{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:SOVYRIORHQJ7WU67W3A4762U4W","short_pith_number":"pith:SOVYRIOR","canonical_record":{"source":{"id":"2507.22899","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.HC","submitted_at":"2025-06-26T00:28:21Z","cross_cats_sorted":[],"title_canon_sha256":"c19b2b5ab59350810ea697e8a27fd86e73de8dd95205b30cc250b3676ae82909","abstract_canon_sha256":"d039a576223c1939c134a8ab7a90ea74c5ae78c0257d76b67f356af0b6d3c6f0"},"schema_version":"1.0"},"canonical_sha256":"93ab88a1d13c13fb53dfb6c1cffb54e5bdda4b16f0d1e66256fe8e147ded0a78","source":{"kind":"arxiv","id":"2507.22899","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.22899","created_at":"2026-07-05T11:46:01Z"},{"alias_kind":"arxiv_version","alias_value":"2507.22899v1","created_at":"2026-07-05T11:46:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.22899","created_at":"2026-07-05T11:46:01Z"},{"alias_kind":"pith_short_12","alias_value":"SOVYRIORHQJ7","created_at":"2026-07-05T11:46:01Z"},{"alias_kind":"pith_short_16","alias_value":"SOVYRIORHQJ7WU67","created_at":"2026-07-05T11:46:01Z"},{"alias_kind":"pith_short_8","alias_value":"SOVYRIOR","created_at":"2026-07-05T11:46:01Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:SOVYRIORHQJ7WU67W3A4762U4W","target":"record","payload":{"canonical_record":{"source":{"id":"2507.22899","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.HC","submitted_at":"2025-06-26T00:28:21Z","cross_cats_sorted":[],"title_canon_sha256":"c19b2b5ab59350810ea697e8a27fd86e73de8dd95205b30cc250b3676ae82909","abstract_canon_sha256":"d039a576223c1939c134a8ab7a90ea74c5ae78c0257d76b67f356af0b6d3c6f0"},"schema_version":"1.0"},"canonical_sha256":"93ab88a1d13c13fb53dfb6c1cffb54e5bdda4b16f0d1e66256fe8e147ded0a78","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:46:01.094127Z","signature_b64":"me+HGIH2Sdl5EwQEK6AVkOzAsooOM3L7CMtztWYmUNi7z0IW5bYdYrqTHyiumSBAaGPU+0vO7U1XerCiDkZiCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"93ab88a1d13c13fb53dfb6c1cffb54e5bdda4b16f0d1e66256fe8e147ded0a78","last_reissued_at":"2026-07-05T11:46:01.093542Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:46:01.093542Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2507.22899","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":"2026-07-05T11:46:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DeEVxX/JM4Ub9Oy44D4uxK+vUWpCpqPkLBv5LXaxCLfJwoRbjEz4YhvMuZVLFGIx+LkgZhyDqbVPLokelbYbDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T19:38:11.316161Z"},"content_sha256":"f83b2f2b5912bf762fd32dd0bbfecf3a7b8386860c73f8975eb8a93af2705ef3","schema_version":"1.0","event_id":"sha256:f83b2f2b5912bf762fd32dd0bbfecf3a7b8386860c73f8975eb8a93af2705ef3"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:SOVYRIORHQJ7WU67W3A4762U4W","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A visual analytics tool for taxonomy-based trajectory data exploration","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.HC","authors_text":"Ahmad Abdou, Ivan A. Hanono Cozzetti","submitted_at":"2025-06-26T00:28:21Z","abstract_excerpt":"The analysis of spatio-temporal data presents significant challenges due to the complexity and heterogeneity of movement patterns. This project proposes a data analytics tool that combines data visualization and statistical computation to facilitate spatio-temporal data analysis through a multi-level approach. The tool categorizes moving objects into distinct taxonomies using Machine Learning models, adding meaningful structure to the analysis. Two case studies demonstrate the methodology's effectiveness. The first analyzed Arctic fox trajectories, successfully identifying and labeling foxes w"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.22899","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/2507.22899/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":"2026-07-05T11:46:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dfKZTfYNqLEmnvs19taylfxlucAvtwFqLHvTXqu6zH8kE8DHnaTkc/dApQo0HzIjo+jG15EZSnFX6EfDBMjbAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T19:38:11.316649Z"},"content_sha256":"7657ba29958a93b519dafdd352f4892bf0fb714d58fb67ad38fde094e4dbb10d","schema_version":"1.0","event_id":"sha256:7657ba29958a93b519dafdd352f4892bf0fb714d58fb67ad38fde094e4dbb10d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/SOVYRIORHQJ7WU67W3A4762U4W/bundle.json","state_url":"https://pith.science/pith/SOVYRIORHQJ7WU67W3A4762U4W/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/SOVYRIORHQJ7WU67W3A4762U4W/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":"2026-08-23T19:38:11Z","links":{"resolver":"https://pith.science/pith/SOVYRIORHQJ7WU67W3A4762U4W","bundle":"https://pith.science/pith/SOVYRIORHQJ7WU67W3A4762U4W/bundle.json","state":"https://pith.science/pith/SOVYRIORHQJ7WU67W3A4762U4W/state.json","well_known_bundle":"https://pith.science/.well-known/pith/SOVYRIORHQJ7WU67W3A4762U4W/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:SOVYRIORHQJ7WU67W3A4762U4W","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":"d039a576223c1939c134a8ab7a90ea74c5ae78c0257d76b67f356af0b6d3c6f0","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.HC","submitted_at":"2025-06-26T00:28:21Z","title_canon_sha256":"c19b2b5ab59350810ea697e8a27fd86e73de8dd95205b30cc250b3676ae82909"},"schema_version":"1.0","source":{"id":"2507.22899","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.22899","created_at":"2026-07-05T11:46:01Z"},{"alias_kind":"arxiv_version","alias_value":"2507.22899v1","created_at":"2026-07-05T11:46:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.22899","created_at":"2026-07-05T11:46:01Z"},{"alias_kind":"pith_short_12","alias_value":"SOVYRIORHQJ7","created_at":"2026-07-05T11:46:01Z"},{"alias_kind":"pith_short_16","alias_value":"SOVYRIORHQJ7WU67","created_at":"2026-07-05T11:46:01Z"},{"alias_kind":"pith_short_8","alias_value":"SOVYRIOR","created_at":"2026-07-05T11:46:01Z"}],"graph_snapshots":[{"event_id":"sha256:7657ba29958a93b519dafdd352f4892bf0fb714d58fb67ad38fde094e4dbb10d","target":"graph","created_at":"2026-07-05T11:46:01Z","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/2507.22899/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The analysis of spatio-temporal data presents significant challenges due to the complexity and heterogeneity of movement patterns. This project proposes a data analytics tool that combines data visualization and statistical computation to facilitate spatio-temporal data analysis through a multi-level approach. The tool categorizes moving objects into distinct taxonomies using Machine Learning models, adding meaningful structure to the analysis. Two case studies demonstrate the methodology's effectiveness. The first analyzed Arctic fox trajectories, successfully identifying and labeling foxes w","authors_text":"Ahmad Abdou, Ivan A. Hanono Cozzetti","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.HC","submitted_at":"2025-06-26T00:28:21Z","title":"A visual analytics tool for taxonomy-based trajectory data exploration"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.22899","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:f83b2f2b5912bf762fd32dd0bbfecf3a7b8386860c73f8975eb8a93af2705ef3","target":"record","created_at":"2026-07-05T11:46:01Z","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":"d039a576223c1939c134a8ab7a90ea74c5ae78c0257d76b67f356af0b6d3c6f0","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.HC","submitted_at":"2025-06-26T00:28:21Z","title_canon_sha256":"c19b2b5ab59350810ea697e8a27fd86e73de8dd95205b30cc250b3676ae82909"},"schema_version":"1.0","source":{"id":"2507.22899","kind":"arxiv","version":1}},"canonical_sha256":"93ab88a1d13c13fb53dfb6c1cffb54e5bdda4b16f0d1e66256fe8e147ded0a78","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"93ab88a1d13c13fb53dfb6c1cffb54e5bdda4b16f0d1e66256fe8e147ded0a78","first_computed_at":"2026-07-05T11:46:01.093542Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:46:01.093542Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"me+HGIH2Sdl5EwQEK6AVkOzAsooOM3L7CMtztWYmUNi7z0IW5bYdYrqTHyiumSBAaGPU+0vO7U1XerCiDkZiCA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:46:01.094127Z","signed_message":"canonical_sha256_bytes"},"source_id":"2507.22899","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f83b2f2b5912bf762fd32dd0bbfecf3a7b8386860c73f8975eb8a93af2705ef3","sha256:7657ba29958a93b519dafdd352f4892bf0fb714d58fb67ad38fde094e4dbb10d"],"state_sha256":"e30153d24782a5fb9d09d2b257d8bfe515ce816205fea9ed6d18ac5afe153602"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"u1pUni6I0gQMmFYtQ8AsFdMTPny3aA8ms3EF6fI3c2nDJEXPqv606HBGby5tPqck04VbZ0GlDOk//Bc+8agtAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-23T19:38:11.320507Z","bundle_sha256":"38f9f220b6612b08497bdf222eef07b3090c774a1d0e7c06e24e4f0eecaae6ec"}}