Report which reference tables are distributed with the package, when they were generated, what they were generated from, and whether they still match the versions that were registered.
Value
A data frame with one row per reference table and the columns
table, kind, rows, columns, generated, script, source, and,
when check = TRUE, hash and status.
Details
The package ships lookup tables for species and life-history information,
survey coverage, spawning times and ICES area assignment. These are
snapshots of external sources taken at a particular time, so an analysis can
depend on how old they are. This function makes that visible, in the same
way extraction() does for the survey data itself.
Two kinds of table are reported. Tables marked "exported" are documented
data sets that users can load directly, such as species_info. Tables
marked "internal" are used by the package but not exported, such as the
statistical-rectangle to ICES-area lookup used by add_ices_areas().
The example survey data sets (dab, mini, wolffish) are not reference
tables and are not reported here; use extraction() on those.
When check = TRUE, the status column takes one of:
"ok": the table matches the registered hash,"changed": the table has been regenerated since the registry was written, sogeneratedandsourcemay be out of date,"unregistered": the table is present but absent from the registry,"missing": the registry lists a table that is not available.
Hashes are taken over the serialised object, with the stream header that records the writing R version stripped out, so a table that has not been rebuilt hashes the same under different R versions. They are intended to detect that a table has been regenerated, not as a cryptographic guarantee.
Examples
## Which reference tables are bundled, and how old are they
reference_tables()
#> table kind rows columns generated
#> 1 spawning_info exported 1023 7 2026-09-15
#> 2 species_info exported 2064 24 2026-09-15
#> 3 survey_info exported 28 4 2026-10-03
#> 4 survey_info_full_raw exported 144401 7 2026-10-03
#> 5 ices_area_lookup internal 6758 8 2026-10-03
#> 6 spread_models internal 12 NA 2026-10-03
#> script
#> 1 data-raw/make_spawning_info.R
#> 2 data-raw/make_species_info.R
#> 3 data-raw/make_survey_info.R
#> 4 data-raw/make_survey_info_full.R
#> 5 data-raw/make_ices_area_lookup.R
#> 6 data-raw/spread_models.R
#> source
#> 1 length_at_maturity repository (GoFish and WKMAT), https://github.com/federico-maioli/length_at_maturity
#> 2 WoRMS via the worrms package; FishBase via rfishbase; DATRAS length-weight table (August 2023); functional groups from Walker et al. (2017), van Denderen et al. (2020) and Mildenberger et al. (2025)
#> 3 ICES DATRAS web service (getSurveyList and related endpoints)
#> 4 ICES DATRAS web service, haul positions by survey and year
#> 5 ICES statistical rectangle and area shapefiles, https://gis.ices.dk
#> 6 Gear spread models fitted to DATRAS haul data by survey
#> hash status
#> 1 d80c7d5493de4baa792d2e1bad1eb99eaf5dc068490a1b6721249729513c5689 ok
#> 2 56d99e3f26f7568237606f9c0f70aa0ad38bab9d51e1b841b8620491623fc3a0 ok
#> 3 4dea03a65c4b1c9b097c468e5f2956426990fa69c3554aaea4d1dc2a5840341a ok
#> 4 0e23e487396e74af3555043e8fa2f5314795fae368f8c6c51851baddfd1f6e7f ok
#> 5 d1af60fcdcc0f1bf2396454cee1242a9d6e10ed687f6a4cfe5a27057c1738bf1 ok
#> 6 fb0c7e2f22cc85bc97baefcf5e2372e98140997f9c218b49aadf3d7f863119d2 ok
## Skip hashing
reference_tables(check = FALSE)
#> table kind rows columns generated
#> 1 spawning_info exported 1023 7 2026-09-15
#> 2 species_info exported 2064 24 2026-09-15
#> 3 survey_info exported 28 4 2026-10-03
#> 4 survey_info_full_raw exported 144401 7 2026-10-03
#> 5 ices_area_lookup internal 6758 8 2026-10-03
#> 6 spread_models internal 12 NA 2026-10-03
#> script
#> 1 data-raw/make_spawning_info.R
#> 2 data-raw/make_species_info.R
#> 3 data-raw/make_survey_info.R
#> 4 data-raw/make_survey_info_full.R
#> 5 data-raw/make_ices_area_lookup.R
#> 6 data-raw/spread_models.R
#> source
#> 1 length_at_maturity repository (GoFish and WKMAT), https://github.com/federico-maioli/length_at_maturity
#> 2 WoRMS via the worrms package; FishBase via rfishbase; DATRAS length-weight table (August 2023); functional groups from Walker et al. (2017), van Denderen et al. (2020) and Mildenberger et al. (2025)
#> 3 ICES DATRAS web service (getSurveyList and related endpoints)
#> 4 ICES DATRAS web service, haul positions by survey and year
#> 5 ICES statistical rectangle and area shapefiles, https://gis.ices.dk
#> 6 Gear spread models fitted to DATRAS haul data by survey