ClimVis – Preparation, Analysis and Visualization of extensive Data with Open Source Programs (R, QGIS, leaflet)

The name ClimVis stands for ‘Climate Visualization’ because originally I was particularly interested in climatology and weather activity. Climatological data, like historic time series or data from numeric weather models, are quite big and therefore, they need to be processed and visualized automatically. The statistics and processing methods used in climatology can also be used in other fields where data has to be analyzed automatically. This could be data from marketing, real estate, journalism, tourism, energy, entertainment, insurance, sports, stock transfer, development aid, etc.

ClimVis provids

Data Preparation
The preparation of big datasets is often quite time consuming. Incorrect or critical data entries, such as missing values, duplicates or misspellings, need to be detected and corrected. For big data this can’t be handled manually but must be done automatically. Therefore, the programming language R is designed for. R contains numerous integrated functions and can be extended by a variety of packages.

In data analysis, statistical methods such as classification or trend analysis are often used. But also methods form digital image processing, like gradient operators or low-pass filters, can give you new informations about your data. However, in the measuring technology simulation models and error calculating are very important. R provides many functions for all these different procedures and is ideally suited for the implementation of these methods.

After data preparation and analysis the right visualization of the gained informations is important. The more understandable your graphical representation is the easier it is for the viewer to understand the shown informations. Spatial data for example can be shown in maps. In case datasets need to be compared, then line charts are better suited. And again, R offers many possibilities for visualizations. Furthermore, R also provides tools to generate data in different formats like geoJSON in order to create web based, interactive maps with the open-source JavaScript library Leaflet. Interactive visualizations are usually intuitive and very informative which makes the data inquiry particularly user friendly.

The documentation of data preparation, analysis and visualization is very important to make the developed process reproducible. But also for the identification of errors in complex procedures the documentation shouldn’t be missing.

The Goals

On this page I want to show some projects I was working on. Thereby, I would like to make new contacts and find:

  • Investors or support for future projects
  • Projects and cooperations as a self-employed entrepreneur
  • Employment with a company, which is open-minded towards open source technologies and provides a comfortable working environment for women.

Do you have data which needs preparation, analysis or visualization?

ClimVis provides consulting and will, in close cooperation with you, develop the right procedures for your tasks.

Don’t hesitate to contact ClimVis.