The Dataset for Tracing Invisible Hearths and Daily Routines through Carbonized Plant Remains and Geochemical Signals in an Early Iron Age Smithy at Pungrt Hillfort, Slovenia

(1) Overview

Context

At the Pungrt Hillfort – an early urban settlement in central Slovenia occupied from the 8th/7th century BC to the 2nd century AD (Figure 1) [1] – a smithy has been discovered in one of the Early Iron Age houses: Building 24 (Figure 2). The remains excavated in the building’s Late Hallstatt construction phase IIb2, dated to the late 6th and early 5th century BC, were inconspicuous and gave no hints of its function. However, the post-excavation micro-refuse analysis revealed a blacksmith’s workshop within the building [2]. Even though high-temperature fires are integral to the blacksmith’s working process, no remains of the fire installation were identified, which is a relatively common problem [3, 4]. In the effort to reconstruct the location of the smithing hearth, we compiled the presented data on charred plant remains, which are primarily related to the use of fire within the building, especially hearth rake-out and redistribution through trampling and sweeping after they have been removed from the hearth [e.g. 5, 6, 7]. We also supplemented the archaeobotanical data with selected geophysical and geochemical parameters that could aid interpretation. The data is published online [8] and underlies the results presented in Gruškovnjak et al. 2026 [9].

Figure 1

Figure 2

(2) Methods

Steps

Field sampling

Sampling for the micro-refuse and sediment analyses was systematically carried out in a grid of 50 × 50 cm or 0.25 m² quadrants (Figure 3). Each quadrant’s entire surface was troweled to obtain a bulk sediment sample (ca. 1L) from the occupation surface. This way, 79 samples covering ca. 20 m² were obtained from the floor inside the building and from the adjacent street.

Figure 3

In addition, eight bulk samples collected from the natural soil sequence underlying the archaeological deposits on the first terrace (see Figure 2, location of the control samples) were selected as suitable controls for this project. The natural soils provided a baseline for comparing the area of high anthropogenic impact with the site’s natural background.

The coordinates of all samples were measured with a total station.

Flotation and wet-sieving

Bulk samples from the occupation surfaces were first air-dried in a laboratory oven at 35°C. The samples were then split into two halves. The first was used to extract the light- and heavy-fraction materials from the sediment matrix, and the other half was retained for sediment analyses. The volume and weight of the samples were recorded before they were processed by bucket flotation and wet-sieving to extract the light and heavy fractions, which were collected on a 0.5 mm sieve. Altogether, 36.09 litres of sediment were processed in this way.

Light fraction examination

The dried organic samples from the 0.5 mm sieve were examined and sorted under a Leica MZ75 stereomicroscope at 6.3–50 × magnification. All recognisable organic remains larger than 0.5 mm were sorted out and divided into the groups of identified (ID) carbonised plant macro-remains (i.e. seeds and fruits, cereal chaff, charcoal), micro mammal finds (bones, teeth, coprolites), fish finds (i.e. scales) and other remains (e.g. of possible carbonised cereal food, tar, fungal spores, molluscs, insects and reptiles). The rare non-carbonised plant items (i.e., needles, fruits) were excluded as contaminants introduced during outdoor sampling and processing (flotation and wet sieving) due to their obviously recent appearance [e.g., 5].

Archaeobotanical analysis

Seeds/Fruits/Chaff

Plant macro-remains (e.g., Figure 4) were identified using the reference collections of seeds, fruits, cereal chaff, charcoal, and wood at the Institute of Archaeology ZRC SAZU [12], and with the help of specialised literature [13, 14, 15, 16, 17, 18]. Plant nomenclature follows Zohary and Hopf [19] for cultivated plants. Slovenian plant nomenclature and ecological characteristics follow Martinčič et al. [20].

