Water quality visualization service for Secchi3000

Track 01: Information design and visualization

Tags: water system monitoring, water quality, crowdsourcing, citizen observations, measurement devices, data visualization, GIS.

Sponsor: SYKE



Visualize the available datasets or demonstrate how the visualization products/tools should look like. Consider the point of view of a limnologist or an environmental expert. The visualization and the tools should provide insights on water quality phenomena in the studied lakes.

Suggest practices that improve the information content and usability of information the above visualization products/tools. They should be applicable for single-volunteer observations or groups of volunteers.



The primary Secchi3000 data was acquired with iQwtr device by volunteers in Mikkeli region during 2015. Additional data was analyzed in 2016.

The dataset is available as…

  1. summarized to turbidity statistics for each lake water body in ESRI ArcGIS Online service (see data section below),
  2. interpreted image data that includes the different black-gray-white areas in two panels and their red-green-blue color statistics at two water depths, and time and location of the observations as an Excel table.

Only a preliminary analysis was carried out for other parameters than turbidity and Secchi depth. Unfortunately, that data is not available as a training data. Moreover, volunteers were not given any schedule for making the observations. The reports didn’t include any standardized template for conditions such as ice cover and algae. The datasets were not connected with any other environmental data.

Changes in humus (CDOM, coloured dissolved organic matter), water colour, Secchi depth and turbidity can be considered the most significant information for the experts using the data. However, all parameters affecting the water quality can be of interest if monitorable by volunteers. For example, you can consider parameters described in the Water Framework Directive.


Approaches and considerations

How to capture seasonal variation during the year? What data is required?

Note: Available data is not necessarily representative of the whole lake, nor the whole year, and not possibly even accurate.



Secchi3000 dataset (ESRI ArcGIS Online)



SYKE open data repositories 




Recent local observations by Xamk environmental engineering students from november 2017.



Additional materials

Detailed description and background for Secchi3000



Results and market reviews of iQwtr implementation of Secchi3000 devices, and the associated documentation.



Test datasets of iQwtr measurements, including original images, interpreted results and software for basic manual analysis. Also, a Matlab-based software is available for manual reprocessing and visualisation (if necessary).




You can consider and try out the below examples and technologies. However, you’re not limited to use them at all, or only them. You should explore different approaches and find technology that supports your idea.


IBM DSX (available in Bluemix)




Pixiedust (data visualisation helper)





Watson IoT




Watson for Unity



Bluemix service catalog (e.g. Watson and IoT)



IBM developer docs




ArcGIS Online of Xamk

Hackathon groups are granted an account for ArcGIS Online GIS platform. Your account has professional map authoring, publishing and analysis capabilities and rights.

A username and a password for the first login are provided per group by the staff.

Do NOT try to sign in here: http://www.arcgis.com/
The SIGN IN address is https://xamk.maps.arcgis.com/


Esri ArcGIS Desktop

You can use a trial desktop installation.



Esri developer docs