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Every Nobel Prize Winner and Where He/She Was Born

Map

ABOUT US
Our work
CONTACT

Graphs

Nobel Winners per 10m People  - ratio of nobel winners to each country's population

Winners by Gender

Most Common Prize Winner Name

Winners by Country

Female winners through the years

Female Winners by Category

Average Winning Age by Category

SERVICES

Digital Humanities

DH includes 3 aspects: using digital materials, tools, and methods in the humanities; developing digital materials, tools, and methods for use in the humanities; and subjecting the digital to humanities study.

ABOUT US

We are Amir Golan and Daniel Sar Israel, third year computer science students at University of Ben-Gurion located in Israel.

This project was made for digital humanities 181 class taught by Dr Yael Netzer.

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About Project

Creation Process

Map

Graphs

Drawing conclusions from the data

Presenting award winners visually

From acquiring the data to a full website

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About The Process

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Main Conclusions

As you can see in the graph "Female Winners Through The Years", females have been winning more nobel prizes in the last 30 years than ever before.

As you can see in the graph "Winners By Country", the African continent has very few winners, which we link directly to the continent's current state.

As you can see in the graph "Winners By Age", the average winning age is 61, so if you are younger than 61 you still have a chance!

First, we had to think of an idea that would interest us and be meaningful at the same time.

Furthermore, we needed a subject that had lots of data that we could present in an interesting way that could give us different insights on the subject. After running through many ideas we finally decided that the Nobel prize was important, had lots of data and we can draw interesting conclusions from it.

 

After the decision was made we started working. First we had to get the data. Since the noble prize is a very popular prize there are many different data sources. We had to find one that contained lots of data and had accurate data. After looking around the web and not finding a source that satisfies both criteria, we decided to use the Nobel Prize website as our source of data. If they don't have the most accurate data, then who does? After acquiring the data from the site , we decided that the data wasn't enough, we wanted more. After being very careful with which site we get information from, we decided that Wikipedia, Wikidata and DBpedia are reliable sources that we could use.

 

Now that we got our data, we have something that we could work with. We started thinking of different ways of displaying our data in order to present our idea in the most interesting and simple way. The data we acquired had many issues that we had to deal with. For example, we wanted to show where each winner was born on a map. Some of the winners were born in countries that don't exist anymore, or some were born in places that are now considered different countries. We made some decisions in order to be consistent throughout our project. First, if a winner was born in a country that doesn't exist anymore, then we show him on the map in the same location that he was born in. Furthermore, if a winner was born in a city that is now under a different country rule we displayed him on the map in his birth country.

 

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Bibliography

Tools

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