The 4×4 Model for Knowledge Content is a guide to get users to engage with your website. The content you produce on your website needs to stand out as on average users will on spend 10 seconds viewing your content.
The Four Models are…
The Water Cooler: The purpose is to grab the users attention and to be direct and to the point. Typically these are headings. Depending on whether you are interested in the topic determines if your choose to engage or not
The Coffee Shop: This is were the content is explore in greater detail but not a fully in depth. It follows on from the water cooler and explains the ideas rather than introducing them.
The Research library: The library is where you go into more dept and detail about a specific topic. It’s the committed time to investigate a topic and contains research and data.
The Lab: This is where users can interact with the data from the research library. It gives the audience the ability to filter and play with data directly.
In week 12 we were asked to create a quick style guide for our 3B Assessment. included in this blog post are precedents (example image) of what inspired my Assessment overall aesthetic, example layout grids, colour palette and typographic examples.
The images below are precedents that inspired my work for 3B. I liked how they have used their colour palettes to make the infographics visually appealing and engaging.
The images below are examples of layouts and grids that I have considered using for my assessment.
LAYOUT EXAMPLES
The following 2 images are example layout for my 3B infographic design. I have played around with using both portrait and landscape layouts to see which one I prefer to use.
EXAMPLE DESIGNS
STYLE GUIDE FOR 3B ASSESSMENT
My style guide for assessment 3B below displays the direction I wish to proceed in and the colour palette being used. I have chosen to go with a red colour palette seeing as though Netflix used red as its primary colour.
For this weeks tutorial class we were asked to develop a dashboard based around student screen use. We used dashboards to help convey the story being told. The dashboards below depict how screen time is being used throughout the week.
The dashboard below is compiled of 3 sheets. The first graph shows the amount of records per hour based over the period of a week. It highlights the fact that screen usage increases towards the afternoon and later at night. The highest amount of screen time is 10pm closer to when people start going to bed. I have also included screen usage per category and activity which shows that almost every category and activity involves some type of screen usage.
UNIVERSITY STUDENTS AVERAGE SCREEN USE
Below is another example of a dashboard created to depict university students time spent using a screen. I have used a bar graph to sort the data into 2 categories (Male and Female) to see any similarities or differences in how they used screens. Interestingly, Female spend more time using a laptop, whilst males prefer to use a desktop device.
In our week 10 tutorial week look at the basics of how to create a dashboard in Tableau. The above dashboard is a group of graphs made to show how university students use their time throughout the period of a week. Included in the dashboard is a bar graph showing the average hours spent in each activity, a tree map of average hours per category and then a simple pie chart which shows students screen use and the average hours spent on each device.
ON AVERAGE HOW MUCH SLEEP ARE UNIVERSITY STUDENTS GETTING?
The story here is to show just how much sleep University students are getting compared to the rest of their daily activities. As we can see from the bar graph above, Uni students over the period of a week, are getting on average 8hrs 30 mins sleep each day. From the visualisation above it tells us that sleep is a vital part in our everyday routine and therefor is much larger than the other activities.
Although we already know that sleep is vital to our life, we wanted to look into how our sleep measured up in comparison to national averages. The requirements of sleep hours tend to stabilise out in early adult life around the age of 20 and although individuals sleep varies, the required amount of sleep is between 7 and 9 hours a night. From this information is clearly shown that from the university students we collected data from, almost everyone was getting close 9hrs per night.
This data visualisation tells a story about the geological finds of dinosaurs and mammals throughout time, via the use of a map. It tells you a story about what was living on earth during certain periods of time and the location of were scientist have found prehistoric fossils.
How does it tell it?
The way it tells the story is through all the dots on the map and the timeline at the bottom. The dots are colour coded to match what kind of species the creature was and where it was found. When a dot is clicked, the user will get an in-depth description of the fossil. The time at the bottom is also colour coded to match the time period. Each row going down representing a more specific time period.
Does it allow for different levels of interrogation that can be seen or used on the part of the reader? e.g. can they drill down to discover more detail?
The PBDB Navigator does allow for different levels of interrogation on the part of the viewer, as viewers can narrow their search down to a specific fossil type, period of time or even continent. The viewer can also access more info on a particular circle by clicking on it, this will reveal more information about the fossil discovery.
Are you able to create multiple stories from it? If so, what are they?
The website has a collections count in the bottom right-hand corner, which counts the number of collections on the screen at that time. From the website, users are able to create multiple stories as they can gather information on multiple time-periods, types of fossils, and where they were collected. Users can discover what fossils where found when and in which locations they were found the most.
What can you say about the visual design- layout, colour, typography, visualisation style?
I think the site could be more aesthetically pleasing. The map is quite basic, and I found the navigation quite confusing before watching the walkthrough video. The colour choice is basic, but it does allow the dots to stand out, and suits the use of the site. I like the visualisation style, but I think it could be better designed to create easier navigation and allow first time users to understand it quicker.
What improvements would you suggest
When first opening the website I would suggest having a walkthrough tutorial to show how to use the data navigator and what each device does, rather than an overload of information at once. I would suggest having different shapes for the varying periods of time as its uses dots for the whole thing and it’s hard to differentiate the periods of time as the colour shades are similar and don’t stand out from one another
Where does the data come from, and comment on its source
The source of this data comes from fossil occurrences that have been found throughout time and placed in scientific publications which are added to the database by the websites contributing members. The data is collected by nearly 400 scientists and 130 institutions in over 24 countries to provide scientists and the public with information about the fossil record
In the week 8 lecture pod we looked at Nathalie Miebach’s TED talk “Art From Data” in which she talks about how data can be used in combination with music and art. Miebach highlights the fact that she uses a combination of sculptures and music to make data not only visible but tactile and audible.
