TODO

• occurrence search: proper message if empty table
• occurrence search: show numer of occurrences in ? occurrence search: (option to) group by family

Arabel

Source code for the (future) Atlas of spiders (ARABEL Database).

Implemented with Python, Django and Vue.js

Data import process

1. convert access database to CSV using jetread. All useful data is in the tables listed below:

./jetread spinnenatlas_20201007.mdb export "STAAL GEGEVENS" -fmt csv > staal_gegevens.csv

./jetread spinnenatlas_20201007.mdb export "LITERATUUR" -fmt csv > litteratuur.csv

./jetread spinnenatlas_20201007.mdb export "GEGEVENS" -fmt csv > gegevens.csv

./jetread spinnenatlas_20201007.mdb export "SOORTEN INFO" -fmt csv > soorten_info.csv

./jetread spinnenatlas_20201007.mdb export "Omschrijving Rode lijst categoriën" -fmt csv > redlist_categories.csv

2. Copy those 4 files to ./data (keep the same filenames)

3. Run the full import script:

$ python manage.py import_all_access

4. Make sure all grid data is in the database (see point below)

5. Reconcile Access data and grid data:

$ python manage.py join_station_squares

Importing grid data

Grid data (=MGRS squares over Belgium) should be imported to the MgrsSquare model/table. GeoDjango's layermapping utility can be used for that. Source data in grid_data directory:

• the mgrs5 file contains both 5km and 10mk squares all over Belgium (from https://github.com/BelgianBiodiversityPlatform/grids-belgium)
• the mgrs1 data is split in two files for zone 31U and 32U (downloaded from https://earth-info.nga.mil/GandG/update/index.php?dir=coordsys&action=mgrs-1km-polyline-dloads and manually clipped)

Example:

from django.contrib.gis.utils import LayerMapping
from website.models import *
mapping = {'name': 'code', 'gzd': 'gzd', 'poly': 'POLYGON'}
lm = LayerMapping(MgrsSquare, '/home/nnoe/Downloads/utm5_grid_belgium.polygon.gpkg', mapping)
lm.save(verbose=True, strict=True)