Datasets:
language:
- en
tags:
- history
- human rights violations
license: mit
pretty_name: TRC Volume 7 Victim Data
size_categories:
- 10K<n<100K
Dataset Card for the TRC Volume 7 Final Report Victim List
Dataset Summary
Languages
English
Data Instances
A typical data point comprises the metadata for a victim in Volume 7 of the TRC's Final Report.
An example from the dataset looks as follows:
{
"full_name": "Thabo Simon Aaron",
"lastname": "Aaron",
"firstname": "Thabo Simon",
"description": "An ANCYL member who was shot and severely injured by SAP members at Lephoi, Bethulie, Orange Free State (OFS) on 17 April 1991. Police opened fire on a gathering at an ANC supporter's house following a dispute between two neighbours, one of whom was linked to the ANC and the other to the SAP and a councillor.",
"place": [
"Bethulie"
],
"homeland": [],
"province": [
"Orange Free State"
],
"hrv": [
"shoot",
"injure"
],
"org": [
"ANC (African National Congress)",
"ANCYL (African National Congress Youth League)",
"Police",
"SAP (South African Police)"
],
"date": [
datetime.date(1991, 4, 17)
],
"coordinates": [
25.97552,
-30.50329
],
"age": 22,
"gender": "Unknown"
}
Data Fields:
full_name:- Type: String
- Description: The complete name of the individual. It contains the first name(s) and last name combined.
- Example: "Thabo Simon Aaron"
lastname:- Type: String
- Description: The last name or surname of the individual.
- Example: "Aaron"
firstname:- Type: String
- Description: The first name(s) or given name(s) of the individual. May contain middle names if applicable.
- Example: "Thabo Simon"
description:- Type: String
- Description: A textual description providing contextual information about the individual. This may include details about significant events, affiliations, or incidents related to the person.
- Example: "An ANCYL member who was shot and severely injured..."
place:- Type: List of Strings
- Description: The location(s) associated with the individual or significant events related to them. Each element in the list represents a different place.
- Example: ["Bethulie"]
homeland:- Type: List of Strings (empty lists allowed)
- Description: The homeland or origin of the individual. May be empty if this information is not available or not applicable.
province:- Type: List of Strings
- Description: The province(s) associated with the individual or significant events related to them. Each element in the list represents a different province.
- Example: ["Orange Free State"]
hrv:- Type: List of Strings
- Description: Codes or keywords representing human rights violations or significant events that the individual experienced or was involved in.
- Example: ["shoot", "injure"]
org:- Type: List of Strings
- Description: Organizations or groups that the individual is affiliated with or related to. Each element in the list represents a different organization.
- Example: ["ANC (African National Congress)", "ANCYL (African National Congress Youth League)", "Police", "SAP (South African Police)"]
date:- Type: List of Date Objects
- Description: Date(s) associated with significant events related to the individual. Each element in the list represents a different date.
- Example: [datetime.date(1991, 4, 17)]
coordinates:- Type: List of Floats
- Description: Geographic coordinates related to the individual or significant events. Typically, the list contains two elements representing latitude and longitude.
- Example: [25.97552, -30.50329]
age:- Type: Integer
- Description: The age of the individual.
- Example: 22
gender:- Type: String
- Description: The gender of the individual. Can be "Male", "Female", or "Unknown" if the gender information is not available or not specified.
- Example: "Unknown"
Each field in the data provides specific information about an individual, their affiliations, and significant events or attributes related to them. The data is structured to facilitate easy analysis and retrieval of information about individuals and their experiences or affiliations.
Curation Rationale
This data was made available by South Africa’s Truth and Reconciliation Commission (TRC) in 2003 in print and electronic form as Volume 7 of the TRC Final Report. Subsequently, the South African History Archive, in partnership with the South African Broadcasting Corporation hosted a .csv file version of this data on their jointly administered website, Truth Commission - Special Report. The .csv version of this dataset contains three fields for each victim: name, incident description, and, age. Incident descriptions consist of a 3-4 sentence description of human rights violation(s) (HRV) experienced by each named individual. These sentences contained a wealth of information stored in text string, such as the name of the town or city where the incident occurred, organizations involved in the HRV or affiliated with the victim, date(s) of incident(s), and the type of violence used. Certain categories of information used in incident descriptions were standardized by the TRC during data entry using a coding frame that contained a fixed vocabulary of 71 terms for references to types of political violence (i.e. “shooting”, “stabbing”, “torture”, etc.). Unfortunately description data was also not encoded in UTF-8.
In 2019, we began working with this data to extract vital metadata using a combination of heuristics and machine learning. This dataset is unique among publicly available human rights datasets in both its size and specificity. In 2021, we debut our first four data visualizations on our website. By making this dataset available, researchers will be able to learn more about the nature of political violence in South Africa between 1960 and 1994/5 at a nationwide scale, as collected by the TRC.
