Piktochart Infographics » Data Collection & Research http://piktochart.com Best Info graphic Design Tue, 21 May 2013 15:24:21 +0000 en-US hourly 1 http://wordpress.org/?v=3.5.1 Common Concepts to Look at When Comparing Multiple Data Visualization Tools Common Concepts to Look at When Comparing Multiple Data Visualization Tools http://piktochart.com/2012/02/common-concepts-to-look-at-when-comparing-multiple-data-visualization-tools-common-concepts-to-look-at-when-comparing-multiple-data-visualization-tools/ http://piktochart.com/2012/02/common-concepts-to-look-at-when-comparing-multiple-data-visualization-tools-common-concepts-to-look-at-when-comparing-multiple-data-visualization-tools/#comments Tue, 28 Feb 2012 02:28:11 +0000 piktochart http://piktochart.com/?p=1743   Ideally, data visualization is a balanced presentation of function and aesthetics with the goal of intuitively relaying a complex idea. It is this balance that often increases effectiveness because the scheme presented is neither too bland, in a bid to increase functionality, nor too flashy to appeal to the user. How well we achieve this balance is based on [...]

The post Common Concepts to Look at When Comparing Multiple Data Visualization Tools Common Concepts to Look at When Comparing Multiple Data Visualization Tools appeared first on Piktochart Infographics.

]]>  

Ideally, data visualization is a balanced presentation of function and aesthetics with the goal of intuitively relaying a complex idea. It is this balance that often increases effectiveness because the scheme presented is neither too bland, in a bid to increase functionality, nor too flashy to appeal to the user. How well we achieve this balance is based on a number of things, including our understanding of how the concept works, an appreciation for the almost limitless scope of data visualization, and the tool used for the actual visualization of the raw data we have.

 

There are a number of data visualization tools available, and luckily not all of them will burn a hole in our pockets. The key is to find one that does not sacrifice quality for the price of “free,” so the best thing to do is compare them. This can be difficult since we can find in excess of 20 tools in just one internet search. The first thing to do is decide what level we are, and what features we need at that level.

 

Common things to consider:

 

How interactive, customizable and user-friendly is the tool? For example, with its lack of basicinstructions, Impure may not be the best tool for someone who is just learning, since there may be some fumbling around even for those who fall into its target audience. Google Fusion Tables is great for its variety of presentation methods, and is likely to appeal to those who rely on aesthetics, but it lacks the level of capacity, customization and functionality that some may need.

 

It is also important to consider if the tool can treat raw unpolished data. This may not be necessary for more advanced users who can sieve through and clean up their own data before imputing it, but those who need help in this area have to be sure that the chosen tool works. Google Refine and DataWrangler are two examples of tools that can sort or clean up raw data.Other things to consider include command line/text only interfaces versus visual tool, web-based versus downloadable, any necessary additional features (such as email) and the overall limitations of the free version. The last factor is important since some will require a paid version in order to use some features that may be required, The R Project for Statistical Computing comes to mind if large data sets are being used.

 

The post Common Concepts to Look at When Comparing Multiple Data Visualization Tools Common Concepts to Look at When Comparing Multiple Data Visualization Tools appeared first on Piktochart Infographics.

]]> http://piktochart.com/2012/02/common-concepts-to-look-at-when-comparing-multiple-data-visualization-tools-common-concepts-to-look-at-when-comparing-multiple-data-visualization-tools/feed/ 0 The future of data visualization- what do you think will be at the forefront? http://piktochart.com/2012/02/the-future-of-data-visualization-what-do-you-think-will-be-at-the-forefront/ http://piktochart.com/2012/02/the-future-of-data-visualization-what-do-you-think-will-be-at-the-forefront/#comments Tue, 28 Feb 2012 02:27:15 +0000 piktochart http://piktochart.com/?p=1741 Data visualization to simplify or data visualization to overload? This picture has been taken from Smashing Magazine’s website.   While data visualization existed in some form since antiquity, the world of computer science and social networking has created a greater need than ever for infographics. That being said, people may lack the software that is necessary [...]

The post The future of data visualization- what do you think will be at the forefront? appeared first on Piktochart Infographics.

]]> Data visualization to simplify or data visualization to overload?

infosthetics02 smashing magazine
This picture has been taken from Smashing Magazine’s website.

 

While data visualization existed in some form since antiquity, the world of computer science and social networking has created a greater need than ever for infographics. That being said, people may lack the software that is necessary to make their own charts or tables. Office productivity software is sometimes able to make the graphics in question, but this usually requires users to familiarize themselves with a particular method of entering data. Likewise, it is easy to make a chart that is misleading. Misleading graphs could be mistaken as an attempt at dishonesty, and therefore, they are best avoided at all costs. Using a powerful set of tools does not need to be overly difficult, and one might find that it also is easy to convert their own digital data to infographics in-house.

