{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2020:VU63GHVS46PRZPDXUKYSPJATD5","short_pith_number":"pith:VU63GHVS","schema_version":"1.0","canonical_sha256":"ad3db31eb2e79f1cbc77a2b127a4131f4d689859e8c5fde1076718faa0aef8a5","source":{"kind":"arxiv","id":"2007.05389","version":1},"attestation_state":"computed","paper":{"title":"COBRA: Compression via Abstraction of Provenance for Hypothetical Reasoning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.DB","authors_text":"Daniel Deutch, Noam Rinetzky, Yuval Moskovitch","submitted_at":"2020-07-10T13:55:09Z","abstract_excerpt":"Data analytics often involves hypothetical reasoning: repeatedly modifying the data and observing the induced effect on the computation result of a data-centric application. Recent work has proposed to leverage ideas from data provenance tracking towards supporting efficient hypothetical reasoning: instead of a costly re-execution of the underlying application, one may assign values to a pre-computed provenance expression. A prime challenge in leveraging this approach for large-scale data and complex applications lies in the size of the provenance. To this end, we present a framework that allo"},"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":"2007.05389","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DB","submitted_at":"2020-07-10T13:55:09Z","cross_cats_sorted":[],"title_canon_sha256":"99bb40a3655c713507a67a2b928e4ff01998221a97671d9671b40910c776edce","abstract_canon_sha256":"71460d770cfa73dd61fee32828242d7564d69bcc3b22e0b1cbdc8795e4d55331"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:17:46.110408Z","signature_b64":"zPK441mlUkYp0+LYL/wShK5lPZQmcVrVbsnszmqNcZJfsusrUasuRYd7Ocdpd+O3EXZHhE8Wn0ZIBHMn0uAxDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ad3db31eb2e79f1cbc77a2b127a4131f4d689859e8c5fde1076718faa0aef8a5","last_reissued_at":"2026-07-05T01:17:46.110062Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:17:46.110062Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"COBRA: Compression via Abstraction of Provenance for Hypothetical Reasoning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.DB","authors_text":"Daniel Deutch, Noam Rinetzky, Yuval Moskovitch","submitted_at":"2020-07-10T13:55:09Z","abstract_excerpt":"Data analytics often involves hypothetical reasoning: repeatedly modifying the data and observing the induced effect on the computation result of a data-centric application. Recent work has proposed to leverage ideas from data provenance tracking towards supporting efficient hypothetical reasoning: instead of a costly re-execution of the underlying application, one may assign values to a pre-computed provenance expression. A prime challenge in leveraging this approach for large-scale data and complex applications lies in the size of the provenance. To this end, we present a framework that allo"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2007.05389","kind":"arxiv","version":1},"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/2007.05389/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":"2007.05389","created_at":"2026-07-05T01:17:46.110121+00:00"},{"alias_kind":"arxiv_version","alias_value":"2007.05389v1","created_at":"2026-07-05T01:17:46.110121+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2007.05389","created_at":"2026-07-05T01:17:46.110121+00:00"},{"alias_kind":"pith_short_12","alias_value":"VU63GHVS46PR","created_at":"2026-07-05T01:17:46.110121+00:00"},{"alias_kind":"pith_short_16","alias_value":"VU63GHVS46PRZPDX","created_at":"2026-07-05T01:17:46.110121+00:00"},{"alias_kind":"pith_short_8","alias_value":"VU63GHVS","created_at":"2026-07-05T01:17:46.110121+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/VU63GHVS46PRZPDXUKYSPJATD5","json":"https://pith.science/pith/VU63GHVS46PRZPDXUKYSPJATD5.json","graph_json":"https://pith.science/api/pith-number/VU63GHVS46PRZPDXUKYSPJATD5/graph.json","events_json":"https://pith.science/api/pith-number/VU63GHVS46PRZPDXUKYSPJATD5/events.json","paper":"https://pith.science/paper/VU63GHVS"},"agent_actions":{"view_html":"https://pith.science/pith/VU63GHVS46PRZPDXUKYSPJATD5","download_json":"https://pith.science/pith/VU63GHVS46PRZPDXUKYSPJATD5.json","view_paper":"https://pith.science/paper/VU63GHVS","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2007.05389&json=true","fetch_graph":"https://pith.science/api/pith-number/VU63GHVS46PRZPDXUKYSPJATD5/graph.json","fetch_events":"https://pith.science/api/pith-number/VU63GHVS46PRZPDXUKYSPJATD5/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/VU63GHVS46PRZPDXUKYSPJATD5/action/timestamp_anchor","attest_storage":"https://pith.science/pith/VU63GHVS46PRZPDXUKYSPJATD5/action/storage_attestation","attest_author":"https://pith.science/pith/VU63GHVS46PRZPDXUKYSPJATD5/action/author_attestation","sign_citation":"https://pith.science/pith/VU63GHVS46PRZPDXUKYSPJATD5/action/citation_signature","submit_replication":"https://pith.science/pith/VU63GHVS46PRZPDXUKYSPJATD5/action/replication_record"}},"created_at":"2026-07-05T01:17:46.110121+00:00","updated_at":"2026-07-05T01:17:46.110121+00:00"}