SoilCompDB: Global soil compressive properties database. Version 1.0

Data collection and processing
Our data collection comprised published journal articles sourced from Web of Science and Scopus databases, using search terms such as 'soil precompression stress,' 'soil compression index,' 'soil compaction index,' 'soil recompression index,' 'soil swelling index,' 'soil precompaction stress,' and 'preconsolidation pressure' for articles published up to February 2022.  A total of 1235 publications were found. Duplicate records were eliminated using the Endnote Web citation management application. The remaining references were exported to Rayyan software for title and abstract screening based on predefined criteria for full-text selection.  After a careful review, we identified 128 papers where the data on soil compressive properties (precompression stress, compression index, and swelling index) were reported in numerical format or legible graphical format and considered suitable for inclusion in the database.  We employed the WebPlotDigitizer software to extract data from figures within the original publications. For each chosen study, we systematically recorded data concerning soil compressive properties and collected information on soil properties, soil conditions, site characteristics, and experimental settings. We compiled 4,743 individual data entries.
Time and place
The database includes data from 128 independent studies published between 1992 and 2021. Each study reported between 1 and 360 measurements, with a study median of 14 measurements and a mean of 38 measurements, totalling 4743 database entries. Our database includes data from 20 countries, with a significant concentration of the data originating from Brazil, followed by Germany, Switzerland, Sweden, and Denmark. The majority of the data came from arable soils, representing approximately 72% of data entries.  
Instruments
The soil compressive properties included in the database were based on soil compressive tests performed in the laboratory by uniaxial method. The procedure used for stress application on soil samples was mainly the stepwise stress application method, while the constant strain rate method was applied in few studies (less than 2% of the data). The component of the compressive curve related to the soil packing state was represented by soil bulk density, void ratio, and strain. The stress component of the curve was represented in a logarithmic form in the entirety of the database. The database also comprised eight different methods for calculating precompresion stress: Casagrande (1936), Dias Junior and Pierce (1995), Lamandé et al. (2017), Sullivan and Robertson (1996), Casini (2012), Culley and Larson (1987), Pacheco Silva (1990), Gregory et al. (2006).
Resources
Web of Science, Scopus – literature search
Endnote Web – removal of duplicates
Rayyan software – initial paper selection based on title and abstract
WebPlotDigitizer – data extraction from figures
Microsoft Access – database platform
Description of the collected data (column, unit, and description)
Sample ID-    A unique identification number assigned to each individual sample within the database                                                                        
Study ID- Identification number assigned to each research study in the database
Reference - Research paper reference
Year - Year of research paper publication                 
Language - Language of the research paper              
Soil classification (SiBCS) - Soil Classification according to the Brazilian System (SiBCS), as described in portuguese-language papers
Soil classification (original in paper) - Soil classification described in research paper 
Soil classification (convertion to Soil Taxonomy orders) -  Soil classification aligned with the Soil Taxonomy system developed by the United States Department of Agriculture (USDA)          
Location - Study location country   
Texture classification (USDA) - Soil textural classification according USDA
Texture  classification USDA (letter code) - Letter code for soil textural classification according USDA: S=sand; LS=loamy sand; SL=sandy loam; SiL=silt loam; Si=silt; L=loam; SCL= Sandy clay loam; SiCL=Silty clay loam; CL=clay loam; SC=Sandy clay; SiC=Silty clay; C=clay
Clay (USDA) - % - Soil clay content (weight based) - (<0.002 mm)                
Silt (USDA) - % - Soil silt content (weight based) - (0.002 < x < 0.05 mm, interpolated for European samples where needed using the k-nearest neighbor technique by Nemes et al. 2006) 
Sand (USDA) - % - Soil sand content (weight based)  - (0.05 < x < 2 mm, interpolated for European samples where needed using the k-nearest neighbor technique by Nemes et al. 2006)
USDA PSD interpolated - =0 if the data was NOT interpolated; =1 if the data was interpolated
Published texture class - Texture classification provided in the source publication when the values for clay, silt and sand were not available
Clay - g kg-1 - Soil clay content - original in the paper
Clay class upper boundary - µm - The clay class upper boundary informed in source publication
Silt - g kg-1 - Silt clay content - original in the paper
Silt class upper boundary - µm - The silt class upper boundary informed in source publication
Sand - Soil sand content - original in the paper
Sand class upper boundary - µm - The sand class upper boundary informed in source publication
Particle size data flag - =0 if no issues; =1 if there are issues (summing)
Sum particle size- g kg-1 - Sum of clay, silt, and sand content
Soil depth FROM – cm - When soil depth is presented as a range (e.g., 0-10cm), it indicates the minimum depth at which soil samples were collected                     
Soil depth TO – cm - When soil depth is presented as a range (e.g., 0-10cm), it indicates the maximum depth at which soil samples were collected                                  
