Reflection of the use of the Oxford Knights Archives

Reflection on The Oxford Knights Archive as a mapping exercise

‘The Oxford Knights Archive (2014-15)’ is a dataset compiled by Corey Albone, Jack Dunne, Namiluko Indie and Bethany Reid last year during their digital history classes.  The dataset contains information on a group of students who graduated from Oxford University before 1715, the information comes from a published book called Alumni Oxoniensis[1] that has been digitized by British History Online. The dataset contains the date of births of all graduates from Oxford University who then went on to become knights.  During our class we were required to create a Google fusion table[2], import the data and then make some changes.  The information was very interesting, however one disadvantage was the amount of differences individual users had when it came  to ambiguous percentages.  All the students in my workshop worked on this at the same time and the percentage varied from between one to six percent.  This is a disadvantage because it does not give a standard result for all users. I did the exercise at home putting in the same data, made the same changes and received a three percent ambiguous result, whereas in class I had a six percent result. The fact that this happened means that google is deciding on what is an ambiguous result each time.

One of the objectives was to create a heat map which showed us the area in which graduates were born and by looking at our results  we were able to discern how far away they lived from Oxford University. If we look at the results from a historical perspective,  generally the majority of the graduates lived quite closely to Oxford and were mainly located in England.  Interestingly  there were no graduates from the East Anglia area, which happens to be nearer geographically  to Cambridge University,  so we could presume that people in that area went to Cambridge instead of Oxford because of the distance.  However as we do not have a dataset with the required Cambridge graduates details, we have to assume that this may have been the case and we can’t class it as a fact.  In addition to this there were very few graduates from Wales showing on the heat map.  However this is an expected result as   Wales at the time was an underpopulated country in relation to England. I also created a heat map for Exeter University and the majority of students for that university were situated in the south-west of England.  So these findings could indicate that during this period, most students went to the nearest university and didn’t not travel far from home. This could be because the roads were not felt safe to travel on, during to civil unrest and fear of crime.

In addition to this there was a mistake that showed up on the dataset regarding one graduate called Richard Breame, his entry showed that he was born in Vancouver, Canada which we know is incorrect because the graduates died a long time ago before Vancouver was established.  The information has misinterpreted the word Surrey as a town of the same name located in Vancouver. The problem is that the computer sees the word Surrey as ambiguous so it has to be changed by stating that it is Surrey, England. Therefore this illustrates that the results may not always been a hundred percent accurate and we need to use them with caution.  Furthermore sometimes it is important to be more specific with name places to ensure you obtain the most accurate result possible.

I think that using a dataset and uploading it onto a Google fusion table can give you some interesting results and also enables speedier research.  For instance it would have taken longer to trace the birthplace of every person who went to Oxford University manually.  By using the heat map function it enables you to see the results instantaneously and gives a clear picture of location and proximity to universities.  However as previously mentioned the results can vary between users and sometimes more specific data needs to be used in terms of accuracy.  Generally I think that using Google fusion tables to interpret historical date is a useful tool for historians.

[1] ‘THE BRITISH LIBRARY – The World’s Knowledge’,; consulted 29 March 2015.

[2] ‘About Fusion Tables – Fusion Tables Help’,; consulted 3 April 2015.


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