Making sense of fossils and artefacts: a review of best practices for the design of a successful workflow for machine learning-assisted citizen science projects

• Published in: PeerJ (San Francisco, CA) Vol. 13; p. e18927
• Main Authors: Eijkelboom, Isaak, Schulp, Anne S, Amkreutz, Luc, Verheul, Dylan, Verschoof-van der Vaart, Wouter, van der Vaart-Verschoof, Sasja, Hogeweg, Laurens, Brunink, Django, Mol, Dick, Peeters, Hans, Wesselingh, Frank
• Format: Journal Article
• Language: English
• Published: United States PeerJ. Ltd 13.02.2025; PeerJ Inc
• Subjects: Archaeology; Archaeology - methods; Best practices; Biodiversity; Biological diversity; Citizen science; Citizen Science - methods; Citizen scientists; Data Mining and Machine Learning; Fossils; Geospatial data; Human-Computer Interaction; Humans; Information management; Machine Learning; Palaeontology; Paleontology; Paleontology - methods; Project design; Scientists; Workflow; Netherlands; North Sea; AI; Archaeology; Citizen science; Palaeontology; Project design

Historically, the extensive involvement of citizen scientists in palaeontology and archaeology has resulted in many discoveries and insights. More recently, machine learning has emerged as a broadly applicable tool for analysing large datasets of fossils and artefacts. In the digital age, citizen sc...