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OBOE has MOVED, please see for updated OBOE information and releases.  This page is only maintained for historical reasons.


OBOE is a suite of OWL-DL ontologies for modeling and representing scientific observations.  The OBOE model is designed as a generic data model with a number of constructs for defining observational data. Key features of OBOE include its ability to represent a wide range of measurement types, a mechanism for specifying measurement context, and the ability to associate the type of entity (e.g., sample, organism, etc.) being measured.  OBOE is being used and developed within the Semtools project for describing a wide variety of ecological data stored within the Knowledge Network for Biodiversity (KNB) as well as extensions for ontology-based data annotation and discovery within the MetaCat software infrastructure. 


This is the main starting point for the OBOE ontology, which includes the core OBOE structures. The goal of this ontology is to contain common terms used across domain extensions. The ontology defines characteristics, measurement standards (units), contextual relationships, and entities, and includes a number of common scientific units (including the SI units) and their corresponding physical characteristics (or dimensions). Domain extensions should import this ontology, and possibly other domain-extensions as needed.

This ontology defines the core model of OBOE and is imported automatically by the standard oboe ontology (above). This ontology includes definitions for observations, measurements, entities, characteristics, protocols, and context. The ontology also includes specific structures for defining units as well as for asserting context relationships as part of measurements (e.g., that an observation was made of an entity when that entity was "located in", was a "part of", etc., some other entity).  


  • Getting started with OBOE (coming soon!)
  • Basic OBOE concepts (coming soon!)
  • Basic modeling patterns in OBOE (coming soon!)
  • Advanced modeling patterns in OBOE (coming soon!)
  • Best practices for creating OBOE extensions (coming soon!) 


For more information on contributing to the development of OBOE or developing OBOE extensions, please contact the Semtools development team ( 


  • Chad Berkley (NCEAS)
  • Shawn Bowers (Gonzaga University)
  • Huiping Cao (New Mexico State University)
  • Matthew Jones (NCEAS)
  • Sergey Krivov (University of Vermont)
  • Ben Leinfelder (NCEAS)
  • Bertram Ludaescher (UC Davis)
  • Joshua Madin (Macquarie University)
  • Margaret O'Brien (UC Santa Barbara)
  • Deanna Pennington (University of New Mexico)
  • Mark Schildhauer (NCEAS)
  • Ferdinando Villa (University of Vermont)
  • Richard Williams (Microsoft Research)
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