This week I had a look at different books on website analysis for the group project. I found Craig .M. Baehr’s Web Development: A Visual-Spatial Approach to be the most useful, as well as our set text Web Style Guide by Patrick J. Lynch and Sarah Horton among others. I learnt about different ways to analyse a site, such as ‘content analysis’ (looks at the type, format, subject and purpose of each content artifact on a page) and ‘visual-spatial analysis’ (looks at a site’s structure through either its context or wholeness). I also learnt about four types of website structure which I have roughly made examples of below – ‘linear’, ‘hypertextual’, ‘hierarchical’ and ‘custom’:


I also looked at individual page structure and interface layouts, such as the ‘frame’ structures that I have tried to illustrate examples of below (the positions of the individual frames on the page may vary between sites):


Looking at a diverse selection of books, including some from different subject areas such as science and psychology, has demonstrated the importance of research in this analysis project. I am starting to see structural elements of the chosen site ‘Creative Spark’ and the understand the thinking and principles behind its design.

This week we also started to work on the next project for ‘Data Visualisation’, which I will begin outlining next week in more detail. ‘Data Visualisation’ is, put simply, collecting data and interpreting it in a visual form. For our project we are to illustrate data on recycling in Australia, with the challenge of making it both visually appealing and readable (we cannot use a typical graph or table structure). Initially we simply looked at the data provided and tried to think of ways to represent each individual statistic before we try and put them together. As the subject is of an environmental nature, we are trying to steer clear of the regular clichés associated with that field such as the colour green and trees etc.When we regroup next we hope to have some decent sketches of potential ideas to represent the data.