The data modeling method "FCO-IM" is a successor of the well known method NIAM; both use natural language to assemble the model. The FCO-IM is an advanced data modeling method which allows more elegant models, capable of better model to model transformations, while remaining to be easily validated by the business and it's users.

FCO-IM advantages compared to other modelling methods are:

Intense user participation, which leads to better model validation
100% conceptual approach, leading to better systems design
Integrated documentation, supporting improved contexting to the model
Extend the model fact by fact, ideal for agile development

Using natural language the meaning of data is modelled:

Clear documentation of business semantics using natural language
Easy validation of models by business users who are no modeling experts
Semantics is integrated in the modeling itself and not added afterwards
Performing model to model transformations maintains the language

Modeling while using real examples reduces misunderstandings:

Models, entities and attributes, are rooted in real business examples
Greatly reduces risk of "lost in translation", business language as input and output
A single example often explains more than any technical or abstract description

Every facttype is seen both as a single indivual as it is part of the whole:

Supports agile or incremental modeling by adding one fact at a time
No half facttypes (attributes) or bundles of facttypes (Entity types), but precisely one single unit of information at a time (one facttype)
Elementary facttypes are easy to spot in FCO-IM, but very hard to see in other models (ERM, UML, OWL, etc.)