{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:43S4IW2E2LESKRRYCKXNLIGFTV","short_pith_number":"pith:43S4IW2E","schema_version":"1.0","canonical_sha256":"e6e5c45b44d2c925463812aed5a0c59d5bf046c7def21d1d44193138e84e68d2","source":{"kind":"arxiv","id":"1705.09366","version":1},"attestation_state":"computed","paper":{"title":"Parallel Space-Time Kernel Density Estimation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.DC","authors_text":"Alexander Hohl, Dinesh Panchananam, Eric Delmelle, Erik Saule, Wenwu Tang","submitted_at":"2017-05-25T21:16:37Z","abstract_excerpt":"The exponential growth of available data has increased the need for interactive exploratory analysis. Dataset can no longer be understood through manual crawling and simple statistics. In Geographical Information Systems (GIS), the dataset is often composed of events localized in space and time; and visualizing such a dataset involves building a map of where the events occurred.\n  We focus in this paper on events that are localized among three dimensions (latitude, longitude, and time), and on computing the first step of the visualization pipeline, space-time kernel density estimation (STKDE),"},"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":"1705.09366","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2017-05-25T21:16:37Z","cross_cats_sorted":[],"title_canon_sha256":"5e6dfd6e9520b6e7b7ae4691ca7b83fc55579717b8261d9a5fdb1b440317cb3b","abstract_canon_sha256":"5e15b83bc087750a9cbfc51f1a4572cb55272be26b16305a44b88b4d6d8b875a"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:43:38.900120Z","signature_b64":"/S7xT89AQt3wd2oMwHapEIv2enGKjqWb+m3r7szUyjwPbgd7H+tZz2nI80dlGkdtudo9j2VO/6ITws9/3pr5Aw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e6e5c45b44d2c925463812aed5a0c59d5bf046c7def21d1d44193138e84e68d2","last_reissued_at":"2026-05-18T00:43:38.899680Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:43:38.899680Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Parallel Space-Time Kernel Density Estimation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.DC","authors_text":"Alexander Hohl, Dinesh Panchananam, Eric Delmelle, Erik Saule, Wenwu Tang","submitted_at":"2017-05-25T21:16:37Z","abstract_excerpt":"The exponential growth of available data has increased the need for interactive exploratory analysis. Dataset can no longer be understood through manual crawling and simple statistics. In Geographical Information Systems (GIS), the dataset is often composed of events localized in space and time; and visualizing such a dataset involves building a map of where the events occurred.\n  We focus in this paper on events that are localized among three dimensions (latitude, longitude, and time), and on computing the first step of the visualization pipeline, space-time kernel density estimation (STKDE),"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1705.09366","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":"1705.09366","created_at":"2026-05-18T00:43:38.899753+00:00"},{"alias_kind":"arxiv_version","alias_value":"1705.09366v1","created_at":"2026-05-18T00:43:38.899753+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1705.09366","created_at":"2026-05-18T00:43:38.899753+00:00"},{"alias_kind":"pith_short_12","alias_value":"43S4IW2E2LES","created_at":"2026-05-18T12:30:58.224056+00:00"},{"alias_kind":"pith_short_16","alias_value":"43S4IW2E2LESKRRY","created_at":"2026-05-18T12:30:58.224056+00:00"},{"alias_kind":"pith_short_8","alias_value":"43S4IW2E","created_at":"2026-05-18T12:30:58.224056+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/43S4IW2E2LESKRRYCKXNLIGFTV","json":"https://pith.science/pith/43S4IW2E2LESKRRYCKXNLIGFTV.json","graph_json":"https://pith.science/api/pith-number/43S4IW2E2LESKRRYCKXNLIGFTV/graph.json","events_json":"https://pith.science/api/pith-number/43S4IW2E2LESKRRYCKXNLIGFTV/events.json","paper":"https://pith.science/paper/43S4IW2E"},"agent_actions":{"view_html":"https://pith.science/pith/43S4IW2E2LESKRRYCKXNLIGFTV","download_json":"https://pith.science/pith/43S4IW2E2LESKRRYCKXNLIGFTV.json","view_paper":"https://pith.science/paper/43S4IW2E","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1705.09366&json=true","fetch_graph":"https://pith.science/api/pith-number/43S4IW2E2LESKRRYCKXNLIGFTV/graph.json","fetch_events":"https://pith.science/api/pith-number/43S4IW2E2LESKRRYCKXNLIGFTV/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/43S4IW2E2LESKRRYCKXNLIGFTV/action/timestamp_anchor","attest_storage":"https://pith.science/pith/43S4IW2E2LESKRRYCKXNLIGFTV/action/storage_attestation","attest_author":"https://pith.science/pith/43S4IW2E2LESKRRYCKXNLIGFTV/action/author_attestation","sign_citation":"https://pith.science/pith/43S4IW2E2LESKRRYCKXNLIGFTV/action/citation_signature","submit_replication":"https://pith.science/pith/43S4IW2E2LESKRRYCKXNLIGFTV/action/replication_record"}},"created_at":"2026-05-18T00:43:38.899753+00:00","updated_at":"2026-05-18T00:43:38.899753+00:00"}