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Environmental data centers have been successfully acquiring, disseminating, and archiving data for decades. However, the increasing volume and number of data sets, coupled with greater demands from more diverse users, are making it difficult for data centers to maintain the record of environmental change. This workshop report focuses on technological approaches that could enhance the ability of environmental data centers to deal with these challenges, and improve the ability of users to find and use information held in data centers. Among the major findings are that data centers should rely more on off-the-shelf technology-including software and commonly available hardware-and should shift from tape to disk as the primary storage medium. Such technological improvements will help solve many data management problems, although data centers and their host agencies will have to continue to invest in the scientific and human elements of data center operations.
This book constitutes the refereed proceedings of the First International Conference on Big Scientific Data Management, BigSDM 2018, held in Beijing, Greece, in November/December 2018. The 24 full papers presented together with 7 short papers were carefully reviewed and selected from 86 submissions. The topics involved application cases in the big scientific data management, paradigms for enhancing scientific discovery through big data, data management challenges posed by big scientific data, machine learning methods to facilitate scientific discovery, science platforms and storage systems for large scale scientific applications, data cleansing and quality assurance of science data, and data policies.