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Enhancing Data Quality Assessment Capabilities by Providing Unique, Authoritative, Discoverable, Referenceable Sensor Model Descriptions
  • Janet Fredericks,
  • Felimon Gayanilo
Janet Fredericks
Woods Hole Oceanographic Institution

Corresponding Author:jfredericks@whoi.edu

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Felimon Gayanilo
Texas A&M University Corpus Christi
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With observational data becoming widely available, researchers struggle to find information enabling assessment for its reliable use. A small first-step toward enabling data quality assessment of observational data is to associate the data with the sensor used to make the observations and to have the sensor description machine-harvestable. In the latest additions to the X-DOMES (Cross-Domain Observational Metadata for Enviromental Sensing) toolset, we have created targeted editors for creating SensorML documents to describe sensor models. The team has adjusted its delivery to enable integration of the X-DOMES content with the GEOCODES (JSON-LD/schema.org) EarthCube project. At our poster-session, we will highlight the new changes and capabilities and demonstrate the use of new X-DOMES tools.