Depth – cm -Specific depth value as presented in paper, or when soil depth is showed as a range (e.g., 0-10cm), it indicates the average depth at which soil samples were collected (e.g 5cm)                                                    
SOC - g kg-1 - Soil organic carbon content informed in research paper or soil organic carbon content calculate from soil organic matter content by multiplying by 0,58                                            
SOC converted from SOM - 1= yes for soil organic carbon derived from soil organic matter content calculations
Particle density - Mg m-3 - Soil particle density                     
Initial matric potential – hPa - Soil water matric potential before loading
log Initial matric potential - Soil water matric potential expressed by log                              
Wetness (based on initial matric potential) -  1=if initial matric potential (MP)<100 hPa; 2= if 100<=initial MP<1000 hPa; 3= initial MP>=1000 hPa
Initial gravimetric water content - g g-1 - Gravimetric soil water content before loading provided by source publication, or calculated by volumetric water content divided by soil bulk density
Initial volumetric water content - m3 m-3 - Volumetric soil water content before loading, when the soil bulk density was not reported
Initial water content data source - Graph or table from where the data was collected, or explanation on calculation used
Matric potential type - Compressive tests performed on soil samples under different conditions: 1= equilibrated at matric potential; 2= field matric potential; 3= air-dried samples                 
Initial bulk density - Mg m-3 - Soil bulk density before loading                     
Initial BD data source - Graph or table from where the data was collected, or explanation on calculation used                                                                                  
Initial volumetric water content calculated - m3 m-3 - Soil volumetric water content calculated by multiplying soil gravimetric water content by soil bulk density
Precompression stress – kPa - Precompression stress                                                                                         
Precompression stress (SD) – kPa - Standard deviation for precompression stress values reported in paper                                                                                        
Precompression stress data source - Graph or table from where the data was collected, or explanation on calculation used
Compression index - Compression index                                 
Compression index (SD) - Standard deviation of compression index values reported in paper                  
Compression index data source - Graph or table from where the data was collected, or explanation on calculation used
Swelling index - Swelling index                            
Swelling index (SD) - Standard deviation of swelling index values reported in paper                                     
Swelling index data source - Graph or table from where the data was collected, or explanation on calculation used
N - Number of replicates used for calculating precompression stress, compression index, and swelling index when mean values are reported
Land use (paper) - Land use described in the research paper
Land use (categories) - Land use categorized
Land use standardized - Land use classified as: arable, forest, grassland, and native vegetation. The latter includes forest, grassland, and savanna
Land use (number code) - Number code for land use: 1=Arable, 2= forest, 3= grassland, and 4= native vegetation
Tillage system - Tillage system
Tillage system (arable soils) - Tillage system for arable soils classified as "conventional" and "conservation"
Coordinates -  Geographical coordinates  of study location
Climate - Climatic region classification: temperate, tropical, subtropical
Climatecod -    Code number assigned to each climatic region: 1=temperate, 2=tropical, 3=subtropical
Sampling position (paper) - Field position where soil samples were collected with details described in the paper
Sampling position - Field position where soil samples were collected standardized
Treatment - Experimental treatment type where the soil samples were collected
Stress rate -  kPa - Stress applied in compressive tests 
Minimum stress – kPa - Minimum stress applied in compressive tests
Maximum stress – kPa - Maximum stress applied in compressive tests
Number of stress rate steps - Number of steps in stepwise stress application procedure
Stess application type - 1=Stepwise stress 2=one sample per stress 3=Strain controlled
Stess application type – min - Time for stress application in each step in stepwise stress application procedure
Degree of deformation at the end of loading - % - Degree of deformation at the end of compressive test
Sample diameter – cm - Diameter of the soil samples
Sample height – cm - Height of the soil samples
Ratio sample diameter and height - Ratio between diameter and height of the soil samples
Sample volume - cm3 -Sample volume when the sample diameter and height are nor presented
Precompression stress calculation method - Calculation method of precompression stress
Precompression stress calculation method (number code) - Number code for calculation method PC:1=Casagrande (1936); 2=Dias Junior and Pierce (1995); 3= Lamandé et al. (2017); 4=O`Sullivan and Robertson (1996); 5=Casini (2012); 6=Culley and Larson (1987);7=ABNT (1990); 8=Gregory et al. (2006)
Description of precompression stress calculation - Brief explanation of precompression stress calculation
Soil compressive curve components - Component of the soil compression curve related to the soil packing state: soil bulk density, void ratio, and strain. 