Figure 4

Whole seeds and larger seed fragments of each species were counted, i.e. measured as the Number of Identifiable Specimens (NISP). In contrast, the presence of tiny, barely identifiable fragments of each species was scored as 1 NISP. Charcoal fragments ranging from 0.5 to 4 mm in size were assessed only in terms of relative abundance. They were placed in test tubes and divided into six relative abundance classes based on visual estimation of how full the test tubes were: absent (scored 0 NISP), very few (scored 10 NISP), few (scored 20 NISP), frequent (scored 30 NISP), abundant (scored 40 NISP) and very abundant (scored 50 NISP) (the scoring was determined by counting a selection of representative samples). After identification and quantification, the numbers of seeds/fruits/chaff and charcoals counted or estimated were converted into concentrations per litre of sediment sample to facilitate comparison of the results.

Hazelnut shell remains were additionally examined to determine whether raw nutshell fragments were burned after consumption or during roasting of whole hazelnuts. Following the criteria of López-Dóringa [21], the pericarp fragments were divided into two groups: the first one with rough edges of pericarp fragments indicating exposure to fire after they had been broken, and the second one with smooth vitrified edges, suggesting they had been broken after charring.

A total of 590 carbonised seeds/fruits were identified in the 79 collected samples. Besides the visualisations obtained through spatial analysis (see below), the results were also presented in three other supplementary ways [see 8]. The first was ubiquity, which compared the presence of individual plant taxa across samples to indicate the percentage of samples in which each taxon was present (for example, if the taxa were present in all samples, ubiquity was 100%). The second was the maximum concentration of individual cultivar taxa in samples. The third was using boxplots to compare the distributions of concentration values across taxa within samples and contexts. In all three cases, the contexts of Building 24 relative to the adjacent Road 1 and of Room A relative to Room C within the building were compared.

Charcoal

Because of the small size of charcoal fragments, the anthracological analysis was performed only on a selection of 16 samples containing larger pieces (2–4 mm). These were still very small and extremely fragile, making the three wood anatomical sections (transversal, tangential, and radial) needed to determine the wood species unobtainable in many cases. The identifications are, therefore, inconclusive (i.e. with “cf.” meaning possibly) or cannot go beyond the level of deciduous/conifer tree sp. In the analysis, the Nikon Eclipse ME 600 light microscope was used, along with the 6.3–50 × Leica MZ75 stereomicroscope, a reference collection, and specialised literature [14].

Cereal food

Fragments of unidentified carbonised organic material (Figure 5: A), suspected to be charred food residues, were also present in the samples. Because of their scarcity and varying fragment sizes, they were only noted as present (scored as 1 NISP). Three fragments of this type of material (Figure 5: B–D) were selected for scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDS) analysis with ZEISS CrossBeam 500 with Octane Elite EDAX. Descriptions and interpretation of their microstructure followed the methodology described in González Carretero, Wollstonecroft, and Fuller [22].

Figure 5

Sediment analysis

The air-dried bulk sediment samples were gently ground in a mortar and pestle and sieved to 2 mm (SIST ISO 11464:2006). Magnetic susceptibility was measured in 10 mL plastic pots using a Bartington MS3 magnetic susceptibility metre with an MS2B dual-frequency sensor, set to the low-frequency setting [23]. Subsamples used for the analyses of total carbon and carbonate content were further homogenised and sieved to 160 μm. Soil texture was determined using the sedimentation pipette method (SIST ISO 11277:2011) and classified according to the American Soil Texture Classification. Active (pH_H2O) soil acidity was measured electrometrically in a soil suspension prepared at a 1:5 (v/v) soil-to-deionised water ratio (SIST ISO 10390:2005). Carbonates were measured with the gas-volumetric Scheibler method after HCl (10%) application (SIST EN ISO 10693:2014). The total carbon and nitrogen content were determined with dry combustion and spectroscopic analysis of the produced CO₂ using Vario Max CN Element Analyser (SIST ISO 10694:1996). Plant available phosphorus and potassium were measured after extraction with ammonium lactate (ÖNORM L 1087).

