{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:GIT47O33M7375676CMMLARE7OV","short_pith_number":"pith:GIT47O33","schema_version":"1.0","canonical_sha256":"3227cfbb7b67f7fefbfe1318b0449f7549d732b7f0460d6ca139565d8cacc1c5","source":{"kind":"arxiv","id":"1906.12322","version":1},"attestation_state":"computed","paper":{"title":"Breadcrumbs: A Feature Rich Mobility Dataset with Point of Interest Annotation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.SI","authors_text":"Arielle Moro, Benoit Garbinato, Bertil Chapuis, Pierre-Adrien Ghiringhelli, Vaibhav Kulkarni","submitted_at":"2019-06-14T14:20:57Z","abstract_excerpt":"In this paper, we present Breadcrumbs, a mobility dataset collected in the city of Lausanne (Switzerland) from multiple mobile phone sensors (GPS, WiFi, Bluetooth) from 81 users for a duration of 12 weeks. Currently available mobility datasets are restricted to geospatial information obtained through a single sensor at low spatiotemporal granularities. Furthermore, this passively collected data lacks ground-truth information regarding points of interest and their semantic labels. These features are critical in order to push the possibilities of geospatial data analysis towards analyzing mobili"},"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":"1906.12322","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SI","submitted_at":"2019-06-14T14:20:57Z","cross_cats_sorted":[],"title_canon_sha256":"8a3bef4fe8f582a30ca8dac7802b3eadd22756618192573768367a8fe6b936ea","abstract_canon_sha256":"41b177c32d0c9de531b647ea01479db5fd7d3faa31c956e4c5295e0b6570755c"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:41:58.667270Z","signature_b64":"tvLMga0PllHsMYknlfBWYynXLp/7r2yUlR1YP3LHYzgefEM+oOV9SJreJVRX+SZuyTNNXDplmkhZMLHrBusfCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3227cfbb7b67f7fefbfe1318b0449f7549d732b7f0460d6ca139565d8cacc1c5","last_reissued_at":"2026-05-17T23:41:58.666503Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:41:58.666503Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Breadcrumbs: A Feature Rich Mobility Dataset with Point of Interest Annotation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.SI","authors_text":"Arielle Moro, Benoit Garbinato, Bertil Chapuis, Pierre-Adrien Ghiringhelli, Vaibhav Kulkarni","submitted_at":"2019-06-14T14:20:57Z","abstract_excerpt":"In this paper, we present Breadcrumbs, a mobility dataset collected in the city of Lausanne (Switzerland) from multiple mobile phone sensors (GPS, WiFi, Bluetooth) from 81 users for a duration of 12 weeks. Currently available mobility datasets are restricted to geospatial information obtained through a single sensor at low spatiotemporal granularities. Furthermore, this passively collected data lacks ground-truth information regarding points of interest and their semantic labels. These features are critical in order to push the possibilities of geospatial data analysis towards analyzing mobili"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1906.12322","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":"1906.12322","created_at":"2026-05-17T23:41:58.666637+00:00"},{"alias_kind":"arxiv_version","alias_value":"1906.12322v1","created_at":"2026-05-17T23:41:58.666637+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1906.12322","created_at":"2026-05-17T23:41:58.666637+00:00"},{"alias_kind":"pith_short_12","alias_value":"GIT47O33M737","created_at":"2026-05-18T12:33:18.533446+00:00"},{"alias_kind":"pith_short_16","alias_value":"GIT47O33M7375676","created_at":"2026-05-18T12:33:18.533446+00:00"},{"alias_kind":"pith_short_8","alias_value":"GIT47O33","created_at":"2026-05-18T12:33:18.533446+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/GIT47O33M7375676CMMLARE7OV","json":"https://pith.science/pith/GIT47O33M7375676CMMLARE7OV.json","graph_json":"https://pith.science/api/pith-number/GIT47O33M7375676CMMLARE7OV/graph.json","events_json":"https://pith.science/api/pith-number/GIT47O33M7375676CMMLARE7OV/events.json","paper":"https://pith.science/paper/GIT47O33"},"agent_actions":{"view_html":"https://pith.science/pith/GIT47O33M7375676CMMLARE7OV","download_json":"https://pith.science/pith/GIT47O33M7375676CMMLARE7OV.json","view_paper":"https://pith.science/paper/GIT47O33","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1906.12322&json=true","fetch_graph":"https://pith.science/api/pith-number/GIT47O33M7375676CMMLARE7OV/graph.json","fetch_events":"https://pith.science/api/pith-number/GIT47O33M7375676CMMLARE7OV/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/GIT47O33M7375676CMMLARE7OV/action/timestamp_anchor","attest_storage":"https://pith.science/pith/GIT47O33M7375676CMMLARE7OV/action/storage_attestation","attest_author":"https://pith.science/pith/GIT47O33M7375676CMMLARE7OV/action/author_attestation","sign_citation":"https://pith.science/pith/GIT47O33M7375676CMMLARE7OV/action/citation_signature","submit_replication":"https://pith.science/pith/GIT47O33M7375676CMMLARE7OV/action/replication_record"}},"created_at":"2026-05-17T23:41:58.666637+00:00","updated_at":"2026-05-17T23:41:58.666637+00:00"}