daiquiri: data quality reporting for temporal datasets
<p>The daiquiri R package generates data quality reports that enable quick visual review of temporal shifts in record-level data. It is designed with electronic health records in mind, but can be used for any type of record-level temporal data (i.e. tabular data where each row represents a sin...
| Main Author: | |
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| Format: | Journal article |
| Language: | English |
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Open Journals
2022
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| _version_ | 1797109653343043584 |
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| author | Quan, TP |
| author_facet | Quan, TP |
| author_sort | Quan, TP |
| collection | OXFORD |
| description | <p>The daiquiri R package generates data quality reports that enable quick visual review of temporal shifts in record-level data. It is designed with electronic health records in mind, but can be used for any type of record-level temporal data (i.e. tabular data where each row represents a single “event”, one column contains the “event date”, and other columns contain any associated values for the event, see Figure 1 for an example).</p>
<p>The package automatically creates time series plots showing aggregated values for each data field (column) depending on its contents (e.g. min/max/mean values for numeric data, no. of distinct values for categorical data), see Figure 2, as well as overviews for missing values, non-conformant values, and duplicated rows, see Figure 3.</p>
<p>The resulting html reports are shareable and can contribute to forming a transparent record of the entire analysis process.</p> |
| first_indexed | 2024-03-07T07:44:32Z |
| format | Journal article |
| id | oxford-uuid:d4c2ac54-5683-4af6-b9a2-e107c1ef719d |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T07:44:32Z |
| publishDate | 2022 |
| publisher | Open Journals |
| record_format | dspace |
| spelling | oxford-uuid:d4c2ac54-5683-4af6-b9a2-e107c1ef719d2023-05-24T14:49:12Zdaiquiri: data quality reporting for temporal datasetsJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:d4c2ac54-5683-4af6-b9a2-e107c1ef719dEnglishSymplectic ElementsOpen Journals2022Quan, TP<p>The daiquiri R package generates data quality reports that enable quick visual review of temporal shifts in record-level data. It is designed with electronic health records in mind, but can be used for any type of record-level temporal data (i.e. tabular data where each row represents a single “event”, one column contains the “event date”, and other columns contain any associated values for the event, see Figure 1 for an example).</p> <p>The package automatically creates time series plots showing aggregated values for each data field (column) depending on its contents (e.g. min/max/mean values for numeric data, no. of distinct values for categorical data), see Figure 2, as well as overviews for missing values, non-conformant values, and duplicated rows, see Figure 3.</p> <p>The resulting html reports are shareable and can contribute to forming a transparent record of the entire analysis process.</p> |
| spellingShingle | Quan, TP daiquiri: data quality reporting for temporal datasets |
| title | daiquiri: data quality reporting for temporal datasets |
| title_full | daiquiri: data quality reporting for temporal datasets |
| title_fullStr | daiquiri: data quality reporting for temporal datasets |
| title_full_unstemmed | daiquiri: data quality reporting for temporal datasets |
| title_short | daiquiri: data quality reporting for temporal datasets |
| title_sort | daiquiri data quality reporting for temporal datasets |
| work_keys_str_mv | AT quantp daiquiridataqualityreportingfortemporaldatasets |