 

One of the current trends seems to be towards providing collections of graphs and charts for readers to peruse at their leisure. While most people might think that an infographic is an island in a sea of text, they have become such an easy way to organize information that they are now being appreciated in their own right. This means that they also need to be made more quickly than in the past to make up for the demand. In the future, data visualization will probably occur at a faster rate than most people can even imagine at the moment.

 

Using dedicated do-it-yourself solutions constitute an excellent way to convert and manipulate infographics on a personal computer. Many people who read blogs expect to see images attached to their favorite websites. However, it oftentimes seems absurd to simply attach photographs without any reason. Perhaps with the trend towards collections of graphs that illustrate various news issues, more blogs will start to turn towards setting up their own collections. This is where DIY tools really get their chance to shine.

The post The future of data visualization- what do you think will be at the forefront? appeared first on Piktochart Infographics.

]]> http://piktochart.com/2012/02/the-future-of-data-visualization-what-do-you-think-will-be-at-the-forefront/feed/ 0 Make The World a Better Place with Proper Presentations http://piktochart.com/2011/12/make-the-world-a-better-place-with-proper-presentations/ http://piktochart.com/2011/12/make-the-world-a-better-place-with-proper-presentations/#comments Wed, 07 Dec 2011 09:05:12 +0000 piktochart http://piktochart.com/?p=1332 One of the questions we often get at Piktochart: What if your users created really dull infographics, or worse, explode the entire infographic with colourful graphics and a terrible mismatch of colours/designs and lo & behold, They Do Not Even Have Any Quality Data. That to us, ladies and gentlemen, is an example of a [...]

The post Make The World a Better Place with Proper Presentations appeared first on Piktochart Infographics.

]]> One of the questions we often get at Piktochart: What if your users created really dull infographics, or worse, explode the entire infographic with colourful graphics and a terrible mismatch of colours/designs and lo & behold, They Do Not Even Have Any Quality Data.

That to us, ladies and gentlemen, is an example of a product failure. From a simple prototype which we have built, we have since re-iterated internally so many times, stalling development again and again. Once we thought it was Eureka, yet another user proved us wrong when he/she did not know how to use a particular button or did not know where to drag something into.

Preliminary look into our most current “prototype” layouts:

A New layout for Piktochart

We arrived at this point after 5, no…. 10 iterations (roughly). We have almost lost count of the number of napkin sketches we have done. There is plenty more to come… But the point is:

 

You  We Can Make The World A Better Place With Proper Data Stories

Do you know what is the impact of well-thought-of data?

It provides the users with the following benefits:

  • Takes the essence of the data immediately
  • Make their own judgement of what to think of that particular set of data- it starts conversations, it gets the brain running
  • Feel compelled to “react” to the data
On the contrary, what happens when the story is not well thought through:
  • Distracts them from the main point of the presentation
  • Little or no take-away/value to the user (to the point there is no point of reading it)
  • There might be some “Whats” answered, very little “How” or “Why” answered
We are working to minimize errors and restrict control over colour/font type/ font size changes so that the user will not run crazy with the amount of customization available. In other words, yes, you will be able to customize colours etc, but not too much effort to allow customization of each and every icon. Apart from that, we have noted that the ability to generate a story out of the presentation is also mighty important, therefore we are thinking of ways to guide the users to do that. (For that, I will leave it to the next post – which contains the What, How, Why approach)
Do you agree, or disagree with our approach? Love to hear your thoughts below!

The post Make The World a Better Place with Proper Presentations appeared first on Piktochart Infographics.

]]> http://piktochart.com/2011/12/make-the-world-a-better-place-with-proper-presentations/feed/ 0 Colours in Telling a story http://piktochart.com/2011/10/colours-in-telling-a-story/ http://piktochart.com/2011/10/colours-in-telling-a-story/#comments Sun, 02 Oct 2011 14:20:16 +0000 piktochart http://piktochart.com/?p=884 3 Ground Rules to Start with:   This rule may appeal less to a pictographic piece of information. No more than 6 colors Use cultural conventions e.g. anger = danger Beware of bad interactions (red/blue etc.) There are 3 safe ways to pick your colour scheme in creating a data visualization. Similar colours (a.k.a. analogous [...]

The post Colours in Telling a story appeared first on Piktochart Infographics.

