{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:RQDEVXFN6S56WKLZ66HAHLPXQE","short_pith_number":"pith:RQDEVXFN","schema_version":"1.0","canonical_sha256":"8c064adcadf4bbeb2979f78e03adf7810900d1551c6ab2661ddaff982c4e41db","source":{"kind":"arxiv","id":"2409.01102","version":2},"attestation_state":"computed","paper":{"title":"GQL and SQL/PGQ: Theoretical Models and Expressive Power","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.DB","authors_text":"Alexandra Rogova, Am\\'elie Gheerbrant, Leonid Libkin, Liat Peterfreund","submitted_at":"2024-09-02T09:31:50Z","abstract_excerpt":"SQL/PGQ and GQL are very recent international standards for querying property graphs: SQL/PGQ specifies how to query relational representations of property graphs in SQL, while GQL is a standalone language for graph databases. The rapid industrial development of these standards left the academic community trailing in its wake. While digests of the languages have appeared, we do not yet have concise foundational models like relational algebra and calculus for relational databases that enable the formal study of languages, including their expressiveness and limitations. At the same time, work on"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2409.01102","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.DB","submitted_at":"2024-09-02T09:31:50Z","cross_cats_sorted":[],"title_canon_sha256":"d80c96590a78b972915c237eec230e6b697c643b25feb4c285393b274d4b5317","abstract_canon_sha256":"924908223c4996113d8473635396b4c49c636be38c0295fc058cd418cc1bd952"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:03:03.675580Z","signature_b64":"TeE+nSO686AKp84OlQccei/J0Ywg1ghu3OBmu7Fnaq6g2T/887Mzo6gtE19hQY/mpaBY34Y+EfT7iOQNEg4qBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8c064adcadf4bbeb2979f78e03adf7810900d1551c6ab2661ddaff982c4e41db","last_reissued_at":"2026-07-05T09:03:03.675090Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:03:03.675090Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"GQL and SQL/PGQ: Theoretical Models and Expressive Power","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.DB","authors_text":"Alexandra Rogova, Am\\'elie Gheerbrant, Leonid Libkin, Liat Peterfreund","submitted_at":"2024-09-02T09:31:50Z","abstract_excerpt":"SQL/PGQ and GQL are very recent international standards for querying property graphs: SQL/PGQ specifies how to query relational representations of property graphs in SQL, while GQL is a standalone language for graph databases. The rapid industrial development of these standards left the academic community trailing in its wake. While digests of the languages have appeared, we do not yet have concise foundational models like relational algebra and calculus for relational databases that enable the formal study of languages, including their expressiveness and limitations. At the same time, work on"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.01102","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2409.01102/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2409.01102","created_at":"2026-07-05T09:03:03.675148+00:00"},{"alias_kind":"arxiv_version","alias_value":"2409.01102v2","created_at":"2026-07-05T09:03:03.675148+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.01102","created_at":"2026-07-05T09:03:03.675148+00:00"},{"alias_kind":"pith_short_12","alias_value":"RQDEVXFN6S56","created_at":"2026-07-05T09:03:03.675148+00:00"},{"alias_kind":"pith_short_16","alias_value":"RQDEVXFN6S56WKLZ","created_at":"2026-07-05T09:03:03.675148+00:00"},{"alias_kind":"pith_short_8","alias_value":"RQDEVXFN","created_at":"2026-07-05T09:03:03.675148+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2604.02553","citing_title":"Efficient Path Query Processing in Relational Database Systems","ref_index":20,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/RQDEVXFN6S56WKLZ66HAHLPXQE","json":"https://pith.science/pith/RQDEVXFN6S56WKLZ66HAHLPXQE.json","graph_json":"https://pith.science/api/pith-number/RQDEVXFN6S56WKLZ66HAHLPXQE/graph.json","events_json":"https://pith.science/api/pith-number/RQDEVXFN6S56WKLZ66HAHLPXQE/events.json","paper":"https://pith.science/paper/RQDEVXFN"},"agent_actions":{"view_html":"https://pith.science/pith/RQDEVXFN6S56WKLZ66HAHLPXQE","download_json":"https://pith.science/pith/RQDEVXFN6S56WKLZ66HAHLPXQE.json","view_paper":"https://pith.science/paper/RQDEVXFN","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2409.01102&json=true","fetch_graph":"https://pith.science/api/pith-number/RQDEVXFN6S56WKLZ66HAHLPXQE/graph.json","fetch_events":"https://pith.science/api/pith-number/RQDEVXFN6S56WKLZ66HAHLPXQE/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/RQDEVXFN6S56WKLZ66HAHLPXQE/action/timestamp_anchor","attest_storage":"https://pith.science/pith/RQDEVXFN6S56WKLZ66HAHLPXQE/action/storage_attestation","attest_author":"https://pith.science/pith/RQDEVXFN6S56WKLZ66HAHLPXQE/action/author_attestation","sign_citation":"https://pith.science/pith/RQDEVXFN6S56WKLZ66HAHLPXQE/action/citation_signature","submit_replication":"https://pith.science/pith/RQDEVXFN6S56WKLZ66HAHLPXQE/action/replication_record"}},"created_at":"2026-07-05T09:03:03.675148+00:00","updated_at":"2026-07-05T09:03:03.675148+00:00"}