Collection launched: 09 Sep 2020
This special issue brings together ongoing digital practices attempting to understand and fight the phenomena of pillage and illicit trade of archaeological objects, in order to boost the discussion and define a set of good practices. In recent years, in fact, despite the 1970 “UNESCO convention on the Means of Prohibiting and Preventing the Illicit Import, Export and Transfer of Ownership of Cultural Property”, plundering and illicit trade of archaeological objects have been on the rise and becoming a global-scale phenomenon, further exacerbated by the turmoil stemmed from the crisis in the MENA regions.
As a consequence of this upsurge, we are assisting the widening of digitally enhanced initiatives, promoted by diverse actors engaged in the protection of endangered cultural heritage and in halting illicit trade, which increasingly rely on technological and digital advances. Remote sensing is being used to detect and monitor illicit excavations, exploring new ways to automate looting recognition methods; Illicit online sales, social media, online forums, the deep web and trafficking networks are being investigated with the support of machine learning, delivering quantitative and content data; 3D imagery-fed blockchain technologies are currently being investigated to customise this emerging technology to immutably trace provenances records and create a record of assets that cannot be tampered with.
The publication of the papers: "Digital Modelling in Museum and Private Collections: A Case Study on Early Italic Armour", "Interferometric SAR and Machine Learning: Using Open Source Data to Detect Archaeological Looting and Destruction", and "Remote and close range sensing for the automatic identification and characterization of archaeological looting. The case of Peru", has been covered by the Ca' Foscari University of Venice and financed by the NETCHER project (NETwork and digital platform for Cultural Heritage Enhancing and Rebuilding, H2020-SC6-TRANSFORMATIONS-2018-2019-2020 - G.A. nº 822585), which is funded under the EU Horizon 2020 programme.
The information and views set out in the papers are those of the authors and do not necessarily reflect the official opinion of the European Commission Directorate-General for Research and Innovation. The Directorate-General for Research and Innovation or any person acting on its behalf are not responsible for the use which may be made of the information contained therein.