This blog provides a step-by-step explanation of how to create a visualization using Many Eyes. The same can be downloaded from the link given below. Since many operating systems do not allow chm files to open, after you have downloaded, if you cannot see the text, right click the file, go to properties and under 'general' tab, click on 'unblock'. Now you should be able to read all the text.
- Many Eyes, a data visualization tool, is a SaaS offered via Cognos and IBM.
- Many Eyes is a "shared visualization and discovery" service.
- It is another rich way to present data and content on the Web.
- It allows the entire internet to upload data, visualize it, and talk about their discoveries with other people
- Users can upload their own datasets, and/or work with existing datasets on the site.
- There are a lot of great options to visualize the datasets.
- When you need to create stunning interactive pictures quickly, IBM’s Many Eyes is a great solution
For more information about the various features, CLICK HERE! Creating a visualization
Now, let us see how to create visualizations using Many Eyes.
1. Create a login at Many Eyes. Here is the url for you.
2. Now, you have to upload the data set. Hope you have data set ready. Or you can choose any of the existing data sets on Many Eyes and create a visualization. For uploading your own data set, go to ‘Upload a data set’ under ‘Participate’ head on the left side of the web page.
3. Now, you are shown a page which details 4 steps.
a. Prepare your data – Format your data into a table. The first column of the data is taken as headers. Hence, make sure, you name all the columns. If there are any units in your data, like $5890, the dollar is removed by Many Eyes. Hence, name your columns like ‘Cost($)’. If say, your unit is 5890 thousands of dollars. Make your header ‘Cost ($ ‘000s).
You can have your data either in a spreadsheet or a plain text format separated by tabs. The size limit of the data is 5MB.
Here are some do’s and don’ts.
For more info about data formats, visit
(source: http://www.indian-elections.com/india-statistics.html)
Election Year | Male(%) | Female(%) | Total(%) |
1952 | - | - | 61.2 |
1957 | - | - | 62.2 |
1962 | 63.31 | 46.63 | 55.42 |
1967 | 66.73 | 55.48 | 61.33 |
1971 | 60.9 | 49.11 | 55.29 |
1977 | 65.63 | 54.91 | 60.49 |
1980 | 62.16 | 51.22 | 56.92 |
1984 | 68.18 | 58.6 | 63.56 |
1989 | 66.13 | 57.32 | 61.95 |
1991 | 61.58 | 51.35 | 56.93 |
1996 | 62.06 | 53.41 | 57.94 |
1998 | 62.78 | 57.88 | 61.97 |
1999 | 63.97 | 55.64 | 59.99 |
2004 | 52.65 | 44.65 | 48.74 |
I have named by headers with (%), since having % in the table is of no use.
b. Paste the data – Copy your data and paste it in the box provided.
c. Check that ‘Many Eyes’ has understood. This is an important step. Once you paste your data and ‘Many Eyes’ reads it, it shows each column is as either text or number. Make sure, text is interpreted as text and number as number. If not interpreted properly, change it in the drop-down given with each column. Here is how it looks like.
d. Provide description of your data – title, what your data is about, source of your data. Except for the title, all are optional.
After you have pasted the data, checked for correct interpretation, click on ‘Create’
4. After clicking on ‘Create’, you are shown your data or a part of it. At the end of the data, click on ‘Visualize’.
You can see all your visualizations and data sets by clicking 'My contributions' under 'My stuff' (after you have logged in).
5. You are shown all the visualization types available. Select the visualization you want for your data. I have selected ‘Bubble chart’ for this dataset.
6. Now, you are shown a page that says ‘Customizing Bubble chart’ and the visualization is shown. Here is the visualization.
Here, is another visualization created using the same data set.
7. You can customize your visualization i.e., you can analyze it from different perspectives. For eg, in the above visualization, you can also change the dropdown to ‘male’ to ‘female’ or ‘total’
8. Now, just name your visualization, and it is saved on ‘Many Eyes’. You can share your visualization (both static image and live visualization that allows users to interact with the visualization), by clicking on 'Share this' under the visualization.
