Scientific level

Examples of domain-specific Thematic Services benefiting from the solutions offered by the EGI Infrastructure.

Target Audience: Oceanographers Climate Researchers Ocean Modellers Ocean Data Managers	"The EGI-ACE webODV – Online extraction, analysis and visualisation of SeaDataNet and Argo data" (Nov. 2022) Agenda, slides and recording: https://indico.egi.eu/event/5980/ About: ODV (Ocean Data View) is a widely used software package for the analysis, exploration and visualization of oceanographic and other environmental data with almost 100,000 registrations since the 1990’s and more than 10,000 active users. ODV has been further developed as part of the EU supported activities of SeaDataNet, the pan-European infrastructure for marine and ocean data management. To make working with web-based large community datasets easier, an online version of the ODV software called webODV has been developed, which provides typical ODV functionality in the form of web services. webODV has been deployed in the cloud in the framework of the EU EGI-ACE project, which seeks to promote scientific analytical cloud services in support of the European Open Science Cloud (EOSC) initiative. In this webinar, we will be able to learn about the webODV Explorer and Extractor components in combination with the large validated Temperature & Salinity data collections as provided by SeaDataNet and EuroArgo – Argo. Instructions on how to register as a user to perform analytics, extractions, and visualisations will also be presented.
Target Audience: Scientific communities and end users.	"Can deep learning models help accelerate electrostatics-driven protein pKa predictions?" (Nov. 2022) Agenda, slides and recording: https://indico.egi.eu/event/5981/ About: pH is a crucial physicochemical property that affects proteins molecular structure, folding, stability, and function. Many computational methods have been developed to calculate pKa values. In the highly accurate, but slow, Poisson–Boltzmann (PB)-based methods, proteins are represented by point charges in a low dielectric medium surrounded by an implicit solvent (high dielectric). Empirical methods rely on statistically fitting parameters over large datasets of experimental pKa values. These are much faster than the physics-based methods, although at the cost of less microscopic insights and unknown predictive power on mutations and proteins dissimilar to those in the training set. In this webinar we will present a novel strategy to combine the best features of PB models – accuracy and interpretability – with the speed of classical empirical methods. The deep learning pKa predictors obtained were trained on a database of 3M theoretical pKa values estimated from 50k structures using a PB method. With this approach, we can retrieve the physics-based predictions with an average error below 0.4 pK units while being up to 1000x faster.
Target Audience: Scientific communities and end users.	"The Virtual Imaging Platform: Scientific Applications as a Service and Beyond" (March, 2022) Agenda, slides and recording: https://indico.egi.eu/event/5824/ About: The Virtual Imaging Platform (VIP) is a web portal for medical simulation and image data analysis. It leverages resources available in the EGI biomed Virtual Organisation to offer an open service to academic researchers worldwide. In the last few years, VIP has addressed interoperability and reproducibility concerns, in the larger scope of a FAIR (Findable, Accessible, Interoperable, Reusable) approach to scientific data analysis. The presentation will give an overview of VIP and its main interests for the audience: Use existing applications as a service on VIP. Import your own applications to make them available to the community benefit from EGI biomed resources in a transparent way and Foster open and reproducible science
Target Audience: Scientific communities and end users.	"ENES Data Space Service" (March, 2022) Agenda, slides and recording: https://indico.egi.eu/event/5743/ About: The ENES Data Space delivers an open, scalable and cloud-enabled data science environment for climate data analysis on top of the EOSC Compute Platform. It provides access to a set of specific Coupled Model Intercomparison Project (CMIP) variable-centric collections to support meteorological and industrial researchers in realistic climate model analysis experiments. Data is downloaded and kept in sync with the Earth System Grid Federation (ESGF) federated data archive. This webinar will provide a general overview of the ENES Data Space service and its main features. Moreover, the webinar will include a tutorial on how to join the ENES Data Space service and a short demo for the participants to get started with the data analysis and visualisation features.
