Towards Interoperable Research Infrastructures for Environmental and Earth Sciences: A Reference Model Guided Approach for Common Challenges.

Abstract

This book summarises the latest developments on data management in the EU H2020 ENVRIplus project, which brought together more than 20 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 climate change, food security, and natural disasters are intrinsically interdisciplinary. Modelling these processes individually is difficult enough, but modelling their interactions 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 research 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 infrastructure 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. This book presents the design, development, deployment, operation, and use of research infrastructures as 20 chapters via five parts. Part one provides an overview of the state of the art of research infrastructure and relevant e-Infrastructure technologies, part two discusses the reference model guided engineering approach, the third part presents the software and tools developed for common data management challenges, 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. This book will provide RI data managers in environmental and earth sciences with a common ontological framework and facilities for modeling 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 training young researchers and data managers in data management skills, RI service development and operation practices, and using RIs for data-centric research. In addition to researchers and developers involved in the data for science theme, the development of the book has also been greatly supported by the project coordinator and RI partners, in particular those specialists willing to serve in the editorial board. We thank all the authors for contributing to the individual chapters, and reviewers for providing valuable feedback on the content. Without their support, this book would not have been possible.