------------------------------------------------------------------------------------------------------------- This file was generated on 2025-02-05 by NAME Adriana Günzel DOI: https://doi.org/10.60507/FK2/3JSPXH A GENERAL INFORMATION 1. Title of the dataset: Plaster Cast of the funerary relief of Hegeso in the Academic Art Museum Bonn (Inv. Nr. 713) 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, 53115 Bonn Email: aguenzel@uni-bonn.de 4. Date of data Collection: 2024-07-06 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: Bonn, Akademisches Kunstmuseum 8. Bibliography : N. Himmelmann - U. Sinn (Hrsg.), Verzeichnis der Abguß-Sammlung des Akademischen Kunstmuseums der Universität Bonn (Berlin 1981), 72 Nr. 713 B DATA & FILE OVERVIEW 1. File List: Funerary_relief_Hegeso_713 Funerary_relief_Hegeso_713 Funerary_relief_Hegeso_713_high_poly (contains high-polygon model) Funerary_relief_Hegeso_713_low_poly (contains low-polygon model, base color texture, normal map, ambient occulsion 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 (RealityCapture) Cleaning was done in Blender Texture Baking was done in Substance Designer Texture was generated in Substance 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 Kluge Previewers originally developed by QDR and maintained at https://github.com/GlobalDataverseCommunityConsortium/dataverse-previewers. Feedback and contributions welcome.