Datafest online final project
Dangerous to be a woman
Violence against female professionals
In the period from January 2016 to May 2020, The Armed Conflict Location & Event Data Project (ACLED) reported 10 755 cases of violence against women. As a result, 3848 women died. Yet some professions seem to be more dangerous for women than the others: several names in the research are listed more often. This is an attempt to discover a pattern.
This perilous world
This map illustrates all cases registered by ACLED in 5 years, worldwide. Every dot on this map is an event of violence towards women. You can read the short description of what exactly happened if you move the mouse pointer to it.
Top-5 of overall cases happen in Asia and South America, with India leading in the sad statistics in absolute numbers (2650 events of violence against women in the last five years).
Professions that are identified and mentioned more often than the others
Swipe to the left to see the top-10 of the most dangerous professions. Tap on the Info icon in the right upper corner. Feel free to share these pictures on social networks by clicking on the three dots in the right bottom corner.
Attackers and Victims
The leadership in violent events belongs to protests: non-peaceful demonstrations can result in clashes with the police, where both sides of the conflict may suffer. 2019 has almost tripled the number of conflicts, where the protesters were on the side of attackers.
The second and the third places in this ranking of offenders belong to armed groups, not connected to the state, and official military forces. In both cases, 2019 was also more violent than the previous year. The same pattern is valid for government abuse, terror attacks, riots, and criminal offense.
Data Limitations
Any dataset has its limitations, and the one provided by the ACLED is no exception. Here is what a reader needs to know to prevent misunderstanding:
Some countries are not covered
ACLED is focused on data about violence, disorder, and crises. Thus, developed countries are mostly not researched. Additionally, some countries with hard-to-get access to the data are also excluded from the dataset. On the first map you can see if the country is presented in the ACLED research.
Only reported cases are covered
ACLED researchers are using open source information like newspaper reports among the other methods of gathering the data. While newspapers can serve as a solid source, it is important to hold in mind that in the countries with no free press some events might be underreported. However, the situation with underreporting violence against women, in particular, is also applicable to the states with the developed media landscape. World Health Organisation estimates that "1 in 3 women worldwide have experienced [...] violence in their lifetime". UN has also estimated that 87 000 women worldwide were intentionally killed in 2017 only. This data is unsurprisingly not matching with the one from the ACLED.
Coverage period differs from region to region
ACLED covers Africa (from 1997 to now), Middle East (from 2016 to now), South and South-Eastern Asia (from 2010 to now), and Europe (from 2018 to now). Thus, European data from 2016 and 2017 is not comparable with the data from other regions.
Cases, not victims or survivors
The aggregated numbers show how many events have happened, not the number of people involved in those events. When several people are attacked at the same time at the same place, it counts as one attack, disregarding the number of people injured or killed. At the same time, some events might involve representatives of different professions (e.g. health and aid workers often work together), so these events might be counted double in both categories.
Professions are seldom identified
We said already that some professions are named more often than others when talking about attacking women. However, the cases where the professions were mentioned make only a small part of all cases of violence against women. Out of 10 755 cases in total fixed by ACLED researchers, 9 328 events were described without naming the profession of women attacked. Apart from those, 156 events included jobless women or refugees, 59 cases included female prisoners. That means in this material we concentrate on only 11% of all cases mentioned in the ACLED dataset.
Woman-first vs. Professional-first
Perhaps the most important question that cannot be answered based on the data: were all these women attacked because they are women, because they belong to a particular ethnicity or religion, or because of their gender, sexual orientation, or profession? While none of this can justify violence against any person, the motivation of an attack is important for this kind of data work. Otherwise, there is a risk of misinterpretation: if let's say, a journalist was accidentally hit in the street by a drunk driver, or a lawyer was shot when the robbers tried to escape, these killings are not supposed to be counted as violence against representatives of the particular profession, are they?
Key findings
The most dangerous countries...
By the number of attacks:
1. Burundi (2,3 cases per 100.000 population)
2. South Sudan (2,1 cases per 100.000 population)
3. Central African Republic (1,9 cases per 100.000 population)

By the number of fatalities:
1. Central African Republic (2,5 deaths per 100.000 population)
2. South Sudan (2,2 deaths per 100.000 population)
3. Belize (0,75 deaths per 100.000 population)
It is dangerous to be...
  • A journalist in Central Africa
  • A police officer in Southern Asia
  • A farmer in Northern Africa
  • A government staffer in Southeast Asia

The most common violent events...
are protests. 55% of cases described involve one or another side of the conflict. Women are more often attacked by protesters than by armed groups or terrorists.
The most dangerous profession for women...
by the number of attacks: a Police officer
by the number of fatalities: a Journalist
About This project
"Dangerous to be a woman" is a cross-border data project started as a task at the Datathon
at DataFest Online-2020.
Data Wizards team
Finalists of the DataFest Online-2020
Data designer
Azerbaijan / Germany
Data analyst
Data designer
Multimedia journalist & Layout
Kazakhstan / Germany
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