report_notes.txt

02/09/2019: first lecture data science
* we already found the group and thought about the topic
* since some of us were on a hill near helsinki the weekend before, to see northern lights
    the idea for the project came quickly 
* we thought about other topics, but finally kept the topic
* one of us volunteered for requesting access to twitter data (Logan)

09/09/2019: first exercise session
* we thought about the realisation of the project
    - project structure, how to reach the end-user
    - data sources: mainly twitter
    - what to do we have or want to archive and remember to do
    - maybe another Twitter access request, so we prolong/ increase our possibilities
* set-up of a github project for the webpage, so that we all can work on the code (Luise)

10/09/2019: first porper team meeting
* we searched for databases
* twitter data fetching is pretty limited
* we searched for alternative data, from with we can conclude to northern lights
* we thought, that weather data is reasonable to take into account
* we researched a bit for meterological data and indicators (as sunwinds, particle stream, athmospheric conditions, ..)
    , but recognized, that we don't have the expertise distinguish between all those parameters
* also: it seems not do be directly possible to calculate northern lights
* we defined, that we want to use
    weather data (clouds, vidibility) from FMI,
    k-index as it represents solar radiation by their magnetic effect from a public accessible database,
    twitter for further validation, precision, images, information e.g. location
    
* set-up overleaf for working on our final report(Vincent)

15/09/2019
* description of the prject's outline and further work on the webpage (set-up backend) (Luise)

TODOs:
* set-up database (sqlite)
* collect data
* storing in database
* preprocess data 
* set-up python backend
* set-up data-connection between python backend and db
* set-up connection between db, webapp-backend, and webapp-frontend