{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:MPY6OCQNSVZONLYN23ZFMJHZ73","short_pith_number":"pith:MPY6OCQN","canonical_record":{"source":{"id":"2008.13028","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DB","submitted_at":"2020-08-29T18:12:08Z","cross_cats_sorted":["cs.HC"],"title_canon_sha256":"0f79e5061636b93b1dff6c0cb5135998860685f0e036ec1225943770eda0d70c","abstract_canon_sha256":"3fd0b30c30e1f7d3528ceaa20122301d6dcb887be8feb8b8f78c0419f1b02b28"},"schema_version":"1.0"},"canonical_sha256":"63f1e70a0d9572e6af0dd6f25624f9feec4fa616d4a4efba273767caff1986df","source":{"kind":"arxiv","id":"2008.13028","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2008.13028","created_at":"2026-07-05T01:31:33Z"},{"alias_kind":"arxiv_version","alias_value":"2008.13028v1","created_at":"2026-07-05T01:31:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2008.13028","created_at":"2026-07-05T01:31:33Z"},{"alias_kind":"pith_short_12","alias_value":"MPY6OCQNSVZO","created_at":"2026-07-05T01:31:33Z"},{"alias_kind":"pith_short_16","alias_value":"MPY6OCQNSVZONLYN","created_at":"2026-07-05T01:31:33Z"},{"alias_kind":"pith_short_8","alias_value":"MPY6OCQN","created_at":"2026-07-05T01:31:33Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:MPY6OCQNSVZONLYN23ZFMJHZ73","target":"record","payload":{"canonical_record":{"source":{"id":"2008.13028","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DB","submitted_at":"2020-08-29T18:12:08Z","cross_cats_sorted":["cs.HC"],"title_canon_sha256":"0f79e5061636b93b1dff6c0cb5135998860685f0e036ec1225943770eda0d70c","abstract_canon_sha256":"3fd0b30c30e1f7d3528ceaa20122301d6dcb887be8feb8b8f78c0419f1b02b28"},"schema_version":"1.0"},"canonical_sha256":"63f1e70a0d9572e6af0dd6f25624f9feec4fa616d4a4efba273767caff1986df","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:31:33.791148Z","signature_b64":"4YmdGcHix33u6Pq/btKewIqur6CNnoGaphLClZ8NOY1eDh6cfM6t3n3TVcLOoObxV2MqY2vBtLepqbJiTKlLAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"63f1e70a0d9572e6af0dd6f25624f9feec4fa616d4a4efba273767caff1986df","last_reissued_at":"2026-07-05T01:31:33.790713Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:31:33.790713Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2008.13028","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T01:31:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GOwFfgwFjjKstuBtxyrc2EL4Qf7oLd0IEfU30/s8o6RoInbQ2j5E9BW3r0ElNoAyjS3WQCjSXzVfbUYK92FmAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T07:37:35.426508Z"},"content_sha256":"6661552d837eb20e216d6942cc64431b67f8f23e80089b06536b886b91ce1e83","schema_version":"1.0","event_id":"sha256:6661552d837eb20e216d6942cc64431b67f8f23e80089b06536b886b91ce1e83"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:MPY6OCQNSVZONLYN23ZFMJHZ73","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"STULL: Unbiased Online Sampling for Visual Exploration of Large Spatiotemporal Data","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.HC"],"primary_cat":"cs.DB","authors_text":"Anas Daghistani, Calvin Yau, David S. Ebert, Guizhen Wang, JingJing Guo, Jos\\'e Florencio de Queiroz Neto, Mingjie Tang, Morteza Karimzadeh, Walid G. Aref","submitted_at":"2020-08-29T18:12:08Z","abstract_excerpt":"Online sampling-supported visual analytics is increasingly important, as it allows users to explore large datasets with acceptable approximate answers at interactive rates. However, existing online spatiotemporal sampling techniques are often biased, as most researchers have primarily focused on reducing computational latency. Biased sampling approaches select data with unequal probabilities and produce results that do not match the exact data distribution, leading end users to incorrect interpretations. In this paper, we propose a novel approach to perform unbiased online sampling of large sp"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2008.13028","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/2008.13028/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T01:31:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"bcULuljtbovJprOGCXkHCEgOBWvmTEOd3Vl2k2LfEVk856oAk0sWDAwMofWDEJDcvsutxwYiE09CFLZDkHOdBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T07:37:35.427078Z"},"content_sha256":"1fa3ce606c4c9db2761aa45e960dd67bc328a5ad6d88736cd43c12f782ec94be","schema_version":"1.0","event_id":"sha256:1fa3ce606c4c9db2761aa45e960dd67bc328a5ad6d88736cd43c12f782ec94be"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/MPY6OCQNSVZONLYN23ZFMJHZ73/bundle.json","state_url":"https://pith.science/pith/MPY6OCQNSVZONLYN23ZFMJHZ73/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/MPY6OCQNSVZONLYN23ZFMJHZ73/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-18T07:37:35Z","links":{"resolver":"https://pith.science/pith/MPY6OCQNSVZONLYN23ZFMJHZ73","bundle":"https://pith.science/pith/MPY6OCQNSVZONLYN23ZFMJHZ73/bundle.json","state":"https://pith.science/pith/MPY6OCQNSVZONLYN23ZFMJHZ73/state.json","well_known_bundle":"https://pith.science/.well-known/pith/MPY6OCQNSVZONLYN23ZFMJHZ73/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:MPY6OCQNSVZONLYN23ZFMJHZ73","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"3fd0b30c30e1f7d3528ceaa20122301d6dcb887be8feb8b8f78c0419f1b02b28","cross_cats_sorted":["cs.HC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DB","submitted_at":"2020-08-29T18:12:08Z","title_canon_sha256":"0f79e5061636b93b1dff6c0cb5135998860685f0e036ec1225943770eda0d70c"},"schema_version":"1.0","source":{"id":"2008.13028","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2008.13028","created_at":"2026-07-05T01:31:33Z"},{"alias_kind":"arxiv_version","alias_value":"2008.13028v1","created_at":"2026-07-05T01:31:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2008.13028","created_at":"2026-07-05T01:31:33Z"},{"alias_kind":"pith_short_12","alias_value":"MPY6OCQNSVZO","created_at":"2026-07-05T01:31:33Z"},{"alias_kind":"pith_short_16","alias_value":"MPY6OCQNSVZONLYN","created_at":"2026-07-05T01:31:33Z"},{"alias_kind":"pith_short_8","alias_value":"MPY6OCQN","created_at":"2026-07-05T01:31:33Z"}],"graph_snapshots":[{"event_id":"sha256:1fa3ce606c4c9db2761aa45e960dd67bc328a5ad6d88736cd43c12f782ec94be","target":"graph","created_at":"2026-07-05T01:31:33Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2008.13028/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Online sampling-supported visual analytics is increasingly important, as it allows users to explore large datasets with acceptable approximate answers at interactive rates. However, existing online spatiotemporal sampling techniques are often biased, as most researchers have primarily focused on reducing computational latency. Biased sampling approaches select data with unequal probabilities and produce results that do not match the exact data distribution, leading end users to incorrect interpretations. In this paper, we propose a novel approach to perform unbiased online sampling of large sp","authors_text":"Anas Daghistani, Calvin Yau, David S. Ebert, Guizhen Wang, JingJing Guo, Jos\\'e Florencio de Queiroz Neto, Mingjie Tang, Morteza Karimzadeh, Walid G. Aref","cross_cats":["cs.HC"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DB","submitted_at":"2020-08-29T18:12:08Z","title":"STULL: Unbiased Online Sampling for Visual Exploration of Large Spatiotemporal Data"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2008.13028","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:6661552d837eb20e216d6942cc64431b67f8f23e80089b06536b886b91ce1e83","target":"record","created_at":"2026-07-05T01:31:33Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"3fd0b30c30e1f7d3528ceaa20122301d6dcb887be8feb8b8f78c0419f1b02b28","cross_cats_sorted":["cs.HC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DB","submitted_at":"2020-08-29T18:12:08Z","title_canon_sha256":"0f79e5061636b93b1dff6c0cb5135998860685f0e036ec1225943770eda0d70c"},"schema_version":"1.0","source":{"id":"2008.13028","kind":"arxiv","version":1}},"canonical_sha256":"63f1e70a0d9572e6af0dd6f25624f9feec4fa616d4a4efba273767caff1986df","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"63f1e70a0d9572e6af0dd6f25624f9feec4fa616d4a4efba273767caff1986df","first_computed_at":"2026-07-05T01:31:33.790713Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:31:33.790713Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"4YmdGcHix33u6Pq/btKewIqur6CNnoGaphLClZ8NOY1eDh6cfM6t3n3TVcLOoObxV2MqY2vBtLepqbJiTKlLAA==","signature_status":"signed_v1","signed_at":"2026-07-05T01:31:33.791148Z","signed_message":"canonical_sha256_bytes"},"source_id":"2008.13028","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6661552d837eb20e216d6942cc64431b67f8f23e80089b06536b886b91ce1e83","sha256:1fa3ce606c4c9db2761aa45e960dd67bc328a5ad6d88736cd43c12f782ec94be"],"state_sha256":"7afa4f07bd98244e6a07c5747d567b8868d4a8b6bdd4cfd43aec5319ad45f64a"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"HBYZBE8Ia+UMFVKy9oiwTvR3L1a7IV/V5SnYEW7kITNxq5PAzYrXi6gp//ppGYVQIKrvgbTTi1ULlnUejZaWCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-18T07:37:35.430900Z","bundle_sha256":"468581227a8ab5162f31fa127faa296e5b0ce44e7519e8c423216d28127e035e"}}