Data sets
A data table consists of rows where the values in each row are separated by tabs. The first row of the table should be "headers" that describe the columns. Here's an example table in the Many Eyes format
Fruit | Colour | Calories |
Apple | Red | 100 |
Banana | Yellow | 120 |
This format can be easily exported from databases or spreadsheets. The size limit is 5 MB per file.
Common mistakes to be avoided
Don’t forget the units
Please label the units in all your data sets! Others would not know until you explicitly mention.
Punctuation matters
Currently the Many Eyes format accepts only two kinds of values: text and numbers. Punctuation, dollar signs, percentage signs, and other characters are automatically removed from numbers. If you need to indicate numbers are percentages or currency, put that information in the column headers.
| Fruit | Cost |
|---|
| Apple | $1.00 |
| Bananas | $1.20 |
|
| Fruit | Cost($) |
|---|
| Apple | $1.00 |
| Bananas | $1.20 |
|
WRONG RIGHT
Don't forget the header row
The header row is important. In addition to describing what the data actually means, the names are needed to set up and label the visualizations. Be sure your data has a header row! If you try the following, the first row will be interpreted as labels, not data.
WRONG
Null or missing data points
If the data set contains some blank cells or a few "n/a" or "*" characters where numbers should be, that's not a problem--the graphs and charts will adjust. However, when a column of data is almost entirely made of markers such as "n/a", the parser will guess that the column is text, not numbers. In the data upload page this can be corrected by hand using the drop-down menu at the bottom of the column.
Rows should all have the same number of items
Each row should have the same number of items. (This includes the header row.) It's easy to copy only part of a data table by mistake, so it's worth double-checking the rows.
Fruit | Calories | |
Apple | 100 | |
Bananas | 130 | 190 |
WRONG
Multiple header rows
Some data tables contain several header rows, often with blank cells, to indicate multiple categories. For example:
| Cheese | | Bread | |
Year | Cost($) | Calories | Cost($) | Calories |
2003 | 3.24 | 200 | 1.29 | 120 |
2004 | 3.31 | 200 | 1.91 | 130 |
2005 | 3.29 | 210 | 1.54 | 120 |
WRONG
Many Eyes does not handle multiple header rows, so in this case you would need to edit your data in a spreadsheet or word processor to merge the headers like this:
Year | Cheese: Cost($) | Cheese: Calories | Bread: Cost($) | Bread: Calories |
2003 | 3.24 | 200 | 1.29 | 120 |
2004 | 3.31 | 200 | 1.91 | 130 |
2005 | 3.29 | 210 | 1.54 | 120 |
RIGHT
Caution
Data Sets
It is a static system. Once the data is uploaded, it cannot be modified, only visualized in multiple ways.The data is made public to everyone on the internet once it is uploaded, so private data is not to be used.
Memory drain
The Java applets take up a lot of memory and may cause CPU drain. Sometimes, it might even crash the browser.
Beware of Garbage In/Garbage Out
Use only that visualization type which is suitable and makes a perfect sense of the input data. Improper selection of visualization type may lead to senseless data interpretation. A small typo in the input data might lead to disastrous change in the visualization
For more information about the various pros/cons, CLICK HERE!Miscellaneous
Community Sharing
- Many Eyes is a site where you can see your data visualizations and multiple people can access them for a collaborative experience.
- It supports collaborative analysis around the visualization of data by drawing on the insight and expertise of users all across the internet to provide broader and deeper analysis of data.
- It aims to democratize visualization by providing a forum for any user of the site to explore, discuss, and collaborate on visual content. For example, a government agency could use this tool to help it understand factors that may indicate potential recipients of government aid.
Rating System for Data & Visualizations
The data sets and visualizations can be rated by the users. Ratings go down as well as up. This is an all in one flagging/liking system. This means if you see some data which is inaccurate, or you just don't like someone's numbers, you can give them a thumbs down. Also, the best rated visualizations and sets are promoted for all to see.
Topic Centers
A topic center is a page devoted to a particular topic or theme. It serves as a way to collect related visualizations and data sets, along with a discussion area. Use topic centers for research on an area (for example, global warming), for a particular group of people (for example, class projects for Visualization 101), or any other theme. Any registered user can create a topic center.
