Study-level coding matrix for a critical systematic review of functional integration in carbon footprint and environmental assessment of viticulture (2020–2026)

This dataset contains the study-level coding matrix supporting the critical systematic review "From Carbon Footprint to Decision Support in Viticulture: A Critical Systematic Review of Functional Integration in Environmental Assessment" (Simões, Pinto & Teixeira; submitted to Sustainable Production and Consumption). The matrix covers the 101 primary/original studies included in the review, published between 2020 and 2026 and retrieved from Web of Science and Scopus. The 26 review articles in the corpus are synthesised separately in the article and are not included here. The file contains five sheets:- README: purpose of the dataset, coding rules, and description of each sheet.- Study_characteristics_101: study identification, search run, study design, methods, data source, functional unit, system boundary, and environmental scope.- Context_scores_101: ordinal coding (0 = absent; 1 = reported; 2 = analytically integrated; 3 = used to explain environmental performance) of 13 contextual dimensions, and the resulting contextualisation criterion.- Functional_coding_101: binary coding of prospective assessment and ten diagnosis-to-action components (diagnosis, concrete strategy, tested alternative, trade-offs, quantitative feasibility, barriers, implementation, longitudinal monitoring, post-implementation environmental reassessment, and operational decision support).- Functional_overlap_101: formula-based co-occurrence counts used in the article. Coding was performed by the first author and verified study by study by the co-authors against the source publications, with disagreements resolved by consensus. Information not explicitly reported in the source publications was not inferred. All frequencies and overlaps reported in the article can be reproduced from this file. The data are provided in Excel format (with formulas) and as CSV files (one per sheet).