]]> 3 Ground Rules to Start with:

 

This rule may appeal less to a pictographic piece of information.

  • No more than 6 colors
  • Use cultural conventions e.g. anger = danger
  • Beware of bad interactions (red/blue etc.)

rgb color harmony

There are 3 safe ways to pick your colour scheme in creating a data visualization.

Similar colours (a.k.a. analogous colours)

Analogous colours are any three colors which are side by side, e.g. Cyan, ocean and blue. For example, blue is the colour of the bar charts, cyan to highlight something important and ocean for everything else in between.

Opposite colours (a.k.a. complementary colours)

These are colours at two opposite ends, e.g. magenta and green (which can also be found in real life scenarios with flowers and leaf). These opposing colors create maximum contrast and maximum stability.

Always stick with social conventions and never use too much of a certain colour e.g. red for danger without very good reason. To demonstrate the smaller scale of things, a different hue paired with lightness is generally recommended as compared to changing colours entirely.

Happy colouring!

The post Colours in Telling a story appeared first on Piktochart Infographics.

]]> http://piktochart.com/2011/10/colours-in-telling-a-story/feed/ 0 Variables in Visual Encoding http://piktochart.com/2011/10/variables-in-visual-encoding/ http://piktochart.com/2011/10/variables-in-visual-encoding/#comments Sun, 02 Oct 2011 13:49:31 +0000 piktochart http://piktochart.com/?p=869 Jock Mackinlay was born in Nuremberg, Germany and received his BA in Mathematics and Computer Science from UC Berkeley in 1975 and his PhD in computer science fromStanford University in 1986, where he pioneered the automatic design of graphical presentations of relational information. Wait, what has he got to do with visual encoding and how we see information? Mackinlay invented several methods of [...]

The post Variables in Visual Encoding appeared first on Piktochart Infographics.

]]> Jock Mackinlay was born in Nuremberg, Germany and received his BA in Mathematics and Computer Science from UC Berkeley in 1975 and his PhD in computer science fromStanford University in 1986, where he pioneered the automatic design of graphical presentations of relational information.

Wait, what has he got to do with visual encoding and how we see information?

Mackinlay invented several methods of visualization and information graphics (otherwise known as infographics) and laid the foundation for Design Criteria, which he breaks into two:

(1) Expressiveness
A set of facts is expressible in a visual language if the sentences
(i.e. the visualizations) in the language express all the facts in
the set of data, and only the facts in the data.
(2) Effectiveness
A visualization is more effective than another visualization if the
information conveyed by one visualization is more readily
perceived than the information in the other visualization.

There are several things that allow visualizations within the sentences to express only the data. For example, clarifying the title, labels, legend, captions and not leaving it up to interpretation, would be a good method of committing the data set to expressiveness.

Separately, it has been advocated to avoid things which will not help with the visualizations, e.g.:

  • Unexpressive marks (lines, bars, gradients)
  • Do not distract with faint gridlines, pastel highlights or other fills which do not explain the data
  • Describe the most important part of the data and keep everything to a minimal.

Taken from the Stanford University presentation slides, they have displayed over 20 ways of visualizing the same data, effectiveness of multiple strains of antibiotics.

 

data visualization
data visualization method 2
data visualization bar chartsbar chart
dot chartsdot and line charts

Is there any method that is clearer and appears more salient to you?

The post Variables in Visual Encoding appeared first on Piktochart Infographics.

]]> http://piktochart.com/2011/10/variables-in-visual-encoding/feed/ 0 Uni, Bi or Tri-Variate http://piktochart.com/2011/10/uni-bi-or-tri-variate/ http://piktochart.com/2011/10/uni-bi-or-tri-variate/#comments Sun, 02 Oct 2011 13:21:58 +0000 piktochart http://piktochart.com/?p=866 On Piktochart, the Chart Wizard helps you to select the method of data visualization which you could use for your data set. This is a little insight to how Wizard does that: Data is usually commonly shown in the 3 formats below: Univariate – x only (contains only one axis of information) Bivariate – x [...]

The post Uni, Bi or Tri-Variate appeared first on Piktochart Infographics.

]]> On Piktochart, the Chart Wizard helps you to select the method of data visualization which you could use for your data set.

