Adapting OGC's SensorThings API and data model to support data management and sharing for environmental sensors

Software is critical in managing environmental sensor data. The Open Geospatial Consortium (OGC) developed the “OGC SensorThings API” (STA) standard to address variability across sensors, observed variables, platforms, and protocols, facilitating development of sensing and Internet of Things applications. This paper details a Python/Django implementation of the STA application programming interface (API) and a PostgreSQL/Timescale implementation of the STA data model, enhancing availability of robust software for management and sharing of environmental sensor data. STA offers a RESTful interface with JSON data encoding, aligning with modern development patterns and facilitating interoperability. Integration of metadata from the Observations Data Model ensures data can be adequately described and interpreted. STA's flexibility allows lightweight query responses or comprehensive metadata inclusion, and a complementary data management API enhances use of STA within multi-user systems. Open-source code and deployment instructions in GitHub enable standalone or cloud deployments, enhancing accessibility and usability for researchers and practitioners. • A Python/Django implementation of OGC SensorThings API (STA) was developed. • The STA data model was adapted to include metadata for environmental sensors. • Open-source software deployments for STA and data model are provided. • Deployment can be stand-alone or part of HydroServer software stack. • HydroServer's STA implementation improves software available for sensor data management.

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Institutions

Publication Details

Journal
Environmental Modelling & Software
Published
2024-10-09
DOI
https://doi.org/10.1016/j.envsoft.2024.106241
Citations
13
Primary Topic
Environmental Monitoring and Data Management
Type
article
Field-Weighted Citation Impact
10.85
Controls
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article

Adapting OGC's SensorThings API and data model to support data management and sharing for environmental sensors

Jeffery S. Horsburgh, Kenneth Lippold, Daniel L. Slaugh
13 citations
Environmental Modelling & Software
Environmental Monitoring and Data Management
10.85
article

Adapting OGC's SensorThings API and data model to support data management and sharing for environmental sensors

Jeffery S. Horsburgh, Kenneth Lippold, Daniel L. Slaugh
article en
13 citations

Abstract

Software is critical in managing environmental sensor data. The Open Geospatial Consortium (OGC) developed the “OGC SensorThings API” (STA) standard to address variability across sensors, observed variables, platforms, and protocols, facilitating development of sensing and Internet of Things applications. This paper details a Python/Django implementation of the STA application programming interface (API) and a PostgreSQL/Timescale implementation of the STA data model, enhancing availability of robust software for management and sharing of environmental sensor data. STA offers a RESTful interface with JSON data encoding, aligning with modern development patterns and facilitating interoperability. Integration of metadata from the Observations Data Model ensures data can be adequately described and interpreted. STA's flexibility allows lightweight query responses or comprehensive metadata inclusion, and a complementary data management API enhances use of STA within multi-user systems. Open-source code and deployment instructions in GitHub enable standalone or cloud deployments, enhancing accessibility and usability for researchers and practitioners. • A Python/Django implementation of OGC SensorThings API (STA) was developed. • The STA data model was adapted to include metadata for environmental sensors. • Open-source software deployments for STA and data model are provided. • Deployment can be stand-alone or part of HydroServer software stack. • HydroServer's STA implementation improves software available for sensor data management.

Environmental Modelling & SoftwareVol. 183
Utah State University (US)
Openalex Percentile: Top 2%
Environmental Monitoring and Data Management
10.85
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