------------------------------------------------------------------------------------------------------------- This file was generated on 2025-10-10 by NAME Adriana Günzel DOI: https://doi.org/10.60507/FK2/EN8NMY A GENERAL INFORMATION 1. Title of the dataset: Attic Red-Figure Lekythos in the Museum of the University of Tübingen (Inv. Nr. 1365) 2. Brief description of the research project and its aims: 3. Author Information A. Investigator Contact Information Name: Günzel, Adriana Institution: Institut für Archäologie und Kulturanthropologie, Abteilung Klassische Archäologie, Universität Bonn Address: Römerstraße 164, 53111 Bonn Email: aguenzel@uni-bonn.de 4. Date of data Collection: 2024-03-21 5. Information about funding sources that supported the collection of the data: Universität Bonn 6. Language of the dataset: English 7. Geographic location of data collection: Tübingen, Museum Alte Kulturen 8. Bibliography : Corpus Vasorum Antiquorum: TUBINGEN, ANTIKENSAMMLUNG DES ARCHAOLOGISCHEN INSTITUTS DER UNIVERSITAT 5, 62,63,64, FIG.26, PL.(2645) 28.4-8 9. Beazley-Archive: Vase Number: 212418, https://www.beazley.ox.ac.uk/record/6B0C034A-6F5F-45A2-9B96-23B1B773108C B DATA & FILE OVERVIEW 1. File List: Krater_5806 Krater_5806_images (images used for reconstruction, distances) Krater_5806_model Krater_5806_highpoly (contains high-polygon model and base color texture) Krater_5806_gameready (contains gameready model, diffuse map, ambient occlusion map, normal map, metallness map, roughness map) 2. Are there multiple versions of the dataset? no C SHARING/ACCESS INFORMATION 1. Was data derived from another source? no 2. Licenses/restrictions placed on the data: no D METHODOLOGICAL INFORMATION 1. Description of methods used for collection/generation of data: Model was generated with photogrammetry (Agisoft Metashape) Cleaning was done in Blender Texture Baking was done in Substance Designer and Painter 2. Methods for processing the data: Can be opend in any 3D-software package 4. People involved in sample collection, processing, analysis and/or submission: Liza-Marie Peters, Matthias Lang, Philippe Pathé Previewers originally developed by QDR and maintained at https://github.com/GlobalDataverseCommunityConsortium/dataverse-previewers. Feedback and contributions welcome.