Dossier on the Election in the Lab

Dossier on the election available in the Lab -a collection of election information from our site. All materials where this election is mentioned.

Election Cards

RUElectionData Telegram channel
External Sources Manager

RUElectionData Telegram channel

Open Data on Russian Elections

The RUElectionData telegram channel began functioning on 1 March 2018. 

Unique data quality: the regularity of the CEC website parsing. One of the most striking achievements of the telegram channel: revealing the rewriting of the results of the 2018 gubernatorial election in Primorsky Krai in the second round. 

RUElectionData.
Source of data:

CEC of the Russian Federation

Parsing time:

Regular parsing during the election and a few days after.

Regular parsing during the election and a few days after.

 

Data format:

Delivered in zip archives. Json, csv, tsv data format

Data completeness:

Data may include supporting information on turnout during voting, PEC information, voter movement and others. Data does not include numerical precincts and complex cases of commission hierarchy. 

Remarked shortcomings:

PECs for Distant Electronic Voting are absent (as of 13.09.2020). Rare and complex cases of the hierarchy of election commissions are not reflected. For example, the inclusion of the Nenets Autonomous District in the data of the Arkhangelsk region for the 13.09.2020 gubernatorial election. Verification by total values is recommended.

 

 

Previous Article Armenia, Yerevan, City Council 2017
Next Article Russia, President 2018
Print
13329
Please login or register to post comments.

Articles on the Elections

DIY Kiesling-Shpilkin diagram

The presentation of a new interactive tool

EG 0 18123

Good news for electoral observers, journalists and election investigators. You have a new and long-awaited tool - the interactive Kiesling-Shpilkin diagram. This detailed video lesson will help you understand how to work with this kit, what the advantages of an integrated approach are, how the tools help each other to detect an anomaly, or how the findings of one tool confirm the findings of another. In the lecture, we detected falsifications in the Moscow region.

RSS
123468910Last