Enhancing Data Quality Assessment Capabilities by Providing Unique,
Authoritative, Discoverable, Referenceable Sensor Model Descriptions
- Janet Fredericks,
- Felimon Gayanilo
Abstract
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.