发表机构
Institute for Artificial Intelligence, University of Stuttgart; Bosch Corporate Research; Web and Internet Science Research Group, University of Southampton（斯图加特大学人工智能研究所; 博世企业研究部; 南安普顿大学网络与互联网科学研究组）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对循环工厂中含多维不确定数值数据的知识图谱查询问题，提出ProbSPARQL，它将不确定数值建模为随机变量，支持相关表达式、过滤器和连接。通过实现和评估，展示了其在引擎内执行的可行性及相关性能优势。
AI 中文摘要
SFB 1574循环工厂正在构建一个共享知识图谱基础设施来集成关于退货产品的数据。核心挑战在于循环工厂数据包含的数值测量具有多维度、不确定性等特点，而当前技术缺乏对此类数据的原生支持。为此提出ProbSPARQL，它将不确定数值建模为随机变量，支持分布感知表达式等。在Apache Jena ARQ上实现并通过Fuseki兼容层暴露。使用项目测量片段评估适用性，在控制基准上评估可扩展性，结果显示了引擎内执行的可行性等。
英文摘要
The SFB 1574 Circular Factory is building a shared knowledge graph infrastructure for integrating data about returned products. A central challenge is that circular-factory data include numeric measurements that (i) originate from sensors or are derived from sensor-based measurements, (ii) are frequently multi-dimensional, and (iii) are inherently uncertain, while downstream triage, validation, reliability-modeling, and reassembly-planning modules require queryable uncertainty representations. Current RDF and SPARQL technologies lack native support for harmonized querying and analysis of such uncertain numeric measurement data. To address this gap, we present ProbSPARQL, an upward-compatible SPARQL extension developed as an early-stage query-layer pilot for this infrastructure. ProbSPARQL models uncertain numeric values as random variables whose distributions are encoded by probabilistic RDF literal datatypes, and supports distribution-aware expressions, probabilistic filters, and divergence-based joins. We implement ProbSPARQL on Apache Jena ARQ and expose it through a Fuseki-compatible execution layer. We assess real-data applicability using project-derived measurement fragments covering GMM-encoded uncertainty and histogram-based empirical roughness distributions, and evaluate scalability separately on controlled ontology-conformant benchmarks with up to 5,000 angle-grinder instances and 1.5M triples. The results show feasible in-engine execution, filter-pushdown speedups over application-layer post-processing, and latency-accuracy trade-offs among divergence-join decision strategies.
Comments18 pages, 5 figures, 1 table. Accepted at ISWC 2026, camera-ready version. Supplementary material and reproducibility artifacts are available online
