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Data from the literature containing information on the age at death of Neolithic burials from Germany. The data were taken from mortality tables (Dx), individual data or bar charts. The data set does not claim to be complete, but focuses on larger burial groups.

Research compendium for 'A pre-Campanian Ignimbrite techno-cultural shift in the Aurignacian sequence of Grotta di Castelcivita, southern Italy' Compendium DOI: https://doi.org/10.5281/zenodo.10639553 The content available at the above provided URL will reproduce the results as documented in the first paper's submission. Instead, the files hosted at https://github.com/ArmandoFalcucci/Castelcivita-Aur-Techno represent the developmental versions and might have undergone modifications since the paper's publication. Maintainer of this repository: Armando Falcucci (armando.falcucci@uni-tuebingen.de; https://orcid.org/0000-0002-3255-1005) Submitted paper: Armando Falcucci, Simona Arrighi, Vincenzo Spagnolo, Matteo Rossini, Owen Higgins, Brunella Muttillo, Ivan Martini, Jacopo Crezzini, Francesco Boschin, Annamaria Ronchitelli, Adriana Moroni. A pre-Campanian Ignimbrite techno-cultural shift in the Aurignacian sequence of Grotta di Castelcivita, southern Italy. In preparation (2024). Abstract: The Aurignacian is the first European technocomplex assigned to Homo sapiens identified across a wide geographic extent. Although archaeologists have identified marked chrono-cultural shifts within the Aurignacian mostly by examining the techno-typological variations of stone tools, unraveling the underlying processes driving these changes remains a significant scientific challenge. Scholars have, for instance, hypothesized that the Campanian Ignimbrite (CI) super-eruption and the climatic deterioration associated with the onset of Heinrich Event 4 had a substantial impact on European foraging groups. The technological shift from the Protoaurignacian to the Early Aurignacian is regarded as an archaeological manifestation of adaptation to changing environments. However, some of the most crucial regions and stratigraphic sequences for testing these scenarios have been overlooked. In this study, we delve into the high-resolution stratigraphic sequence of Grotta di Castelcivita in southern Italy. Here, the Uluzzian is followed by three Aurignacian layers, all sealed by the eruptive units of the CI. Employing a comprehensive range of quantitative methods—encompassing attribute analysis, 3D model analysis, and geometric morphometrics—we demonstrate that the technological features commonly associated with the Early Aurignacian developed well before the deposition of the CI tephra. Our study provides thus the first direct evidence that the volcanic eruption played no role in this cultural process. Furthermore, we show that local paleo-environmental proxies do not correlate with the identified patterns of cultural continuity and discontinuity. Consequently, we propose alternative research paths to explore the role of demography and regional trajectories in the development of the Upper Paleolithic. Keywords: Early Upper Paleolithic; Italy; Aurignacian; lithic technology; geometric morphometrics; 3D model analysis; cultural evolution; human-environment interaction; open science. Overview of contents and how to reproduce: Within this repository, various folders house data (data), code (script), and output files (output) pertinent to the paper. The data folder encompasses the complete dataset, the core dataset, and 2D outline coordinates utilized for the geometric morphometrics study. To replicate the results, download the entire repository and employ Castelcivita-Aur-Techno.Rproj and open the folder script, following the numbered folder structure. For ensuring reproducibility, the renv package (v. 1.0.3) was utilized, following the procedures detailed in its vignette. All analyses and visualizations in the paper were conducted using R 4.3.1 on Microsoft Windows 10.0.19045 (64-bit). As the necessary packages are available in the renv folder, they are not explicitly listed here. Licenses: Code: MIT (http://opensource.org/licenses/MIT), copyright holder: Armando Falcucci (2024). Data and intellectual work: Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), copyright holder: the authors (2024).

