Natalia Miebach is a Boston-based artist who translates weather data in sculptures and musical notes. In this Ted Talk, Natalie explains her sculpture creation of Hurricane Noel in 2007. Her unique sculpture can be read and played as musical piece, as every element in the sculpture reverts to a musical note. Natalie explains that weather systems and patterns are invisible to most of us. However, by using sculptures and music, Natalie makes what was invisible, visible. Natalie’s sculpture is accessible through multiple outlets – art, science and music, making it a ground-breaking innovation.
This ted talk was really interesting, as I had never seen music and data visualization combined before. I think Natalie’s approach, in visualizing the data by converting them to music notes was really creative & unique. This was a really interesting and insightful was to view data and revealed that data can really be visualised in any way provided it create meaning.
Natalie ensures that the sculptures and the music created is a direct interpretation of the data. It isn’t manipulated to look or sound a certain way based on her personal interests, which is very important in data & journalism.
Miebach, N. (2011). Art made of storms [Image]. Retrieved 24 September, 2018 from https://www.ted.com/talks/nathalie_miebach
Miebach, N. (2011, July). Art made of storms [Video File]. Retrieved from https://www.ted.com/talks/nathalie_miebach
It is very common in this day and age to feel like we are being overloaded with information and the solution is data visualizing, combine numbers and patterns together then designing that information so it makes more sense, or it tells a story or allows us to focus only on the information that’s important.
There is always interesting and odd patterns hidden in this data that you can only see when you visualize it. As David refers to In his lecture , there is a popular phrase that “Data is the new oil”, however he believes “Data is the new soil” because it is a fertile, creative medium.
Data Visualization is a quick solution to explore data, even the information is terrible, graphs can be beautiful. Visualizing information is a form of knowledge compression, “design is about solving problems and providing elegant solutions, and information design is about solving information problems.”
Data journalism is the helping public discourse establish what they can trust. The guardian came up with a code/algorithm which looked at the achievement of gold medals, and how much more value was derived from country’s who had less population and less expectation of winning compared to more favoured country’s.
“Data is the new oil” or “Data is the new soil” because it is a fertile, creative medium.
Data is the kind of ubiquitous resource that we can shape to provide new innovations and new insights. visualizations, infographics, data visualizations, they all came out and play important roles to help visualize and analyse massive data on the Internet. Reading graphs is effortless and when you’re navigating dense information, beautiful graphics or a lovely data visualization, it’s a relief.
What is Data Journalism? – The Guardian
“Its not about opinions , its about what’s really there”
Journalism is about telling that story using then power of data. Data journalism is the use of key information sense, key data, key reference elements to inform a story.Data journalism is the recognition of the power of measurement in helping public conversations and public discourse in general.
Data journalism is something new, it relies entirely on the technologies of the moment and didn’t exist before 2009. Graphs help understanding data and news more effectively.
The most important thing about any data that’s applied whether it’s a spreadsheet or any other is that it has to be precise it and has to be accurate and has to be a logical way for the code to talk to it and get back the right information.
Why Use Graphs ? To make comparisons easier.
There is an over use of bubble charts – Designers often chose graphs styles purely based on aesthetic purposes, even though it doesn’t effectively aid the information.
Bar goods are good because they allow for simple comparisons. Bubble charts prompt the viewers to compare the height & width of the bubbles, instead of comparing the circumference of the circles. Circles almost always prompt audience to compare the circle sizes. Squares are much easier to compare, more accurately.
Bubble charts + colour scales often suggests the statistics are similar , even thought the actually aren’t, as it’s hard for the human eye to recognise a difference In the information.
The wrong type of graph can obscure really important information (which could have saved lives, in the historical example of the Nasa rocket crash).
Bar charts are most commonly understood because they have a great familiarity. They allow for you to quickly compare information & they contrast the differences between high & low.
Pie charts are another graph that are commonly mis-used. They are for minimal amount of data comparison.
*This image was taken from the lecture pod.
McCandles, D. (2010). leonGraphsPod720p. Retrieved from https://vimeo.com/177306425
Designers choose what is aesthetic, our vision and brains struggle to measure surface area, better equipped at analysing length. Due to this we struggle to differentiate statistics that involve circles and tend to underestimate size, figures and values. So in conclusion, Why do we use graphs? To make comparisons easier! As Alberto Cairo started ‘The more accurate and easier it is to make a judgment the more likely the reader will take away a perception of the presented patterns’.
Historical & contemporary visualisation methods.
Summary: The functional art- this lecture discussed the importance of using graphs, graphs help make comparisons easier. The lecturer gave an example of how extracting information from a table of data can be very difficult. Then we viewed the same information in a graph the information was much more impressionable & understandable.
*This image was taken from the lecture.
This is not a great example “what you show is just as important as what you hide “– it is important to inflict some design & not just use what a software creates. The more information provided is more demanding on the viewer, as they need to process more.
*This image was taken from the lecture.
Quite a funny anti- info-graph. The lecturer refers to info-graphs as empty eye candy. A reoccurring point mentioned in this lecture is how designers can often chose the wrong/ or least effective way to present data. We viewed examples of graphs which were created purely based on aesthetics or u
Cmielewski, L. (2016). leonGraphsPod720p. Retrieved from https://vimeo.com/177306425
Historical & Contemporary Visualisation
Visualising – allows audience to grasp information with less words as possible.
This lecture discusses the importance of data visualization in our history, specifically referring to the Crimean War (1958). He also shows the power of data visualisation by recounting the events of the napoleon war.
Communitive powers. Can reduce time needed to understand an event. It’s much more than representing information. It’s about giving the audience tools to understand & judge the data themselves. Another good point made in the lecture is that data visualisations are more complex today because we have access to much more data than ever before.
Otto Neurath ISOTYPE: International system of Typographic picture education. The designer used the repetition of a symbol / instead of making the symbol larger.
Raw data is difficult, but graphics make it more digestible. Sometimes, focusing on a particular part of information can be more effective & powerful than showing everything you know. Idea of “education through the eye”.
*This image was taken from the lecture.
Florence Nightingales graph , for me , was very powerful & highlighted the importance of data visualisation in history.
Cmielewski, L. (2016). Visualisation: Historical and contemporary visualisation methods- Part 1. Retrieved from https://vimeo.com/176255824
Week 3 Lecture Pod. (2018). Retrieved from https://vimeo.com/176274669
-Latin word nomen– pertaining to names
it consists of names categories
inherently un-ordered, e.g dairy & fruit do not have higher greater mathematical value than each other.
It can be counted, but you can’t take the average of nominal data.
When there is only 2 categories available, it is referred to as dichotomas , so either yes or no answer.
Numbers are assigned to make the data analysis easier.
Assignments of numbers are orbitry.
You can count it & use it calculate percentages.
It is numeric
0 doesn’t = the absence of anything, e.g 00am doesn’t mean there is not time.
Difference between 11:00 – 11:30
It is numeric, it has meaning full data
0 = absence of product
Using the correct data type is very important for designers, to collect & communicate data in the most effective manner. Ordinal – consecutive numbers are used to represent different categories. Qualitative data is descriptive information, whereas quantitative data is numerical information.
Week 2 Lecture Pod. (2018). Retrieved from https://vimeo.com/176274669