5. Metrics and narratives

Two components frequently included in collection descriptions are quantitative metrics (e.g. the precise or estimated number of objects or taxa) and richer narratives about the collection and its history. To represent these, LtC has adopted the MeasurementOrFact class used in Darwin Core and ABCD, and added an ltc:measurementFactText property. This property is for holding the richer text narratives in collection descriptions and, if required, categorising them using the measurementType property. This might be used, for example, to define and store a historical narrative and brain-dump of notes from a retiring curator about a collection separately. It also separates the text descriptions from quantitative measures stored in the measurementValue property, which is intended to make validation and programmatic aggregation and computation on the measurementValue property more straightforward.

"ObjectGroup": {

    "collectionName": "Collection of the Natural History Museum, London",

    "hasMeasurementOrFact": [
    {
        "measurementType": "Object count",
        "measurementValue": "72190070"
    },
    {
        "measurementType": "Collection history",
        "measurementMethod": "Text narrative",
        "measurementRemarks": "Text derived from Wikipedia",
        "measurementFactText": "The foundation of the collection was that of the Ulster doctor Sir Hans Sloane (1660–1753), who allowed his significant collections to be purchased by the British Government at a price well below their market value at the time. This purchase was funded by a lottery. Sloane's collection, which included dried plants, and animal and human skeletons, was initially housed in Montagu House, Bloomsbury, in 1756, which was the home of the British Museum."
    }
    ]
}

Figure 17: JSON example of a quantitative metric and textual narrative using the MeasurementOrFact class.

Similarly to the other generic classes described earlier, the MeasurementOrFact class can be associated with many of the other classes in the standard to add defined, dynamic properties, and is also repeatable.

It’s also possible to use the MeasurementOrFact class to qualify or quantify relationships between other classes in the standard, in conjunction with the ResourceRelationship class. This is covered in more detail in the later section on modelling approaches.

5.1 Metric examples

There are no prescribed metrics included in the standard. It is hoped that over time data requestors/aggregators will define the metrics that they require using the standard and its MeasurementOrFact class. Data providers can then use these as recipes to follow to generate the information needed to facilitate easier and more automated sharing and comparison. The intent being that over time libraries of standard metrics can be published and shared. For example, BioSchemas provides a library of usage profiles: https://bioschemas.org/profiles.

measurementType	Metric Description
object count	The total number of specimens and/or items. If the metric is attached to an object group then the count is of the collection being described. If the metric is attached to the Institution then it is the overall count for that institution.
digitisation level percentage	The percentage of the whole collection being described, that is “digitised”. Explicitly state what is meant by digitised - imaged and/or a database record (metadata) exists etc. Could be used in combination with the object count metric.
digitisation level count	An actual number of digitised records in the collection being described [define digitised]
imaged level percentage	The percentage of the collection described in the record that has an image. Could be used in combination with the object count metric.
imaged level count	An actual number of digitised records with images
georeferenced level percentage	The percentage of the collection described in the record that has verified Lat Lon coordinates. Could be used in combination with the “object count” metric.
georeferenced level count	The actual number of records that have verified Lat Lon coordinates
taxonomic rank	Count of the taxa at the rank indicated in measurementFactText. Do not abbreviate the rank.
storage volume	The cubic volume of the record (Institutional or Collection). Could be used in combination with the object count metric.
storage footprint	The area of the record (Institutional or Collection). Could be used in combination with the object count metric.

Table 7: Example Latimer Core simple metrics in tabular format (CSV file in the Latimer Core repo)

Metric Description	measurementType
https://github.com/tdwg/mids/blob/working-draft/current-draft/MIDS-definition-v0.15-29Jul2021.md#44-information-elements-expected-at-mids-level-0	MIDS-0 object count
https://github.com/tdwg/mids/blob/working-draft/current-draft/MIDS-definition-v0.15-29Jul2021.md#43-information-elements-expected-at-mids-level-1	MIDS-1 object count
https://github.com/tdwg/mids/blob/working-draft/current-draft/MIDS-definition-v0.15-29Jul2021.md#43-information-elements-expected-at-mids-level-2	MIDS-2 object count
https://github.com/tdwg/mids/blob/working-draft/current-draft/MIDS-definition-v0.15-29Jul2021.md#43-information-elements-expected-at-mids-level-3	MIDS-3 object count

Table 8: Example MIDS metrics in tabular format (CSV file in the Latimer Core repo)