Overview The repository contains an extensive dataset (n = 538) comprising 3D meshes representing various classes of lithic artifacts such as cores, blades, bladelets, flakes, and retouched tools. These artifacts originate from the Protoaurignacian (rsa') and Early Aurignacian (gic, ars) layers of Grotta di Castelcivita (40.49563600N, 015.20922177E) in southern Italy (Gambassini, 1997). The layers date back to approximately 41,000 to 39,800 years ago (Douka et al., 2014). A new technological assessment of the rsa’–ars sequence has been conducted utilizing the models included in this repository (Falcucci et al., in preparation). Grotta di Castelcivita holds significant importance for the study of Early Upper Paleolithic cultural dynamics due to its substantial archaeological content and the presence of the Campanian Ignimbrite geochronological marker, which seals the archaeological sequence of the site (Giaccio et al., 2008). The artifacts in this dataset were 3D-scanned using an Artec Space Spider and an Artec Micro, both from Artec Inc. in Luxembourg. The scanning process adhered to recently published protocols (Falcucci, 2022; Göldner et al., 2022b; Göldner et al., 2022a). The use of the Artec Micro was particularly instrumental in digitizing extremely small lithics, such as retouched bladelets with length values around 1 cm. The creation of this open-access repository is intended to encourage archaeologists to participate in collaborative initiatives, thereby contributing to the advancement of research in the field of lithic technology and facilitating broader access to the prehistoric record. This initiative aligns with the promotion of Open Science practices in archaeological sciences, as advocated by Marwick et al. (2017). Description of the dataset This repository includes a zipped folder containing 3D meshes in ply format (CTC_3d_Meshes.zip), accompanied by a csv file containing crucial information essential for the scientific utilization of the models (CTC_3D_Dataset.csv). The unique ID assigned to each item, compiled by A. Falcucci during data collection, comprises the site abbreviation (CTC) and a progressive numeric system. The attributes in the csv file are listed and described below: ID: A unique identifier for each lithic artifact, consisting of the site abbreviation (CTC) and a numeric progression. Scanner: Information indicating which scanner was used for obtaining the 3D models, either the Artec Spider or the Artec Micro. Layer: Stratigraphic layer of provenience, categorized as rsa’, gic, or ars. Raw_material: Classification of lithics based on raw material’s macro-categories, including coarse-grained chert, fine-grained chert, limestone, quartzite, radiolarite, and undetermined. Class: Sorting of artifacts into classes such as blank, core, core-tool, hammerstone, and tool. Blank: Classification of knapped artifacts according to the blank category (blade, bladelet, flake, other, and undetermined). Technology: Sorting of artifacts into technological categories, including initialization, maintenance, optimal, other, semi-cortical, and undetermined. Cortex: Estimated percentage of cortex, categorized as 0%, 1-33%, 33-66%, 66-99%, and 100%. Preservation: Classification of blanks based on their degree of breakage, such as complete, distal, mesial, proximal, and undetermined. Cores and core-tools are not classified here. Volume: Volume of artifacts in cubic millimeters. Surface: Surface area of artifacts in square millimeters. Length, Width, and Thickness: Maximal linear