{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:ROOVRJPDA6EA5CNIGDYNKQZQGX","short_pith_number":"pith:ROOVRJPD","schema_version":"1.0","canonical_sha256":"8b9d58a5e307880e89a830f0d5433035c51db044160c2e59c3019860d982c409","source":{"kind":"arxiv","id":"2403.03661","version":1},"attestation_state":"computed","paper":{"title":"Development and evaluation of Artificial Intelligence techniques for IoT data quality assessment and curation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.DB","authors_text":"Jorge Lanza, Laura Mart\\'in, Luis S\\'anchez, Pablo Sotres","submitted_at":"2024-03-06T12:29:47Z","abstract_excerpt":"Nowadays, data is becoming the new fuel for economic wealth and creation of novel and profitable business models. Multitude of technologies are contributing to an abundance of information sources which are already the baseline for multi-millionaire services and applications. Internet of Things (IoT), is probably the most representative one. However, for an economy of data to actually flourish there are still several critical challenges that have to be overcome. Among them, data quality can become an issue when data come from heterogeneous sources or have different formats, standards and scale."},"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":"2403.03661","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.DB","submitted_at":"2024-03-06T12:29:47Z","cross_cats_sorted":[],"title_canon_sha256":"1b7508165387329d348efc69ede96f9812fbe9c37423792e4e1b12bc1acd4097","abstract_canon_sha256":"e356e3cc40e7e820832b662f644fe4cc5246fc4246de1f99b4872c65bdd9d844"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:52:51.341636Z","signature_b64":"isDDpGFeg292oi41DCxHHj7fUTf0ZXKI8G+CjBGwD77pR8D2uynWRzJ3paVEpu3FeEqu0NbIzt7vEnhCvsSWAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8b9d58a5e307880e89a830f0d5433035c51db044160c2e59c3019860d982c409","last_reissued_at":"2026-07-05T07:52:51.341200Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:52:51.341200Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Development and evaluation of Artificial Intelligence techniques for IoT data quality assessment and curation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.DB","authors_text":"Jorge Lanza, Laura Mart\\'in, Luis S\\'anchez, Pablo Sotres","submitted_at":"2024-03-06T12:29:47Z","abstract_excerpt":"Nowadays, data is becoming the new fuel for economic wealth and creation of novel and profitable business models. Multitude of technologies are contributing to an abundance of information sources which are already the baseline for multi-millionaire services and applications. Internet of Things (IoT), is probably the most representative one. However, for an economy of data to actually flourish there are still several critical challenges that have to be overcome. Among them, data quality can become an issue when data come from heterogeneous sources or have different formats, standards and scale."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.03661","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/2403.03661/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2403.03661","created_at":"2026-07-05T07:52:51.341258+00:00"},{"alias_kind":"arxiv_version","alias_value":"2403.03661v1","created_at":"2026-07-05T07:52:51.341258+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.03661","created_at":"2026-07-05T07:52:51.341258+00:00"},{"alias_kind":"pith_short_12","alias_value":"ROOVRJPDA6EA","created_at":"2026-07-05T07:52:51.341258+00:00"},{"alias_kind":"pith_short_16","alias_value":"ROOVRJPDA6EA5CNI","created_at":"2026-07-05T07:52:51.341258+00:00"},{"alias_kind":"pith_short_8","alias_value":"ROOVRJPD","created_at":"2026-07-05T07:52:51.341258+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/ROOVRJPDA6EA5CNIGDYNKQZQGX","json":"https://pith.science/pith/ROOVRJPDA6EA5CNIGDYNKQZQGX.json","graph_json":"https://pith.science/api/pith-number/ROOVRJPDA6EA5CNIGDYNKQZQGX/graph.json","events_json":"https://pith.science/api/pith-number/ROOVRJPDA6EA5CNIGDYNKQZQGX/events.json","paper":"https://pith.science/paper/ROOVRJPD"},"agent_actions":{"view_html":"https://pith.science/pith/ROOVRJPDA6EA5CNIGDYNKQZQGX","download_json":"https://pith.science/pith/ROOVRJPDA6EA5CNIGDYNKQZQGX.json","view_paper":"https://pith.science/paper/ROOVRJPD","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2403.03661&json=true","fetch_graph":"https://pith.science/api/pith-number/ROOVRJPDA6EA5CNIGDYNKQZQGX/graph.json","fetch_events":"https://pith.science/api/pith-number/ROOVRJPDA6EA5CNIGDYNKQZQGX/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/ROOVRJPDA6EA5CNIGDYNKQZQGX/action/timestamp_anchor","attest_storage":"https://pith.science/pith/ROOVRJPDA6EA5CNIGDYNKQZQGX/action/storage_attestation","attest_author":"https://pith.science/pith/ROOVRJPDA6EA5CNIGDYNKQZQGX/action/author_attestation","sign_citation":"https://pith.science/pith/ROOVRJPDA6EA5CNIGDYNKQZQGX/action/citation_signature","submit_replication":"https://pith.science/pith/ROOVRJPDA6EA5CNIGDYNKQZQGX/action/replication_record"}},"created_at":"2026-07-05T07:52:51.341258+00:00","updated_at":"2026-07-05T07:52:51.341258+00:00"}