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This paper presents the approach adopted by the EGI-ACE project for the setup and delivery of Data Spaces for various scientific domains. The work was implemented by members of the EGI e-infrastructure and of several European Research Infrastructures in the context of the European Open Science Cloud programme. Our results are several Data Space services that enable the reuse and exploitation of open, scientific big data for compute intensive use cases. The paper illustrates the EGI-ACE approach through two examples: (1) EMSO ERIC Data Portal for seafloor and water column research and (2) ENES Data Space for climate research.

This paper presents the approach adopted by the EGI-ACE project for the setup and delivery of Data Spaces for various scientific domains. The work was implemented by members of the EGI e-infrastructure and of several European Research Infrastructures in the context of the European Open Science Cloud programme. Our results are several Data Space services that enable the reuse and exploitation of open, scientific big data for compute intensive use cases. The paper illustrates the EGI-ACE approach through two examples: (1) EMSO ERIC Data Portal for seafloor and water column research and (2) ENES Data Space for climate research., Competing Interests: No competing interests were disclosed., (Copyright: © 2024 Sipos G et al.)

META-pipe is a complete service for the analysis of marine metagenomic data. It provides assembly of high-throughput sequence data, functional annotation of predicted genes, and taxonomic profiling. The functional annotation is computationally demanding and is therefore currently run on a high-performance computing cluster in Norway. However, additional compute resources are necessary to open the service to all ELIXIR users. We describe our approach for setting up and executing the functional analysis of META-pipe on additional academic and commercial clouds. Our goal is to provide a powerful analysis service that is easy to use and to maintain. Our design therefore uses a distributed architecture where we combine central servers with multiple distributed backends that execute the computationally intensive jobs. We believe our experiences developing and operating META-pipe provides a useful model for others that plan to provide a portal based data analysis service in ELIXIR and other organizations with geographically distributed compute and storage resources.

META-pipe is a complete service for the analysis of marine metagenomic data. It provides assembly of high-throughput sequence data, functional annotation of predicted genes, and taxonomic profiling. The functional annotation is computationally demanding and is therefore currently run on a high-performance computing cluster in Norway. However, additional compute resources are necessary to open the service to all ELIXIR users. We describe our approach for setting up and executing the functional analysis of META-pipe on additional academic and commercial clouds. Our goal is to provide a powerful analysis service that is easy to use and to maintain. Our design therefore uses a distributed architecture where we combine central servers with multiple distributed backends that execute the computationally intensive jobs. We believe our experiences developing and operating META-pipe provides a useful model for others that plan to provide a portal based data analysis service in ELIXIR and other organizations with geographically distributed compute and storage resources.

One of the important direction of cloud technologies development nowadays is a creation of methods for integration of various cloud infrastructures. An actuality of such direction in academic field is caused by a frequent lack of own computing resources and a necessity to attract additional ones. This article is dedicated to existing approaches to cloud infrastructures integration with each other: federations and so called cloud bursting. A federation in terms of OpenNebula cloud platform is built on a one master zone and several slave ones schema. A term zone means a separate cloud infrastructure in the federation. All zones in such kind of integration have a common database of users and the whole federation is managed via master zone only. Such approach is most suitable for a case when cloud infrastructures of geographically distributed branches of a single organization need to be integrated. But due to its high centralization it's not appropriate when one needs to join cloud infrastructures of different organizations. Moreover it's not acceptable at all in case of clouds based on different software platforms. A model of federative integration implemented in EGI Federated Cloud allows to connect clouds based on different software platforms but it requires a deployment of sufficient amount of additional services which are specific for EGI Federated Cloud only. It makes such approach is one-purpose and uncommon one. A cloud bursting model has no limitations listed above but in case of OpenNebula platform what the Laboratory of Information Technologies of Joint Institute for Nuclear Research (LIT JINR) cloud infrastructure is based on such model was implemented for an integration with a certain set of commercial cloud resources providers. Taking into account an article authors experience in joining clouds of organizations they represent as well as with EGI Federation Cloud a cloud bursting driver was developed by LIT JINR cloud team for OpenNebula-based clouds integration with each other as well as with OpenStack-based ones. The driver's architecture, technologies and protocols it relies on and an experience of its usage are described in the article.

META-pipe is a complete service for the analysis of marine metagenomic data. It provides assembly of high-throughput sequence data, functional annotation of predicted genes, and taxonomic profiling. The functional annotation is computationally demanding and is therefore currently run on a high-performance computing cluster in Norway. However, additional compute resources are necessary to open the service to all ELIXIR users. We describe our approach for setting up and executing the functional analysis of META-pipe on additional academic and commercial clouds. Our goal is to provide a powerful analysis service that is easy to use and to maintain. Our design therefore uses a distributed architecture where we combine central servers with multiple distributed backends that execute the computationally intensive jobs. We believe our experiences developing and operating META-pipe provides a useful model for others that plan to provide a portal based data analysis service in ELIXIR and other organizations with geographically distributed compute and storage resources.

META-pipe is a complete service for the analysis of marine metagenomic data. It provides assembly of high-throughput sequence data, functional annotation of predicted genes, and taxonomic profiling. The functional annotation is computationally demanding and is therefore currently run on a high-performance computing cluster in Norway. However, additional compute resources are necessary to open the service to all ELIXIR users. We describe our approach for setting up and executing the functional analysis of META-pipe on additional academic and commercial clouds. Our goal is to provide a powerful analysis service that is easy to use and to maintain. Our design therefore uses a distributed architecture where we combine central servers with multiple distributed backends that execute the computationally intensive jobs. We believe our experiences developing and operating META-pipe provides a useful model for others that plan to provide a portal based data analysis service in ELIXIR and other organizations with geographically distributed compute and storage resources., Competing Interests: No competing interests were disclosed.