A pan-European dataset revealing variability in lithic technology, toolkits, and artefact shapes ~15-11 kya

Abstract

Comparative macro-archaeological investigations of the human deep past rely on the availability of unified, quality-checked datasets integrating different layers of observation. Information on the durable and ubiquitous record of Paleolithic stone artefacts and technological choices are especially pertinent to this endeavour. We here present a large expert-sourced collaborative dataset for the study of stone tool technology and artefact shape evolution across Europe between ~15.000 and 11.000 years before present. The dataset contains a compendium of key sites from the study period, and data on lithic technology and toolkit composition at the level of the cultural taxa represented by those sites. The dataset further encompasses 2D shapes of selected lithic artefact groups (armatures, endscrapers, and borers/perforators) shared between cultural taxa. These data offer novel possibilities to explore between-regional patterns of material culture change to reveal scale-dependent processes of long-term technological evolution in mobile hunter-gatherer societies at the end of the Pleistocene. Our dataset facilitates state-of-the-art quantitative analyses and showcases the benefits of collaborative data collation and synthesis.

Fig. 1

Spatiotemporal characteristics of the dataset. (a) Geographic overview of macro-regions (boxed numbers) and their corresponding key sites (small numbers); 1 = Southern Scandinavia (SS), 2 = Lithuania (LT), 3 = Northern Germany (NG), 4 = Britain (GBS), 5 = Poland (PL), 6 = Belgium and Southern Netherlands (BSN), 7 = Bohemia and Moravia (BOMO), 8 = Southern Germany (SG), 9 = Northern France (NF), 10 = Austria, Slovakia and Hungary (ASH), 11 = Switzerland (CH), 12 = Northeastern Italy (NEI), 13 = Western France (SWF), 14 = Cantabrian Spain (IBC), 15 = Mediterranean Iberia (IBM), 16 = Atlantic Iberia (IBA). (b) Time slices I to IV in relation to established chronological schemes in Late Glacial/incipient Holocene archaeology. (c) Number of expert-submitted named archaeological cultures (NACs) per time slice and macro-region.

Fig. 2

Workflow of collaborative data compilation and synthesis. Numbers indicate successive stages of data processing, from definition and preparation to validation.

Fig. 3

Trait structure of main data domains and site-specific metadata. (a) Toolkits data domain (I). (b) Technology data domain (II). (c) Metadata.

Fig. 4

Folder tree structure of the data repository.

Fig. 5

Overview of lithic artefact outlines in the dataset. (a) Number of digitized armature outlines (AR) for each time slice (left) and their distribution across individual macro-regions (right). (b) Number of digitized endscraper outlines (ES) for each time slice (left) and their distribution across individual macro-regions (right). (c) Number of digitized borer/perforator outlines (BR) for each time slice (left) and their distribution across individual macro-regions (right). Note that the borer dataset includes incomplete artefacts.

Fig. 6

Data quality. (a) Quality scores computed for each archaeological key site (see text for explanation) from 0 = poor to 6 = excellent. (b) Detailed break-down of site-specific quality scores in relation to time slices and individual macro-regions (Supplementary Table 4). Black circles indicate median values computed for each macro-region within a given time slice.

Fig. 7

Overview and exemplification of lithic data structure. (a) Pan-European scale of observation with all 16 macro-regions (boxed numbers) and their associated archaeological key sites (small numbers). (b) Macro-regional scale of observation (example: Poland); (c) Macro-regional data matrix of observations on toolkit composition (I) and technology (II) coded as presences/absences (na = information not available in the literature) and sorted according to time slices. (d) Digitized 2D outlines of lithic armature within a selected time slice (example: TS IV) of the same macro-region. This data structure facilitates the diachronic and synchronic analysis of within and cross-domain lithic variation.