Scrap available information on the Internet related to:

• mobile network operators (such as MCC, MNC, brand, network type, countries of operation...)
• countries (such as country name, 2 and 3-chars ISO codes, tld, boundaries and neighbours...)
• international dialplan (such as msisdn prefix and associated countries, signaling point codes...)

Using public data from the the following websites:

• Wikipedia
• ITU-T
• The CIA World Factbook
• txtNation
• Ewen Gallic blog

And generate re-engineered JSON and Python dictionnaries from them.

The code from this repository, that is used to generate the dataset, is licensed under the terms of the AGPLv3. The data downloaded from Wikipedia is licensed under the terms of the Creative Commons Attribution-ShareAlike license. The 4 other websites used as source do not indicate any specific licensing for the data provided.

Several sources are available on the Internet:

• ISO website:
  • https://www.iso.org/obp/ui/#search
  • https://www.iso.org/obp/ui/#iso:pub:PUB500001:en
• Wikipedia:
  • https://en.wikipedia.org/wiki/Mobile_country_code

• ITU-T documents:
  • List of MCC: https://www.itu.int/pub/T-SP-E.212A
  • List of MNC: https://www.itu.int/pub/T-SP-E.212B
  • Operational bulletins: https://www.itu.int/pub/T-SP-OB
• Wikipedia:
  • List of MCC: https://en.wikipedia.org/wiki/Mobile_country_code
  • List of MNC: international networks listed in the MCC page, and 6 pages linked from there, one per world region
• Other websites:
  • https://www.mcc-mnc.com/ (contains several errors, e.g. related to country codes)
  • https://clients.txtnation.com/hc/en-us/articles/218719768-MCCMNC-mobile-country-code-and-mobile-network-code-list (csv file)
  • https://clients.txtnation.com/hc/en-us/articles/218719468-Operator-Details-Operator-Network-CC-MCC-MNC (xls file)
  • https://cellidfinder.com/mcc-mnc
  • https://docs.routee.net/docs/list-of-mccmnc-codes

• ITU-T documents:
  • https://www.itu.int/pub/T-SP-E.164D
• Wikipedia:
  • https://en.wikipedia.org/wiki/List_of_country_calling_codes
  • https://en.wikipedia.org/wiki/List_of_mobile_telephone_prefixes_by_country#International_prefixes_table
  • https://en.wikipedia.org/wiki/International_Networks_(country_code) (for international networks)
• Other websites:
  • https://github.com/google/libphonenumber/tree/master/resources/geocoding/en
  • https://phonenum.info/en/country-code/

• Wikipedia:
  • https://en.wikipedia.org/wiki/List_of_countries_and_territories_by_land_borders
• Other websites:
  • http://www.naturalearthdata.com/downloads/10m-cultural-vectors/ (open US-based initiative, see admin 0 data)
  • https://github.com/nvkelso/natural-earth-vector (vectorized data from naturalearthdata)
  • https://www.cia.gov/library/publications/the-world-factbook/appendix/appendix-d.html (CIA open data)
  • https://developers.google.com/maps/documentation/javascript/geocoding (Google maps API)

The CIA World Factbook is more complete than Wikipedia when coming to geography and borders referencement.

Specifically for the minimum distance between countries, here are valuable sources:

• https://egallic.fr/en/closest-distance-between-countries/
  • with updated R code and computed values: https://gist.github.com/mtriff/185e15be85b44547ed110e412a1771bf/
• http://nils.weidmann.ws/projects/cshapes.html (CShapes dataset and R package)
• https://zenodo.org/record/46822 for sea-distances only
  • with related information provided here: https://halshs.archives-ouvertes.fr/halshs-01288748/document
• https://www.transtats.bts.gov/Distance.asp for distances between airports

Some other sources may be found online ; additionally, it seems the R programming language has nice geography-related packages.

ITU-T is publishing bi-mensual bulletins (23 or 24 a year, depends...), containing all additions and modifications to numbering plans and MNC identifiers. Complete lists of MCC-MNC can be found in bulletin 1111 from 2016 and bulletin 1162 from 2018. Moreover, differentials can be provided into individual bulletin.

One of the script can be used to download all bulletins in PDF (starting from 1111), and convert them into text, using the Linux command pdftotext. All resulting documents are available in the itut/ directory.

Bulletins 1111 from 2016 and 1162 from 2018 contain a full list of declared MCC-MNC. Bulletin 1199 contains a full list of declared international signaling point codes. The script extract them and put resulting JSON and Python files into the raw/ directory for further integration.

After checking several sources, it seems Wikipedia has the most complete, up-to-date and accurate information. Therefore, the tool primarily uses it to build the JSON / Python dictionnaries. Information related to MCC-MNC is completed with the csv listing from the txtNation website and the ITU-T operational bulletins 1162. The list of Signaling Point Codes is extracted from ITU-T bulletin 1199. Geographical information are taken from the CIA World Factbook to gather information related to each country, including borders and telephony-related. This is completed with the data provided on the egallic blogpost for getting close countries in addition to neighbours one.

