The datasets section of the organization administrator panel provides a comprehensive list of all your organizations datasets. This includes any unpublished and unreleased datasets.
You can click the + New button to create a new dataset, or double click on any dataset to edit that dataset and its access configuration.

Featured datasets

Featured datasets will be prominently displayed on the main page of your organization's data portal, and may rank higher in search results. To feature a dataset, right click on that dataset and change it's status to featured.

Bulk management

As your organization creates datasets, you may find it easier to perform certain dataset management operations in bulk. To do so, shift/cmd+click to select multiple datasets in the list, and right click and select the option to edit in bulk.
The dataset bulk editor allows you to harmonize the permission group, tags, featured status, and published status across multiple datasets.

Merging datasets

In certain cases, you may want to bring tables from multiple datasets together by merging multiple datasets into one. To merge datasets, select multiple datasets, right click on them, and select the "Merge datasets" option.
When merging datasets, all existing source datasets will be deleted and combined into a single dataset. This dataset will contain all tables from the various source datasets. You can choose the final dataset's name, published status, and access controls before merging.
When merging resources across datasets, Redivis will leverage the following strategies:
  • Tags: Include all distinct tags from the source datasets, up to the maximum number of tags allowed on a dataset.
  • Documentation: Include all distinct documentation blocks from the source datasets.
  • Introduction: An additional documentation block will be added that contains introduction information from all source datasets (as well as some basic information about the merge), allowing you to repopulate the introduction after the dataset is merged.
  • Versions: Redivis will create the minimum number of versions in the output dataset, such that the chronological version history of all input tables is preserved. This might mean that the merged dataset will have more versions than any of the source datasets, depending on the specific release timestamps of respective versions.
  • Tables: All tables from the source datasets will be present in the output dataset. If two tables have the same name, a suffix will be added to one of them such that both tables can be preserved.
  • Projects: Any researchers referencing the source datasets in their projects will have their projects automatically updated, such that they are still referencing the same source tables and can run the projects exactly as they did before.
Last modified 1yr ago