dimensions in millimeters of artifacts based on their technological orientation. Core_classification: Classification of cores and core-tools into various technological categories, including bipolar, carinated, platform cores, and core shatters. This detailed list enhances the utility and encourages the reuse of the 3D models for scientific purposes. Additionally, the unique ID enables the collection of additional techno-typological information available in the published dataset associated with the lithic technology paper: https://doi.org/10.5281/zenodo.10639552. We strongly recommend that users of the 3D models refer to the GitHub repository to obtain the most up-to-date techno-typological information. Additionally, we kindly ask users to provide proper attribution for both datasets. References Douka K., Higham T., Wood R. et al. (2014) On the chronology of the Uluzzian. J. Hum. Evol., 68: 1-13. doi:10.1016/j.jhevol.2013.12.007 Falcucci A. (2022) MicroStone: Exploring the capabilities of the Artec Micro in scanning stone tools. protocols.io. doi:https://dx.doi.org/10.17504/protocols.io.81wgb6781lpk/v1 Gambassini P. (1997) Il Paleolitico di Castelcivita: Culture e Ambiente. Electa, Naples Giaccio B., Isaia R., Fedele F.G. et al. (2008) The Campanian Ignimbrite and Codola tephra layers: Two temporal/stratigraphic markers for the Early Upper Palaeolithic in southern Italy and eastern Europe. Journal of Volcanology and Geothermal Research, 177: 208-226. doi:https://doi.org/10.1016/j.jvolgeores.2007.10.007 Göldner D., Karakostis F.A. & Falcucci A. (2022a) Practical and technical aspects for the 3D scanning of lithic artefacts using micro-computed tomography techniques and laser light scanners for subsequent geometric morphometric analysis. Introducing the StyroStone protocol. PLoS One, 17: e0267163. doi:10.1371/journal.pone.0267163 Göldner D., Karakostis F.A. & Falcucci A. (2022b) StyroStone: A protocol for scanning and extracting three-dimensional meshes of stone artefacts using Micro-CT scanners V.2. protocols.io. doi:dx.doi.org/10.17504/protocols.io.4r3l24d9qg1y/v2 Marwick B., d’Alpoim Guedes J., Barton C.M. et al. (2017) Open science in archaeology. SAA Archaeological Record, 17: 8-14. doi:10.17605/OSF.IO/3D6XX Funding statement and acknowledgements Research and fieldwork at Grotta di Castelcivita are coordinated by Adriana Moroni and Annamaria Ronchitelli of the University of Siena. The digitization of lithic artifacts received support from the Deutsche Forschungsgemeinschaft (DFG) under grant agreement no. 431809858, with the project titled "Investigating Early Upper Paleolithic Technological Variability and Cultural Dynamics South of the Alps", awarded to Armando Falcucci. Access to scanning instrumentation was provided by the Department of Geosciences, Early Prehistory and Quaternary Ecology working group at the Eberhard Karls University of Tübingen. Gratitude is expressed to the Soprintendenza Archeologia Belle Arti e Paesaggio per le province di Salerno e Avellino for permissions and ongoing support for the research. The Società Grotte di Castelcivita and the Municipality of Castelcivita are acknowledged for their logistical support. Recognition is extended to all researchers and students actively involved in the recovery, preparation, and study of the archaeological record from Grotta di Castelcivita throughout the years of research at the site. Finally, our fondest remembrance goes to Paolo Gambassini, whose research activities played a crucial role in making this study possible.

