  Museum collection strategies are governed by a variety of factors, including
topical focus, acquisition funds, availability of works in the art market,
donations and specific coincidental opportunities. Yet, it remains unclear if
more fundamental collection patterns emerge, exist, and are shared between
museums, which could for example allow an established artist to estimate when a
contemporary art museum would acquire their works. Here we collect and analyze
data from 12 European contemporary art museums, taking into account artwork
creation dates, collection acquisition dates, and the associated artist age at
both points in time. From this simple quantitative construct we are able to
reveal a striking gradient of museum profiles at the aggregate level. This lag
can function to constitute a macroeconomic index of "mean museum collection
lag", ranging from 3 years in the most dynamic cases (Kiasma) to 33 years in
the most established institutions (Reina Sofia). Meanwhile, on the granular
level, plotting artist age over collection year, and using artist-age vs
artwork-collection matrices, a detailed picture becomes evident, where
individual museums are characterized by shared patterns and a rich
heterogeneity of ideographic details. Regularities include continuous
acquisitions, systematic acquisition of older materials over time, and brief
bursts, where whole oeuvres of individual artists join specific collections.
Hence, we are able to shed light on the detailed collection history of museums,
transcending the anecdotal nature of art historical storytelling via the
provision of a quantitative context. Our approach of cultural data analysis
combines expertise in art, art history, computational social science, and
computer science. Our joint perspective builds a bridge between and serves an
audience of museum professionals, art market actors, collectors, and individual
artists alike.
