10.18710/NZHGW3 Barahmand, Zahir Zahir Barahmand https://orcid.org/0000-0001-9031-596X University of South-Eastern Norway DataverseNO 2026 Engineering systems thinking model sustainability large-scale study strategic decision-making University of South-Eastern Norway University of South-Eastern Norway Barahmand, Zahir Zahir Barahmand University of South-Eastern Norway Eikeland, Marianne Marianne Eikeland Wang, Liang Liang Wang Heirati, Nima Nima Heirati 2026-02-26 2026-02-26 2026-02-25 2026-02-26 2026-04-22 2026-01-15/2026-02-20 diagnostic matrix;Used systems thinking model references;SEEDS components in a case study 10.18710/NZHGW3/RQCJ3Q 10.18710/NZHGW3/SU6LUK 10.18710/NZHGW3/8NPKIJ 173388 3733 9895 13707 20263 7764 4739 13846 186962 26081 16890 application/pdf text/comma-separated-values text/comma-separated-values text/plain application/vnd.openxmlformats-officedocument.spreadsheetml.sheet text/comma-separated-values text/comma-separated-values text/plain application/zip application/zip text/plain 3.0 Creative Commons Attribution 4.0 International License. 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. University of South-Eastern Norway