Manual transcription of approx. 38 min lengthy voiceovers in German from the digitized version of the documentary film "Terremoto - Erdbeben in Peru" from 1970 (producer: Ferdinand Khittl KG München, commissioner: Bayer AG Leverkusen) using the program f4transcript for time coding. The documentary shows the joint humanitarian relief operation of Bayer AG with the German Red Cross (DRK) in the 1970 earthquake disaster zone of Caraz in Peru, Callejón de Huaylas, Province of Ancash. The original and digitized film is preserved and licensed by Bayer Corporate Archives Leverkusen, Germany.

Manual transcription of approx. 20 min lengthy voiceovers in German from the digitized version of the documentary film "Die Tür des Minaretts blickt nicht mehr nach Mekka" from 1970 (producer: Ferdinand Khittl KG München, commissioner: Bayer AG Leverkusen) using the program f4transcript for time coding. The documentary film shows the joint humanitarian relief operation of Bayer AG Leverkusen with the German Red Cross (DRK) in the 1970 earthquake disaster zone of Gediz in Turkey. The original and digitized film is preserved and licensed by Bayer Corporate Archives Leverkusen, Germany.

Data Statement for CommitBench - Dataset Title: CommitBench - Dataset Curator: Maximilian Schall, Tamara Czinczoll, Gerard de Melo - Dataset Version: 1.0, 15.12.2023 - Data Statement Author: Maximilian Schall, Tamara Czinczoll - Data Statement Version: 1.0, 16.01.2023 - Code URL: https://github.com/maxscha/commitbench EXECUTIVE SUMMARY We provide CommitBench as an open-source, reproducible and privacy- and license-aware benchmark for commit message generation. The dataset is gathered from github repositories with licenses that permit redistribution. We provide six programming languages, Java, Python, Go, JavaScript, PHP and Ruby. The commit messages in natural language are restricted to English, as it is the working language in many software development projects. The dataset has 1,664,590 examples that were generated by using extensive quality-focused filtering techniques (e.g. excluding bot commits). Additionally, we provide a version with longer sequences for benchmarking models with more extended sequence input, as well a version with CURATION RATIONALE We created this dataset due to quality and legal issues with previous commit message generation datasets. Given a git diff displaying code changes between two file versions, the task is to predict the accompanying commit message describing these changes in natural language. We base our GitHub repository selection on that of a previous dataset, CodeSearchNet, but apply a large number of filtering techniques to improve the data quality and eliminate noise. Due to the original repository selection, we are also restricted to the aforementioned programming languages. It was important to us, however, to provide some number of programming languages to accommodate any changes in the task due to the degree of hardware-relatedness of a language. The dataset is provides as a large CSV file containing all samples. We provide the following fields: Diff, Commit Message, Hash, Project, Split. DOCUMENTATION FOR SOURCE DATASETS Repository selection based on CodeSearchNet, which can be found under https://github.com/github/CodeSearchNet LANGUAGE VARIETIES Since GitHub hosts software projects from all over the world, there is no single uniform variety of English used across all commit messages. This means that phrasing can be regional or subject to influences from the programmer's native language. It also means that different spelling conventions may co-exist and that different terms may used for the same concept. Any model trained on this data should take these factors into account. For the number of samples for different programming languages, see Table below: Language Number of Samples Java 153,119 Ruby 233,710 Go 137,998 JavaScript 373,598 Python 472,469 PHP 294,394 SPEAKER DEMOGRAPHIC Due to the extremely diverse (geographically, but also socio-economically) backgrounds of the software development community, there is no single demographic the data comes from. Of course, this does not entail that there are no biases when it comes to the data origin. Globally, the average software developer tends to be male and has obtained higher education. Due to the anonymous nature of GitHub profiles, gender distribution information cannot be extracted. ANNOTATOR DEMOGRAPHIC Due to the automated generation of the dataset, no annotators were used. SPEECH SITUATION AND CHARACTERISTICS The public nature and often business-related creation of the data by the original GitHub users fosters a more neutral, information-focused and formal language. As it is not uncommon for developers to find the writing of commit messages tedious, there can also be commit messages representing the frustration or boredom of the commit author. While our filtering is supposed to catch these types of messages, there can be some instances still in the dataset. PREPROCESSING AND DATA FORMATTING See paper for all preprocessing steps. We do not provide the un-processed raw data due to privacy concerns, but it can be obtained via CodeSearchNet or requested from the authors. CAPTURE QUALITY While our dataset is completely reproducible at the time of writing, there are external dependencies that could restrict this. If GitHub shuts down and someone with a software project in the dataset deletes their repository, there can be instances that are non-reproducible. LIMITATIONS While our filters are meant to ensure a high quality for each data sample in the dataset, we cannot ensure that only low-quality examples were removed. Similarly, we cannot guarantee that our extensive filtering methods catch all low-quality examples. Some might remain in the dataset. Another limitation of our dataset is the low number of programming languages (there are many more) as well as our focus on English commit messages. There might be some people that only write commit messages in their respective languages, e.g., because the organization they work at has established this or because they do not speak English (confidently enough). Perhaps some languages' syntax better aligns with that of programming languages. These effects cannot be investigated with CommitBench. Although we anonymize the data as far as possible, the required information for reproducibility, including the organization, project name, and project hash, makes it possible to refer back to the original authoring user account, since this information is freely available in the original repository on GitHub. METADATA License: Dataset under the CC BY-NC 4.0 license DISCLOSURES AND ETHICAL REVIEW While we put substantial effort into removing privacy-sensitive information, our solutions cannot find 100% of such cases. This means that researchers and anyone using the data need to incorporate their own safeguards to effectively reduce the amount of personal information that can be exposed. ABOUT THIS DOCUMENT A data statement is a characterization of a dataset that provides context to allow developers and users to better understand how experimental results might generalize, how software might be appropriately deployed, and what biases might be reflected in systems built on the software. This data statement was written based on the template for the Data Statements Version 2 schema. The template was prepared by Angelina McMillan-Major, Emily M. Bender, and Batya Friedman and can be found at https://techpolicylab.uw.edu/data-statements/ and was updated from the community Version 1 Markdown template by Leon Dercyznski.

