Well-visualized data sets support renaturation projects

© Data Mining und Value Creation
Project team: Yves Annanias (Leipzig University), Mr. Taubert (LMBV), Dr. Daniel Wiegreffe (Leipzig University), Milan Pentrack (Fraunhofer IMW), Stefan Kutter (LMBV)

Pilot project with LMBV completed

A team of scientists from the Data Mining and Value Creation project has successfully completed the pilot project with Lausitzer und Mitteldeutsche Bergbau-Verwaltungsgesellschaft mbh (LMBV). The pilot project developed a prototype software solution for more efficient processing of inquiries about mining rehabilitation activities.

LMBV’s specially designed geo-information system, which is constantly being developed to meet LMBV’s requirements, served as the starting point. However, due to the immense increase of available data and documents, it became more and more complex for LMBV to efficiently answer inquiries of third parties, which refer to the areas renatured by LMBV.

Visual preparation of text and geodata

As part of the pilot project, the data model for LMBV’s renaturation data was restructured. For this purpose, a graph-based database was chosen in order to better model the connections between the individual data and documents.

In order to better take into account hazard warnings, prohibitions and restrictions on use in renaturation planning, the scientists developed a web application that links text data with geodata and displays them visually on digital maps. The corresponding information is automatically extracted from the texts using machine learning.

To extract the bids and bans from LMBV documents, the researchers used the Active Learning paradigm to train a Support Vector Machine model* with as little manually annotated training data as possible. Using an existing mapping of documents to geo-coordinates, the constraints extracted in this way can be directly displayed on a map.

*mathematical method for pattern recognition

© Data Mining und Value Creation
Extract from the visualization tool

Analysis of mass data becomes possible

The object of research within visualization is the clear representation of a large amount of overlapping areas on a map. The solution used includes an aggregation of the data in the form of a heat map that can be filtered by category. In addition, for detailed views a so-called multiple coordinated view representation was developed in order to reduce the overlapping of areas in the map. Finally, the prototype was tested for usability by means of an evaluation study.

Stefan Kutter, head of the geoinformatics department at LMBV, is satisfied with the progress of the project: “With the present software solution, we have succeeded in exemplarily presenting, restructuring and analyzing the problem of evaluating mass data of different origins. In perspective, the present approach can be a supplement to the existing geoinformatics system of LMBV. Especially the intelligent and self-learning text recognition should be developed and deepened in further projects, based on the current findings.”

The work of the pilot project will be continued and expanded in the research project “Smart Regional Development Infrastructure (SARDINE)” within the Smart Infrastructure Hub Leipzig.


New data platform for renaturation projects