MetaData Repository (MDR) database was also extended in order to leverage on the computing resources of the EGI Federated Cloud infrastructure for hosting the distributed repositories of clinical research.

Big Data Analytics for agricultural monitoring using Copernicus Sentinels and EU open data sets

The key aspect in the early adopter demonstrator was to show how federated EOSC resources can facilitate a range of Sentinel data applications across agricultural user domains. During the programme the adopter demonstrated how EOSC federated compute resources can be used to effectively compose Big Data processing chains that combine open access agricultural parcel data sets with application ready dense high resolution Copernicus Sentinel-1 and -2 image time series. These time series are relevant for a number of scientific use cases, for instance, following crop phenology, and novel agronomic applications. The results of the adopter feed directly into the ongoing development of public EU Member States’ service tasks in monitoring common agricultural policy measures. A key aspect of the adopter is to project EOSC as an essential enabling platform for the required upscaling in the information needs of the new European Green Deal and related agricultural data space development.

Towards an e-infrastructure for plant phenotyping pilot (Agricultural Sciences)

In recent years, high-throughput plant phenotyping platforms are playing a key role to produce massive datasets, including millions of plant images concerning hundreds of different genotypes at different phenological stages in both field and controlled environments. The ongoing robotization of experimental processes foreshadows an explosion in the volume and complexity of the data produced by the different research facilities. As a direct consequence, there is a strong need of deploying an e-Infrastructure to store, describe, analyse and share data. The EGI Federation supported this research project providing the computing and storage resources to improve the scalability and the reliability of  and enable federated access to the plant phenotyping e-infrastructure.

More information

EOSC Early Adopter Programme

Giuseppe La Rocca is Community Support Lead at the EGI Foundation.
Diego Scardaci is Technical Solution Team Lead at the EGI Foundation.

Contributors: Ivan Rodero (EMSO-ERIC), Giovanni Pizzi (EPFL), Sergey Goryanin (ECRIN), Guido Lemoine (European Commission), Vincent Negre (INRAE), Enol Fernandez (EGI Foundation), Stefano Nicotri (INFN), Giacinto Donvito (INFN), Hans van Piggelen (SURFSara) and Nicolas Cazenave (CINES).