Priority 1: GIS-powered regional Historic Environment Records (HERs) and national datasets present a powerful research tool with new data management and visualisation software indicating that an even greater potential exists. Enhancement of database records and their terminology is an important priority for realising this potential and therefore help to address a range of research questions relating to the Iron Age.
Priority 2: The increased availability of remotely sensed data presents challenges and opportunities. In unimproved and semi-improved ground availability of LiDAR (ALS – Airborne Laser Scanning) data is likely to stimulate a significant change in the detection and interpretations of earthwork remains (Cowley et al 2020). While multi- and hyperspectral imaging may help to extend the windows for detection of buried sites through crop proxies (Moriarty et al 2018). The development of AI and Machine learning enabled detection of archaeological features in remote sensed data is promising and offers a means to explore the proliferating datasets. For the Iron Age in particular, such approaches can enhance our understanding of the period’s diverse settlement forms and should be a key focus for any new survey programmes undertaken.