In January 2019, the US Department of Energy, Office of Science program in Advanced Scientific Computing Research, convened a workshop to identify priority research directions (PRDs) for in situ data management (ISDM). A fundamental finding of this workshop is that the methodologies used to manage data among a variety of tasks in situ can be used to facilitate scientific discovery from many different data sources—simulation, experiment, and sensors, for example—and that being able to do so at numerous computing scales will benefit real-time decision-making, design optimization, and data-driven scientific discovery. This article describes six PRDs identified by the workshop, which highlight the components and capabilities needed for ISDM to be successful for a wide variety of applications—making ISDM capabilities more pervasive, controllable, composable, and transparent, with a focus on greater coordination with the software stack and a diversity of fundamentally new data algorithms.

中文翻译：

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原位数据管理的优先研究方向：使不同数据源的科学发现成为可能

2019 年 1 月，美国能源部高级科学计算研究科学计划办公室召开了一次研讨会，以确定原位数据管理 (ISDM) 的优先研究方向 (PRD)。本次研讨会的一个基本发现是，用于在各种原位任务中管理数据的方法可用于促进来自许多不同数据源（例如模拟、实验和传感器）的科学发现，并且能够做到因此，在众多计算规模上将有利于实时决策、设计优化和数据驱动的科学发现。本文介绍了研讨会确定的六个 PRD，重点介绍了 ISDM 在各种应用中取得成功所需的组件和功能——使 ISDM 功能更加普遍、可控、