Project description


My name is Mikhail Ageev. Since February 2018 I’ve been working as a Data/Visual Journalist at CurrentTimeTV (venture of RFE/RL and VOA) in Prague.

Our department called DIGIM is a tiny group of less than 20 people (journalists, video-producers, social-media folks) who works only with our website

On a daily basis we cover ex-Soviet countries: Russia, Ukraine, Belarus, Kazakhstan, Azerbaijan, Kyrgyzstan, Armenia, Uzbekistan, Tadjikistan and Baltic countries.

Most of the submitted projects are created with the help of my great colleagues who listed in Project Members field. Our other interactives may be found here

What makes this project innovative?

This portfolio constits of a different types of stories that includes various visualization techniques: 1) Interactive SVG schemes 2) Interactive Photos 3) Maps 4) Charts 5) Calculators 6) Big Data Analysis (the last link) Represented stories cover four Presidential Elections in Russia, Kremlin official phonecalls, cross-border trade in Eurasian Union, deadly fire in Kemerovo, cropped photo-album of Vladimir Putin-2000 team and combined economy, wages, healthcares and freedom in ex-USSR. It's hard to call our focus countries an Open-Data developed region. That's why this portfolio is in Russian and based on parsed Russian official data, Eurasian Economic Commission statistics and WorldBank/IMF/FreedomHouse/etc data.

What was the impact of your project? How did you measure it?

* The most engaging was a story of "Putin Team - 2000": 236K visit with avg 7 minutes per visit. It got 100+ retweets and 100+ likes on Twitter and 3.9K shares on Facebook. * Comparison of Norway with ex-USSR countries also did well on Twitter with 45 RTs and 68 Likes Avg time on page is not this good — 2+ minutes with 34K unique visitors. * Russian Elections Map hitted avg 7:55 minutes per visit with gawky 13K unique visitors. * EAEU cross-trade got avg 4:07 minuts with 4K unique visits (Nursultan Nazarbaeyv resigned on the day of publication of the article). At the same time we got 300+ on-page FB likes. * Another measure of success: our colleagues accross the RFE/RL network are likely to pick up our stories or to create a static version of it (is they are not able to localize it). Like this adaptation of "Kremlin Calling Project" * Article about Kyrgyzstani "startups" was picked up by our colleagues from RFE/RL Kyrgyz Services. They added some value (research) to the original post and published it both in Russianсамые-успешные-стартапы-в-кыргызстане-в-2018-году-/29791370.html and Kyrgyz website used in this article combines 3 government databases and allows journalist to track legal entities and budget spendings.

Source and methodology

The main technique used is: to parse the publicly available data using Python, analyze it (Excel or MySQL) and represent findings in a structured well-formated way. For the listed projects different sources of data were used: * Parsed Russian Elections Commision data on last four Presidential Elections * Parsed and analyzed spreadsheets (based on TNVD codes) on cross-trading published at Eurasian Economics Commission website for "Oil and Gas vs Cogniac and Cheese" article * Parsed official press-releases at for "Kremlin Calling" Project * Talked to the visitors of the notorious Zimnya Vishnya Trade Center, analyzed photos and videos to built a model of the entertainment area that went on fire on March 25, 2018 * Used my side-project to track startups that earned 1M+ soms in Kyrgyzstan "Kyrgyzstani Most Successful Startups in 2018". combines three Government databases in Kyrgyzstan: Legal Entities register, Open-Budget and Gov Procurement Database * For the "Norway vs ex-USSR Countries" Project, Pension and Inflation calculators used data provided by International Organizations

Technologies Used

Each project is unique and requires different types of technology: * For parsing of webpages and spreadsheets I mostly prefer Python and libs like xlrd, BS4 * For charts — amCharts and HighCharts libraries, GoogleCharts, Excel * For maps — OpenStreetMaps with LeafLet lib and SVG-layers for country-specific visulizations * Frontend is built using own templates with Bootstrap and jQuery on board, sometimes with SVG-animations * Other tools used: VSCode, Adobe XD/Photoshop/Illustrator, Django, SQL

Project members

Dmitry Treschanin Kristina Zakurdaeva Olga Serebryanaya Mikalay Schatsko Lyubov Moiseenko


Additional links


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