A computerized data set of demographic, economic and social data for 227 countries of the world. Information presented includes population, health, nutrition, mortality, fertility, family planning and contraceptive use, literacy, housing, and economic activity data. Tabular data are broken down by such variables as age, sex, and urban/rural residence. Data are organized as a series of statistical tables identified by country and table number. Each record consists of the data values associated with a single row of a given table. There are 105 tables with data for 208 countries. The second file is a note file, containing text of notes associated with various tables. These notes provide information such as definitions of categories (i.e. urban/rural) and how various values were calculated. The IDB was created in the U.S. Census Bureau''s International Programs Center (IPC) to help IPC staff meet the needs of organizations that sponsor IPC research. The IDB provides quick access to specialized information, with emphasis on demographic measures, for individual countries or groups of countries. The IDB combines data from country sources (typically censuses and surveys) with IPC estimates and projections to provide information dating back as far as 1950 and as far ahead as 2050. Because the IDB is maintained as a research tool for IPC sponsor requirements, the amount of information available may vary by country. As funding and research activity permit, the IPC updates and expands the data base content. Types of data include: * Population by age and sex * Vital rates, infant mortality, and life tables * Fertility and child survivorship * Migration * Marital status * Family planning Data characteristics: * Temporal: Selected years, 1950present, projected demographic data to 2050. * Spatial: 227 countries and areas. * Resolution: National population, selected data by urban/rural * residence, selected data by age and sex. Sources of data include: * U.S. Census Bureau * International projects (e.g., the Demographic and Health Survey) * United Nations agencies Links: * ICPSR: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/08490

Midyear population estimates and projections for all countries and areas of the world with a population of 5,000 or more // Source: U.S. Census Bureau, Population Division, International Programs Center// Note: Total population available from 1950 to 2100 for 227 countries and areas. Other demographic variables available from base year to 2100. Base year varies by country and therefore data are not available for all years for all countries. See methodologyhttps://www.census.gov/programs-surveys/international-programs/about/idb.html

Dataset

This dataset was created by voiceofchina

Released under Apache 2.0

Contents

📦 MP-IDB-YOLO – Ultralytics YOLO-Formatted Malaria Parasite Image Dataset for Instance Segmentation and Object Detection

This dataset is a repackaged version of the original MP-IDB (The Malaria Parasite Image Database for Image Processing and Analysis), formatted for Ultralytics YOLO (You Only Look Once) instance segmentation annotation. The goal of this release is to make it easier for researchers and practitioners to apply state-of-the-art instance segmentation or object detection techniques to malaria cell detection and classification tasks.

⚠️ This dataset is a derivative work. All original images and annotations belong to the original MP-IDB authors. This version only converts them into Ultralytics YOLO-compatible format.

📚 About the Original Dataset

The original MP-IDB dataset was created and released by Andrea Loddo, Cecilia Di Ruberto, Michel Kocher, and Guy Prod’Hom, and is described in the following publication:

MP-IDB: The Malaria Parasite Image Database for Image Processing and Analysis
In Processing and Analysis of Biomedical Information, Springer, 2019.
DOI: 10.1007/978-3-030-13835-6_7

The dataset includes annotated microscopic blood smear images of four malaria species:

• Plasmodium falciparum
• Plasmodium malariae
• Plasmodium ovale
• Plasmodium vivax

Each image contains cells in one or more of the following parasite life stages, indicated in filenames:

• R: Ring
• T: Trophozoite
• S: Schizont
• G: Gametocyte

Expert pathologists provided the ground truth for each image.

🛠️ What’s Included in This YOLO Version

This version of the dataset includes:

• ✅ Original images from MP-IDB
• ✅ Instance Segmentation annotations in Ultralytics YOLO format (.txt files)
• ✅ Class definitions matching parasite species and life stages
• ✅ A YAML file ready for training using the Ultralytics Package

This reformatting is designed to save time for those building instance segmentation or object detection models for medical imaging and accelerate prototyping using YOLO and the Ultralytics Package.

📜 License and Attribution

The original MP-IDB dataset is released under the MIT License by Andrea Loddo and contributors. Please make sure to cite the original work if you use this dataset in your own research or application:

The Database of Political Institutions presents institutional and electoral results data such as measures of checks and balances, tenure and stability of the government, identification of party affiliation and ideology, and fragmentation of opposition and government parties in the legislature, among others. The current version of the database, which is now hosted at the IDB, expands its coverage to about 180 countries for 40 years. Researchers at the World Bank Development Research Group first compiled the database in 2000 (see citation information below). It has become one of the most cited databases in comparative political economy and comparative political institutions. Almost 3,000 studies have used this database so far as a source of institutional and political data in their empirical analysis. | This dataset contains important information and resources. For comprehensive details, documentation, and inquiries, please contact data@worldbank.org. Additional metadata and related resources are available on this page.

a database of modulators of protein-protein interactions. It contains exclusively small molecules and therefore no peptides. The data are retrieved from the literature either peer reviewed scientific articles or world patents. A large variety of data is stored within IPPI-DB: structural, pharmacological, binding and activity profile, pharmacokinetic and cytotoxicity when available, as well as some data about the PPI targets themselves.

