In ecohealthalliance/eidith: Data access and analytical tools for the PREDICT EIDITH database

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Eidith Package Data Processing

The eidith package downloads data from the EIDITH database to a local database stored on your machine. Default calls to the ed_get() or ed_db_download() will automatically process the data in several ways after it is downloaded to your local database.

Importantly, the R package does not change any data in the main EIDITH database, it only processes the downloaded data in your local database.

The main automatic processing steps are:

• Converting variable names from camelCase to snake_case to make it easy to distinguish between raw and cleaned data.
• Converting some variable names to clearer ones: all _id variables are numeric primary keys, other identifiers now go by _id_name.
• Where there are multiple _id_name-type columns that are very similar except for a small set of cases, we drop all but one for ease of use. These can be retrieved from raw data if needed.
• Dropping columns that are entirely blank
• Dropping redundant columns
• Cleaning up whitespace and capitalization variability
• Re-arranging table order to put the most pertinent information first.
• Normalizing all animal taxonomic information to match the ITIS database.
• Coercing some free-form entries (e.g. specimen_type) to a standard set of categories
• Converting yes/no fields to TRUE/FALSE
• Fixing obvious spelling errors
• Extracting variables from free-form text of viral interpretation (Genbank numbers and whether virus is known).

For column name details, including descriptions of fields (when available), the command ?ed_metadata will open a datatable that contains details about how each field name was processed, renamed, or dropped.

Direct API Access and Raw Data

The eidith R package automatic processing steps do not permanently alter or delete any upstream data.

If you want to access raw EIDITH data from the web API directly (for instance, if you want to compare differences between raw data and the automatically-cleaned version ed_db_download() creates), you can use the ed_get() functions, such as get_ed_events(), with the postprocess = FALSE option:

For events:

ed_get_events(postprocess=FALSE)

For animals:

ed_get_animals(postprocess=FALSE)

And so on. These raw data tables can be saved in your R environment and can be compared to the eidith R package tables -- simply use ed_metadata() to load the metadata table, or from within RStudio use ?ed_metadata to open a searchable datatable.

ecohealthalliance/eidith documentation built on Aug. 30, 2022, 7:45 a.m.