Target Audience: Scientific communities, end users and service providers who are interested in discovering how we have been making efficient use of EGI High Throughput Compute (HTC) resources over more than 10 years to provide services to worldwide researchers in structural biology and life sciences.	"WeNMR - Structural biology in the cloud - 10 years of experience of using EGI services" (April 2020) Agenda, slides and recording: https://indico.egi.eu/event/5084/ About: Structural biology deals with the characterization of the structural (atomic coordinates) and dynamic (fluctuation of atomic coordinates over time) properties of biological macromolecules and adducts thereof. Gaining insight into 3D structures of biomolecules is highly relevant with numerous applications in health and food sciences, with as current example unravelling the structural details of Sars-Cov2 in the COVID-19 pandemic. Since 2010, the WeNMR project has implemented numerous web-based services to facilitate the use of advanced computational tools by researchers in the field, using the grid computational infrastructure provided by EGI. These services have been further developed in subsequent initiatives under the H2020 EGI-ENGAGE West-Life project and the BioExcel Center of Excellence for Biomolecular Computational Research. The WeNMR services are currently operating under the European Open Science Cloud with the H2020 EOSC-Hub project, with the HADDOCK portal sending >10 millions jobs and using ~2700 CPU years per year. In my talk, I will summarise 10 years of successful use of e-infrastructure solutions to serve a large worldwide community of users (>16’000 to date), providing them with user-friendly, web-based solutions that allow to run complex workflows in structural biology. I will illustrate this with details of the HADDOCK service and how we could increase our capacity to serve COVID-related projects. Suggested tutorials Submitting HTC Jobs: Submitting High Throughput Compute jobs
Target Audience: Scientific communities working in the domain of Earth Observation.	"C-SCALE Notebooks for Earth Observation" (June 2023) About: The C-SCALE project has been federating compute and data resource providers around centralized EGI services, aiming at providing users with seamless access to processing capacities as well as source data for their analyses. Alongside the traditional IaaS and PaaS services, Jupyter Notebooks have been identified as an environment suitable not only for interactive analysis within C-SCALE, but also for documenting the different steps one needs to take in discovering and accessing geospatial data across Europe. The demonstration of C-SCALE's example notebooks and procedures will focus on those essential features: simple steps to get started using the federated resources for interactive resources of Earth Observation data. Slides and code https://github.com/c-scale-community/c-scale-notebooks
Target Audience: Scientific communities working in the domain of Earth Observation.	"C-SCALE Earth Observation - Metadata Query Service" (March 2023) About: The C-SCALE Earth Observation Metadata Query Service (EO-MQS) makes Copernicus data distributed across providers within the C-SCALE Data federation discoverable and searchable. Slides and code https://github.com/c-scale-community/c-scale-tutorial-eo-mqs
Target Audience: Scientific communities working in the domain of Earth Observation.	"Introduction to openEO Platform" (December 2022) About: openEO platform provides intuitive programming libraries to process a wide variety of earth observation datasets. This large-scale data access and processing is performed on multiple infrastructures, which all support the openEO API. This allows use cases from explorative research to large-scale production of EO-derived maps and information. Slides and code https://github.com/c-scale-community/c-scale-tutorial-openeo
Target Audience: Scientific communities and end users.	"I-NERGY, European AI-on demand platform" (July 2023) About: I-NERGY aims to support and develop novel AI-based energy services as part of the enrichment of European AI-on demand platform. This webinar will present the objectives and scope of the project, its requirements in terms of resources and the successful utilisation of EGI infrastructure. The webinar will conclude with a demo of I-NERGY services.
Target Audience: Scientific communities and end users.	"Access to the EISCAT tools with help of EGI checkin" (June 2023) About: The present era of rapid technological advances creates a challenge for data providers and scientists to create and maintain FAIR data and services not just for future operations but also for historical data gathered and analysed with technologies that are slowly phasing out of their usage. GUISDAP is an open-source software package, written in MATLAB, C and Fortran and provided and maintained by EISCAT, for analysis and visualisation of its incoherent scatter radar data as well as for some other radars in the world. One way how to preserve GUISDAP operability and accessibility by the user community is to make it accessible through a Jupyter notebook docker deployment through EISCAT resources and in the frame of an EOSC project. This will help to ensure the FAIRness of EISCAT data by providing tools for reanalysis and visualisation that will be accessible by any potential EISCAT user with the help of EGI check-in technology.

Last modified July 18, 2023 by Sebastian Luna-Valero : Add new tutorials (#607)