MINT Release updates

Last updated: 2020-04-01

March, 2020

  • Release MINT-UI 4.3.4
    • Changelog
    • Users can run their ModelConfigurations
  • Release DAME 3.3.0 (Desktop Application for Model Execution).
    • Execute models from MINT on Desktop/Server
  • Release ModelCatalog v1.4.0
    • Users can insert their ModelConfigurations

February, 2020

January, 2020

December, 2019

MINT Data Catalog

MINT Model Catalog:

Ingestion API:

  • Release 1.1.0:
    • Gather model ensemble execution results

Ensemble Manager API

  • Release 1.0.0:
    • Execute models using singularity
    • Include parallelism option in config
    • Adding DELETE request to executionsLocal to delete cache of execution

November, 2019


  • Release of MINT NetCDF convention
    • We propose a self-describing data format for structured gridded datasets for MINT data catalog and visualization based on the NetCDF and the CF convention. Check here for the lastest document. Please open new issues on GitHub or on Google doc for comments.
  • Release of MINT-GeoViz
    • We are releasing the v1 of MINT-GeoViz, an interactive visualization library for large geospatial datasets that follow MINT NetCDF convention. Check out this GitHub repo for more details.
    • Check out our full demo and notebook examples on how to use the library

October, 2019

Data Catalog

  • Release D-REPR: a library for reading heterogeneous datasets into common representations. Check its GitHub for more information.

May, 2019

Model Catalog

  • New content: The MINT model catalog has been expanded to include a semantic representation of units, scientific variables and links to Wikidata. Check the release on GitHub for more information.
  • New APIs for adding content: We have expanded our APIs with a new client based on Open API that allows anyone to insert models in the model catalog. The API is accessible in the following link:
  • New APIs for accessing content: 3 new methods have been added to our GRLC API. The first one, to obtain additional information of a Scientific Variable given its label (getStandardVariableMetadata). The other two (getInputCompatibleConfig) and (getOutputCompatibleConfig) retrieve those models or software compatible with a target model. This facilitates understanding which software has variables that may interoperate with other software.
  • A new client for accessing content: With our new Python client, now it is possible to access the content in the model catalog without having to issue SPARQL queries or API queries. Check it out here.
  • New examples: Check out our notebook for examples on how to use the client.
  • The Model Explorer has been updated to show the contents of models in a more user-friendly manner. Check here the latest version. Please open new issues on GitHub if you find bugs.