On the Design and Implementation of Easy Access to External Spatiotemporal Datasets in NFDI

Christian Beilschmidt, Dominik Brandenstein, Johannes Drönner, Nikolaus Glombiewski, Michael Mattig, Bernhard Seeger
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Abstract

Across many scientific domains, the ability to process large amounts of heterogeneous spatiotemporal data from various sources is crucial for solving challenging research questions. For example, in NFDI4Biodiversity, researchers need to combine observation data with satellite images to correlate the loss of biodiversity with climate change variables. In general, large data sets are not available on the system (called consumer) where the processing is performed, but first have to be retrieved from one or multiple external systems (called providers) that offer a corresponding service. Moreover, a consumer is often unaware of the datasets the providers offer. Ideally, a provider follows FAIR principles and thus supports mechanisms to greatly simplify the data exchange. However, in practice, there are multiple providers with valuable datasets that are not as FAIR as desired or lack spatiotemporal-specific support for data exchange. Instead of improving each potential provider at the source, we propose an intermediary spatiotemporal data exchange layer (SDExL) that helps simplify data exchange so that domain experts easily gain access to valuable data with little technical know-how.
NFDI中易于访问外部时空数据集的设计与实现
在许多科学领域,处理来自不同来源的大量异构时空数据的能力对于解决具有挑战性的研究问题至关重要。例如,在nfdi4生物多样性中,科学家需要将观测数据与卫星图像结合起来,将生物多样性的丧失与气候变化变量联系起来。通常,大型数据集在执行处理的系统(称为消费者)上不可用,而首先必须从提供相应服务的一个或多个外部系统(称为提供者)中检索。此外,消费者通常不知道提供者提供的数据集。理想情况下,提供者遵循FAIR原则,因此支持大大简化数据交换的机制。然而,在实践中,有多个具有有价值的数据集的提供者,它们不像期望的那样公平,或者缺乏对数据交换的时空特定支持。我们没有从源头上改进每个潜在的提供者,而是提出了一个中间的时空数据交换层(SDExL),它有助于简化数据交换,以便领域专家无需多少技术知识即可轻松访问有价值的数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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