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Historical Figures Mortality Dataset
NLP / Natural Language Processing
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About
This dataset provides structured information on the life, work, and death of over 1.22 million notable deceased individuals [1]. It is the largest dataset of its kind and was developed using a five-step method to infer birth and death years, binary gender, and occupation from community-submitted data across various language versions of Wikipedia [1]. The technical approach employed text mining to clean historical data and minimise missing values [1]. This resource offers new insights into the demographics of mortality in relation to gender and profession throughout history [1].
Columns
- Id: A unique Wikidata identifier for each individual [2].
- Name: The full name of the person [2].
- Short description: A brief description of the individual. Approximately 6% of entries are missing this information [2].
- Gender: The gender or sex of the individual. Male is the most common gender, representing 80% of entries, with around 11% of gender data missing [3].
- Country: The country or historical region associated with the individual. Approximately 27% of this data is missing, with the United States of America being the most common country, representing 12% of entries [3].
- Occupation: The occupation title of the individual. Around 17% of occupation data is missing, and Artist is the most frequent occupation, accounting for 23% of entries [3].
- Birth year: The year of birth, ranging from -2700 to 2016, with a mean of 1840 [4-6]. All entries have birth year data [5].
- Death year: The year of death, ranging from -2659 to 2021, with a mean of 1910 [6-8]. Almost all entries include death year data, with only one missing value [8].
- Manner of death: Describes how the individual died (e.g., suicide, natural causes, or capital punishment). This field is largely incomplete, with 96% of entries missing this information. Natural causes is the most common recorded manner of death, representing 3% of entries [8].
- Age of death: The age at which the individual died, ranging from 0 to 169 years, with a mean age of 69.3 years [8-10]. Nearly all entries have age of death data, with only one missing value [10].
Distribution
The dataset is provided as a CSV file, specifically
AgeDataset-V1.csv, and has a file size of 116.78 MB [2]. It contains 10 columns and includes data on 1.22 million people [2].Usage
This dataset is ideal for:
- Conducting demographic research, particularly on historical mortality trends [1].
- Analysing the relationship between gender, profession, and life span [1].
- Studying the life cycles and work patterns of notable individuals throughout history [1].
- Social science and computer science research applications [11].
Coverage
The dataset covers individuals from more than 300 contemporary or historical regions globally [1]. The time range for birth years spans from -2700 to 2016, and for death years, from -2659 to 2021 [4-8]. Demographically, it includes 107,000 females and 124 non-binary people, alongside a significant number of male individuals [1, 3]. It also features 90,000 researchers [1]. It is important to note the significant amount of missing data for 'Manner of death' (96%), 'Country' (27%), 'Occupation' (17%), and 'Gender' (11%) [2, 3, 8].
License
CC BY-NC-SA 4.0
Who Can Use It
- Academic researchers in history, sociology, demography, and computer science for studying historical patterns and social phenomena [1, 11].
- Data scientists and analysts interested in large-scale historical datasets and text mining applications [1, 11].
- Anyone with an interest in biographical data or the lives of notable historical figures.
Dataset Name Suggestions
- Historical Figures Mortality Dataset
- Notable Deceased Persons Life & Work Data
- Global Historical Demographics Dataset
- Prominent Individuals Life History Dataset
- Wikipedia Notable Lives Dataset
Attributes
Original Data Source: Historical Figures Mortality Dataset
QUALITY