Uninfluenceable Activities

Uninfluenceable activities belong to a category of transitions which contain only a few activities which constantly occur during the creation of an artefact. These special tran- sitions usually run parallel to all other transitions in the creativity map. This type of transitions is not helpful for most of the analysis. At the same time, the information can be stored inside the states. The information itself is not lost. As a result, these transitions are usually hidden in the creativity map, to reduce the amount of data. However, these special transitions shall not be unmentioned for the sake of completeness.

The following transitions belong to this category:

Time Transition

The time transition marks the time spent on the creation of an artefact. This transition runs parallel to every normal transition. The information of this transition is somewhat trivial and usually not required for the analysis.

writing readin_g conte mplat ing time time time

Figure 3.20 depicts a part of a creativity map with time transition. One can imagine that these transitions are quite confusing in a larger creativity map. Furthermore, every state contains the actual timestamp. The time transition only indicates that the clock progressed.

Thinking Transition

Every person is constantly thinking during the whole life, even when sleeping. It is impos- sible for a human to stop subconscious thinking. People think when reading, writing and so on. Therefore, there could be a thinking transition parallel to every normal transition - same as the time transition. However, these thinking transitions are not important for a later analysis. Only an action, resulting from the subconscious process, like inspiration, is of interest.

3.11

Summary

This chapter provides the formal underpinning for the process of mapping the human creativity. The generalised transition system (GTS) was introduced as a flexible model. It represents the ideal foundation for the analysis of the creative process. The, on the GTS based, creativity maps are capable of representing the creative process in its entirety. The precision and granularity of the creativity map is only limited by the collection method of the raw data and the resulting accurateness.

The GTS consists of two elements: states and transitions. States represent the different stages or versions of the creative product. The content of a state is not limited to the artefact itself, but several elements, stored in a state vector. Those elements can be for example the artefact, gained knowledge and quality aspects (like the results from discussions or inspections of the artefact).

Actions are represented as transitions from one state to a second one. The end state of the transition is usually a new state, but can also be an old state in special cases. Furthermore, all transitions are labelled, describing the current action. Through this, it is possible to describe the whole creative process, including the creational activity but also intellectual activities like contemplating, reading, discussion and so on. This thesis is focussing on the activities and their representation as transitions in the creativity map. The activities are the atomic elements of the creative process.

Each activity belongs to a certain viewpoint. A viewpoint represents all activities which change the same element of the state vector. For example one viewpoint represents all creational activities, responsible for changes made to the artefact. Another viewpoint might represent all activities responsible for the gain of knowledge.

A simple recording of the activities is leading to a linear representation of the creative process, the creative path. However, the creative process is not linear but chaotic. It is necessary to be able to describe the whole complexity of the creative process. As a result, the creativity map was introduced [136]. Through this, it is possible to cover all aspects of the creative process. The creativity map is generated from the creative path. The map creation process transforms the states and transitions of the creative path into their logical relation. Through this it is possible to represent situations where the creator abandoned the current approach and went back to a previous idea.

Creativity maps can be of very large size, depending on the length of the creation process as well as the number of the undertaken activities. The presented approach enables the creation of partial creativity maps. Through this, it is possible to hide parts of the creativity map based on certain attributes of the states as well as a hiding based on the viewpoints or transition types. These attributes can be for example the timestamp or noticeable changes to the attribute itself (e.g. a large increase of words in a document).

States and transitions as well as the, on these applicable, operations share a sound math- ematically underpinning and are standardised. This allows the comparison of two or more creativity maps. Moreover, the comparison is not limited to creativity maps belonging to the same domain. The foundation of the creativity maps is always the same, regardless of the domain the artefact is belonging to. This is the first model which enables the analysis and comparison of creative process from different creators and different domains.

Another huge benefit of the creativity map is its adequacy for computer based processing. Other approaches, as discussed in Chapter 2, depend on human processing of the data. This is of course hard and error-prone. Not to mention the enormous amount of time necessary for large projects.

Pattern-Based Information

Extraction

Objectives

ˆ Introduction of behavioural patterns.

ˆ Introduction of the behavioural pattern description language.

ˆ Presentation of the usage of the description language with examples. ˆ Description of the most common types of behavioural patterns.

“I have had my results for a long time: but I do not yet know how I am to arrive at them.”

4.1

Introduction

This chapter will introduce techniques for the automated extraction of information from a creativity map. The thesis is focussing on information, which is represented by the arrangement (constructs) of transitions in the creativity map. These constructs are the mappings of the creative behaviour. The constructs of transitions are from now on re- ferred to as patterns. The patterns are introduced in this chapter as so-called behavioural patterns. A behavioural pattern represents a search pattern, based on the knowledge of the creator and the community. The definitions of those behavioural patterns are user- based and hence provide full flexibility for the analysis of the creative process. A language, enabling machine-readable definitions of behavioural patterns, will be presented. The lan- guage utilises an Extended Backus-Naur Form (EBNF) style notation. The behavioural patterns will be applied on the creativity map via a parser. The aim of this chapter is the introduction of an approach, satisfying the need of extracting information about the creative process. Examples are used to demonstrate the flexibility and versatility of this approach. This chapter provides a solution for research question number one: How can information about creative behaviour, which is hidden inside the creativity map, be characterised? As well as partially answering research question number two: Which computer-aided technique enables the extraction of information from creativity maps?