Capture and use knowledge about data in BlueDolphin

In our world we use data.
We need knowledge to understand or describe which data we have and how we use it.
Knowlegde about data in the world at this moment, but the real challenge is on knowledge about data in the world that keeps changing.

A data element is the central object to capture knowledge about data in BlueDolphin - it represents data in the real world of today or tomorrow.
To that object we can connect all sorts of data about that data element.
Connecting data to objects lies in the nature of BlueDolphin and can be done in multiple ways via the available tool features like the common questionnaires and views a.k.a. 'werkset'.

The basic properties of a data element are (1) its unambiguous name (2) its definition in the broadest sense, so including data defining its structure or being.
Next we can connect all sorts of data to that data element, which has already grown to be a data definition - a body of data - a data element with flesh on the bones by adding (1) and (2) to it.
We can add information to do data governance on the data definition.
We can add information about usage of the data definition.

We may connect the data definition to technical data elements like (unambiguous names of) database elements - relational or other types, message elements - xml, json or other formats, file elements - csv or other formats.
Anything goes as long as we can refer to it, which requires the unambiguous name.
Via the relationship between a data definition and technical data element we are connected to all the data about that technical data element.

Like technical data elements, we can connect data definitions to definitions of concepts and semantic relations including the data about them as well.

Last but not least, we can connect data definitions to their existence in data models of all sorts.
Data models come in many sorts for many purposes.
As an example, we have defined four kinds of data models pointed to software development:

a) conceptual model of business context, which gets requirements and data constraints from the world to model semantics of data concepts.
In BlueDolphin you can already model essential semantics between data element objects, which is basically a diagram of concept terms and semantic relations.

b) data model of application context, which orders data elements in data entities and attributes with semantic relations between entities.
BlueDolphin's Logical Data View has been designed for this kind of models - a Data Object type of object is used as an object for each data entity.
A data entity can be related to its data definition (Data Definition type of object) and all the knowledge about it.
This expression of the data identity of the data object is called the Primary Key (PK) in BlueDolphin, which is loosely related but must not to be confused with the PK in a database model.
Semantic relations between data entities can be expressed using crowfoot-notation, either via the PK or just between the data entities.
Note that this type of models does not have a specific purpose like software development yet e.g. relational database modelling (normalization, compound keys, etc) or Object-Oriented modelling (class type of entities, etc).
c) logical model of software implementation, which orders data elements for implementation in software e.g. a relational database, an object-oriented data layer of an application, a star model in a datawarehouse solution.
These models contain technical data elements, which may be of interest to grow your knowledge about data elements in BlueDolphin.
When you already have knowledge about data elements in BlueDolphin, then BlueDolphin gives input to the creation of these models.
The BlueDolphin features of interest in this stage of software development concern import and export of data.

d) physical data model of software implementation, which models the actual implementation of data elements in software.
These models contain technical data elements, which may be of interest to grow your knowledge about data elements in BlueDolphin.
When you already have knowledge about data elements in BlueDolphin, then BlueDolphin gives input to the creation of these models.
The BlueDolphin features of interest in this stage of software development concern import and export of data.

The above illustrates how we capture and use knowledge about data with BlueDolphin.
More tool features will come, if you have feature wishes then please add a comment to this post.