Data journalists improve their data analysis and visualization skills to use for publications


A three-day training for the employees of 8 media outlets, who had previously received basic knowledge in data journalism in January of this year, was held 14 - 16 August in Bishkek.

Among the continuing participants were teams from «Tazabek», «Turmush», «PolitClinicа», «T-Media», Peshcom, Govori TV and MediaHub.

Internews Data Journalism Program's mentors conducted a three-day training in a hybrid format.

Saviya Hasanova trained participants in data analysis and scraping skills, taught them the advanced formulas in summary tables. Alexander Bogachev held online training sessions and prepared video lessons on visualization and mapping.

Savia Hasanova noted the program participants' high level of thematic applications and their painstaking work on manual data collection from different sources.

Data-journalists in their materials raised acute topics on urban infrastructure, the mortality of soldiers in the army, the pricing policy of Yandex-taxi.

Hasanova noted three distinctive features of the current data fellows:

First, most teams create their own unique data sets and use less of the data from the National Statistics.

Secondly, there are more publications in the video format for YouTube channels.

And the third important point is that this time, journalists have started working more on creating maps.  


The most interesting application this time was from Bermet Borubaeva, the ecogroup "Bishkek smog", who had conducted important research on fares in cash in the capital's "marshrutkas" (buses), based on manual unique data collection. Municipal authorities poorly account for the flow of money from numerous passengers, leading to financial leakages from the city budget.


Argen Baktybek uulu from the MediaHub YouTube channel noted that their team had produced several materials as part of this program and actively had been using the acquired skills not only to create data stories but also for investigative journalism.

 -For example, we were looking for the owner of a new casino recently opened in the country and managed to put together a dataset overnight. It became the basis for proving that a former official was one who supported its opening. After learning new skills in the training sessions, we've made even more use of data and visualization applications, which is working out great for us, he said.