HydroServer：一种支持收集、通信、存储、管理和共享现场环境传感器数据的软件堆栈

IF 4.6 2区环境科学与生态学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Environmental Modelling & Software Pub Date : 2025-07-24 DOI:10.1016/j.envsoft.2025.106637

Jeffery S. Horsburgh , Kenneth Lippold , Daniel L. Slaugh , Maurier Ramirez

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引用次数: 0

摘要

使用现场环境传感器收集数据的科学家和从业人员需要有效的软件来管理和共享他们产生的数据。HydroServer软件栈被设计为一个基于标准的系统，可以收集、存储、管理和共享环境传感器数据。HydroServer软件最初是水文科学大学联盟（CUAHSI）水文信息系统（HIS）的一部分，现已现代化，使用开放地理空间联盟（OGC）的SensorThings应用程序编程接口（API）和数据模型标准，以便更好地灵活和标准化地摄取来自多个传感器和来源的数据。以及为各种不同的用户和用例查询和检索托管数据。HydroServer软件是开源的，并提供了针对云部署的部署说明，这使得研究人员和从业者都可以访问和使用它。

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HydroServer: A software stack supporting collection, communication, storage, management, and sharing of data from in situ environmental sensors

Scientists and practitioners who collect data using in situ environmental sensors need effective software for managing and sharing the data they produce. The HydroServer software stack was designed as a standards-based system that enables collection, storage, management, and sharing of environmental sensor data. Originally part of the Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI) Hydrologic Information System (HIS), the HydroServer software has been modernized to use the Open Geospatial Consortium's (OGC) SensorThings application programming interface (API) and data model standard to better enable flexible and standardized ingestion of data from multiple sensors and sources, along with query and retrieval of hosted data for a variety of different users and use cases. The HydroServer software is open source with deployment instructions targeted for cloud deployments, which makes it accessible and useable by both researchers and practitioners.

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来源期刊

Environmental Modelling & Software 工程技术-工程：环境

CiteScore

9.30

自引率

8.20%

发文量

241

审稿时长

60 days

期刊介绍： Environmental Modelling & Software publishes contributions, in the form of research articles, reviews and short communications, on recent advances in environmental modelling and/or software. The aim is to improve our capacity to represent, understand, predict or manage the behaviour of environmental systems at all practical scales, and to communicate those improvements to a wide scientific and professional audience.