University of Patras (GREECE)
About this paper:
Appears in: INTED2016 Proceedings
Publication year: 2016
Pages: 2765-2773
ISBN: 978-84-608-5617-7
ISSN: 2340-1079
doi: 10.21125/inted.2016.0161
Conference name: 10th International Technology, Education and Development Conference
Dates: 7-9 March, 2016
Location: Valencia, Spain
Motivated by the well-known saying “a picture speaks a thousand words” we investigate whether we can use computer graphics and work the other way round claiming also that a “thousand words” can draw – or generate - a picture. In particular, we investigate whether we can exploit single words used to describe a notion and transform them into building blocks of different color in order to produce a family of images that capture basic characteristics and properties of this particular notion as conceived by an audience.

Our work falls into the general area of data visualization. Current approaches visualize sets of words using either (i) words in a frequency-based manner or (ii) graphs, e.g., trees, that are generated according to conceptual associations among words provided as input. Instead, in this work, we suggest an innovative approach according to which sets of words describing a notion are directly mapped to abstract images. Words are transformed to image components. We automatically detect conceptual interconnections among words exploiting their structural properties (like, for example, a common root) and reflect them to colors. Different colors represent different words of the set. The word frequency is represented by the size of image components. The final image visually represents a notion and is generated by packing image components using efficient computer science algorithms.

To this aim, we first convert words to their hexadecimal equivalents. Then, based on them, we generate their equivalent rgb colors. Furthermore, we associate each word used to describe a notion with a rectangle in the Euclidean space. The size of rectangles visualizes the degree to which a particular word contributes to the description of a notion and is determined by the frequency of appearance of words in the description. Efficiently packing all colored rectangles we generate a family of equal-sized images expressing a notion in terms of an abstract drawing.

For our implementation we use Matlab, a simple mathematical programming environment not requiring advanced programming skills which has been widely used in academia and industry by users coming from various backgrounds of engineering, science and economics.

The scenario we use as our working case comes from the higher education. Students of the Department of Cultural Heritage Management and New Technologies of the University of Patras, Greece, were asked to submit a single word that acts as conceptual reference in the context of each of four courses, namely Discrete Mathematics, Introduction to Algorithms, Topics in Mobile and Wireless Networks and Computational Culture. Three languages were used: Greek, English and Spanish. Then, using the approach previously outlined, we produced images that constitute the visual description of each course in each language.

Our approach stems from our vision for a culture-inspired data analysis and visualization framework which fruitfully interlaces cultural elements incorporated in language with methods from computer science and technology.
Culture-based data visualization, coloring, rectangle packing, algorithms, images, notions, words.