Community Use Cases

Societal challenges

Frictionless Data Exchange pilots a demonstrator service for fast and highly scalable exchange of data across repositories storing research datasets, manuscripts and scientific software. This pilot wants to showcase how scholarly communication resources can be effectively, regularly and reliably exchanged across systems, and to apply ResourceSync protocol on real-world use cases. Moreover, the objective is also to show data synchronization across a cross-disciplinary network of repositories and between repositories and global added-value services. Frictionless Data Exchange benchmarked OAI-PMH against ResourceSync in a number of scenarios and according to a number of criteria – for example: enhancing ResourceSync by means of developing of a ResourceSync On-Demand Dump concept and its implementation and adoption in real use cases; supporting OpenAIRE in adopting ResourceSync-based ingestion of scientific papers from publishers.

SCIENTIFIC OBJECTIVES OF THE DEMONSTRATOR

This pilot wants to showcase how scholarly communication resources can be effectively, regularly and reliably exchanged across systems, and to apply ResourceSync protocol on real-world use cases. Moreover, the objective is also to show data synchronisation across a cross-disciplinary network of repositories and between repositories and global added-value services.

• Showcase how scholarly communication resources can be effectively, regularly and reliably exchanged across systems;
• Apply ResourceSync protocol on real-world use cases;
• Show data synchronisation across a cross-disciplinary network of repositories and between repositories and global added-value services.

Technical challenges

• FINDABILITY & ACCESSIBILITY: increasing resources findability and accessibility on the web;
• INTEROPERABILITY: improving interoperability of scientific repositories;
• REUSABILITY: increase resources reuse in big data analytics tasks involving text and data mining;
• increasing scalability of data exchange among scholarly communication systems.

How EOSC can help and add value

• A clear path to go beyond the current state of the art in information exchange between EOSC data providers and services;
• Scalable client/server implementation of the ResourceSync protocol for easy adoption by data providers;
• Awareness of existing issues and the proposed solution.

MAIN ACHIEVEMENTS:

• Benchmarking OAI-PMH against ResourceSync in several scenarios and according to some criteria, including:
• Enhancing ResourceSync using developing of a ResourceSync On-Demand Dump concept and its implementation and adoption in real use cases.
• Supporting OpenAIRE in adopting ResourceSync-based ingestion of scientific papers from publishers.

Societal challenges

The Photon Neutron Data Science Demonstrator leverages on the photon-neutron community to improve computing facilities by creating a virtual platform for all users. Photons and Neutrons are widely used for research in many scientific fields and they require large Research Infrastructures (RI). Research at these RIs makes use of large-area detectors, multichannel detection, and high repetition of measurements. This leads to large quantities of data and raises the need to perform data analysis in an efficient manner. Thousands of users of the RIs propose, conduct and analyze data from scientific experiments in a wide range of application domains. Access is granted after a thorough peer-review of the scientific proposals. Often, these users’ groups are small teams of scientists coming from universities and research organizations using RIs in various locations in Europe according to the specific characteristics of the beamlines; in general, more than one analytical facility is needed for the same experiment. Critical issues are data storage, sustained access to the data and an efficient data analysis ecosystem.

Technical challenges

• Exploit and improve the crystfel framework for distributed computing.
• Provide compatible data analysis software
• Allow transparent and secure remote access to data
• Standardize data formats NeXus/HDF5 and annotation of data
• Test and establish (if feasible) web-services for easy consumption and visualization of the data
• Exploit existing authentication and authorization solutions
• Allow long term preservation of data
• Promote data policies in laboratories

How EOSC can help and add value

• Deploy and test of the software used by a large community in structural biology at Free Electron Lasers and Synchrotrons on a local OpenStack cloud platform and on local HPC clusters at DESY, Hamburg.
• Examination of the workflow to identify and establish community-specific cloud services and gain insight into technical, organizational, legal issues and interoperability requirements.
• Several applications from the Photon and Neutron field have been containerized, deployed and partially profiled.
• Identification of some features, which would be helpful in a further deployment, like tools and service facilitating server-less partitioning of data analysis pipelines.
• Scale up the on-site OpenStack infrastructure due to successful proof of concept, which has greatly raised interest and visibility in the user community. This development on the hardware side is complemented by integrating new OpenStack modules into our cloud instance.

Societal challenges

This project aims to perform modeling studies to explore how future energy systems can evolve and to quantify the tradeoffs and interlinkages between different aspects of the global energy systems in the context of international climate change policy and sustainable development.

Technical challenges

These analyses utilise Integrated Assessment Models (IAMs), which are models of the energy, environment, and economic systems to quantify key variables of interest in these scenarios – such as emissions pathways consistent with international climate policy goals, tradeoffs of climate mitigation with land use and food security, among others.

How EOSC can help and add value

The community got access to the EGI Federated Cloud and is working to adapt their application to the cloud paradigm. An initial prototype is under preparation.

