{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:BU6EU2OCP2EU6IKEUZWHG3FOXY","short_pith_number":"pith:BU6EU2OC","schema_version":"1.0","canonical_sha256":"0d3c4a69c27e894f2144a66c736caebe02e1626eab770a36525a207c51ba66ae","source":{"kind":"arxiv","id":"2406.01964","version":1},"attestation_state":"computed","paper":{"title":"Measure-Observe-Remeasure: An Interactive Paradigm for Differentially-Private Exploratory Analysis","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DB","cs.HC"],"primary_cat":"cs.CR","authors_text":"Ali Sarvghad, Gerome Miklau, Hyeok Kim, Jessica Hullman, Narges Mahyar, Priyanka Nanayakkara, Yifan Wu","submitted_at":"2024-06-04T04:48:40Z","abstract_excerpt":"Differential privacy (DP) has the potential to enable privacy-preserving analysis on sensitive data, but requires analysts to judiciously spend a limited ``privacy loss budget'' $\\epsilon$ across queries. Analysts conducting exploratory analyses do not, however, know all queries in advance and seldom have DP expertise. Thus, they are limited in their ability to specify $\\epsilon$ allotments across queries prior to an analysis. To support analysts in spending $\\epsilon$ efficiently, we propose a new interactive analysis paradigm, Measure-Observe-Remeasure, where analysts ``measure'' the databas"},"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":"2406.01964","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2024-06-04T04:48:40Z","cross_cats_sorted":["cs.DB","cs.HC"],"title_canon_sha256":"e3c1bdced04e9435e53fa42a302964ee4fad93e2a1f2a70b5a5d3fbb2f024e36","abstract_canon_sha256":"dfc494eff8a2ff64dc50839fc2498ac5aeb7e5e5a2ca66c10adb0d92f68c6e79"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:27:12.208471Z","signature_b64":"6xQ322cKwyIG8B7qRhNehuGpNsI1ZUAAmhFpM8oP0+BFC1FFE9PQaWrq8q7y7nWL06ps5fM7eo2zv0WgePOEBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0d3c4a69c27e894f2144a66c736caebe02e1626eab770a36525a207c51ba66ae","last_reissued_at":"2026-07-05T08:27:12.208058Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:27:12.208058Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Measure-Observe-Remeasure: An Interactive Paradigm for Differentially-Private Exploratory Analysis","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DB","cs.HC"],"primary_cat":"cs.CR","authors_text":"Ali Sarvghad, Gerome Miklau, Hyeok Kim, Jessica Hullman, Narges Mahyar, Priyanka Nanayakkara, Yifan Wu","submitted_at":"2024-06-04T04:48:40Z","abstract_excerpt":"Differential privacy (DP) has the potential to enable privacy-preserving analysis on sensitive data, but requires analysts to judiciously spend a limited ``privacy loss budget'' $\\epsilon$ across queries. Analysts conducting exploratory analyses do not, however, know all queries in advance and seldom have DP expertise. Thus, they are limited in their ability to specify $\\epsilon$ allotments across queries prior to an analysis. To support analysts in spending $\\epsilon$ efficiently, we propose a new interactive analysis paradigm, Measure-Observe-Remeasure, where analysts ``measure'' the databas"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.01964","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/2406.01964/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":"2406.01964","created_at":"2026-07-05T08:27:12.208114+00:00"},{"alias_kind":"arxiv_version","alias_value":"2406.01964v1","created_at":"2026-07-05T08:27:12.208114+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.01964","created_at":"2026-07-05T08:27:12.208114+00:00"},{"alias_kind":"pith_short_12","alias_value":"BU6EU2OCP2EU","created_at":"2026-07-05T08:27:12.208114+00:00"},{"alias_kind":"pith_short_16","alias_value":"BU6EU2OCP2EU6IKE","created_at":"2026-07-05T08:27:12.208114+00:00"},{"alias_kind":"pith_short_8","alias_value":"BU6EU2OC","created_at":"2026-07-05T08:27:12.208114+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2412.16825","citing_title":"SoK: Usability Studies in Differential Privacy","ref_index":31,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/BU6EU2OCP2EU6IKEUZWHG3FOXY","json":"https://pith.science/pith/BU6EU2OCP2EU6IKEUZWHG3FOXY.json","graph_json":"https://pith.science/api/pith-number/BU6EU2OCP2EU6IKEUZWHG3FOXY/graph.json","events_json":"https://pith.science/api/pith-number/BU6EU2OCP2EU6IKEUZWHG3FOXY/events.json","paper":"https://pith.science/paper/BU6EU2OC"},"agent_actions":{"view_html":"https://pith.science/pith/BU6EU2OCP2EU6IKEUZWHG3FOXY","download_json":"https://pith.science/pith/BU6EU2OCP2EU6IKEUZWHG3FOXY.json","view_paper":"https://pith.science/paper/BU6EU2OC","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2406.01964&json=true","fetch_graph":"https://pith.science/api/pith-number/BU6EU2OCP2EU6IKEUZWHG3FOXY/graph.json","fetch_events":"https://pith.science/api/pith-number/BU6EU2OCP2EU6IKEUZWHG3FOXY/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/BU6EU2OCP2EU6IKEUZWHG3FOXY/action/timestamp_anchor","attest_storage":"https://pith.science/pith/BU6EU2OCP2EU6IKEUZWHG3FOXY/action/storage_attestation","attest_author":"https://pith.science/pith/BU6EU2OCP2EU6IKEUZWHG3FOXY/action/author_attestation","sign_citation":"https://pith.science/pith/BU6EU2OCP2EU6IKEUZWHG3FOXY/action/citation_signature","submit_replication":"https://pith.science/pith/BU6EU2OCP2EU6IKEUZWHG3FOXY/action/replication_record"}},"created_at":"2026-07-05T08:27:12.208114+00:00","updated_at":"2026-07-05T08:27:12.208114+00:00"}