{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:A4ZHTSY3JMQBCTUOL5CPFAAIMQ","short_pith_number":"pith:A4ZHTSY3","schema_version":"1.0","canonical_sha256":"073279cb1b4b20114e8e5f44f280086425f367f128f77cc3d750eb97d1ffa2cd","source":{"kind":"arxiv","id":"1907.11762","version":1},"attestation_state":"computed","paper":{"title":"Multivariate Pointwise Information-Driven Data Sampling and Visualization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.GR","cs.IT","math.IT","stat.AP"],"primary_cat":"cs.HC","authors_text":"Ayan Biswas, James Ahrens, Soumya Dutta","submitted_at":"2019-07-26T19:32:53Z","abstract_excerpt":"With increasing computing capabilities of modern supercomputers, the size of the data generated from the scientific simulations is growing rapidly. As a result, application scientists need effective data summarization techniques that can reduce large-scale multivariate spatiotemporal data sets while preserving the important data properties so that the reduced data can answer domain-specific queries involving multiple variables with sufficient accuracy. While analyzing complex scientific events, domain experts often analyze and visualize two or more variables together to obtain a better underst"},"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":"1907.11762","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.HC","submitted_at":"2019-07-26T19:32:53Z","cross_cats_sorted":["cs.GR","cs.IT","math.IT","stat.AP"],"title_canon_sha256":"7e546b4caa93fca9580cbea1a39be3c832730ea66bfc6687158d09513fa794e7","abstract_canon_sha256":"eafef7957c4ee38a895fcb819ab52cd114d75ed7989f4e581e556175435c5787"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:39:23.149775Z","signature_b64":"1feshjzOQlL/dbIpltE+QJxQwJpf3CO64o/fqwUTGO8CImNSICK1rMCGaPMq301hK4Vpy0lV97SNzJza5+67BA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"073279cb1b4b20114e8e5f44f280086425f367f128f77cc3d750eb97d1ffa2cd","last_reissued_at":"2026-05-17T23:39:23.149234Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:39:23.149234Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Multivariate Pointwise Information-Driven Data Sampling and Visualization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.GR","cs.IT","math.IT","stat.AP"],"primary_cat":"cs.HC","authors_text":"Ayan Biswas, James Ahrens, Soumya Dutta","submitted_at":"2019-07-26T19:32:53Z","abstract_excerpt":"With increasing computing capabilities of modern supercomputers, the size of the data generated from the scientific simulations is growing rapidly. As a result, application scientists need effective data summarization techniques that can reduce large-scale multivariate spatiotemporal data sets while preserving the important data properties so that the reduced data can answer domain-specific queries involving multiple variables with sufficient accuracy. While analyzing complex scientific events, domain experts often analyze and visualize two or more variables together to obtain a better underst"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.11762","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":""},"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":"1907.11762","created_at":"2026-05-17T23:39:23.149335+00:00"},{"alias_kind":"arxiv_version","alias_value":"1907.11762v1","created_at":"2026-05-17T23:39:23.149335+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.11762","created_at":"2026-05-17T23:39:23.149335+00:00"},{"alias_kind":"pith_short_12","alias_value":"A4ZHTSY3JMQB","created_at":"2026-05-18T12:33:12.712433+00:00"},{"alias_kind":"pith_short_16","alias_value":"A4ZHTSY3JMQBCTUO","created_at":"2026-05-18T12:33:12.712433+00:00"},{"alias_kind":"pith_short_8","alias_value":"A4ZHTSY3","created_at":"2026-05-18T12:33:12.712433+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/A4ZHTSY3JMQBCTUOL5CPFAAIMQ","json":"https://pith.science/pith/A4ZHTSY3JMQBCTUOL5CPFAAIMQ.json","graph_json":"https://pith.science/api/pith-number/A4ZHTSY3JMQBCTUOL5CPFAAIMQ/graph.json","events_json":"https://pith.science/api/pith-number/A4ZHTSY3JMQBCTUOL5CPFAAIMQ/events.json","paper":"https://pith.science/paper/A4ZHTSY3"},"agent_actions":{"view_html":"https://pith.science/pith/A4ZHTSY3JMQBCTUOL5CPFAAIMQ","download_json":"https://pith.science/pith/A4ZHTSY3JMQBCTUOL5CPFAAIMQ.json","view_paper":"https://pith.science/paper/A4ZHTSY3","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1907.11762&json=true","fetch_graph":"https://pith.science/api/pith-number/A4ZHTSY3JMQBCTUOL5CPFAAIMQ/graph.json","fetch_events":"https://pith.science/api/pith-number/A4ZHTSY3JMQBCTUOL5CPFAAIMQ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/A4ZHTSY3JMQBCTUOL5CPFAAIMQ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/A4ZHTSY3JMQBCTUOL5CPFAAIMQ/action/storage_attestation","attest_author":"https://pith.science/pith/A4ZHTSY3JMQBCTUOL5CPFAAIMQ/action/author_attestation","sign_citation":"https://pith.science/pith/A4ZHTSY3JMQBCTUOL5CPFAAIMQ/action/citation_signature","submit_replication":"https://pith.science/pith/A4ZHTSY3JMQBCTUOL5CPFAAIMQ/action/replication_record"}},"created_at":"2026-05-17T23:39:23.149335+00:00","updated_at":"2026-05-17T23:39:23.149335+00:00"}