Services for the European Open Science Cloud
Services for the European Open Science Cloud
The European Network for Earth System Modelling, or ENES, brings together the scientific community working on these themes. ENES aims to: help in the development and evaluation of state-of-the-art climate and Earth system models, encourage exchanges of software and results, help in the development of high-performance computing facilities dedicated to long high-resolution, multi-model ensemble integrations.
ENES was launched in 2001 and the institutions involved in this network include university departments, research and computer centres, meteorological services and industrial partners. ENES engages in improving European competitiveness and expertise by continuously working on extending the network Europewide. This community is strongly involved in the assessments of the Intergovernmental Panel on Climate Change (IPCC) and provides the predictions EU mitigation and adaptation policies are elaborated on.
The main service is the ENES Climate Analytics Service (ECAS) and a related user-oriented virtual research environment called “ECAS Lab”. ECASLab is a user-friendly, scientific data analysis environment that integrates data and analysis tools to support scientists in their daily research activities. The environment combines the features of ECAS with a large set of Python libraries for data manipulation, analysis, and visualization. ECAS builds on the Ophidia big data analytics framework and is the main component of the ECASLab. It represents a complete software stack developed for the analysis of large multidimensional data (‘datacubes’) in several eScience domains (e.g. climate change).
ECAS is one of the EOSC-Hub Thematic Services. It aims to address several challenges, by integrating a set of operational products that enable a paradigm shift for climate analytics. ECAS aims to reduce the need for local data download, by relying on server-side and parallel processing, and to reduce the effort of maintaining client-side tools, by managing a set of aspects on the server side, thus easing the demand on the clients. ECAS also reduces the need for the user to orchestrate complex workflows, by taking advantage of the workflow capabilities to run very complex experiments and take the coordination burden off the users, providing an end-to-end workflow experience. This will encourage flexible and open data sharing according to the FAIR principles and will enable PID-based provenance support through the integration with specific services like B2HANDLE. And finally, ECAS aims to improve performance, by enabling users to more easily exploit high performance computation and big data management, through a High Performance Data Analytics approach. The EOSC is being set up to be Europe’s virtual environment for all researchers to store, manage, analyse and re-use data for research, innovation and educational purposes.
I will take an active part in the process, due to my current involvement, as CMCC Foundation, in the EOSC-hub project. CMCC, jointly with DKRZ, hosts two ECAS instances that are intended to serve the climate community, through the ECASLab virtual environment. ECASLab will offer user interfaces, such as Jupyter, to make the execution of analytics experiments on large climate datasets straightforward and user-friendly. Besides scientific research, we’ll also provide some free access resources for training activities and evaluation purposes. Training and dissemination actually represent two key elements to increase both the user base and the awareness in the community of the paradigm shift towards High Performance Data Analytics.
EOSC will set the ground for an ambitious landscape fostering open (data-driven) science and open innovation across various domains. This will provide new opportunities for both the scientific research and the private sector, directly affecting the citizens and the society in general. In particular, I see a great value in the long tail of research that could introduce new and unexplored market opportunities, across different sectors, in the climate services context. In terms of research, EOSC will make cross-domain fertilization a reality, providing an open science environment able to envisage new scientific frontiers and deal with the many challenges deriving from them.
Well, 10 years is a very long time from now! Yet, what looks intriguing to me is the role that (machine) learning will play in climate science and more in general in open science research, besides the already active part of simulation and data management. This will represent a great shift for scientific communities and, at the same time, a strong opportunity for EOSC in the long run to evolve towards next generation data science frontiers.
ECAS is currently offered by the sites at Euro-Mediterranean Center on Climate Change (CMCC) and the Deutsches Klimarechenzentrum (DKRZ). To access the ECAS service or to learn more about the different datasets available, please follow the instructions for registration and access at the two sites: CMCC and DKRZ.