Literature-KG v0.1 — RDF Serialisation of a 3,397-Work Systemic-Resilience Bibliometric Corpus (Scopus + OpenAlex, retrieval 2026-04-17)

The Literature-KG is the bibliometric-landscape knowledge graph underpinning Section 1.4 (“Bibliometric Landscape of Systemic-Resilience Research”) and Section 1.6 (“Dual-Graph Companion”) of Bühler, Hollenbach et al., “Systemic Resilience of Interdependent Infrastructure: Multi-Hazard Interactions, Cascading Failures, and the Governance of Climate Risk” (Natural Hazards, Springer, under review; DOI: 10.XXXX/natural-hazards-XXXXX — to be updated upon acceptance). v0.1 bundle: the RDF serialisation graph/literature-kg.ttl (˜151,508 triples — 3,397 lit:ReviewCorpusArticle instances, 12,033 deduplicated foaf:Person authors, LDA k=10 topic scheme, Louvain keyword and citation communities, PageRank on the top-200 directed citation subgraph) together with the reproducibility scripts scripts/build_literature_kg.py and scripts/fetch_openalex_institutions.py. Source data: Scopus Search API (English articles/reviews/conference papers 2000–2025 mentioning systemic resilience, infrastructure resilience, or network resilience combined with climate, network vulnerability, or critical infrastructure) + OpenAlex (CC0). Deduplicated by DOI (OpenAlex first, Scopus filling gaps) and by normalised title. Raw retrieval parquet is retained under CC0-pass-through from OpenAlex; the Scopus contribution is one unique record. Ontology: the graph uses FaBiO (fabio:JournalArticle), CiTO (cito:cites), FOAF (foaf:Person), SKOS (topic and community concept schemes), and local lit: properties. It is jointly instantiable with the IRG v0.3.1 core ontology (Zenodo, sibling record — DOI forthcoming) via the irg-lit.ttl bridge for the dual-graph analyses. Paper-F usage: the graph is the row-source for Phase-4 insight queries Q12–Q19 (per-peril disconnect, geographic disconnect, temporal lag, sector coverage, top-impact papers vs. top-events — the 0-of-15 match rate reported in Paper F §2.8.5 is derived from this graph joined with the Damage-KG).文献知识图谱（Literature-KG）是支撑Bühler、Hollenbach等人发表于《自然灾害》（Springer旗下，审稿中，DOI：10.XXXX/natural-hazards-XXXXX——录用后更新）的论文《相互依存基础设施的系统韧性：多灾害交互、级联失效与气候风险治理》中1.4节「系统韧性研究的文献计量全景」与1.6节「双图谱配套」的文献计量全景知识图谱。 v0.1版本数据包包含RDF序列化图谱literature-kg.ttl（约151,508条三元组——包含3,397个lit:ReviewCorpusArticle实例、12,033个去重后的foaf:Person作者实体，采用潜在狄利克雷分配（Latent Dirichlet Allocation，LDA）主题数k=10的主题方案，结合卢万（Louvain）关键词与引文社区发现算法，以及基于前200个有向引文子图的页面排名（PageRank）算法），附带可复现脚本scripts/build_literature_kg.py与scripts/fetch_openalex_institutions.py。 源数据来源于Scopus搜索API（2000-2025年收录提及系统韧性、基础设施韧性或网络韧性，且结合气候、网络脆弱性或关键基础设施的英文文章、综述与会议论文）以及OpenAlex（采用CC0协议）。数据通过DOI（优先以OpenAlex数据去重，Scopus填补空缺）与标准化标题进行去重处理。原始检索的Parquet格式数据保留自OpenAlex的CC0-直通授权；Scopus贡献的数据为单条唯一记录。 本图谱采用的本体包括FaBiO（fabio:JournalArticle）、CiTO（cito:cites）、FOAF（foaf:Person）、SKOS（主题与社区概念体系）以及自定义lit:属性。通过irg-lit.ttl桥接文件，可与IRG v0.3.1核心本体（Zenodo平台关联记录——DOI待公布）联合实例化，用于双图谱分析。 F论文应用场景：本图谱为第4阶段洞察查询Q12至Q19提供行数据源，涵盖单灾害断开连接、地理断开连接、时间滞后、行业覆盖范围、高影响力论文与高影响事件；F论文§2.8.5中报告的15项查询0匹配率，即0-of-15 match rate，是通过本图谱与损伤知识图谱（Damage-KG）关联推导得出。