Understanding ownership structures is rarely difficult because the individual data points are unavailable. The real challenge is understanding how numerous companies, shareholders, subsidiaries and historical relationships interact with one another.

The example of FACC AG illustrates why a three-dimensional representation can make this task significantly easier. Instead of presenting ownership relationships as a conventional two-dimensional table or a flat network diagram, Data2Space can transform the structure into a spatial environment that can be explored from different perspectives.

From a Flat Ownership Chart to a Spatial Business Graph

In a conventional representation, FACC AG and the companies connected to it are arranged on a two-dimensional screen. As the number of relationships increases, lines begin to cross, labels become smaller and the viewer has to mentally reconstruct which connection belongs to which company.

The visualization shown above already demonstrates the complexity of the FACC AG environment. Companies such as FACC Operations GmbH, FACC Austria Holding GmbH, Fischer Beteiligungsverwaltungs GmbH, FREQUENTIS AG, AIT Austrian Institute of Technology GmbH, universities and other organizations appear as interconnected nodes.

In Data2Space, these relationships can instead become a spatial business graph. Companies can be positioned at different depths and heights, while connections can be examined from the front, from the side, from above or from behind.

This changes the analytical experience fundamentally: the user no longer has to understand the entire structure simultaneously.

Current and Historical Relationships in the Same Space

One particularly powerful application is the exploration of current and historical ownership relationships.

A two-dimensional database view normally forces the analyst to switch between records, dates or different versions of a corporate structure. The user has to remember what was visible previously and compare it mentally with the current situation.

Spatial Computing offers another approach.

Different relationship states can be represented as different spatial layers or visual states. An analyst could, for example:

• inspect the current ownership structure;
• move to a historical state;
• identify companies that have entered or left the structure;
• examine changes in ownership relationships;
• follow a relationship through several stages of corporate development;
• return to the current structure without losing the overall spatial orientation.

The key advantage is that time can become another dimension of analysis.

Why Three Dimensions Reduce Cognitive Complexity

Three-dimensional visualization does not simply add a third axis for visual effect. It creates additional possibilities for organizing information.

A complex structure can be distributed:

left ↔ right — different ownership branches
above ↕ below — levels within a corporate structure
front ↔ behind — different relationship layers or historical states

This means that relationships that would otherwise compete for the same space on a screen can occupy different spatial positions.

The analyst can physically move around the structure and isolate individual branches. Instead of asking “Which line belongs to which company?”, the user can simply change position and perspective.

Following a Relationship Instead of Reading a Table

The real analytical value emerges when the user selects an individual company.

Starting with FACC AG, the analyst can move toward a particular ownership relationship and investigate the connected entity. From there, another relationship can be followed.

The process becomes similar to navigating a virtual mind map:

FACC AG → ownership relationship → connected company → next relationship → underlying entity

Instead of repeatedly opening database records, the analyst remains inside the same spatial model.

This makes it easier to recognize structures that are difficult to detect in lists—for example, clusters of companies, multiple connections to the same organization, or relationships that become apparent only when several levels are considered together.

Historical Analysis Becomes an Exploration

Historical ownership data becomes especially interesting when it is spatialized.

Imagine the FACC AG structure at one point in time as a spatial configuration. A subsequent historical state can then be compared with it. Relationships can disappear, new relationships can emerge, and corporate structures can change.

Rather than merely reading:

Relationship A existed in year X and relationship B exists today,

the analyst can see how the structure evolved.

This is important for financial analysis, due diligence, corporate research and investment analysis because the present structure is often only the result of a longer sequence of transactions and organizational changes.

Spatial Computing Makes Business Graphs Intuitive

Data2Space builds on the principle that business relationships are inherently graph-shaped.

Traditional databases are excellent at storing the individual records. Two-dimensional screens are excellent at displaying them in tables and diagrams. But humans often understand complex relationships more intuitively when they can see the whole structure and navigate through it.

Spatial Computing adds precisely this capability.

The FACC AG example demonstrates how a business graph can become an environment that the analyst explores rather than merely a diagram that the analyst reads.

From Data Retrieval to Spatial Investigation

The most important difference is therefore not simply that the visualization is three-dimensional.

It is that the analyst can change the way the question is asked.

Instead of:

“Which companies are connected to FACC AG?”

the question becomes:

“What does the FACC AG ecosystem look like, how is it connected, and how has it changed over time?”

That shift—from retrieving individual data points to exploring relationships—is at the heart of Data2Space.

For complex ownership structures, three-dimensional visualization can therefore provide a much more intuitive way to investigate both where a company stands today and how it got there.