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Cross-Domain Observational Metadata for Environmental Sensing (X-DOMES)

Standards-based description of environmental sensor metadata, including provenance, is paramount to automated data discovery, access, archival, processing, as well as quality control and assessment.  

Leveraging existing relationships with large NSF-funded data management programs, EarthCube building blocks and working groups, and environmental sensor manufacturers and consortia, we will establish a community of sensor manufacturers and other stakeholders to provide a unifying approach to describing sensors and observations across geo-science domains.  Built on an existing sensor metadata model that references registered, standards-based vocabularies, the X-DOMES pilot project will provide a suite of tools, built upon community-adopted standards of the Open Geospatial Consortium (OGC) and World Wide Web Consortium (W3C) to demonstrate and facilitate the generation of metadata documents that are discoverable and accessible on-line and/or directly from onboard sensor descriptions.  We will also demonstrate mechanisms to associate the data with the metadata through standards-based web services.  With vendor-ready tools implemented throughout a broad-based community, the X-DOMES Network will lay the foundation for the development of and adoption of interoperable access to much needed content-rich sensor metadata.


  • Janet Fredericks, Woods Hole Oceanographic Institution (WHOI)
  • Michael Botts, Botts Innovative Research, Inc
  • Carlos Rueda, Monterey Bay Aquarium Research Institute (MBARI)
  • Felimon Gayanilo, Texas A & M University (TAMUCC)
  • John Graybeal, Marine Metadata Interoperability (MMI)
  • Krzysztof Janowicz, University of California Santa Barbara (UCSB)

Benefits to Scientists

  1. This project provides a cross-domain approach to collection of and access to sensor metadata, which enables sharing sensor data across disciplines.
  2. X-DOMES transforms when knowledge is captured - , which is at the point of action where it is best understood. The use of standards-based technology (OGC SWE - in particular SensorML) enables fully-described provenance which is associated with the data and persists throughout the data life cycle, including •the Original Equipment Manufacturers description of the model •the operator’s description of actions affecting data quality and capabilities of the sensor •the processing and quality control applied to sensor data •the processing that provides derived products •the actions on a sensor that affect data (calibration/maintenance, etc.)
  3. Registration of terms enables discoverability through use of W3C Web Services to create documents that are resolvable and web-accessible through community repositories. Then, ontologies can be developed to enable the development of relationships of data within- and across-domains.
  4. Upon discovery of fully described observations, researchers will be able to determine how an observation was made, thereby fostering integration and reuse with confidence.
  5. By engaging sensor manufacturers to start the description of sensor metadata and processes in machine-harvestable, standards-based encodings, interoperable mechanisms will be enabled for many providers who otherwise would not be able to easily offer their data utilizing these frameworks. And, data facilities can point to sensor descriptions that include content that can be used for data quality assessment.

Project Deliverables

A SensorML viewer/editor is needed to enable sensor manufacturers and operators to create fully described sensor descriptions, without knowledge of the underlying technologies. The editor looks like a technical specifications sheet. • The SensorML- Sensor Model Viewer 1.0 is complete. • SensorML- Sensor-Model Profiler/Editor will be completed over the next few months (Aug 2016).

The Q2O (QARTOD-to-OGC) project (2007-2011) created a quality-assessment reference implementation model for fully describing how an observation came to be, including sensor descriptions, configuration, processing (QC, QC-flagging, and derived products) and sensor history (events) ( The X-DOMES project enabled us to upgrade the model from SWE 1.0 to SWE 2.0. (See

The X-DOMES ( domain has been secured and the MMI ORR software is being updated and improved for broader community use and better capabilities. (See Github for listing of enhancements.)   The new software is DOCKR enabled and has been installed on and is now a "sandbox" as the ESIP Community Ontology Registry.

Over the next several months, the X-DOMES semantic repository will be used to host representative vocabularies needed to describe environmental sensors.  The X-DOMES team led a workshop at the ESIP 2016 Summer Meeting in July 2016.   They demonstrated the ontology registry (COR and XORR) which is used to create terms for sensor types and observable properties and to develop relationships that enable their association (Semantic Web Technologies).

In Fall 2016, sensor manufacturers were approached to describe their sensor models utilizing the SensorML Viewer/Editor to generate fully described sensor metadata for targeted sensor models with references to registered terms within an ontology registry (X-ORR).   The concept of describing the characteristics and capability of sensor models was expanded to creating a document to uniquely identify each sensor, as built.  The SensorML document describing the model is to be 'owned' and registered by the manufacturer.  The specific sensor SensorML creates a uniquely identifiable description of each sensor.  It can easily be created by a manufacturer and then ownership would be transferred to the sensor owner.  This enables tracking for sensor management.

Early 2017, the X-DOMES team began assessment of the SensorML registry, where the sensor descriptions can be stored online, creating resolvable URLS.  This will enable persistence, versioning and discoverability.

By the summer of 2017, X-DOMES collaborators will begin testing the ability to integrate these technologies into their data management systems.

The X-DOMES Network has been created within the ESIP Enviro-sensing Community

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