Innovative clearance data model for demining operational data collection: Insights from field trials in Zimbabwe
Year: 2024
Type: article
Abstract: From September 2023 to March 2024 a field trial on a live manual demining site was conducted to test a new and innovative approach for the collection and analysis of operational data. The approach, titled the Clearance Data Model, involved the collection of sixty-six data attributes for each mine found. For the first time the mine itself would become the accountable unit of demining data, against which an expanded range of relevant attributes particular to that specific mine would be recorded. This novel approach represented a considerable expansion to the operational data collected concerning Victim Operated Explosive Devices such as mines, booby-traps and victim operated Improvised Explosive Devices from the field. Previously few if any details about individual accountable mines were collected. The trial proved that is it entirely practical to collect such levels of data without impeding operational efficiency. It also showed that such data has significant benefits for quantitative operational risk management, as well as overall operations and quality management. For example, the recording of mine depth alongside excavation times enables oversight of individual excavation speed and management of any risk identified.
Source: Heliyon
Institutions: Cranfield University, Defence Academy of the United Kingdom
Language: English
Subfield: Experimental and Cognitive Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $2,100
Funder: Cranfield University
OpenAlex ID: W4404733138