Spatial analysis

The spatial distribution analysis was performed in a Geographic Information System (GIS) environment and in Surfer, using concentration-per-litre values for archaeobotanical remains.

The GIS analysis was used to display the results at the resolution of the original collection grid (e.g. Figure 6: A, C). For the visualisation of quantities, we used gradual symbols and the natural breaks classification method. The number of classes was selected for each category individually. We selected at least the number of classes needed to display class 0 individually, and more if needed, to better distribute the value ranges (e.g., Figure 6: B).

Figure 6

To obtain a high-resolution density plot attempting to reconstruct the actual distribution sampled, we used kriging interpolation in Surfer 16 software (e.g., Figure 6: B, D), as suggested by Ullah, Duffy, and Banning [24]. The display acquired in ArcGIS guided the selection of minimum values to ensure that the areas with zero values were represented realistically. The intervals were selected for each category individually to display the patterns necessary for interpretation clearly.

(3) Dataset description

The dataset includes the following list of folders (indicated with a symbol ) containing listed or described files:

• 1. Sampling grid

  • 1.1. Floorplan photo

               Orthophoto of the sampled context of Building 24 and Road 1 (file types: JPG, TFW, TIF, XML).

  • 1.2. Grid shapefiles

               Shapefiles with the sampling grid (O24_grid) and grid centroids (O24_grid_point) (file types: CPG, DBF, PRJ, SBN, SBX, SHP)

  • 1.3. Figures

               Figures of the orthophoto with overlain sampling grid and/or excavated features (file type: JPG). Three different versions include: (1) numbered grid and two features (vessel built into the floor and charcoal layer, see Figure 2); (2) numbered grid (Figure 3); (3) unnumbered grid.

• 2. Light fraction

  • 2.1. Identification

               Table 2.1. Raw Data (file type: XLSX): counts of identified light fraction materials (archaeobotanical and faunal)

  • 2.2. Photographs

               Stereomicroscope photographs of select identified materials (Figure 4) (file types: JPG, LAN, XML).

    • 2.2.1. Fruits or seeds

                 Echinochloa crus-galli

                 Fabaceae

                 Hordeum vulgare

                 Juglans regia

                 Lens culinaris

                 Panicum miliaceum

                 Pisum sativum

                 Setaria cf italica

                 Triticum cf spelta

                 Triticum monococum

                 Triticum sp

    • 2.2.2. Cereal food

  • 2.3. Archaeobotanical analysis

               Table 2.3.1 (file type: XLSX): A list of identified plant taxa grouped into five economic-environmental plant groups.

               Table 2.3.2 (file type: XLSX): Ubiquity of plant taxa: comparison between Road 1 and Building 24 and between Rooms A and C within the building.

               Table 2.3.3 (file type: XLSX): Maximum concentrations of identified macro remains of individual cultivar taxa in a particular sample and Number of samples (percentages) containing individual cultivar taxa: comparison between Road 1 and Building 24.

               Table 2.3.4 (file type: XLSX): Maximum concentrations of identified macroremains of an individual cultivar taxon in a particular sample and Number of samples (percentages) containing individual cultivar taxa: comparison between Rooms A and C.

               Table 2.3.5 (file type: XLSX): Boxplots comparing distributions of concentration values for various groups of taxa between samples and contexts (Road 1, Building 24, Room A and Room C).

               Table 2.3.6 (file type: XLSX): Evaluation of break edge surfaces of Corylus avellana pericarp fragments.

  • 2.4. Anthracological analysis

               Table 2.4 (file type: XLSX): Results of anthracological analysis of 16 selected samples.

  • 2.5. Cereal food analysis

                 Folders with SEM microphotographs and EDS measurements of three selected cereal food samples (file types: JPG, DOCX) (Figure 5).

