September 28, 2023


Make Some Fun

98/ About samples and numbers in artwork historical past

4 min read

“There Will Be Numbers” Andrew Piper (1)

Any (digital) artwork historic assortment is made up of samples of an indefinite inhabitants of artists and their artworks. Sampling in artwork historical past is rarely ‘at random’, however is at all times a ‘handy sampling’, with a bias’ since info sources are endlessly restricted. Subsequently, analysing samples is important in artwork historic analysis.

On this publish, two equal however unbiased samples of French artists are examined on the nominal, ordinal and interval stage. They’re extracted from the long-term challenge of the Iconography of Venus from the Center Ages to Fashionable Occasions (2). The evaluation demonstrates how the temporal distributions of the artists are considerably completely different in each samples. 

The evaluation of the samples

 Pattern 1 of 386 artists, and Pattern 2 of 669 artists, are chosen datasets of French artists restricted in alphabetical order by letters A, B, C, D of their surnames. The datasets comprise additionally the given names, the gender, dates and locations of start and loss of life or, no less than, the yr and place of exercise as identified. Pattern 1, represents 39,5% of the complete dataset of 977 artists, compiled in 2004-2008 and revealed within the Topical Catalogue ‘The French Venus’ Vol. 2.1 in 2009 (3). Pattern 2 is representing 40,3% of the provisional dataset of 1658 artists, compiled in 2009-2021 and revealed in ‘The French Venus model 2.1.3’ in April 2021 (4). Thus their relative dimension with respect to the complete datasets is equal, although each samples differ largely in dimension. Moreover, their numbers per letter, expressed as relative percentages % (i.e. 10,6 33,4 28,8 27,2 and 12,4 32,4 27,6 27,6 respectively), affirm the equivalence of each samples on the ordinal stage of measurement.

The evaluation on the interval stage of measurement is made with the start date of the artist for the time-frequency distribution in 20 intervals of 25 years from 1500 to 1999 (Fig. 1).

Fig. 1

The massive discrepancy between each samples is outstanding. It may be higher proven within the graph of relative frequencies in %, given the completely different sizes of the samples (Fig. 2). Logically, the mixed Pattern (1+2) may be thought-about because the much less biased and exhibits clearly that the temporal distribution of artists is just not accurately represented in Pattern 1 from interval 1824-50 onwards. 

Fig. 2

Additionally the sharp drop of variety of artists in interval 1900-24 is noteworthy and was not detected in Pattern 1.

Word that this time-frequency distribution relies on the start date of the artist and, clearly, doesn’t symbolize the distribution of the whole variety of artists (depicting Venus) energetic in every interval. Assuming a coaching interval of 20 years and an energetic life-span of 40 years, the whole variety of artists energetic in every interval may be estimated as about double the given figures (5). 

The function of feminine artists

An evaluation on the nominal stage, i.e. the gender, reveals a really small variety of 19 feminine artists in Pattern 1 and a a lot larger variety of 87 feminine artists in Pattern 2

Fig. 3

This time-frequency distribution discloses the function of the feminine artists within the bigger relative variety of artists of Pattern 2 within the 19thand 20th centuries (Fig. 2).


There’s a variety of discuss concerning the rising digitalisation of art-historical archives (6). This publish demonstrates with quantitative knowledge the variations between two samples of artists in a specific case associated to the intervals of compilation: 2004-2008 and 2009-2020, respectively. The grouping of each samples ends in a pattern with a smaller bias.

Amongst many accessible WEB developments, one in every of particular curiosity for this case is the very massive database of the ‘Salons et expositions de teams 1673-1914’with greater than 210,000 notices about artists and their exhibited works (7). Most feminine artists in Pattern 2 have been retrieved from these Salons. 

The complete artwork historical past is greater than what’s present in classical artwork historic books or in Google ‘Artwork & Tradition’, particularly with respect to the gender concern of artists. It’s time for social decanonization in artwork historical past: “a strategy of customers’ interactions with cultural content material on the net or by way of digital means (…) with the potential to redirect consideration towards a much wider spectrum of cultural manufacturing than was thought-about by historic canons.“ (Nuria Rodríguez-Ortega, Might 11, 2018).(8).


  1.  Andrew Piper “There Will Be Numbers” Journal of Cultural Analytics, Might 23, 2016 DOI: 10.22148/16.006
    AndrewPiper, Division of Languages, Literatures, and Cultures at McGill College, is editor of the Journal of Cultural Analytics

    A Digital Thematic Analysis Assortment contributing to distant viewing, macroanalysis and the quantitative strategy in artwork historical past: ‘Venus Iconography’. Six Topical Catalogues have been revealed, with 19,300 artworks by 6628 artists, categorized in 18 major matters.


3. Topical Catalogue ‘The French Venus’ Vol. 2.1  counts 2,997 artworks of 997 recognized French artists and is accessible at
4. The revision of Vol. 2.1 is a long-term challenge and revealed in subsequent variations. This version 2.1.3 consists of now 5,033 artworks of 1,658 artists. The compilation is up to date for 1055 artists with surname within the alphabetical checklist [A,B,C,D]. They symbolize already 64% of the present checklist of artists. 
5. This intrinsic downside has been mentioned in publish of June 29, 2013  Statistics in Art History (V): Drowning in numbers of artists’ 
6. See publish of Might 9, 2020 ‘On-line sources of French artwork for assortment freaks, a sequel’ 
7. See publish of April 27, 2012 Exhibition Catalogues in the Digital Age 
8. See publish of  Might 30, 2018  ‘Meta-Analysisin Digital Artwork Historical past (IV): canonization, decanonization, community evaluation’


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