Group Members: Simon, Brian, Katherine, Sarah

TA: Akshita Gundavarapu (BG)

First Meeting: 05/03/23

• Finish challenges and limitations section (Sarah)

• Add or remove a research question (Katherine)

• Add or remove a word or two to the Implications secton (Brian)

• Final double check (All)

Our projects intention is to analyze and represent equipment losses from the Russia-Ukraine war in order to demonstrate the social and economic impact on both countries. We are employing a variety of data visualization tools, two robust datasets representing Ukraine and Russia respectively, and publicly collected datasets about Russian Sanctions to further our research. Through our work we hope to make apparent large-scale differences in war propaganda and attitudes from both parties, and its relation to equipment losses specifically.

Data visualization, Misinformation, Conflict, Welfare, Public-Health

• Through analyzing day-by-day losses from both sides of the ongoing conflict, how can we move to compare our findings to the propaganda and misinformation being reported by both parties?
• What are the total (to-date) equipment losses for both parties in the conflict?
• Are there observable trends in the rate at which equipment is being lost for both sides? (i.e. dips, maximums)
• How can we compare the findings in this dataset to the total resources both sides have available?
• What is the financial figure associated with the loss of this equipment, and how can we estimate the cost associated with each loss?

In the midst of the Ukraine-Russian war that is still on-going until today, there has been a lot of news delivered about the impact and the deteriorating consequences from each side. However, it is hard sometimes for the general public to get a grasp of what is the most up-to-date data and information of the losses on equipment, personnel, and so forth to interpret the weight of the impact on each party. Hence, it is easy to develop bias based on which media sources that you obtain the information about the war from. Our group is interested in displaying a transparent data set of the losses of equipments from Russia and compare the numbers between both parties.

The dataset aggregates equipment losses over time from both sides of the Russia-Ukraine war. Through our research and our specific focus on visualizing those losses, we want to make transparent the war's impact on both parties. In doing so, we aim to put to scale the intensity of the war and compare/contrast the equipment losses to the overall sizes of both armies. Within this space, we have combed through many related datasets and articles (both in Russian and English) to match figures to the conflict. We are aware of the challenges and limitations that afflict war-related loss reporting and aim to make conservative estimates about the scale of these losses. Our long-term goals from this analysis are to put into fiscal terms the impact of these equipment losses, and to potentially elaborate on this figure with information about runway and resource management from both sides. Our dataset is sourced from Kaggle (Russia-Ukraine Equipment Losses 2022), and was compiled from daily reports by Petro Ivaniuk, a data scientist from Lviv, Ukraine. To gain perspective and to further the effectiveness of our research, we are utilizing a variety of different articles. This article from the Wall Street Journal (Russia Likely Lost More Than Half...), and this article from Oryx (Attack On Europe: Documenting Russian Equipment Losses) accomplish a similar goal and provide useful information.

Ukraine-Russia War Equipment Losses (Ivaniuk, 2022)

Petro Ivaniuk. Data Scientist, PhD at CheAI

The main data sources are Armed Forces of Ukraine and Ministry of Defence of Ukraine.

Additional Sources:

• Oryxspioenkop.com

• LiveUaMap.com

• Correctiv.org

• NYTimes.com

The dataset is an act of solidarity with Ukraine. The data scientist(s) who created it are Ukrainian citizens and want to publish resources to make clear the impact of the war and gather support.

There are two datasets in our data, both have about 350 rows (days) of observations.

There are 18 columns.

We have to be considerate of the estimates associated with the data as there are potential biases for both sides of the conflict. As the author(s) of the dataset are Ukrainian, we have to be liberal with our estimates of both Russian and Ukrainian losses so as to reduce bias. We are actively counteracting this by using a dataset that features high quality digital images of the specific equipment in the dataset (some many thousands of photos). As for questions of power, we want to understand more about the systems and governments involved in the conflict:

• Who has control over the data reported in the dataset? By what means can they control or alter the results of the dataset and its validity?

• Where is our data sourced from? Is that source reliable, and can we trust the institution it comes from?

• What does the differences (if any) between the two datasets (Ukraine and Russia) tell us about the way the data was sourced or collected?

Throughout the war between Russia and Ukraine, there have been countless reports on the impacts of the war both economically and politically. From our research, we hope to shed light on how accurate the media has depicted the destruction that has occurred as a result of the Russia-Ukraine war. Utilizing our dataset that includes data of equipment losses, we will form an understanding of how both sides of the Russia-Ukraine war have suffered economically. Considering that the war has fallen out of the media’s eye, our research may also bring forth how exactly the war has been impacting both of the countries recently. In comparison to the information that is spread by the news, our research may reveal some misinformation and unreliability that has been widespread to create propaganda about the reality of how the war is truly going. We hope to bring awareness to not only the catastrophes of this war, but also to the problem of misinformation that occurs in the media. Our findings may be helpful to those in charge of producing the news sources that report on the war. Specifically, there is potential to find that where the news resource comes from could sway how accurate the reports are. Our findings could reveal biases in the media.

Our biggest limitation and challenge from this project is the unreliability of our data set and information. Due to our topic being about a war that is still occuring today, it is important to remember that both sides are unlikely to report all their losses. The data set also only includes the number of equipment losses that have photo or videographic evidence. Meaning that the total number of destruction is much higher than recorded. Another difficulty we must acknowledge during this report is our lack of access to all the data and information being used as a communication source for this war. This is due to multiple barriers such as language and lack of accessibility to online resources. There are various online applications that are being used to spread awareness and quick information that we do not know about, have access to, nor have the capabilities to read in that language.

What are possible limitations or problems with this data? (at least 200 words) TO-DO: Add a second paragraph talking about the data specifically.