            IG A 264

            IG A 266

            IG A 267

               Table 2.5 (file type: XLSX): Microstructure description and interpretation for three selected cereal food samples.

• 3. Sediment analysis

           Soil parameters (file type: DOCX): Description of sediment analysis results (pH, organic matter, nitrogen, phosphates, potassium, carbonates) in Building 24 and Road 1 and their comparison with control samples.

           Table 3.1. (file type: XLSX): Sediment analysis (pH, organic matter, nitrogen, phosphates, potassium, carbonates and magnetic susceptibility) results for Building 24 and Road 1.

• 4. Spatial analysis

  • 4.1. Input tables

           Table 4.1.1 (file type: XLSX): Archaeobotanical analysis results used in GIS and Surfer. The X and Y columns give the coordinates of the grid centroids.

           Table 4.1.1 (file type: XLSX): Sediment analysis results used in GIS and Surfer. The X and Y columns give the coordinates of the grid centroids.

  • 4.2. Archaeobotanical remains

           Spatial analysis results for individual plant groups or taxa. All folders contain subfolders, Grid and Kriging. The Grid subfolder contains the distribution displayed at the sampling grid resolution obtained in GIS (file type: JPG or PDF). The Kriging subfolder contains a high-resolution spatial distribution obtained with kriging interpolation in Surfer software and a kriging analysis report (e.g. Figure 6: A–B).

    • 4.2.1. Cultivars (LF1)

    • 4.2.2. Cultiv. Cereals (LF1_1)

    • 4.2.3. Cultiv. Millets (LF1_2)

    • 4.2.4. Cultiv. Legumes (LF1_3)

    • 4.2.5. Weeds (LF2)

    • 4.2.6. Meadow (LF3)

    • 4.2.7. Lakeshore (LF4)

    • 4.2.8. Possibly Gathered (LF5)

    • 4.2.9. Cereal food (LF6)

    • 4.2.10. Charcoal (LF7)

    • 4.2.11. Noncultivated (LF9)

    • 4.2.12. All seeds fruits (LF10)

    • 4.2.13. Corylus all

    • 4.2.14. Corylus burnt

    • 4.2.15. Corylus roasted

    • 4.2.16. Juglans regia

    • 4.2.17. Rubus idaeus

  • 4.3. Soil parameters

               Spatial analysis results for individual parameters obtained in sediment analysis. All folders contain subfolders Grid and Kriging. The Grid subfolder contains the distribution displayed at the sampling grid resolution obtained in GIS (file types: JPG or PDF). The Kriging subfolder contains a high-resolution spatial distribution obtained with kriging interpolation in Surfer software and a kriging analysis report (file types: JPG, GSR2, docx) (e.g. Figure 6: C–D).

    • 4.3.1. Magnetic susceptibility

    • 4.3.2. pH

    • 4.3.3. Organic matter

    • 4.3.4. Plant-available phosphorus

    • 4.3.5. Nitrogen

    • 4.3.6. Potassium

(4) Reuse potential

The data constitute an invaluable comparative dataset that can be reused in archaeobotanical, archaeometallurgical, household, and methodological studies. It allows comparisons with other smithies and household contexts, as well as comparisons of types of archaeobotanical data obtained by different sampling strategies. In addition, it can facilitate validation of results published in the related research paper [9].

Author contributions

Luka Gruškovnjak: conceptualisation, formal analysis, funding acquisition, methodology, visualisation, writing – original draft, writing – review & editing.

Tjaša Tolar: formal analysis, visualisation, writing – original draft, writing – review & editing.

Agni Prijatelj: conceptualisation, formal analysis, methodology, visualisation, writing-original draft, writing–review & editing.

Barbara Šetina Batič: formal analysis, visualisation.

Petra Vojaković: conceptualisation, visualisation, writing – review & editing.

Helena Grčman: formal analysis, project administration, resources, writing – original draft.

Matija Črešnar: conceptualisation, funding acquisition, project administration, writing – review & editing.