The provided scripts require Python3, and lxml for the ones extracting data from web sites (parse_wikipedia_tables.py and parse_worldfactbook_infos.py). No installation is required, just run the scripts as is.

The Wikipedia, World Factbook, Egallic and txtNation data, and ITU-T bulletins can be imported and processed by using the following commands:

$ ./parse_wikipedia_tables.py --help
usage: parse_wikipedia_tables.py [-h] [-j] [-p]

dump Wikipedia ISO-3166 country codes, MCC and MNC tables into JSON or Python
file

optional arguments:
  -h, --help  show this help message and exit
  -j          produce JSON files (with suffix .json)
  -p          produce Python files (with suffix .py)

$ ./parse_worldfactbook_infos.py --help
usage: parse_worldfactbook_infos.py [-h] [-j] [-p]

dump country-related informations from the CIA World Factbook into JSON or
Python file
[...]

$ ./parse_various_csv.py --help
usage: parse_various_csv.py [-h] [-j] [-p]

dump csv files from the Egallic blog (distance between countries) and the
txtNation website (list of MCC-MNC)
[...]

and

$ ./parse_itut_bulletins.py --help
usage: parse_itut_bulletins.py [-h] [-d] [-j] [-p]

download ITU-T operational bulletins, convert them to text, extract lists of
MNC and SPC

Then, in order to load all those imported data with aligned and coherent values (e.g. country names, ISO codes and other information and numbering), the module patch_dataset can be used. It exports the Wikipedia, World Factbook, Egallic, txtNation and ITU-T datasets, after applying few corrections and fixes on them:

>>> from patch_dataset import *
[...]
>>> WIKIP_ISO3166
[...]

The command gen_dataset.py then generates new JSON and Python dictionnaries based on those re-engineered data and store them in new files prefixed with "p1":

• MNC: dict of MCCMNC 5/6-digit-str, MNO(s) information
• MCC: dict of MCC 3-digit-str, Operators-related information
• MSISDN: dict of MSISDN prefixes, countries
• MSISDNEXT: dict of MSISDN prefixes, countries and extra-territories
• ISPC: dict of international signaling point codes, countries and operators
• CC2: dict of alpha-2 code, country-related information
• CNTR: dict of country, country-related information (similar to CC2)
• TERR: dict of country or territory, borders and neighbour related information

$ ./gen_dataset.py
[...]
[+] gen/p1_mnc.json file generated
[+] gen/p1_mnc.py file generated
[+] gen/p1_mcc.json file generated
[+] gen/p1_mcc.py file generated
[+] gen/p1_msisdn.json file generated
[+] gen/p1_msisdn.py file generated
[+] gen/p1_msisdnext.json file generated
[+] gen/p1_msisdnext.py file generated
[+] gen/p1_ispc.json file generated
[+] gen/p1_ispc.py file generated
[+] gen/p1_cc2.json file generated
[+] gen/p1_cc2.py file generated
[+] gen/p1_cntr.json file generated
[+] gen/p1_cntr.py file generated
[+] gen/p1_terr.json file generated
[+] gen/p1_terr.py file generated

The following one-liner can be used to update the whole final dataset (without downloading ITU-T bulletins):

$ ./parse_wikipedia_tables.py -j -p && ./parse_worldfactbook_infos.py -j -p && ./parse_various_csv.py -j -p && ./parse_itut_bulletins.py -j -p && ./gen_dataset.py

Now you can use those dictionnaries to get complete information for any MCC, MNC, MSISDN prefix, and related geographical information.

Finally, 3 little command-line tools are provided to make direct use of the extracted and engineered dataset:

$ ./chk_mnc.py --help
usage: chk_mnc.py [-h] [-x] [MCCMNC [MCCMNC ...]]

provides information related to mobile operator(s); if no argument is passed,
lists all known MCC-MNC

positional arguments:
  MCCMNC      0 or more 5/6-digit string for MCC-MNC

optional arguments:
  -h, --help  show this help message and exit
  -x          provides extended information for MNO(s)

$ ./chk_msisdn.py --help
usage: chk_msisdn.py [-h] [-x] [MSISDN [MSISDN ...]]

provides information related to international telephone prefix; if no argument
is passed, lists all known MSISDN prefixes

positional arguments:
  MSISDN      0 or more digit string for MSISDN

optional arguments:
  -h, --help  show this help message and exit
  -x          provides extended country-related information

$ ./chk_cntr.py --help
usage: chk_cntr.py [-h] [-x] [COUNTRY [COUNTRY ...]]

provides information related to a given country or territory; if no argument
is passed, lists all known countries and territories

positional arguments:
  COUNTRY     0 or more string for country (can be an alpha-2 code too)

optional arguments:
  -h, --help  show this help message and exit
  -x          provides extended country-related information

All command-line tools are available straight in the root directory of the project. Data downloaded and extracted from Internet are put in the raw/ directory, except document from the ITU-T which are downloaded as PDF and converted to text in the TS/ directory. Re-engineered data are put in the gen/ directory.