CR-IDB: Cheese Ripeness Image Data BaseCR-IDB is the public image dataset described in the following article: TBDAuthors: Alessandra Perniciano, Luca Zedda, Andrea Loddo, Cecilia Di Ruberto, and Barbara PesDataset acquisitionThe dataset was obtained through the collaboration between Biosabbey s.r.l. and the Department of Mathematics and Computer Science (DMI) of the University of Cagliari under an agreement facilitated by DMI.Massimiliano Sicilia of Laore Sardegna oversaw the acquisition process as part of his collaboration with Biosabbey s.r.l.Subsequently, Andrea Loddo, affiliated with DMI at the University of Cagliari, curated and organized the dataset, which he currently maintains.NOTE: please indicate the following in case of using this dataset in your own work:TBD---------------------------------------------------------------------------------------------------------------Description:CR-IDB comprises three subsets sourced from each dairy: Podda-Granarolo, Gennargentu-Conad, and Lattebusche-Conad. All images were captured with a single light source, centered on cardboard, and have an initial resolution of 6016 x 4,016 pixels, further resized at 1800 x 1800 pixels. Image acquisition was performed using a Nikon D750 camera with a CMOS 35.9 x 24.0 mm sensor at 24 megapixels resolution.Copyright (c) 2024 andrealoddo

The TIMSS Advanced 2008 International Database is available to all individuals interested in the data collected and analyzed as part of TIMSS Advanced 2008. The aim is to support and promote the use of the data by researchers, analysts, and others interested in improving education. The database is available for download. The database includes the student achievement data as well as the student, teacher, school, and curricular background data for the 10 participating countries. The student teacher, and school data files are in SAS and SPSS formats with programs and macros. The database site also contains an updated version of the 1995 database that includes the rescaled achievement scores for advanced mathematics and physics produced using the current TIMSS scaling methods. The database is accompanied by the TIMSS Advanced 2008 User Guide, Foy, P., & Arora, A. (Eds.), containing four chapters accompanied by four supplements. There also is a link for obtaining the IEA IDB Analyzer. TIMSS Advanced 2008 assesses student achievement in advanced mathematics and physics in the final year of secondary school—the twelfth grade in many countries. TIMSS Advanced is part of IEA’s series of TIMSS international assessments designed to provide comparative information about educational achievement across countries. Because TIMSS Advanced assesses students in their last year of secondary school who have studied advanced mathematics or physics to prepare them for further study of mathematics and science at the tertiary level, the results are of particular importance for educational decision making.

ALL_IDB_1-2 The ALL_IDB1 version 1.0 can be used both for testing segmentation capability of algorithms, as well as the classification systems and image preprocessing methods. This dataset is composed of 108 images collected during September, 2005. It contains about 150 blood images each class 50 images, where the lymphocytes has been labeled by expert oncologists. The images are taken with different magnifications of the microscope ranging from 300 to 500.

What this dataset tests

Whether an invariant survives distillation. Same task.Same pressure.Smaller or altered model.

  Why this exists

Distillation often preserves outputswhile breaking structure. This benchmark checks structure.

  Data format

Each row compares

source behavior
distilled behavior

under a defined stressor.

  Labels

retained
partially-retained
not-retained

Retention is judged against invariant behaviornot accuracy.

  What is… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/db-invariant-retention-v0.1.

This dataset contains gamma-ray spectral measurements and associated metadata for nuclear material samples, including Material_type (U, Pu, MOX), material form/compound, isotopic concentrations (e.g., 238Pu, 239Pu, ..., 241Am) and raw spectral channels (Channel_0 … Channel_16383). It’s intended for research and teaching on spectral analysis, dimensionality reduction, classification (material ID), and regression (isotopic composition estimation).

Link: https://www-nds.iaea.org/idb/

The data and metadata in the IDB Database are licenced under the Creative Commons Attribution 4.0 International (CC BY 4.0), unless explicitly stated. Publications using data derived from the IDB Database should cite the database and the data authors.

