Protocol Digital Rural Smart (DRS) v1.0: Translating Rural Practitioner Knowledge into Digital Monitoring Requirements

This protocol provides a structured method for translating rural practitioner knowledge into candidate requirements for digital monitoring technologies while preserving its provenance, context, uncertainty and evidence status. It addresses the risk of treating practical knowledge as independently validated fact or excluding it because it is not formal scientific evidence. The method distinguishes traditional and locally embedded knowledge, experiential practitioner observations, scientific evidence and engineering assumptions. It combines a knowledge-classification framework, a semi-structured elicitation template, a traceability template and safeguards against misrepresenting evidence. Each knowledge statement is linked to candidate measurable variables, possible sensing approaches, supporting or conflicting evidence, uncertainty, sensor and inference limitations, and candidate design implications. A worked precision-apiculture example examines six pre-existing, anonymised beekeeper statements against published scientific evidence. It illustrates agreement and disagreement with research, practitioner observations that sensors cannot directly measure, and engineering assumptions embedded in monitoring practice. Version 1.0 has not been tested with participants; its usability and transferability to other rural domains remain to be assessed. This record contains the protocol, a reusable blank CSV traceability template and its data dictionary. The method is designed to be technology- and sector-neutral. The protocol was developed through a Virtual Mobility grant under COST Action CA24170 SMART-RURAL. This publication is based upon work from COST Action SMART-RURAL (CA24170), supported by COST (European Cooperation in Science and Technology).

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-10-19
DOI
https://doi.org/10.5281/zenodo.23480419
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
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article

Protocol Digital Rural Smart (DRS) v1.0: Translating Rural Practitioner Knowledge into Digital Monitoring Requirements

Codrin Dinu Vasiliu, Ru Wikmann
Zenodo (CERN European Organization for Nuclear Research)
Smart Agriculture and AI
article

Protocol Digital Rural Smart (DRS) v1.0: Translating Rural Practitioner Knowledge into Digital Monitoring Requirements

Codrin Dinu Vasiliu, Ru Wikmann
article en

Abstract

This protocol provides a structured method for translating rural practitioner knowledge into candidate requirements for digital monitoring technologies while preserving its provenance, context, uncertainty and evidence status. It addresses the risk of treating practical knowledge as independently validated fact or excluding it because it is not formal scientific evidence. The method distinguishes traditional and locally embedded knowledge, experiential practitioner observations, scientific evidence and engineering assumptions. It combines a knowledge-classification framework, a semi-structured elicitation template, a traceability template and safeguards against misrepresenting evidence. Each knowledge statement is linked to candidate measurable variables, possible sensing approaches, supporting or conflicting evidence, uncertainty, sensor and inference limitations, and candidate design implications. A worked precision-apiculture example examines six pre-existing, anonymised beekeeper statements against published scientific evidence. It illustrates agreement and disagreement with research, practitioner observations that sensors cannot directly measure, and engineering assumptions embedded in monitoring practice. Version 1.0 has not been tested with participants; its usability and transferability to other rural domains remain to be assessed. This record contains the protocol, a reusable blank CSV traceability template and its data dictionary. The method is designed to be technology- and sector-neutral. The protocol was developed through a Virtual Mobility grant under COST Action CA24170 SMART-RURAL. This publication is based upon work from COST Action SMART-RURAL (CA24170), supported by COST (European Cooperation in Science and Technology).

Zenodo (CERN European Organization for Nuclear Research)
Academia Română, Filiala Iași (RO), Romanian Academy (RO)
Openalex Percentile: Top 15%
Smart Agriculture and AI
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