Soil compressive curve components (number code) - Number code for component of the soil compressive curve related to the soil packing state: 1= soil bulk density; 2= strain; 3= void ratio
Curve components source - Source of the component of the soil compressive curve related to the soil packing state: 1= showed in the paper, 2= according to original method for precompression stress calculation, 3= described in method, but not clear in the paper
Compressive curve available - Original soil compressive curve available in the paper: 1= No 2=Yes
Comments - Brief comments on the paper
Issues and remarks
We sought out important information not included in the paper by directly communicating with the authors whenever possible. In cases where multiple papers covered the same experiment, we prioritized the one offering more comprehensive details. If two papers complemented each other, we included both. When analyzing studies comparing various methods for calculating soil precompression stress, we exclusively gathered data calculated using the widely accepted Casagrande (1936) method. To ensure comparability across studies, we standardized the collected data by converting it to the same unit. The standardization process involved: i) assuming that 58% of soil organic matter (SOM) was soil organic carbon (SOC) when only SOM was reported, ii) calculating soil bulk density using a soil particle density of 2.65 Mg m-3 when only total porosity data were provided, and iii) harmonizing all texture data to the USDA classification system, which defines the silt/sand boundary as 50 μm, utilizing the k-nearest neighbor approach (referred to as "similarity method" by Nemes et al. (1999).  
Reference
Associação Brasileira de Normas Técnicas - ABNT. NBR 12007: Ensaio de adensamento unidimensional. Rio de Janeiro: 1990.
Casagrande, A., 1936. Determination of the preconsolidation load and its practical significance. In: Proceedings of the International Conference on Soil Mechanics and Foundation Engineering, vol. III, Harvard University, Cambridge, MA, pp. 60–64.Casini, F. 2012. Deformation induced by wetting: A simple model. Can. Geotech. J. 49:954–960 10.1139/T2012-054. doi:10.1139/t2012-054
Culley, J.L.B., Larson, W.E., 1987. Susceptibility to compression of a clay loam Haplaquoll. Soil Sci. Soc. Am. J. 51, 562–567.
Dias Junior, M.S., Pierce, F.J., 1995. A simple procedure for estimating preconsolidation pressure from soil compression curves. Soil Technology 8, 139–151. doi:10.1016/0933-3630(95)00015-8
Gregory, A.S., Whalley, W.R., Watts, C.W., Bird, N.R.A., Hallett, P.D., Whitmore, A.P., 2006. Calculation of the compression index and pre-compression stress from soil compression test data. Soil Till Res. 89:45-57. doi:10.1016/j.still.2005.06.012
Lamandé, M., Schjønning, P., Labouriau, R., 2017. A novel method for estimating soil precompression stress from uniaxial confined compression tests. Soil Sci. Soc. Am. J. 81 https://doi.org/10.2136/sssaj2016.09.0274.
Nemes, A.,  Wösten, J.H.M., Lilly, A.,  Oude Voshaar, J.H., 1999. Evaluation of different procedures to interpolate the cumulative particle-size distribution to achieve compatibility within a soil database. Geoderma 90: 187-202. 129 
O'Sullivan, M.F., Robertson, E.A.G., 1996. Critical state parameters from intact samples of two agricultural topsoils. Soil Tillage Res 39(3 – 4):161 – 173.