This project provides a comprehensive dataset of over 125,000 missing and unaccounted-for people in Mexico from the 1960s to 2025. The dataset is sourced from the publicly available records on the RNPDO website and represents individuals who were actively missing as of the date of collection (July 1, 2025). To protect individual identities, personal identifiers, such as names, have been removed.Dataset Features:The data has been cleaned and translated to facilitate analysis by a global audience.Fields include:SexDate of birthDate of incidenceState and municipality of the incidentData spans over six decades, offering insights into trends and regional disparities.Additional Materials:Python Script: A Python script to generate customizable visualizations based on the dataset. Users can specify the state to generate tailored charts.Sample Chart: An example chart showcasing the evolution of missing persons per 100,000 inhabitants in Mexico between 2006 and 2025.Requirements File: A requirements.txt file listing the necessary Python libraries to run the script seamlessly.This dataset and accompanying tools aim to support researchers, policymakers, and journalists in analyzing and addressing the issue of missing persons in Mexico.

Mexican cartels lose many members due to conflict with other cartels and arrests. Yet, despite their losses, cartels managed to increase violence for years. We address this puzzle by leveraging data on homicides, missing persons and arrests in Mexico for the past decade, along with information on cartel interactions. We model recruitment, state incapacitation, conflict and saturation as sources of cartel size variation. Results show that by 2022, cartels counted 160,000–185,000 units, becoming a top employer. Recruiting at least 350 people per week is essential to avoid their collapse due to aggregate losses. Furthermore, we show that increasing incapacitation would increase both homicides and cartel members. Conversely, reducing recruitment could substantially curtail violence and lower cartel size., Data obtained from Plataforma de Proyección de Datos Abierta, was processed to obtain a network structure. https://ppdata.politicadedrogas.org/ Trends were produced by solving a set of differential equations., Datasets are in a CSV format. Code is available for RStudio or R.

"All the data for this dataset is provided from CARMA: Data from CARMA (www.carma.org) This dataset provides information about Power Plant emissions in Mexico. Power Plant emissions from all power plants in Mexico were obtained by CARMA for the past (2000 Annual Report), the present (2007 data), and the future. CARMA determine data presented for the future to reflect planned plant construction, expansion, and retirement. The dataset provides the name, company, parent company, city, state, zip, county, metro area, lat/lon, and plant id for each individual power plant. The dataset reports for the three time periods: Intensity: Pounds of CO2 emitted per megawatt-hour of electricity produced. Energy: Annual megawatt-hours of electricity produced. Carbon: Annual carbon dioxide (CO2) emissions. The units are short or U.S. tons. Multiply by 0.907 to get metric tons. Carbon Monitoring for Action (CARMA) is a massive database containing information on the carbon emissions of over 50,000 power plants and 4,000 power companies worldwide. Power generation accounts for 40% of all carbon emissions in the United States and about one-quarter of global emissions. CARMA is the first global inventory of a major, sector of the economy. The objective of CARMA.org is to equip individuals with the information they need to forge a cleaner, low-carbon future. By providing complete information for both clean and dirty power producers, CARMA hopes to influence the opinions and decisions of consumers, investors, shareholders, managers, workers, activists, and policymakers. CARMA builds on experience with public information disclosure techniques that have proven successful in reducing traditional pollutants. Please see carma.org for more information"

The Harmonised Cognitive Assessment Protocol (HCAP) is part of the Healthy Cognitive Aging Project, a study examining how people's memory and thinking change as they get older. In England, HCAP is a sub-study of ELSA, the English Longitudinal Study of Ageing (ELSA), a longitudinal survey of ageing and quality of life among older people that explores the dynamic relationships between health and functioning, social networks and participation, and economic position as people plan for, move into and progress beyond retirement. (The main ELSA study is held under SN 5050.)

ELSA-HCAP1 took place in 2018 and interviewed ELSA core members aged 65 and over. It included a second, shorter interview with an informant, a family member or friend nominated by the ELSA core member to complete an interview on their behalf. ELSA-HCAP2 took place in 2023 and interviewed ELSA-HCAP1 sample members and additional ELSA core members aged 65 and over, and also included an informant interview.

The HCAP study originated with the Health and Retirement Study (HRS) in the United States, which is a sister study to ELSA, a longitudinal study of people aged 50 and over in the United States. Researchers on HRS developed the protocols for HCAP, in discussion with researchers from ELSA and other international studies, and fieldwork in the United States began while ELSA-HCAP in England was still in the planning stages.

The aim of ELSA-HCAP is to measure the prevalence of dementia and cognitive impairment among older people in the ELSA panel, in order to:

• Understand more about how widespread these conditions are in England and increase our understanding of dementia;
• Test how well the cognitive assessments used in this study can identify these conditions.
• Examine the 5-year change in cognitive function in the subset of respondents who take part across multiple waves of ELSA-HCAP.

