{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2013:6OSFPWIUM2U6DVWHTOG5KQWIL7","short_pith_number":"pith:6OSFPWIU","schema_version":"1.0","canonical_sha256":"f3a457d91466a9e1d6c79b8dd542c85fea8a45270594de39a4e1699d7b41ce99","source":{"kind":"arxiv","id":"1311.7676","version":2},"attestation_state":"computed","paper":{"title":"Constructing Gazetteers from Volunteered Big Geo-Data Based on Hadoop","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.DC","authors_text":"Krzysztof Janowicz, Linna Li, Song Gao, Wenwen Li, Yue Zhang","submitted_at":"2013-11-29T19:52:42Z","abstract_excerpt":"Traditional gazetteers are built and maintained by authoritative mapping agencies. In the age of Big Data, it is possible to construct gazetteers in a data-driven approach by mining rich volunteered geographic information (VGI) from the Web. In this research, we build a scalable distributed platform and a high-performance geoprocessing workflow based on the Hadoop ecosystem to harvest crowd-sourced gazetteer entries. Using experiments based on geotagged datasets in Flickr, we find that the MapReduce-based workflow running on the spatially enabled Hadoop cluster can reduce the processing time c"},"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":"1311.7676","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2013-11-29T19:52:42Z","cross_cats_sorted":[],"title_canon_sha256":"8bfa1061cef550a1724041bfefcb0c169c14532b9f4a919508ba01db4789a3db","abstract_canon_sha256":"c57c9f45cbcce6c697783f14c8b168a1be567a9f2fdcce641f6f3711812619a3"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:59:47.458589Z","signature_b64":"M+k7rSxymk5d+s1Yj7230YEk7zAHTlHHbDobyefqP+XFlLTJmFbpwUJ+776kuagGqgbsnANGCgJfdhuL2RaqCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f3a457d91466a9e1d6c79b8dd542c85fea8a45270594de39a4e1699d7b41ce99","last_reissued_at":"2026-05-18T02:59:47.457805Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:59:47.457805Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Constructing Gazetteers from Volunteered Big Geo-Data Based on Hadoop","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.DC","authors_text":"Krzysztof Janowicz, Linna Li, Song Gao, Wenwen Li, Yue Zhang","submitted_at":"2013-11-29T19:52:42Z","abstract_excerpt":"Traditional gazetteers are built and maintained by authoritative mapping agencies. In the age of Big Data, it is possible to construct gazetteers in a data-driven approach by mining rich volunteered geographic information (VGI) from the Web. In this research, we build a scalable distributed platform and a high-performance geoprocessing workflow based on the Hadoop ecosystem to harvest crowd-sourced gazetteer entries. Using experiments based on geotagged datasets in Flickr, we find that the MapReduce-based workflow running on the spatially enabled Hadoop cluster can reduce the processing time c"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1311.7676","kind":"arxiv","version":2},"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":"1311.7676","created_at":"2026-05-18T02:59:47.457931+00:00"},{"alias_kind":"arxiv_version","alias_value":"1311.7676v2","created_at":"2026-05-18T02:59:47.457931+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1311.7676","created_at":"2026-05-18T02:59:47.457931+00:00"},{"alias_kind":"pith_short_12","alias_value":"6OSFPWIUM2U6","created_at":"2026-05-18T12:27:36.564083+00:00"},{"alias_kind":"pith_short_16","alias_value":"6OSFPWIUM2U6DVWH","created_at":"2026-05-18T12:27:36.564083+00:00"},{"alias_kind":"pith_short_8","alias_value":"6OSFPWIU","created_at":"2026-05-18T12:27:36.564083+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/6OSFPWIUM2U6DVWHTOG5KQWIL7","json":"https://pith.science/pith/6OSFPWIUM2U6DVWHTOG5KQWIL7.json","graph_json":"https://pith.science/api/pith-number/6OSFPWIUM2U6DVWHTOG5KQWIL7/graph.json","events_json":"https://pith.science/api/pith-number/6OSFPWIUM2U6DVWHTOG5KQWIL7/events.json","paper":"https://pith.science/paper/6OSFPWIU"},"agent_actions":{"view_html":"https://pith.science/pith/6OSFPWIUM2U6DVWHTOG5KQWIL7","download_json":"https://pith.science/pith/6OSFPWIUM2U6DVWHTOG5KQWIL7.json","view_paper":"https://pith.science/paper/6OSFPWIU","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1311.7676&json=true","fetch_graph":"https://pith.science/api/pith-number/6OSFPWIUM2U6DVWHTOG5KQWIL7/graph.json","fetch_events":"https://pith.science/api/pith-number/6OSFPWIUM2U6DVWHTOG5KQWIL7/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/6OSFPWIUM2U6DVWHTOG5KQWIL7/action/timestamp_anchor","attest_storage":"https://pith.science/pith/6OSFPWIUM2U6DVWHTOG5KQWIL7/action/storage_attestation","attest_author":"https://pith.science/pith/6OSFPWIUM2U6DVWHTOG5KQWIL7/action/author_attestation","sign_citation":"https://pith.science/pith/6OSFPWIUM2U6DVWHTOG5KQWIL7/action/citation_signature","submit_replication":"https://pith.science/pith/6OSFPWIUM2U6DVWHTOG5KQWIL7/action/replication_record"}},"created_at":"2026-05-18T02:59:47.457931+00:00","updated_at":"2026-05-18T02:59:47.457931+00:00"}