Nathalie Miebach talked about how she used the interactions of barometric pressure, wind and temperature readings that were recorded from Hurricane Noel in 2007, to create a 3 Dimensional model and musical scores. The 3D model was made up of individual beads, bands which all represent different weather elements that can be read as musical notes.
The process starts by extracting information from a specific environment and then comparing it to information found online from satellite images and weather data. The information is then compiled onto clipboards with 2-3 variables, it is then translated onto a basket made up of vertical and horizontal elements with assigned values. Over time, elements of form reveal relationships that may not be visible on 2D graphs.
This TED talk shows that you can be creative with data and thinks outside the barriers of 2D graphs and use other mediums to visualise data.
For this weeks lecture pod we looked at a TED talk by David McCandless, were he talks about the Beauty of Data Visualisation. His opening point is, “it feels like we’re all suffering from information overload, but the good news is that the solution is to just use our eyes more”. By visualising information we can see the patterns and connection that matter and then design information to make sense, tell a story and only focus on the important information.
The Billion Dollar O Gram arose out of frustration that Daniel McCandless had after dealing with reporting on the billion dollar amounts in the press. He decided to collect a bunch of reported figures from various news outlets and scaled boxes according to those amounts.
Each colour represents the motivation behind the money. By doing so you now start to see patterns and connections between numbers that otherwise would have been scattered across multiple reports. Daniel McCandless has now turned what was unorganised, scattered data into a visualisation that the audience can now explore.
McCandless talks about how he keeps hearing the phrase “ Data is the new oil” but he adapts this metaphor slightly to say that “data is the new soil”. For him, it feels more like a fertile, creative medium. He explains this as over the years, we’ve produced a huge amount of information and data that is irrigated with networks and connectivity, and it’s been worked and tilled by unpaid workers and governments.
David McCandless looked at the work of danish physicist Tor Norretranders in which he converted the senses into computer terms. The above graph shows that your sense of sight is the fastest about the same bandwidth as a computer network. Then you have touch, which is about the speed of a USB key. Followed by hearing and smell, which are similar to that of a hard disk. And then you have taste, which is the smallest and he describes as barely the throughput of a pocket calculator. He talks about how the bulk of our vision is visual and unconscious.
In summary, he states the fact that he feels design is about solving problems and providing elegant solutions, and information design is about solving information problems.
In week 6 we looked at what Data Journalism is and how it is used in the Guardian . Professor Nigel Shadbolt describes Data Journalism as the use of key information sense, key data and key reference elements to inform a story. It’s not just about the existence of data or obtaining it and putting it out there, but the processing that goes into it to work out what it tells you. Paul Lewis states that you have to ask the right questions to get the right answers. The first video talks about how data visualisation lets you tell a story in a way that people watching it will understand and enjoy.
PART 2: History of Data Journalism
In part 2, we looked at the history of data visualisation used by the guardian from the very start issue in 1821. Since the start the guardian has been wrestling with data, trying to present data in an interesting way that brings the story alive.
The Guardians first inclusion of data visualisation was a long table of data that shows a list of every school in Manchester and the statistics of people attending as education was not compulsory for another 60 years. The next visualisation to be recorded was in October 1916, showing the groundwork of what was still to come by showing sections of the land ahead. In 1938, the Manchester Guardian commercial visualised London clearing bank assets by using proportional, stacked line charts. More recently, the Guardian produced a data visualisation were they collected data collected by The Meteorological Society, and showed every meteorite that they know of and their position.
PART 3: Data Journalism in Action – London Olympics
The medal tables used during the Olympics are a good examples of data visualisation as everyone wants to know how their country ranks and who’s in the lead. The visualisation made by the Guardian for the 2012 London Olympics allowed viewers to interpret the data themselves and interact based on their own interests.
The most important aspect to remember here is that whilst Data Visualisations have been used for many years now, they are now being produced at increasing rates and we are able to make more complex data easier to understand for viewers to then interact with.
Why do we use graphs? Simply, Graphs make it easy to make comparisons. As designers we need to tailor the way we show stuff to be read and understood easily. The more accurate and easy the judgement is to make, the more likely that readers will take away the correct perception of patterns you are presenting.
Bar charts are a great example of charts that make it simple to make comparisons, bubble charts on the other hand are not so good at this. By using circles, the audience is likely to misinterpret the data being displayed as they will likely only look at the hight and width of the bubble to make comparisons, rather than the whole area. this is good if you only want a general idea of the data but not good for detail.
We also looked at the three most common types of graphs used.
Bar Chart: these are simple and easy to use as we have a familiarity with them and therefore don’t have to spend time learning how to read a new type of graph. Bar charts are used when comparing data across categories and effective with numerical data that splits into different categories. They help to real the highs and lows of data.
Line Chart: Line charts cones individual numerical data points and are a simple way to visualise a sequence of values. Their primary use is to display trends over a period of time.
Pie Chart: Pie charts are used to show the relative proportions and percentages of information. These are often the most incorrectly presented type of graph with many people not knowing how to correctly create a pie chart.
From this lecture pod, the main point was to show us how different types of graphs can be used depending on what data and story you wish to present. We learned that sometimes if the incorrect type of data is presented, it can be misleading and lead to accidents happening.
DATA VISUALISATION 