HCAP scores developed by Alden Gross and colleagues - February 2024

For the third edition (February 2024), harmonised general and domain-specific cognitive scores were added from HCAP studies across six countries: China, England, India, Mexico, South Africa and the USA. The harmonised cognitive function scores have been developed by Alden Gross and colleagues. These scores empirically reflect comparable domains of cognitive function among older adults across the six countries, have high reliability and are useful for population-based research. The accompanying documentation includes a guidance file and the publication by Gross et al. (with supplement) that explains the scores and how they were derived. Each of the 1,273 participants in HCAP1 has a score on general cognitive function, executive function, language, orientation, and memory.

ELSA-HCAP2 and Family and Friends (Informant) data deposited - February 2025

For the fourth edition (February 2025), the ELSA-HCAP2 and Family and Friends (Informant) 2023 data and documentation were deposited. The ELSA-HCAP2 dataset contains 2,022 cases and the Family and Friends (Informant) dataset contains 1,807 cases. Data were collected between April to November 2023 for ELSA-HCAP2 and April to December 2023 for Family and Friends (Informants). ELSA-HCAP2 had an additional aim; to examine the 5-year change in cognitive function in the subset of respondents that took part in ELSA-HCAP1 in 2018.

RE-DEPOSIT of ELSA-HCAP2 and Family and Friends (Informant) data - August 2025

For the fifth edition (August 2025), updated versions of the HCAP2 respondent and informant datasets were deposited, with an updated version of the score variables data dictionary, and a new HCAP2 technical report. Information on the changes is provided below.

Changes in the HCAP2 respondent dataset version 2

The re-deposited version of the HCAP2 respondent dataset includes the cross-sectional and longitudinal weights. The ethnicity variable ‘fqethnmr’ has also been added along with recoded versions of the Logical Memory and Constructional Praxis test items that align with the ‘cleaned’ summary scores. Corrections have been made to the scores in ‘AT_delayed_exact’, the missing values for variables ‘TMT_A_secs’ and ‘TMT_B_secs’ have been corrected/recoded, and ‘indager’ has been recalculated to reflect respondent age at the point of sampling.

Changes in the HCAP2 informant dataset version 2

In re-deposited version of the HCAP2 informant dataset, variable ‘CSI_cogact1a_me’ has been added, corrections have been made to the derived variable ‘csi_cogact_attempt’, and a small number of cases in ‘I_educ_final’ and ‘I_freq_final’ have been recoded. Further minor changes have been made to variable and value labels and to the order of the variables in the dataset.

A joint venture involving the National Atlas programs in Canada (Natural Resources Canada), Mexico (Instituto Nacional de Estadstica Geografa e Informtica), and the United States (U.S. Geological Survey), as well as the North American Commission for Environmental Co-operation, has led to the release (June 2004) of several new products: an updated paper map of North America, and its associated geospatial data sets and their metadata. These data sets are available online from each of the partner countries both for visualization and download. The North American Atlas data are standardized geospatial data sets at 1:10,000,000 scale. A variety of basic data layers (e.g. roads, railroads, populated places, political boundaries, hydrography, bathymetry, sea ice and glaciers) have been integrated so that their relative positions are correct. This collection of data sets forms a base with which other North American thematic data may be integrated. Any data outside of Canada, Mexico, and the United States of America included in the North American Atlas data sets is strictly to complete the context of the data. The North American Atlas - Railroads data set shows the railroads of North America at 1:10,000,000 scale. The railroads selected for this data set are either rail links between major centres of population or major resource railways. There is no classification of rail lines. This data set was produced using digital files supplied by Natural Resources Canada, Instituto Nacional de Estadstica Geografa e Informtica, and the U.S. Geological Survey.

This dataset is compiled from the Mexican Population and Household Census from 2005 (Conteo de Poblacion y Vivienda 2005). The data is at municipal level (of almost 2,000 municipalities) and is comprised of total population, population by age groups, population by sex, average age by sex and the male to female ratio. Where there were inconsistencies in municipality boundaries between the Mexican data and the available shapefile, the data have been combined in the appropriate fashion. The polygons that contain data from more than one municipality are labeled with all municipality names. Values of -1 represent no available data.

This dataset is compiled from the Mexican Population and Household Census from 2005 (Conteo de Poblacion y Vivienda 2005). The data is at municipal level (of almost 2,000 municipalities) and is comprised of number of localities and their populations by the size of localities. Where there were inconsistencies in municipality boundaries between the Mexican data and the available shapefile, the data have been combined in the appropriate fashion. The polygons that contain data from more than one municipality are labeled with all municipality names. Values of -1 represent no available data.