Abstract

This book summarises the latest developments on data management in the EU H2020 ENVRIplus project, which brought together several environmental and earth science research infrastructures into a single community. It provides readers with a systematic overview of the common challenges faced by research infrastructures and how a ‘reference model guided’ engineering approach can be used to achieve greater interoperability among such infrastructures in the environmental and earth sciences. The research problems behind environmental and societal challenges such as cli-mate change, food security and natural disasters are intrinsically interdisciplinary. Modelling these processes individually is difficult enough, but modelling their inter-actions is another order of complexity entirely. Scientists are challenged to collaborate across conventional disciplinary boundaries, but must first discover and extract data dispersed across many different sources and in many different formats. Effective re-search support environments are needed for various user-centralised research activities, from formulating research problems to designing experiments, discovering data and services, executing workflows, and analysing then publishing the final results. Such support environments also have to manage research data during their entire lifecycle, throughout the phases of data acquisition, curation, publication, processing and use. Moreover, support environments must support the management of underlying infra-structure resources for computing, storage and networking. In this ecosystem, research infrastructure (RI) is an important form of supportive environment that bridges the gap between the curation of research data and user-centred scientific activity, and also between research data and the underlying physical infrastructure. It brings together facilities, resources and services used by the scientific community to conduct research, establish best practices for science, and foster innovation. The book presents the design, development, deployment, operation and use of re-search infrastructures as 20 chapters via five parts. The part one provides an overview of the state of the art of research infrastructure and relevant e-Infrastructure technolo-gies, part two discusses the reference model guided engineering approach, the third part presents the software and tools developed for common data management chal-lenges, the fourth part demonstrates the software via several use cases, and the last part discusses the sustainability and future directions. The main readers of the book will be developers, managers, operators and potential users of research infrastructures in environmental and earth sciences. The book will provide RI data managers in environmental and earth sciences with a common onto-logical framework and facilities for modelling data management requirements, and practical data management guidelines during entire research life-cycle. It will provide RI stakeholders with very practical case studies on RI architecture design, service interoperability, and system-level environmental research. The book can also be a textbook for the training young researchers and data managers data management skills, RI service development and operation practices, and using RIs for data-centric research. The development of the book has been greatly supported by the project coordinator and all partners, in particular those who are involved in the data for science theme. We thank all the authors who contribute to the book chapters, and editorial board members who provide a detailed review and valuable feedback on the content. With-out their support, this book would not have been possible.

Highlights

  • To tackle the scientific challenges discussed in the previous chapter, researchers need access to sophisticated research support environments that enable efficient discovery, access, interoperation and re-use of the data, tools, etc. available for advanced data science and provide a platform for the integration of all resources into cohesive observational, experimental and simulation investigations with replicable workflows

  • We review the requirements gathering performed in the context of the cluster of European environmental and Earth science research infrastructures participating in the environmental research infrastructures (ENVRI) community, and survey the common challenges identified from that requirements gathering process

  • Societal challenges facing the world today like climate change, food security and disaster prediction/response can only be addressed by making optimal use of such data, which requires scientists to collaborate across disciplinary boundaries, as these challenges are intrinsically transdisciplinary in nature

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Summary

Introduction

To tackle the scientific challenges discussed in the previous chapter, researchers need access to sophisticated research support environments that enable efficient discovery, access, interoperation and re-use of the data, tools, etc. available for advanced data science and provide a platform for the integration of all resources into cohesive observational, experimental and simulation investigations with replicable workflows. When describing a system supporting a broad range of applications, it is common to talk of an architectural framework In this sense, the ENVRI RM is an architectural framework for the design of a distributed system for environmental research infrastructures. The challenge, is to functionally integrate existing environmental RIs to permit researchers to freely and effectively interact with the full range of research assets potentially available to them, allowing them to collaborate and conduct innovative interdisciplinary research regardless of the particular research community to which they belong Realising this ideal requires a broad understanding of the fundamental commonalities of environmental science research infrastructure services, : in terms of concepts, in terms of processes, in terms of data and services, and in terms of technology adoption. The latter typically contains some basic metadata about the object, as well as information about how to access it

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