Transformation of Knowledge, Information and Data: Theory and Applications considers transformations within the context of computing science and information science, as they are essential in changing organizations.
Data today is in motion, going from one location to another. It is more and more moving between systems, system components, persons, departments, and organizations. This is essential, as it indicates that data is actually used, rather than just stored. In order to emphasize the actual use of data, we may also speak of information or knowledge.
When data is in motion, there is not only a change of place or position. Other aspects are changing as well. Consider the following examples:
• The data format may change when it is transferred between systems. This includes changes in data structure, data model, data schema, data types, etc.
• Also, the interpretation of data may vary when it is passed on from one person to another. Changes in interpretation are part of data semantics rather than data structure.
• The level of detail may change in the exchange of data between departments or organizations, e.g., going from co-workers to managers or from local authorities to the central government. In this context, we often see changes in level of detail by the application of abstraction, aggregation, generalization, and specialization.
• Moreover, the systems development phase of data models may vary.
This is particularly the case when implementation-independent data models
are mapped to implementation-oriented models (e.g., semantic data
models are mapped to operational database specifications).
These examples illustrate just a few possibilities of changes in data. Numerous other applications exist and everybody uses them all the time. Most applications are of vital importance for the intelligent functioning of systems, persons, departments, and organizations.