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analysis of data for social good: network theory and stochastic process methods to characterise data
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LeWiBo_on_map.ipynb
README.md
analysis_mobility_trajectories_oh_data.ipynb
bikes_mobility_analysis.ipynb
data_on_map_visualisation.ipynb
get_schools_from_locations.ipynb
map.png
mobilitydata analyzer.ipynb
paleodata_meta_analysis.ipynb
user_activity_analysis_depersonalised.ipynb

README.md

Data analysis methods

Here we apply some standard data analysis methods to analyze and visualize the data for social good. The methods we are using are mostly based on:

  1. network theory https://github.com/Liyubov/networks_beauty

  2. stochastic processes https://github.com/Liyubov/networks_random_walking

Repository for analysis of mobility data and trajectories analysis https://github.com/Liyubov/mobility_analysis

Motivation for this project

These are projects, which inspired creation of this repository:

  1. Unicef school mapping project and Magicbox git repository https://www.unicef.org/innovation/school-mapping

  2. Lecturers without borders project, hosted at CRI www.scied.network

  3. Open global mobility data of airplane traffic from https://bluehub.jrc.ec.europa.eu/migration/app/index.html?state=5cc845a97758cd17cdecd1fb

Data description

The open datasets for this project are taken from:

  1. citizen science projects, such as https://scistarter.org/lecturers-without-borders-collecting-information-a
  2. open database from mobility data https://bluehub.jrc.ec.europa.eu/migration/app/index.html?state=5cc845a97758cd17cdecd1fb and from Erasmus travel data

Data visualisation

First of all, we start with visualisation of the data. We are working with data from csv files structured as: |institution name | institution type| institution location| institution contact| institution properties| The notebooks here are dedicated to data visualisation and data analysis Example of open data files can be found here https://data.cityofnewyork.us/Education/School-Point-Locations/jfju-ynrr

Data visualisation sources for interactive maps

Links from Hugo on blocks:

Codes browsers :

Toolkits:

Code

data_on_map_visualisation.ipynb

We visualise datafiles from two example files

  1. the csv file with data on randomized anonymized educational institutions data
  2. the dbf with open data from https://toolbox.google.com/datasetsearch/search?query=schools%20around%20the%20globe&docid=2T2%2BDeqbWNzcqeorAAAAAA%3D%3D The example of data are randomized data from educational centres around the world. Due to the data privacy reasons we are visualising only in the average characteristics of the data, such as average number of data points and average parameters of datapoints (such as number of resources needed in datapoints etc.).

mobilitydata analyzer.ipynb

We analyze open GLOBAL mobility data from open flights where we get information about all cross-border flights. Our main goal is to understand trends in growth of mobility cross-borders vs. intercontinental flights. More information on it is here https://github.com/Liyubov/mobility_analysis

LeWiBo_on_map.ipynb

It is file for the visualisation of activities of the project "Lectures without borders": lectures uploaded to the airtable visualised on a world map, preprocessing data from dataframe exported from csv file with all lectures made or planned. More details about project and activities (lectures, seminars of Lectures without borders) are on www.scied.network We collect the information about schools around the globe on Open Street map file. Contact us if you would like to contribute. We also plan to extent mapping to general projects, such as Open Street map plus Humanitarian dataprojects https://data.humdata.org/dataset/hotosm_arm_roads

analysis_mobility_trajectories_oh_data.ipynb

We analyze INDIVIDUAL mobility data from openhumans example of data in order to understand movements of individuals. (work in progress for analysis of individual trajectories)

bikes_mobility_analysis.ipynb

We start to analyze bike mobility data and other properies of bikes sharing systems in Berlin. The notebook is inspired by A.Kapp workshop at City lab Berlin https://github.com/technologiestiftung/bike-sharing . This notebook is in progress.

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