Assignment 2 Guidelines (finalized)
With this assignment as we have grown more comfortable with open work, please change the permission of your site to anyone on the web.
In Assignment #2 (circa 1500 words + map(s)) you will be building a dataset from the Zanzibar Gazette and will be visualizing its spatial information on maps (as well as for the other information it contains). You will compos a small essay about what your dataset is able to communicate. You can do this assignment alone or in pairs. You will write this essay in Google Sites and it will include embedded live maps in UMap or AGOL or screenshots of maps made in other platforms. You also have the option of creating an ESRI Storymap in which case no text in Google Sites is required, just a link.
Note on working in groups: The project should be scaled to match the size of the group. It can be written together, but since both Google Sites and ESRI storymaps do not allow co-writing, it should be put together in one space and linked to from the student accounts. Please write on your own site what part of the work you were specifically responsible for.
There are seven steps to this assignment :
1) Using the pre-downloaded pdfs of the Zanzibar Gazette from the British Online Archives (1892-1919), you should browse through the newspapers to identify some element of their information that would make a good spatial dataset. By "good" is meant here, one that can be used to tell a relevant spatial data story using one of the mapping techniques we have explored thus far this semester.
2) You should build your dataset in our shared drive in the sub-folder ZG_datasets. There is no required number of points, but a rich assignment will have approximately 50-100 pieces of information per person working on the assignment. This might mean 100 rows of data, each with a corresponding location, or 50 rows of data (locations of events) with a corresponding location and category (the location of the business and the kind of business). Consider that you will want to have locational, temporal and or topical breadth in your dataset. You are encouraged to consult with the instructor in designing your dataset.
A dataset which was begun in drive has to do with licenses for certain professions allotted by the colonial power. You are welcome to build upon this one.
3) You will need to create some derived datasets using pivot tables and VLOOKUP. The use of data validation is optional. An excellent introduction to how to use these functions in Google Sheets is given by one of the former interns of the OpenGulf research group, Nada Ammagui.
4) You will need to geocode the datasets. I recommend using Geocode by Awesome Table which you can install as an extension in Google Sheets. You can also use Geonames or Historical OSM or just googling to attempt to find places. NB: There may be places you cannot find. You may also want to consult maps of Zanzibar. Some can be found here, here, here and here.
5) You should do a small amount of research to contextualize your topic. If you need help looking for related keywords, I am happy to do some analysis of the full corpus to help. You will need to link your essay to some web or print.
6) Include some images from our trip to Special Collections. Consider going back and looking for relevant ones from this list provided by the head of ASC. Caption your sources.
7) Questions you can use to guide your work on this assignment include:
Why did you choose this particular topic?
What tools helped you visualize the data you had the best?
What obstacles did you encounter in transforming a historical archival source into structured data?
Did you have to guess any of the locations? What evidence did you use?
What story -- small or large -- does your dataset help you tell? How are you able to relate it to the question of colonialism in Africa?
What would you do if you had more time? or more computational power?
Do the datasets of others in the class help you understand more about your own?
Some readings: You do not need to cite these specific sources, but they might be of interest for contextualizing some of your datasets:
Due date: 15 November