Societal challenges

ECRIN is a non-profit organisation that links scientific partners and networks across Europe to facilitate multinational clinical research. The main goal of this use case is to deploy the ECRIN MetaData Repository (MDR) CORE database and metadata conversion tool in the European Open Science Cloud.

Technical challenges

The first objective of the proposed project is to extend the MDR demonstrator to run in production in the EOSC environment and be part of the EOSC catalogue and to complete the data base by integrating all major data sources dedicated to clinical research.

The second objective is to include others EOSC services not already included into MDR: we plan to include also EGI Fed Cloud Resources to host the distributed repositories.

How EOSC can help and add value

This use case was facilitated by the EOSC-hub project via the following services: EGI Cloud Compute, EGI Cloud Container Compute, EGI DataHub, EUDAT B2FIND

Specific steps:

– Setup of the EGI Data Hub service

– Investigate the metadata scheme and requirements for future harvesting with B2FIND

– Deploy the ECRIN Portal on the EGI Federated Cloud

– Enable harvesting of a single global metadata repository (MDR) instance with B2FIND

– Integration testing and enable harvesting of one or more MDR instance with B2FIND

Societal challenges

Cloud platforms allow users to execute tasks directly from their web browser and are a key enabling technology not only for commerce but also for computational science. Research software is often developed by scientists with limited experience in (and time for) user interface design, which can make research software difficult to install and use for novices. When combined with the increasing complexity of scientific workflows (involving many steps and software packages), setting up a computational research environment becomes a major entry barrier. AiiDAlab is a web platform that enables computational scientists to package scientific workflows and computational environments and share them with their collaborators and peers.

Technical challenges

AiiDA is a workflow manager for computational science with a strong focus on provenance and performance. Through its flexible plugin infrastructure, it supports a wide range of simulation codes and makes them available for use through the Python programming language, and automatically records the full provenance of your simulation pipeline in a graph. AiiDAlab lets you run and manage AiiDA-powered workflows through tailored web applications in the browser. Use the App store to pick and install apps from the application registry or write your own in just a few lines of python using jupyter widgets and appmode. This service is supported by the MaX European Centre of Excellence, the MARVEL National Centre for Competence in Research, the European H2020 MarketPlace project, by swissuniversities as well by a number of other partners.

How EOSC can help and add value

Specific steps

• Integration with the EGI Check-in service
• Deploy the AiiDA lab instance on the EGI Federated Cloud
• Use of the AiiDA lab instance for a tutorial and support of at least 6 different simulation codes
• Onboarding of users, testing and scaling, provide apps to connect to HPC resources

Societal challenges

AGINFRA+ addresses the challenge of supporting user-driven design and prototyping of innovative e-infrastructure services and applications. It particularly tries to meet the needs of the scientific and technological communities that work on the multi-disciplinary and multi-domain problems related to agriculture and food. 

Technical challenges

AGINFRA+ aims to exploit core e-infrastructures such as EGI.eu, OpenAIRE, EUDAT and D4Science, towards the evolution of theAGINFRA data infrastructure, so as to provide a sustainable channel addressing adjacent but not fully connected user communities around Agriculture and Food. To this end, the project will develop and provide the necessary specifications and components for allowing the rapid and intuitive development of variegating data analysis workflows, where the functionalities for data storage and indexing, algorithm execution, results visualization and deployment are provided by specialized services utilizing cloud based infrastructure(s). Furthermore, AGINFRA+ aspires to establish a framework facilitating the transparent documentation and exploitation and publication of research assets (datasets, mathematical models, software components results and publications) within AGINFRA, in order to enable their reuse and repurposing from the wider research community.

How EOSC can help and add value

A main goal of the early adopter is to create a DataMiner (DM) cluster and make it available to all the communities served by the D4Science infrastructure.

Specific steps:

• Deploy the DM cluster in a single cloud provider and enable EOSC monitoring and accounting
• Develop monitoring probes to check the status of the DM cluster
• Integration of monitoring probes in the EOSC Monitoring service
• Assessment of operational continuity of the application and onboarding of AGINFRA+ VREs in the EOSC Portal.

Societal challenges

The “Integration of toxicology and risk assessment services into the EOSC marketplace” project involve the infrastrucutre of

OpenRiskNet. The main challenge is developing an e-infrastructure for safety assessment, including toxicology and especially predictive toxicology, structural biology, bioinformatics, cheminformatics.

The main goal is to assess OpenRiskNet’s services for EOSC integration.

Technical challenges

OpenRiskNet e-infrastructure provides access to research data, algorithms and modelling tools supporting predictive toxicology and risk assessment goals based on new approach methods. Here are available resources and services to a variety of communities requiring risk assessment, including chemicals, cosmetic ingredients, pesticides, food, therapeutic agents and nanomaterials.

How EOSC can help and add valu

This use case was facilitated by the EOSC-hub project via the following services: EGI Cloud Compute, EGI Online Storage, EOSC AAI

Specific steps:

• Testing of the EOSC services
• Integration of EOSC AAI and deployment of OpenRiskNet services on EOSC cloud resources
• Onboard and manage OpenRiskNet services in the EOSC Marketplace