Information content entities
An ‘information content entity’ (ICE) is a ‘generically dependent continuant’ (GDC) that ‘is about’ some thing. Because it is a GDC, an ICE can be copied from one ‘material information bearer’ to another. Examples: an “‘age since planting measurement datum’ ‘is about’ some ‘Spermatophyta’” (among other things); a “‘minimal inhibitory concentration’ ‘is about’ some ‘dose response curve’”, another ICE. Aboutness axioms should reinforce the content of term definitions.
The ‘information content entity’ ‘data item’ class holds singular entities or collections of entities that specifically record inputs or outputs of processes / equipment / human interaction. OBI distinguishes the following types of data items, usually called “datums”, as follows:
- A ‘measurement datum’ class names and models the datum outputs of an assay, and their contextual semantics.
- A ‘settings datum’ class which enables modeling an apparatus control input.
- A ‘predicted data item’ class that applies to output of a ‘prediction’ process.
A data item (aka datum) may have an associated ‘value specification’ that holds a numeric or categorical value, or may have a textually-encoded, parsable ‘has representation’ data property that points to any XSD Literal value such as the string “20g” or “Every thursday”. More on this to come.
(Diagram: data-ice.drawio)
An ‘information content entity’ (ICE) is a ‘generically dependent continuant’ (GDC) that ‘is about’ some thing. Because it is a GDC, an ICE can be copied from one ‘material information bearer’ to another. Examples: an “‘age since planting measurement datum’ ‘is about’ some ‘Spermatophyta’” (among other things); a “‘minimal inhibitory concentration’ ‘is about’ some ‘dose response curve’”, another ICE. Aboutness axioms should reinforce the content of term definitions.
The ‘information content entity’ ‘data item’ class holds singular entities or collections of entities that specifically record inputs or outputs of processes / equipment / human interaction. OBI distinguishes the following types of data items, usually called “datums”, as follows:
- A ‘measurement datum’ class names and models the datum outputs of an assay, and their contextual semantics.
- A ‘settings datum’ class which enables modeling an apparatus control input.
- A ‘predicted data item’ class that applies to output of a ‘prediction’ process.
A data item (aka datum) may have an associated ‘value specification’ that holds a numeric or categorical value, or may have a textually-encoded, parsable ‘has representation’ data property that points to any XSD Literal value such as the string “20g” or “Every thursday”. More on this to come.
(Diagram: data-ice.drawio)