Automating the Collection of Semantic Sensor Network Metadata in the Field with Mobile Applications

McGuinness, Deborah L.
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The Human-Aware Data Acquisition Infrastructure (HADatAc)
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In the past few decades, the field of ecology has grown from a collection of disparate researchers who collected data on their local phe­nomenon by hand, to large ecosystems-oriented projects partially fueled by automated sensor networks and a diversity of models and experiments. These modern projects rely on sharing and integrating data to answer questions of increasing scale and complexity. Interpreting and sharing the big data sets generated by these projects relies on information about how the data was collected and what the data is about, typically stored as metadata. Metadata ensures that the data can be interpreted and shared accurately and efficiently. Traditional paper-based metadata collection methods are slow, error-prone, and non-standardized, making data shar­ing difficult and inefficient. Semantic technologies offer opportunities for better data management in ecology, but also may pose a challenging learning curve to already busy researchers. This paper presents a mo­bile application for recording semantic metadata about sensor network deployments and experimental settings in real time, in the field, and without expecting prior knowledge of semantics from the users. This application enables more efficient and less error-prone in-situ metadata collection, and generates structured and shareable metadata.
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