The following release notes cover most recent changes or known issues related to the Researcher Workbench Data Explorer. To learn more about accessing and using Data Explorer, see this support article.
Note: Data Explorer is not available for use with CDR v7 in Researcher Workbench. To continue your analysis, please use the most recent CDR v9 or CDR v8 in the Researcher Workbench.
CDRv9 Known Issues
Known Issue - Has EHR Flag
The “Has EHR Data” filter is underreporting EHR counts due to the exclusion of ‘Participant-Mediated EHR’ values from the total. In Data Explorer, the filter currently displays a count of 423,082; however, the correct Controlled Tier value is 481,919. At this time, we recommend using other filter criteria. A future UI enhancement is planned to improve this experience.
Known Issue - Missing Surveys
The COPE, COVID-19, Emotional Health History and Well-Being, and Behavioral Health and Personality surveys are currently missing from the Data Explorer when using v9 Controlled Tier data collection. Our team is actively working to resolve this issue. In the meantime, these surveys can be accessed by querying it directly using a custom SQL query.
Known Issue - Wheelchair Filter
The filter “Wheelchair use at enrollment” populates as “0” count. Our team is working to provide an update to this filter in the near future.
Known Issue - Age Filter
The only available age filter option in the Data Explorer is the “Current Age” filter. In the Registered Tier, the age slider is labeled “18–125”; however, it only returns participants aged “18–90.” This behavior is expected due to privacy methodology, as participants over age 89 are excluded from the Registered Tier dataset. Please update the slider to reflect this range accordingly.
Known Issue - Lifestyle Survey
When selecting certain criteria from the “Lifestyle” survey an error message may populate and certain numeric answer responses may not populate. For example, when attempting to select the response the question “How old were you when you first started regular cigarette smoking every day?” the following error message may populate:
Something went wrong
Not found: Table wb-bright-olive-4015:C2025Q4R6_index_061026.T_ILDH_surveyOccurrence_surveyLifestyle was not found in location us-central1
This survey and full responses can be accessed by querying the survey directly. See an example of how to access surveys by following our Featured Workspaces.
CDRv8 Known Issues
Known Issue - CDRv8 R9
When using Data Explorer for CDRv8, it will default to CDRv8 R9. Please select CDR “v8r9” in the UI when working with Data Explorer.
Known Issue - Age Filter
The only available age filter option in the Data Explorer is the “Current Age” filter. In the Registered Tier, the age slider is labeled “18–125”; however, it only returns participants aged “18–90.” This behavior is expected due to privacy methodology, as participants over age 89 are excluded from the Registered Tier dataset. Please update the slider to reflect this range accordingly.
Known Issue - Additional Tables when using source concepts
When selecting certain criteria using source concepts during the “Save Data Snapshot” step, the Data Explorer may include additional tables outside of the concepts you selected. For example, it may add a procedure, measurement, or ingredient table. We recommend using standard concepts to circumvent this issue.
Known Issue - Variant Search UI
The variant search function in the Data Explorer is still under development. Therefore some aspects of this feature may be inaccessible such as gene sorting and filtering, to include filtering by allele count, allele number and allele frequency. Additionally, when using the “+ Select All Results” button in the interface, it may populate a “Error: “Something went wrong — Cohort not found” message on the side panel view. Despite the message, you can still select all variants and proceed through the Data Explorer workflow.
Known Issue - View Hierarchy UI
When using the “View in hierarchy” feature to select concepts, you may not be taken directly to the corresponding location in the hierarchy on the next page. Instead, you will need to scroll to locate the relevant concepts. A future UI enhancement is planned to improve this experience.
Known Issue - Age Cohort Count Difference
If you created an age specific cohort in the legacy workbench, we recommend you create a new cohort in the new workbench. Age-cohort discrepancies may appear between previous Cohort Builder and Data Explorer at maximum age range categories that are multiples of four year boundaries. The Data Explorer approximates leap years using a 365.25‑day divisor. Every four‑year cycle aligns exactly with this calculation, making the age value highly sensitive to small timestamp differences. As a result, even a few hours of difference between the query timestamp and the participant’s birth timestamp can shift the computed age across the boundary (e.g., from 39 to 40). At non‑multiples of four, the fractional part of the age calculation provides a buffer, so small timing differences don’t affect the final rounded‑down age. For example, if the participant is born on March 1, 1984 at 2:00 AM, and a query for age was performed using Data Explorer on March 1, 2024 at 2:00 PM, the Cohort Builder may show 40 years old, but the Data Explorer may show 39 years old. This is an expected difference between the two tools.
Known Issue - Age Cohort Count Difference
You may see count differences between the previous Cohort Builder and the Data Explorer when using temporal criteria in the new Data Explorer. The Data Explorer calculates date differences with TIMESTAMP_DIFF, which measures time down to the millisecond before rounding to days, while the Cohort Builder uses a different SQL method. Although both apply the same inclusive 30‑day logic, small variations, such as which event date is used as the reference point or how fractional days near the boundary are handled, can result in slight count discrepancies. This is to be expected. If you created a cohort using the previous legacy workbench with the temporal feature, we recommend continuing that work in the original dataframe for consistency. For any new cohort development, you can use the Data Explorer tool in Researcher Workbench.
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