OnWorks favicon

SPAWNN download for Windows

Free download SPAWNN Windows app to run online win Wine in Ubuntu online, Fedora online or Debian online

This is the Windows app named SPAWNN whose latest release can be downloaded as spawnn-0.1.9.jar. It can be run online in the free hosting provider OnWorks for workstations.

Download and run online this app named SPAWNN with OnWorks for free.

Follow these instructions in order to run this app:

- 1. Downloaded this application in your PC.

- 2. Enter in our file manager https://www.onworks.net/myfiles.php?username=XXXXX with the username that you want.

- 3. Upload this application in such filemanager.

- 4. Start any OS OnWorks online emulator from this website, but better Windows online emulator.

- 5. From the OnWorks Windows OS you have just started, goto our file manager https://www.onworks.net/myfiles.php?username=XXXXX with the username that you want.

- 6. Download the application and install it.

- 7. Download Wine from your Linux distributions software repositories. Once installed, you can then double-click the app to run them with Wine. You can also try PlayOnLinux, a fancy interface over Wine that will help you install popular Windows programs and games.

Wine is a way to run Windows software on Linux, but with no Windows required. Wine is an open-source Windows compatibility layer that can run Windows programs directly on any Linux desktop. Essentially, Wine is trying to re-implement enough of Windows from scratch so that it can run all those Windows applications without actually needing Windows.





The SPAWNN toolkit is an innovative toolkit for spatial analysis with self-organizing neural networks which is particularily useful for spatial analysis, visualization and geographical data mining.

To run the toolkit, simply download and execute (double-click) the jar-file.

Please cite:
- Hagenauer, J., & Helbich, M. (2016). SPAWNN: A Toolkit for SPatial Analysis With Self-Organizing Neural Networks. Transactions in GIS, 20(5), 755-775.

Other related publications:
- Hagenauer, J. (2016). Weighted merge context for clustering and quantizing spatial data with self-organizing neural networks. Journal of Geographical Systems, 18(1), 1-15.
- Hagenauer, J., & Helbich, M. (2013). Contextual neural gas for spatial clustering and analysis. International Journal of Geographical Information Science, 27(2), 251-266.


  • Implements Self-Organizing Map and Neural Gas algorithms
  • Supports different approaches for considering spatial dependence
  • Provides linkage between networks and geographical data
  • Implements powerful clustering algorithms for structuring the networks


Machine Learning, GIS

This is an application that can also be fetched from https://sourceforge.net/projects/spawnn/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.