Initial Data Collection and Normalization
In 2019, we encoded the data into UTF-8. Next, we normalized the text so that there were no trailing or leading white spaces. We also ensured that certain peculiarities, such as double white spaces in the middle of a text were removed. Finally, we provided proper None values
Who are the source language producers?
This list was originally compiled from many sources but the bulk of information was drawn from statements given by victims, their family or witnesses and provided to TRC statement takers during 1994-1998. Statement taking consisted of an individual providing information about the incident(s), a statement taker recording that information in the form of notes, which served as the basis for subsequent data entry. In order to receive status as a victim, some degree of corroboration was conducted by TRC staff with additional evidence.
Annotations
Our additional annotations include the fields: hrv, places, homeland, provinces, gender, and dates.
Annotation process
To annotate the data, we leveraged Python and spaCy to automate the identification of categories of human rights violations, places, homelands, provinces, gender, and dates. To identify coordinates, we automated the mapping of identifiable places with no toponyms in South Africa, such as Cape Town. For more challenging places (approximately 2,000 locations), we performed manual validation. In some cases, specifically places with many toponyms, we provided the most likely candidate.
Who are the annotators?
The annotators for places were Steve Davis (PI) Robert Vaughan (Geographer).
Personal and Sensitive Information
The dataset contains the names and ages (where available) of victims of human rights violations in South Africa. These details were made public by the TRC in 2003 after the publication of Volume 7 of the TRC Final Report. In 2012, the South African History Archive (SAHA), in collaboration with the South African Broadcasting Corporation (SABC) posted an electronic version of this information hosted on Truth Commission – Special Report. “Truth Commission – Special Report” was a weekly television news digest of TRC proceedings broadcast in South Africa. The SAHA-SABC website also includes a new user interface and search function for improving access to hearing transcripts and a glossary of victims.
Social Impact of Dataset
This dataset improves access to data collected by the TRC by facilitating further data-driven research. Prior to our work, geo-political entities, types of violence and organizations were embedded within text strings and thus not available as a structured dataset. Our structured dataset allows researchers to now track broad patterns in political violence over chronological, geographic or thematical dimensions using various machine learning methods. The most immediate applications of this data set are the creation of new data visualizations and forms of quantitative analysis. The legibility enabled by our dataset extends the work of the TRC by preserving its archive for future generations in a new digital format. The aim of our work is sustaining and deepening the public’s understanding of human rights violations that occurred during the apartheid era. This data also informs ongoing debates about past and present human rights concerns beyond the domain of South African history.
Discussion of Biases
This dataset is not an exhaustive list of all individuals who were the victims of human rights violations during the apartheid era. A variety of circumstances including access to resources and transport, skepticism about the TRC’s motives, and the personal difficulty of revisiting severe trauma prevented many victims from participating in the statement-taking process. As noted by the TRC itself, these limitations are especially apparent for specific categories of victims such as women and victims of sexual assault, who are likely underrepresented in this data due to the reasons listed above. Additionally, the TRC’s process of corroboration may have excluded some victims from inclusion in its official victims list. Another source of bias is the TRC’s use of a coding frame to standardize descriptive terms related to violence. The coding frame limited data entry staff to approximately sixty terms. Given the complexity of the original statements given by individuals, problems of translation and compression of detail undoubtedly shaped the resultant descriptions that form the basis of this dataset. However, at the time of the composition of Volume 7 the state of database management to some degree required this approach.
Other Known Limitations
In nearly every instance of geopolitical entity coordinates, we are used the coordinates geographic center for that particular town, city or location. The original dataset did not include the exact street address of most incidents, presumably for issues related to privacy. The coordinates we provide in our dataset are rough estimates for any geopolitical entity.
The names of perpetrators generally do not appear in the original list uploaded to the SAHA-SABC website. Occasionally the authors of the original list indicated that the name of a perpetrator was known to the TRC. In those instances incident descriptions generically attribute actions using the term ‘known perpetrator’.
Additionally, it is important to note that only a small percentage (+/- 8%) of victims were invited to give testimony in public hearings held by the TRC.
Dataset Curators
Steve Davis, Associate Professor of History, University of Kentucky
William J.B. Mattingly, Postdoc Fellow, Smithsonian Institution
Jennifer Hootman, Coordinator of Digital Scholarship, William T. Young Library, University of Kentucky
Robert Vaughan, Research Assistant, University of Kentucky
Jamari Turner, Graduate Assistant, University of Kentucky
Licensing Information
Citation Information
Contributions
We would like to thank all victims, witnesses and Truth and Reconciliation commissioners and staff for assembling the data that comprises Volume 7 of the Final Report. We also thank the South African History Archive and the South African Broadcasting Corporation for making the initial dataset available as a CSV file.