How to design information resources with a cartographic component: a technical approach be SE INFOTECH

The creation of web maps and information resources with spatial data has long gone beyond simple visualization of points on a map. Modern services require a data model capable of working with large amounts of spatial information, ensuring correct interpretation of oblects and supporting analytics scenarios.  

 

In this article SE INFOTECH team shares its approach to designing cartographic solutions, using the example of a digital resource dedicated to recording documented cases of cannibalism during the Holodomor famine in Ukraine. 

 

Development structure: why the mapping service is a separate stream  

The mapping module was separated into a separate development stream because it required its own logic, specific analytics and a separate testing cycle. 

 

This made it possible to: 

• separate the general functionality of the information resource and the map;
• avoid conflicts in requirements;
• ensure independent validation of data and visualizations;
• build architecture taking into account the load on spatical queries. 

 

Requirements analysis and task setting 

The initial requirements called for displaying historical events with geographic references. However, after decomposition, it became clear that the model should: 

• process events confirmed by multiple sources;
• aggregate records to avoid duplication;
• reflect relationships between objects;
• support attribute data for further analytics 

 

This determined the further approach to building the model and layer structure. 

 

Geoanalysis: the basis for accurate modeling  

During the geoanalysis stage, the following were formed: 

• classes of spatial object (event, source, territorial unit);
• attribute structure (date of recording, number of sources, source of confirmation, coordinates);
• relationships between entities (1:N for sources, N:1 for territories);
• an algorithm for merging duplicate events when different historical sources report on the same geographical event. 

 

The latter is a critical point. Instead of storing dozens of records, the service works with a single normalized entity, which: 

• simplifies processing;
• reduces the load on the server;
• increases display accuracy;
• imploves user experience 

 

Visualization model: selection of technical solutions 

After geoanalysis, visualization methods were identified that optimally reflect heterogeneous historical data: 

• categorization of events by the number of independent sources (color, size of makers);
• clustering at the zoom level for stability when scaling;
• pop-up details for in-depth analysis of attributes;
• minimization of unnecessary layers to avoid style conflicts and performance issues. 

  

Important: categorization by number of sources proved to be key — it not only adds informativeness, but also allows users to interpret the degree of reliability of an event.  

 

Technical implementation and layout of the web map 

During the map integration stage into the web interface, the team implemented: 

• layer hierarchy (base layers, event layers, aggregation mechanisms);
• stylization according to categories;
• a refined query system that optimizes resource consumption;
• adaptability and behavior at different scales;
• interaction of the map with the backend model, ensuring consistency of attributes.  

  

This approach made it possible to create a web atlas capable of working with complex historical information, ensuring data accuracy and user convenience. 

  

Conclusion: cartographic services as an analytics tool  

The project showed that a high-quality cartographic service is the result of a combination of: 

• business analysis;
• Geoinformatics;
• a well-thought-out data model;
• optimal visualization;
• and architectural solutions at the backend and frontend levels.  

 

This approach ensures scalability, accuracy, and high availability of the service – important characteristics for government-level mapping solutions