Calligraphy (from Greek) is the visual art of designing letters with a pen, ink or pencil. It is“the art of giving form to signs in an expressive, harmonious, and skillful manner” (Wikipedia)

I discuss the calligraphy of data here, consider it the art of visualising data to bring out its symphony, the way each of its parts contribute to the balance of the whole. My previous paper on the topic, uploaded to the Research Gate in 2013 covered some of the basic aspects of modelling and its benefits. Curiously enough, in the last couple of years, readership and interest on the topic has increased tremendously with the growth of data science as a discipline in itself. It is this new vigour and interest in the architecture of data that encourages me to rewrite my previous paper to bring in additional and fresh perspectives on the techniques possible in
the area of expressing the structure of data.

What is a data model?

A data model is a visual representation of an information system and shows how the entities within the domain and their attributes relate to each other. The model captures the metadata of the business objects in a way that makes it intuitive to be used by a wide spectrum of users across the organisation.¹

The scope of modelling can be the entire business do main, a sub-system or specifically an application. This guide discusses five data modelling techniques. The objective is to explain the concepts of the different models and how they represent the business objects, also how the model becomes a catalogue of the enterprise metadata.

The DAMA definition states: “Data modelling is the process of discovering, analysing, and scoping data requirements, and then representing and communicating these requirements in a precise form called the data model.”
DAMA DMBoK. https:// http://www.dama-uk.org/.Accessed: 2020-12-10