This is a little insight to how Wizard does that:

Data is usually commonly shown in the 3 formats below:

  • Univariate – x only (contains only one axis of information)
  • Bivariate – x and y (contains two axis of information)
  • Trivariate – x, y, z (contains three axis of information)

Wait a minute, still don’t get it? Attached below is an example that shows the difference between uni, bi and trivariate data formats.

univariate bivariate trivariate data

There are some data formats which are suitable for univariate, bivariate and trivariate. Among them:

Univariate

  • Line charts
  • Bar charts
  • Stacked bar charts
  • Scatter plots
  • Percentages
  • Candle chart

Bivariate

  • All of the above
  • Area chart
  • Histogram

Trivariate

  • All of the above (in univariate)
  • Bubble chart
  • Geo Map combined with one of the above
  • Tree Map

We have not mentioned several in the list above for the methods of visualizations that we are planning to develop in the total of 20. Are any of the above your favourites?  I generally find more success with uni or bi, while trivariate requires quite a lot of “digestion” from the users. Which form of data do you usually display?

The post Uni, Bi or Tri-Variate appeared first on Piktochart Infographics.

]]> http://piktochart.com/2011/10/uni-bi-or-tri-variate/feed/ 0 Why Visualize Data? http://piktochart.com/2011/10/why-visualize-data/ http://piktochart.com/2011/10/why-visualize-data/#comments Sun, 02 Oct 2011 10:52:39 +0000 piktochart http://piktochart.com/?p=862 We are living in the age where data is huge. We can now monitor everything and establish connections (or just correlations between events). With so much going on, we have to find the best way to communicate all these information. Data visualization the following: Conveys: Persuades people about something Collaborates: Presents an interesting/thought provoking argument [...]

The post Why Visualize Data? appeared first on Piktochart Infographics.

]]> We are living in the age where data is huge. We can now monitor everything and establish connections (or just correlations between events). With so much going on, we have to find the best way to communicate all these information.

Data visualization the following:

  • Conveys: Persuades people about something
  • Collaborates: Presents an interesting/thought provoking argument
  • Reasoning: Makes decision

“Data can change things if stories are told correctly.”  A quote by Jeffrey Veen

Some examples where we can exercise this ability particularly well, with data visualization done right:

The above is a short presentation done by Jeffrey Venn who talked about how big data can be visualized to save the world (in a way). He takes us back to the 1800s to look at a cholera outbreak. While most visualizations mashed up the map and an airborne disease, John Snow took a closer look at the data and realized that the problem could have started from a water irrigation system. Very likely to stem out from a faulty water pump.

The interpretation of data must alwasy be left to your users. The more important thing is to ensure that your users are left with a tool which can help them interpret data.

“Let go of the control. Allow your readers to find their own story.”

This post was inspired by the slides at Stanford Edu and Jeffrey Veen’s presentation.

The post Why Visualize Data? appeared first on Piktochart Infographics.

]]> http://piktochart.com/2011/10/why-visualize-data/feed/ 0 6 Useful Databases to Dig for Data (and 100 more) http://piktochart.com/2011/08/6-useful-databases-to-dig-for-data/ http://piktochart.com/2011/08/6-useful-databases-to-dig-for-data/#comments Thu, 04 Aug 2011 08:00:10 +0000 piktochart http://piktochart.com/?p=149 In your presentation, quoting from Wikipedia might not always be the best (unless they are linked to reputable papers and sources). Here are 6 major databases (some are crowd-sourced so they are by organisations and individuals) and we have about 100+ links which can be very useful. 1. Freebase Freebase is an open platform for [...]

The post 6 Useful Databases to Dig for Data (and 100 more) appeared first on Piktochart Infographics.

]]> In your presentation, quoting from Wikipedia might not always be the best (unless they are linked to reputable papers and sources). Here are 6 major databases (some are crowd-sourced so they are by organisations and individuals) and we have about 100+ links which can be very useful.

1. Freebase

Freebase is an open platform for data-sharing and an automatic way of plotting data sets by timeline and map automatically. Useful feature with topics ranging from fictional characters to Modest Mouse.

2. UN Data

Large data sets on virtually all the public data UN collects- you have to sign up to get access to the API but it will only take 1 minute for the access to be emailed into your account.

3. WorldBank

Where else would you go for data on financial standings of the any country’s economy, but the World Bank? Among some topics included, by country:

4. Data.gov

Data.gov is leading the way in democratizing public sector data and driving innovation. This movement has spread throughout cities, states, and countries.  5 of 50+ categories:

5. Infochimps

Contains paid and free data sets just about anything. What is also cool is that it is not just about downloading datasets in csv etc, but also has an API that you can play with to extract data. Try Twitter as your search metric and you will see what I mean.

6. NeedleBase
Also acclaimed as the Wikipedia for data, this database meets its expectation. They have some data visualisations ready on a limited number of data sets which are available to the public. But the information is of quality.

