Analysis of Data Visualisation Activity

What story does it tell?

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

7th Oct 2019 0

Lecture Pod 6: Data Journalism

PART 1: What is Data Journalism?

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.

History of Data Journalism at The Guardian. (2019). Retrieved 6 October 2019, from https://www.youtube.com/watch?v=iIa5EoxyvZI

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

Data journalism in action: the London Olympics. (2019). Retrieved 6 October 2019, from https://www.youtube.com/watch?v=WyjBJzigm0w

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.

6th Oct 2019 0

Lecture Pod 3&4: Historical and contemporary visualisation methods

We use visualisation as a way to present large pr complex data sets in a way that enables our audience to grasp the complexities with the least amount of work possible. In this week lecture pod, week looked at historical uses of data visualisations and more specifically at Napoleons Invasion on Russia, Florence Nightingale Crimean War data and Otto Neurath’s introduction of ISOTYPE.

We first viewed Napoleons invasion of Russia in 1812 and the graph below shows the strength of troops at the start of the invasion and the decrease of strength towards the end. It does this by the line thickness becoming thinner to represent a decrease in strength. This visualisation enables viewers to grasp a difficult concept and allow them understand the concept faster. By constructing a graph, it makes interpreting the data easier than viewing the raw data collected. Graphs allow the audience to view information much faster and get the full picture without the complications of sorting through data.

From Napoleon to Tableau: A Brief History of Data Visualization as it evolved – Adaptive Systems. (2019). Retrieved 6 October 2019, from https://adaptivesystemsinc.com/from-napoleon-to-tableau-a-brief-history-of-data-visualization-as-it-evolved/

During the Crimean War in 1858, Florence Nightingale realised that soldiers were dying from causes that were not related to battle wounds. Nightingale strived to improve the living conditions of injured troops and kept a record of the death tolls as evidence to put forward an argument to the British Military. She turned her records into graphs that show the causes of mortality in the easts army soldiers. The graph uses area to show mortality rates for each month of the year. Interestingly, she discovered that troops were dying of diseases 32x the rate of those with battle wounds.

Otto Neurath was a pioneer in socialist politics and economics in Vienna. His mission was to make social and economic relationships understandable though visualisation. The point being made is that rather than overwhelming the audience with information, Neurath has simplified the data into a visualisation using graphics that are simple and easy to understand.

ISOTYPE Visualization. (2019). Retrieved 6 October 2019, from http://steveharoz.com/research/isotype/

Why Visualise?

Visualising helps us to gain an insight and understanding into complex issues.

Extracting meaning from a table is difficult as our brains have not developed to deal with the large amount of data in this form. By using graphs with information as a visual tools, helps us to understand the data and save time/energy that would have been used to try and understand the information.

The key point from this lecture is that methods of data visualisations have evolved over time to make reading data easier and that simplifying data is effective in communicating a story effectively and quickly. The idea is that if you don’t present your data to readers so they can see, read, explore and analyse it, then they may not even take your word for it. You need to try and convince the audience or give them the information to convince themselves.

1st Oct 2019 0