SEEK Observation Ontology

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Intended audience

This document is intended for SEEK and Kepler developers. It is a DRAFT DESIGN DOCUMENT and does not reflect functionality as it currently exists in Kepler or SEEK. Comments and feedback are appreciated.

Core principles

This description reflects the agreement reached at the San Antonio KR meeting. The core Observation Ontology is referred to as OBOE in the following only for reference and with no pretense of proposing a name.

(to be written)

Abstract overview of the annotation process

Annotation of a dataset according to OBOE starts with the instantiation of a oboe:Observation instance at the user's request. Its Observable property points initially to a new instance of the generic Observable class.

The user is then assisted through the annotation process following the pattern:

1. Define the oboe:Observable. This can be left general, or its class can be found through a lookup in the knowledge base (concept name search, ontology browsing, google-like search on annotation properties and related docs...)
2. Define one new Observation (recurse to step 1) per each trait of the observable that is measured in the dataset. This can be assisted by the ontology, filtering Observables to represent the know traits of the top-level observable. Note: hasTrait->Observable should probably be a property in oboe:Observable, to use as superproperty for "traits" in domain ontologies. No InterWiki reference defined in properties for Wiki called 'Note'!). Such observations are linked to the top-level observation through the hasObservation property. This definition goes down to the instantiation of oboe:Measurement and the definition of oboe:ObservedDimensionality.
3. Define one new Observation (recurse to step 1) per each context of each trait represented in the dataset. Interface assists by predefining common contexts (time, space) and preloading templates relative to the correspondent Observables. The semantics of the specific observables guides the definition. Measurements and dimensionality may be defined as in step 2 if the semantics of the context requires it.
4. Per each context defined, define the mapping between the Observation representing the context and the oboe:Measurement entered for the trait contextualized. This process must be defined (see examples).

Annotation user stories

This section contains examples of annotation of hypothetical datasets, detailing the user steps according to the "grammar":

user_story := (user_step)*

user_step := (System_question System_example Answer_pattern)

• LeafBiomassDataset example