Save User history in relational database which includes pageids of articles (create a new internal labeling) read and have another database of the actual articles with view history, first view, last update, url, wikipediaPgid, location etc, . Thus, nice joins can be done with users and articles they have read to get nice stats.

Article scraper to get timeperiod from wikipedia article. (Check to see if wikipedia api already has this) . Result will be put in article database so that it can be used for future users.

scrape info about that year

Make color schemes for different event types: for example major wars, government takeovers, corporate / industrial events, and scientific breakthroughs.

circles with different opacity around every pin so that the colors stack

in the article database we will do calculations to find shortest distance to cities of a certain size and perhaps have something to tile the regions of influence of each city.

Gives Users access to their history as well as stuff like how many articles they have read in a certain area/timeperiod/etc as well as recommends them other areas to look at that they might find interesting. Essentially done after User History and Articles issue.

We should make pins of different types for different things

Timeline will be created at bottom of webpage that will allow people to see what articles they have read belong to each timeperiod

Have an menu (Even something that looks as simple as python -m http.server) which allows people to report failures in tiles as well as holds a list of unverified tiles for future verification) in case people wish to verify tiles in their free time

Take snapshots and overlay on lat/lon enabled map. Then analyze image by following edges, and saving lat/lon points. Map these points to certain country by finding the closest name of the same color. Also, account for countries that have bad border gore (esp. noncontiguous borders like Burgundy and Prussia). Will be used to display articles regarding that time period.

Pins shouldn't be the same size at every scroll to make dense locations viewable, also maybe cities or landmark dense locations should be large pins so clicking on rome wont always force click you on the monument that is the closest to the bottom of rome.

Frontend:
Check Scalability of How many markers can be placed
Backend:

A computer vision project to take maps and find geographic points of similarity between the map and the base map. The computer will generate an outline of the geographic borders at the same projection and scale as the base map and then color in this outline using the original map. In addition to this seemingly difficult task, the computer will also have to be able to read text within the geographic borders so that it can write down the names of countries when it creates this map.