A random collection of data sets

Directory of Data sets

Directory of crazy amounts of data sets and related stuff

Datamob: http://datamob.org/datasets

The really big list here is taken from DataWrangling

The list is not very updated as it was a 2009 update. A good place to start looking for data- although it might not be the most updated ones.

 

Datasets listed in the original post on Jan 17, 2008:

The post 6 Useful Databases to Dig for Data (and 100 more) appeared first on Piktochart Infographics.

]]> http://piktochart.com/2011/08/6-useful-databases-to-dig-for-data/feed/ 0 Scraping Data from a Table in a HTML Page via Google Docs http://piktochart.com/2011/07/scraping-data-from-a-table-in-a-html-page-via-google-docs/ http://piktochart.com/2011/07/scraping-data-from-a-table-in-a-html-page-via-google-docs/#comments Thu, 21 Jul 2011 07:04:43 +0000 piktochart http://piktochart.com/?p=114 This is a pretty neat tutorial we found at EagerEyes’ blog. It allows you to scrap data from a table in a HTML page and get all of that data via Google Docs, which is a spreadsheet that more and more are becoming accustomed to. 1.  Create a new spreadsheet on GDocs and enter the [...]

The post Scraping Data from a Table in a HTML Page via Google Docs appeared first on Piktochart Infographics.

]]>

This is a pretty neat tutorial we found at EagerEyes’ blog. It allows you to scrap data from a table in a HTML page and get all of that data via Google Docs, which is a spreadsheet that more and more are becoming accustomed to.

1.  Create a new spreadsheet on GDocs and enter the following expression in the top left cell: =ImportHtml(URL, “table”, num), e.g. =ImportHtml(www.piktochart.com/dataset,”list=Coffee-brewing,0)

  • URL here is the URL of the page (between quotation marks)
  • “table” is the element to look for (Google Docs can also import lists),
  • num is the number of the element, in case there are more on the same page (which is rather common for tables).
  • The latter supposedly starts at 1, but I had to use 0 to get it to pick up the correct table.

2. Once this is done, Google Docs retrieves the data and inserts it into the spreadsheet, including the headers.

3. The last step is to download the spreadsheet as a CSV file.

This is a very interesting and short way of making data input possible from a website to GDocs for work!

The post Scraping Data from a Table in a HTML Page via Google Docs appeared first on Piktochart Infographics.

]]> http://piktochart.com/2011/07/scraping-data-from-a-table-in-a-html-page-via-google-docs/feed/ 0 5 Excellent Resources to View/Create Visualisations http://piktochart.com/2011/07/5-excellent-resources-to-viewcreate-visualisations/ http://piktochart.com/2011/07/5-excellent-resources-to-viewcreate-visualisations/#comments Thu, 21 Jul 2011 07:04:27 +0000 piktochart http://piktochart.com/?p=126 There are several places we go to for inspiration in terms of getting data visualizations done right. Among them are the 5 resources below. It is not just important to select the right types of visualizations for the data, but also get the colours, spacing, font, hue/opacity/saturation right! P/S: There are full degrees in graphic [...]

The post 5 Excellent Resources to View/Create Visualisations appeared first on Piktochart Infographics.

]]> There are several places we go to for inspiration in terms of getting data visualizations done right. Among them are the 5 resources below. It is not just important to select the right types of visualizations for the data, but also get the colours, spacing, font, hue/opacity/saturation right!

P/S: There are full degrees in graphic design for data visualizations now.

1. ChartsBin

Allows you to look at interactive graphs/charts. Data ranges from population statistics to “do you think people take advantage of you” surveys. Data sets are likely to be huge and  all data are referenced(Harvard style referencing). Allows you to embed the data and create interactive maps online instantly! (without installation and coding)

Our verdict: Not easy to get the values in pre-defined dataset, but it should work better since this is still the beta stage.

Geographic map with ChartsBin

2. d3.js by Github

Allows you to create fancy data visualisations such as chord diagram, treemap, sunburst, streamgraph, bubble charts. Worth a look!

 

3. JunkCharts

Recycling charts for art. Very interesting posts to expand your mind about what data visualisations can do.

Data visualisation with Junkcharts

 

4. Dynamic Diagrams

You can just view data visualisations here, but they are in-te-res-ting.

5. Bloomberg

Who would have thought Bloomberg has a selection of the most colourful data visualisations?

Bloomberg Insights Data Visualisation

The post 5 Excellent Resources to View/Create Visualisations appeared first on Piktochart Infographics.

]]> http://piktochart.com/2011/07/5-excellent-resources-to-viewcreate-visualisations/feed/ 0