{ "format" : "linked-data-api", "version" : "0.2", "result" : {"_about" : "http://vocabs.ardc.edu.au/repository/api/lda/codata/codata-research-data-management-terminology/v001/resource.text?uri=https%3A%2F%2Fterms.codata.org%2Frdmt%2Fdata-cleaning", "definition" : "http://vocabs.ardc.edu.au/repository/api/lda/codata/codata-research-data-management-terminology/v001/resource.text?uri=https%3A%2F%2Fterms.codata.org%2Frdmt%2Fdata-cleaning", "extendedMetadataVersion" : "http://vocabs.ardc.edu.au/repository/api/lda/codata/codata-research-data-management-terminology/v001/resource.text?_metadata=all&uri=https%3A%2F%2Fterms.codata.org%2Frdmt%2Fdata-cleaning", "primaryTopic" : {"_about" : "https://terms.codata.org/rdmt/data-cleaning", "altLabel" : [{"_value" : "Data cleansing", "_lang" : "en"}
      , {"_value" : "Data scrubbing", "_lang" : "en"}
      ], "definition" : "Process of detecting and correcting corrupt or inaccurate records from a dataset. Data cleaning is a continuous process that requires corrective actions throughout the data lifecycle. Data cleaning involves identifying, replacing, modifying or deleting incomplete, incorrect, inaccurate, inconsistent, irrelevant, and improperly formatted data. Typically, the process involves updating, correcting, standardising, and de-duplicating records to create a single view of the data, even if they are stored in multiple disparate systems.", "editorialNote" : "Expert review decision, 2021-22: Edit", "inScheme" : {"_about" : "https://terms.codata.org/rdmt", "hasTopConcept" : ["https://terms.codata.org/rdmt/data-cleaning"]}
      , "prefLabel" : {"_value" : "Data cleaning", "_lang" : "en"}
      , "topConceptOf" : {"_about" : "https://terms.codata.org/rdmt", "hasTopConcept" : ["https://terms.codata.org/rdmt/data-cleaning"]}
      , "type" : ["http://www.w3.org/2000/01/rdf-schema#Resource", "http://www.w3.org/2004/02/skos/core#Concept"]}
    , "type" : ["http://purl.org/linked-data/api/vocab#ItemEndpoint", "http://purl.org/linked-data/api/vocab#Page"]}
}