This is the measurement data from the geomagnetic prospection of the Ahlen-Falkenberger Moor (district of Cuxhaven, Lower Saxony, Germany) as part of the research project Preserved in the bog - relics of prehistoric settlement landscapes in the Elbe-Weser triangle funded by Niedersachsen Vorab. A total of about 800 ha were measured. The aim was to locate archaeological sites as well as landscape features. The measurements were carried out with a MXV3 system from Sensys with 6 FGM650/3 probes with a distance of 0.5m. Each probe consists of 2 sensors with 650mm basedistance and gives the gradient of the vertical component of the magnetic field (Z). The location was measured using a Stonex S10 GPS with Sapos HEPS correction data, resulting in a horizontal position accuracy of 0.01 – 0.02m and an elevation accuracy of 0.02 – 0.03m. The data were exported using DLMGPS (Sensys), whereby the coordinates of the individual probes are automatically determined from the central GPS position on the device. The data were exported without automatic track compensation. Due to the system, the position data is in UTM32/ETRS84 (EPSG 4647) and for conformity with PANGAEA also in WGS84 (EPSG 4326) (conversion is done with spTransform in R). Measurement carried out by D. Dallaserra (NIhK) and J. Lühmann (NIhK)

This is the measurement data from the geomagnetic prospection of the Ahlen-Falkenberger Moor (district of Cuxhaven, Lower Saxony, Germany) as part of the research project Preserved in the bog - relics of prehistoric settlement landscapes in the Elbe-Weser triangle funded by Niedersachsen Vorab. A total of about 800 ha were measured. The aim was to locate archaeological sites as well as landscape features. The measurements were carried out with a MXV3 system from Sensys with 11 FGM650/3 probes with a distance of 0.25m. Each probe consists of 2 sensors with 650mm basedistance and gives the gradient of the vertical component of the magnetic field (Z). The location was measured using a Stonex S10 GPS with Sapos HEPS correction data, resulting in a horizontal position accuracy of 0.01 – 0.02m and an elevation accuracy of 0.02 – 0.03m. The data were exported using DLMGPS (Sensys), whereby the coordinates of the individual probes are automatically determined from the central GPS position on the device. The data were exported without automatic track compensation. Due to the system, the position data is in UTM32/ETRS84 (EPSG 4647) and for conformity with PANGAEA also in WGS84 (EPSG 4326) (conversion is done with spTransform in R). Measurement carried out by D. Dallaserra (NIhK) and J. Lühmann (NIhK)

This is the measurement data from the geomagnetic prospection of the Ahlen-Falkenberger Moor (district of Cuxhaven, Lower Saxony, Germany) as part of the research project Preserved in the bog - relics of prehistoric settlement landscapes in the Elbe-Weser triangle funded by Niedersachsen Vorab. A total of about 800 ha were measured. The aim was to locate archaeological sites as well as landscape features. The measurements were carried out with a MXV3 system from Sensys with 6 FGM650/3 probes with a distance of 0.5m. Each probe consists of 2 sensors with 650mm basedistance and gives the gradient of the vertical component of the magnetic field (Z). The location was measured using a Stonex S10 GPS with Sapos HEPS correction data, resulting in a horizontal position accuracy of 0.01 – 0.02m and an elevation accuracy of 0.02 – 0.03m. The data were exported using DLMGPS (Sensys), whereby the coordinates of the individual probes are automatically determined from the central GPS position on the device. The data were exported without automatic track compensation. Due to the system, the position data is in UTM32/ETRS84 (EPSG 4647) and for conformity with PANGAEA also in WGS84 (EPSG 4326) (conversion is done with spTransform in R). Measurement carried out by D. Dallaserra (NIhK) and J. Lühmann (NIhK)

Oxygen isotopes in biogenic silica (δ18O BSi) from lake sediments allow for quantitative reconstruction of past hydroclimate and proxy–model comparison in terrestrial environments. The signals of individual records have been attributed to different factors, such as air temperature (T air ), atmospheric circulation patterns, hydrological changes and lake evaporation. Here, we provide 55 composite down–core records published to date and complemented with additional lake basin parameters (e.g. lake water residence time and catchment size) to best characterize the signal properties. Records feature widely different temporal coverage and resolution ranging from decadal–scale records covering the last 150 years to records with multi–millennial scale resolution spanning glacial–interglacial cycles. Best coverage in number of records (N=37) and datapoints (N=2112) is available for northern hemispheric (NH) extra–tropic regions throughout the Holocene (corresponding to Marine Isotope Stage 1; MIS 1).