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| - There is some question as to what types of ontologies are required for topical annotations and signature annotations. There may be one overall ontology, in which both styles of annotation draw terms from, or it may be convenient to have separate ontologies for each style. The ontology for topical annotations may be inherently more general, representing one or more simple classification axes that allow users to label actors and data with relevant terms. To illustrate, an actor that calculates the Shannon-Weiner index might be labeled as a "BiodiversityIndex" and a model that generates spatially explicit maps of species distributions might be labeled as a "SpatialSpeciesDistributionModel."[1] The signature ontology would specifically be used to label the semantic types of data that are contained within a data set or that flow between two or more actors. Thus, this ontology would contain terms that are concretely tied to real-world measurements as represented by data. For example, the annotation for a particular column in a biodiversity data set might be "PsychotriaLimonensisArealDensity" (it would also have a structural type describing units, etc). A particular "BiodiversityIndex" actor might take input data with the type "SpeciesArealDensity", and the ontology would allow us to deduce that the Psychotria limonensis data is semantically compatible with the actor's input requirement. |
| + There is some question as to what types of ontologies are required for topical annotations as opposed to signature annotations. There may be one overall ontology for both styles of annotation, or it may be convenient to have separate ontologies for each. The ontology for topical annotations may be inherently more general, representing one or more simple classification axes that allow users to label actors and data with relevant terms. To illustrate, an actor that calculates the Shannon-Weiner index might be labeled simply as a "BiodiversityIndex" and a model that generates spatially explicit maps of species distributions might be labeled as simply a "SpatialSpeciesDistributionModel".[1] The signature ontology would specifically be used to label the semantic types of data that are contained within a data set or that flow between two or more actors. Thus, this ontology would contain terms that are concretely tied to real-world measurements (and models) as represented by data. For example, the annotation for a particular column in a biodiversity data set might be "PsychotriaLimonensisArealDensity" (it would also have a structural type describing units, etc). A particular "BiodiversityIndex" actor might take input data with the type "SpeciesArealDensity", and the ontology would allow us to deduce that the Psychotria limonensis data is semantically compatible with the actor's input requirement.[2] |
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| - [#1] The term "SpatialSpeciesDistributionModel" is highly specialized. In practice, such terms are more likely than not described, or "built from" existing terms and ontology structures. For example, the notion of a "Model" may be explicitly captured by an ontology, where a "Model" is a composite structure having multiple parts. In this example, the term "SpatialSpeciesDistributionModel" may be explicitly defined within the ontology, or even implicitly defined by the annotation itself as being a ''Model'' that ''computes'' a ''SpatialMap'' ''from'' a set of ''SpatialDistribution'' ''of'' ''Species''. |
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| + [#1] The term "SpatialSpeciesDistributionModel" is highly specialized, and might not exist as such in an ontology. In practice, such terms are "built from" existing terms and ontology structures. In this example, the term "SpatialSpeciesDistributionModel" may be explicitly defined within an ontology as a sub-concept of one or more terms (i.e., placed within a subsumption hierarchy). For example, the term may be defined as a sub-concept of a "Model", or possibly a sub-concept of a "DistributionModel", or even a sub-concept of both a "SpatialDistributionModel" and a "SpeciesDistributionModel" (assuming these terms are present). Alternatively, an ontology may define the term "Model" as a composite structure having multiple parts (e.g., what the model takes as input and computes as output, dependencies, and so on). As such, the term "SpatialSpeciesDistributionModel" may be defined as a specialization of a "Model" structure by specializing its parts, e.g., asserting that it is a "Model" that "computes" a "SpatialMap" "from" a set of "SpatialDistribution" "over" "Species", where the terms in double-quotes are drawn from an ontology. These two approaches capture the different styles of ontology refered to above. Note that the latter is more precise, and potentially more appropriate for signature annotations because it "breaks" the term into input and output parts. |
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| + [#2] Note that in this case, it is also common that two columns are used to represent a species' areal density (one for the species in question, and another for its areal density value), resulting in a much more complex annotation (i.e., stating that the species in one column has the areal density of another column), but via the annotation and the ontology, we can still deduce the compatibility. |
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