Skip to main content

Add-on containing MECODA widgets to analyse data from citizen science observatories

Project description

Mecoda-Orange

Orange Data Mining Widgets to analyse data from science citizen observatories. See documentation.

MECODA (ModulE for Citizen Observatory Data Analysis) is an online tools repository to facilitate the analysis and viewing of all sorts of citizen science data.

MECODA is part of Cos4Cloud, a European Horizon 2020 project to boost citizen science technologies.

Features

  • Minka: collect observations from Minka API, using mecoda-minka library.
  • OdourCollect: collect observations from OdourCollect API, using PyOdourCollect library.
  • canAIRio: composed for two widgets, one for CanAIRio Fixed Stations data and other for CanAIRio Mobile Stations data.
  • Ictio: process observations from ictio.org zip file, using IctioPy library.
  • Natusfera: collect observations from Natusfera API, using mecoda-nat library.
  • Smart Citizen: collect observations from the SmartCitizen API, using two widgets, one for collecting information about the kits in the smartcitizen platform and another one for the actual timeseries data. For making use of the timeseries data, it is necessary to add the orange timeseries add-on.

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

Mecoda Orange-1.8.2.tar.gz (56.5 kB view details)

Uploaded Source

Built Distribution

Mecoda_Orange-1.8.2-py3-none-any.whl (2.3 MB view details)

Uploaded Python 3

File details

Details for the file Mecoda Orange-1.8.2.tar.gz.

File metadata

  • Download URL: Mecoda Orange-1.8.2.tar.gz
  • Upload date:
  • Size: 56.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/34.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.63.0 importlib-metadata/4.11.3 keyring/18.0.1 rfc3986/1.5.0 colorama/0.4.3 CPython/3.8.10

File hashes

Hashes for Mecoda Orange-1.8.2.tar.gz
Algorithm Hash digest
SHA256 5554d7fd026ce8744199bd69eb40f53309f4a3174e50f03e931505ebe73b76da
MD5 be2bc254b00dabbd3e88596f4e541523
BLAKE2b-256 103f3c4aed39be848e59ee646698b7a3a96568a2f6f8942d17be1ea815d4c015

See more details on using hashes here.

Provenance

File details

Details for the file Mecoda_Orange-1.8.2-py3-none-any.whl.

File metadata

  • Download URL: Mecoda_Orange-1.8.2-py3-none-any.whl
  • Upload date:
  • Size: 2.3 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/34.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.63.0 importlib-metadata/4.11.3 keyring/18.0.1 rfc3986/1.5.0 colorama/0.4.3 CPython/3.8.10

File hashes

Hashes for Mecoda_Orange-1.8.2-py3-none-any.whl
Algorithm Hash digest
SHA256 fc67cab10a712a39e3f5892dfa3f5548612f4204b01b23cc3f09db0e7d22b96e
MD5 02118bb906340bba68b8e267172ed9f4
BLAKE2b-256 7f06a4319dc9787954a069493886ecbfc3f7102aee5776ade82e370ab03d15df

See more details on using hashes here.

Provenance

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page