DSSM - Pandora & IsoMemo spatiotemporal modeling

Shiny App for spatiotemporal modeling developed with the Pandora & IsoMemo initiatives.

Access to online versions:

• MAIN versions:
  • Search: https://pandorasearch.earth/ or https://isomemosearch.com/
  • Search & Modeling: https://isomemoapp.com/app/dssm
• BETA versions:
  • Search: https://isomemoapp.com/app/dssm-data-app-beta
  • Search & Modeling: https://isomemoapp.com/app/dssm-beta

Documenation

• https://pandora-isomemo.github.io/DSSM/

Installation instructions

• https://pandora-isomemo.github.io/docs/apps.html#dssm---data-search-and-spatiotemporal-modelling

Release notes (Changelog):

• see NEWS.md

Folder for online models

• inst/app/predefinedModels

How to use this Package

Refer to the vignette for a description of the usage of the MapR package. You can find it in the documentation of this package.

Notes for developers

When adding information to the help sites, docstrings or the vignette of this package, please update documentation locally as follows. The documentation of the main branch is build automatically via github action.

devtools::document() # or CTRL + SHIFT + D in RStudio
devtools::build_site()

When testing with a local docker container, please make sure to rebuild the docker image after changes in the R code or dependencies. You can do this from the root of the repository via:

docker build -t dssm-app:latest .

After that, start the container as usual via:

docker run -p 3838:3838 dssm-app:latest

and access the app in your browser at http://localhost:3838/. Stop the container with CTRL + C in the terminal.

Optional:

Add -it for interactive mode, or --rm to remove the container after stopping.

Acknowledgments

This project is licensed under the GNU General Public License v3. It incorporates third-party packages with their respective licenses:

• rnaturalearth (MIT License) - Provides map data from Natural Earth. See LICENSE.md for full license details.

Interactive basemaps shown via Leaflet providers are provided by third parties and remain subject to their own licenses, attribution requirements, and terms of use. Users are responsible for ensuring permitted reuse and publication of any exported or published maps. A reference list of supported Leaflet providers is available at leaflet-providers preview.

Recommended Citations

If you reference methods implemented through this application in academic work, please also cite mclust as recommended by its authors:

Scrucca L, Fraley C, Murphy TB, Raftery AE (2023). Model-Based Clustering, Classification, and Density Estimation Using mclust in R. Chapman and Hall/CRC. ISBN 978-1032234953, doi:10.1201/9781003277965, https://mclust-org.github.io/book/.

For complete license information, please see LICENSE.md.