{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,6]],"date-time":"2026-10-06T06:18:26Z","timestamp":1791267506061,"version":"4.1.0"},"reference-count":22,"publisher":"Association for Computing Machinery (ACM)","issue":"10","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Proc. VLDB Endow."],"published-print":{"date-parts":[[2014,6]]},"abstract":"<jats:p>The Resource Description Framework (RDF) is a standard for conceptually describing data on the Web, and SPARQL is the query language for RDF. As RDF is becoming widely utilized, RDF data management systems are being exposed to more diverse and dynamic workloads. Existing systems are workload-oblivious, and are therefore unable to provide consistently good performance. We propose a vision for a workload-aware and adaptive system. 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