4D Research Lab degrees of certainty definition v.1

Tijm Lanjouw, Jitte Waagen

February 2020


For 3D visualizations we apply a classification of 6 classes, listed below. Classes are defined based on the principle of ‘potential variability’. Potential variability is a subjective assessment of the degree of possible variation within a model part. It is an indication of the reliability of sources or certainty of our knowledge about how a certain object or part looked like.

Each project may include a specific application of this classification, with particular definitions for each class. An example is that class definitions may reference particular sources (parallels, depictions) used repeatedly for various elements in the model.

Number of classes

We believe in a limited number of ordinal qualitative classes, with the main aim of clarity and legibility. It is also to avoid the creation of small meaningless classes, that may start to resemble a quantitative scale; the qualitative arguments must always be the main focus. We do not recommend using subclasses of uncertainty (i.e. 2.1-2.5) for this reason.


In case of typical issues such as ambiguity, for example contradicting sources, possibly leading to a weight-of-argument formula, this gets solved in the text/database.


Our classification of uncertainty can apply to any scale, from the individual building block (i.e. a brick) to a complete house. In the resulting models, one can introduce various grain sizes for attributing uncertainty, i.e. dealing with walls, windows and roofs separately, but also associate an uncertainty index with a complete house (this is analogous to how we view annotations must be incorporated, as they can refer to various grain sizes, i.e. granularity; in fact, uncertainty is a subclass of annotation).


The various indications of uncertainty of individual building blocks can aggregate into a cumulative certainty, this is exactly why there are different grain sizes.


Simple indications of the certainty classes listed below may be incorporated into the model as colour codes. The justification and reasoning go into the report, the accompanying text and/or database.

Modelling should take into account the integration of colour coding. To accomplish this, two general methods are proposed: 1) keep model parts with a different certainty classification apart as separate (mesh) objects in the 3D model. The colour coding must be applied as separate material to the corresponding model parts. 2) if model parts cannot be kept separate, but must be integrated in single objects, separate colour coded textures are made for these objects.

Degrees of Certainty

Certainty Class









Scanned remains


Quite certain


Logical extension

Missing part of relatively complete


Moderately certain


Close parallel

Same type, direct relation


Not so certain


General parallel

Same type, indirect relation


Quite uncertain


Historic context

General stylistic traditions


Very uncertain

Very high


Constructional argument


  • Certain, no potential variability: empirically attested. Examples: physical archaeological remains, or high resolution photographs.
  • Quite certain, low potential variability: object/element must have been present by logical extension of class 1), or depicted on highly reliable depiction, colour and shape of infill certain. Examples: the other half of a symmetrical sculpture, a gap in a continuing wall, or an architectural drawing.
  • Moderately certain, limited potential variability: close parallel or good historical depiction; same object type but uncertainty about exact colour or shape, so limited potential variability. Examples: another similar sculpture from the same artist, a house from the same block, artistic rendering of the actual object.
  • Not so certain, considerable potential variability: general parallel; same object type but only contextual/from a different source. Examples: a sculpture or house from the same period and region, a painting depicting a scene from that city with likely similar houses, historical sketches or generalised depictions of the actual object.
  • Quite uncertain, high potential variability: historic context; no similar object types, but an object with a similar function from the same period and region. Examples: general stylistic sculpture traditions such as Archaic or Classical, or general table ware from the 17th century.
  • Very uncertain, very high potential variability: no direct evidence that the object was ever present, existence is purely theoretical. Examples: argument based on constructional reasoning.