Fencl Martin, Nebuloni Roberto, C M Andersson Jafet, Bares Vojtech, Blettner Nico, Cazzaniga Greta, Chwala Christian, Colli Matteo, de Vos Lotte, El Hachem Abbas, Galdies Charles, Giannetti Filippo, Graf Maximilian, Jacoby Dror, Victor Habi Hai, Musil Petr, Ostrometzky Jonatan, Roversi Giacomo, Sapienza Fabiola, Seidel Jochen, Spackova Anna, van de Beek Remco, Walraven Bas, Wilgan Karina, Zheng Xin
Department of Hydraulics and Hydrology, Czech Technical University in Prague, Prague 6, 16629, Czech Republic.
IEIIT-CNR (National Research Council of Italy), Milano, Italy.
Open Res Eur. 2024 Feb 13;3:169. doi: 10.12688/openreseurope.16068.2. eCollection 2023.
Opportunistic sensors are increasingly used for rainfall measurement. However, their raw data are collected by a variety of systems that are often not primarily intended for rainfall monitoring, resulting in a plethora of different data formats and a lack of common standards. This hinders the sharing of opportunistic sensing (OS) data, their automated processing, and, at the end, their practical usage and integration into standard observation systems. This paper summarises the experiences of the more than 100 members of the OpenSense Cost Action involved in the OS of rainfall. We review the current practice of collecting and storing precipitation OS data and corresponding metadata, and propose new common guidelines describing the requirements on data and metadata collection, harmonising naming conventions, and defining human-readable and machine readable file formats for data and metadata storage. We focus on three sensors identified by the OpenSense community as prominent representatives of the OS of precipitation: Commercial microwave links (CML): fixed point-to-point radio links mainly used as backhauling connections in telecommunication networks Satellite microwave links (SML): radio links between geostationary Earth orbit (GEO) satellites and ground user terminals. Personal weather stations (PWS): non-professional meteorological sensors owned by citizens. The conventions presented in this paper are primarily designed for storing, handling, and sharing historical time series and do not consider specific requirements for using OS data in real time for operational purposes. The conventions are already now accepted by the ever growing OpenSense community and represent an important step towards automated processing of OS raw data and community development of joint OS software packages.
机会性传感器越来越多地用于降雨测量。然而，它们的原始数据是由各种通常并非主要用于降雨监测的系统收集的，这导致了大量不同的数据格式以及缺乏通用标准。这阻碍了机会性传感（OS）数据的共享、其自动化处理，最终也阻碍了其实际应用以及与标准观测系统的集成。本文总结了参与降雨机会性传感的OpenSense成本行动的100多名成员的经验。我们回顾了收集和存储降水机会性传感数据及相应元数据的当前做法，并提出了新的通用指南，描述了对数据和元数据收集的要求，统一命名约定，并为数据和元数据存储定义了人类可读和机器可读的文件格式。我们重点关注OpenSense社区确定为降水机会性传感突出代表的三种传感器：商业微波链路（CML）：主要用作电信网络回程连接的固定点对点无线电链路；卫星微波链路（SML）：地球静止轨道（GEO）卫星与地面用户终端之间的无线电链路；个人气象站（PWS）：公民拥有的非专业气象传感器。本文提出的约定主要用于存储、处理和共享历史时间序列，并未考虑将机会性传感数据实时用于业务目的的特定要求。这些约定现已被不断壮大的OpenSense社区接受，代表了朝着机会性传感原始数据的自动化处理以及联合机会性传感软件包的社区开发迈出的重要一步。
