Supplementary data for: A governance-aware systems thinking architecture for sustainability at scale

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Barahmand, Zahir, 2026, "Supplementary data for: A governance-aware systems thinking architecture for sustainability at scale", https://doi.org/10.18710/NZHGW3, DataverseNO, V1
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This dataset supports the paper “A Governance-Aware Systems Thinking Architecture for Sustainability at Scale.” The study addresses a key challenge in large-scale sustainability research: how to ensure transparency, consistency, and auditability when integrating heterogeneous evidence and systems thinking approaches. The paper introduces STAI³RS, a governance framework designed to ensure rigor and reproducibility in sustainability synthesis. STAI³RS stands for Scalable, Transparent, Analytical, Interpretable, Reliable, Reproducible, Robust, and Systematic, and provides cross-cutting principles and procedural cues for applying systems thinking methods at scale. Building on this governance layer, the paper presents SEEDS (Systems Evidence Extraction and Decision Support), a six-component operational model that structures sustainability synthesis from problem framing to decision support. SEEDS integrates boundary governance, evidence extraction, harmonization, synthesis, and iterative learning into a transparent and auditable workflow. The dataset includes materials that document the governance diagnostics and operational implementation of these frameworks. In particular, Table S2 presents a case study demonstrating the SEEDS workflow in practice through a large-scale feedstock evidence mapping study spanning over 130,000 peer-reviewed studies across biomass- and waste-to-X conversion technologies. This case study illustrates how governance rules, audit trails, and harmonization procedures enable reproducible synthesis across three large scientific corpora. SEEDS_components_in_practice These materials support reuse, verification, and extension of governance-aware systems thinking approaches in sustainability research and decision support. (2026-02-25)
Subject Engineering
Keyword systems thinking model, sustainability, large-scale study, strategic decision-making
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00_ReadMe.txt
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Published Feb 26, 2026
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MD5: 34c4d377fc705ab6787ab6763b00f972
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classical_systems_thinking_model_references.csv
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Published Feb 26, 2026
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A structured reference list of the systems thinking traditions reviewed in the study. The file provides the bibliographic foundation supporting the governance diagnostic analysis and enables traceability to the original methodological sources.
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SEEDS_components_in_practice.pdf
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Published Feb 26, 2026
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Supplementary Table S2 documenting the operational instantiation of the SEEDS (Systems Evidence Extraction and Decision Support) model under STAI3RS governance principles. The table describes how governance procedures — including boundary specification, assumption registers, uncertainty handling, harmonization, audit trails, and reproducibility mechanisms — are implemented across the SEEDS workflow.
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systems_thinking_governance_diagnostic_matrix.csv
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Published Feb 26, 2026
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MD5: 6a0bc1d34044b36a8d1e059668669ecb
A governance diagnostic matrix synthesizing insights from classical systems thinking traditions. The file documents each tradition’s purpose, known limitations in large-scale sustainability synthesis, and corresponding governance mitigation requirements. This matrix formed the analytical basis for deriving the STAI3RS governance principles.
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