As big data has emerged as a hot issue and data using population has increased, needs for understanding the meaning of data and hidden information and knowledge underneath it also have drastically grown larger . Therefore, in turn, various researches ...
As big data has emerged as a hot issue and data using population has increased, needs for understanding the meaning of data and hidden information and knowledge underneath it also have drastically grown larger . Therefore, in turn, various researches have been conducted on data visualization for instance visualization methods or the development of data visualization tools. Especially, researches on visualizing text data are growing rapidly these days due to the current condition of the increased acceptance of electronic documents. Most of newly produced and shared documents are digital ones and previously published documents are being digitized as technology advances.
Many researches on utilizing and processing text data, an unfailing fund of information, have been carried out in this regard. Especially, various text visualization studies have been conducted to express vast data in the form of visual images that are easier to understand for the public. Due to the nature of it, text data has taken on the linguistic form. Text data could be seen as a structure that has its own content, narrative, theme, and story. Therefore, it could be understood only when it is taken as a whole. In other words, a fragment of it cannot say it right. This unique characteristic of text data is not like that of any other data visualization materials. In this sense, it is necessary to understand the characteristic of the data itself.
In this context, this study first aims to understand the unique characteristic of text as a data visualization material. Second, it focuses on the textuality of data which is transformed or re-manifested on the visualizing process which is for expressing text data in a form of images. Copious researches on the relationship of language and image have been conducted in various fields such as philosophy, linguistics, and semiotics for a long time. This study aims to understand characteristics of text data and explore how those characteristics influence the visualization process by analyzing textuality in text visualization images based on existing relative researches.
For this, this research systemically organizes textualities based on Beaugrande & Dressler(1981)'s 'textualities' which set out seven standards of textuality by reviewing various definitions of text linguists on the basis of the concept of text, which is a basic form of communication.
Second, this study categorizes textualities in order to apply textuality of linguistic text to not just simple images but visualized images. Based on this categorization, this study defines 'fundamental attributes' of text visualization: cohesion, coherence, intentionality, and acceptability. They are fundamental requirements of text visualization. This study also defines 'character attributes' of text visualization: informativity and intertextuality. They are shown in a visualized image on the basis of fundamental attributes. Moreover, this research reviews various cases of text visualization in order to investigate how each characteristic manifests itself.
The main conclusions obtained from this study are as follows:
First, informativity is a character attribute of text visualization images. It manifests itself by advancing informativity of the visualization material which is the text in this case. This could be done by summing up and compressing information, choosing novel data, inserting interpretations of an artist, comparing data, and deconstruction and reconstruction of data.
Second, intertextuality is the other character attribute of text visualization images. Intertextuality in text manifests itself by using intertextuality shown in the text data which are used for materials of visualization, applying image viewer’s background knowledge and custom into visual expression, and imitating existing expressions.
The significance of this study is as follows:
First, this study focuses on text visualization among various visualization of different data forms so that it could be a reference as a theoretic basis on a field of text visualization of which importance is rapidly increasing.
Second, the definition of textuailty redefined by this study in order to apply textuality based on linguistic text to visualization images could be utilized as an analyzing tool for many other visual images as well as data visualization works. Moreover, different analyzing tools and standards could be come out on the basis of analysis process this study suggests.
Lastly, this study tries to explain the relationship between data characteristics and their visual representations by connecting expression aspects of data visualization and attributes of the data. In turn, this study could ultimately contribute to improving qualities of data visualization since an efficient expression method is a key to achieving a high level of quality, user acceptance, and understanding of information.