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DaProS: A Data Property Specification Tool to Capture Scientific Sensor Data Properties

机译:DaProS:一种数据属性规范工具,可捕获科学的传感器数据属性

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Environmental scientists have begun to use advanced technologies such as wireless sensor networks and robotic trams equipped with sensors to collect data, such as spectral readings and carbon dioxide, which is leading to a rapid increase in the amount of data being stored. This has resulted in a need to evaluate promptly the accuracy of the data, the meaning of the data, and the correct operation of the instrumentation in order to not lose valuable time and information. Performing such evaluations requires scientists to rely on their knowledge and experience in the field. Field knowledge is rarely shared or reused by other scientists mostly because of the lack of a well-defined methodology for sharing information and appropriate tool support. This work presents the Data Property Specification (DaProS) tool that assists practitioners in specification and refinement of properties that can be used to check data quality. The tool can be used to capture scientific knowledge about data processes in remote sensing systems through the use of decision trees and questionnaires that guide practitioners in the specification process. In addition, the tool uses Disciplined Natural Language (DNL) property representations for scientists to validate that the specifications capture the intended meaning.
机译:环境科学家已经开始使用先进的技术,例如无线传感器网络和配备传感器的机器人电车来收集数据,例如光谱读数和二氧化碳,这导致存储的数据量迅速增加。这导致需要及时评估数据的准确性,数据的含义以及仪器的正确操作,以免浪费宝贵的时间和信息。进行此类评估需要科学家依靠他们在该领域的知识和经验。其他科学家很少共享或重用现场知识,这主要是因为缺乏明确的信息共享方法和适当的工具支持。这项工作介绍了数据属性规范(DaProS)工具,可帮助从业人员规范和完善可用于检查数据质量的属性。通过使用决策树和调查表来指导从业人员进行规范过程,该工具可用于捕获有关遥感系统中数据过程的科学知识。此外,该工具使用纪律自然语言(DNL)属性表示形式供科学家使用,以验证规范是否捕获了预期的含义。

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