Cite the database IDB Database, IAEA, 2025, https://nds.iaea.org/idb, https://doi.org/10.61092/iaea.gaef-dhff

CM-IDB: The Cheese Making Image Database for Image Processing and AnalysisCM-IDB is the public image dataset described in the following article: Detecting coagulation time in cheese making by means of computer vision and machine learning techniques (Doi: 10.1016/j.compind.2024.104173).Authors: Andrea Loddo, Cecilia Di Ruberto, Giuliano Armano, Andrea ManconiDataset acquisitionThe dataset was obtained through the collaboration between Biosabbey s.r.l. and the Department of Mathematics and Computer Science (DMI) ofthe University of Cagliari under an agreement facilitated by DMI.The acquisition process was overseen by Massimiliano Sicilia of Laore Sardegna as part of his collaboration with Biosabbey s.r.l.Subsequently, Andrea Loddo, affiliated with DMI at the University of Cagliari, curated and organized the dataset, which is currently maintained by him.# NOTE: please cite the following manuscript in case of using this dataset in your own work:@article{loddo2025detecting, title={Detecting coagulation time in cheese making by means of computer vision and machine learning techniques}, author={Loddo, Andrea and Di Ruberto, Cecilia and Armano, Giuliano and Manconi, Andrea}, journal={Computers in Industry}, volume={164}, pages={104173}, year={2025}, publisher={Elsevier}}---------------------------------------------------------------------------------------------------------------Description:The dataset for this study was assembled by collecting a series of 8 image sets from a Sardinian (Italy) dairy company (Podda Formaggi).Each set illustrates the coagulation process of milk, showing the transition from a liquid state to a gelatinous form known as curd.An image at different positions within the sequence for each set identifies the precise moment when this transformation begins, referred to as the curd-firming time.The images were taken using a camera with a CMOS sensor of size 35.9x24.0 mm and a resolution of 24 Mpixel, specifically a Nikon D750.All images are in RGB format, with a resolution of 6016x4016 pixels, and were taken at approximately 10-second intervals.Within each set, the images are organized chronologically and labeled based on the stage of maturation: pre-CF-time (negative class) or CF-time (positive class).The time interval between consecutive images varies, with negative examples taken every 10 seconds and positive examples taken every 2 seconds.Copyright (c) 2024 andrealoddo

This aggregate data collection is an extract of the International Data Base (IDB), a computerized central repository of demographic, economic, and social data for all countries of the world. Data available in this collection include total midyear population estimates and projections (1950-1985), percent urban population, estimates and projections of crude birth rate, crude death rate, net migration rate, rate of natural increase, and annual growth rate, infant mortality rate and life expectancy at birth by sex, percent literate by sex, and percent of the labor force in agriculture.

The International Registry of Reproductive Pathology Database is part of pioneering work done by Dr. Kenneth McEntee to comprehensively document thousands of disease cases studies. His large and comprehensive collection of case reports and physical samples was complimented by development of the International Registry of Reproductive Pathology Database in the 1980s. The original FoxPro Database files and a migrated access version were completed by the College of Veterinary Medicine in 2016. Access CSV files were completed by the University of Illinois Library in 2017.

The WTO's Integrated Data Base (IDB) contains imports by commodity and partner countries and Most Favored Nation (MFN) applied and, where available, data on preferential tariffs at the most detailed commodity level of the national tariffs.

WTO Integrated Database (IDB) and Consolidated Tariff Schedule (CTS) contains annual imports (values) and tariff structures (current and final Bound, MFN Applied and Preferential tariffs, ad-valorem or not) since 1996 at the National tariff line level for WTO member countries only. | This dataset contains important information and resources. For comprehensive details, documentation, and inquiries, please contact data@worldbank.org. Additional metadata and related resources are available on this page.

Indonesia External Debt: Government: International Organisations: IDB data was reported at 1.061 USD bn in May 2019. This records a decrease from the previous number of 1.061 USD bn for Apr 2019. Indonesia External Debt: Government: International Organisations: IDB data is updated monthly, averaging 527.116 USD mn from Jan 2008 (Median) to May 2019, with 137 observations. The data reached an all-time high of 1.063 USD bn in Jan 2019 and a record low of 248.101 USD mn in Feb 2009. Indonesia External Debt: Government: International Organisations: IDB data remains active status in CEIC and is reported by Directorate General of Budget Financing and Risk Management. The data is categorized under Indonesia Premium Database’s Government and Public Finance – Table ID.FA012: External Debt: by Country and International Organisations.

For details of Table 4 visit www.census.gov/hhes/fertility and for details of Table 5 visit www.census.gov/health. (XLSX)

This dataset is constructed to analyze the cross-country relationships of different types of public policies and support to the agrifood sector with the consumption patterns of different food commodities. It includes agricultural policy indicators and daily food consumption data spanning 49 Organisation for Economic Co-operation and Development (OECD) and Inter-American Development Bank (IDB) countries from 1986 to 2022. The dataset is compiled from three key sources: (i) the 2022 Global Dietary Database (GDD); (ii) the OECD Agricultural Policy Indicators database; and (iii) the Agrimonitor database from the IDB. Details on the dataset and the descriptions of the variables are provided in Appendices A-C of Reshaping the Agrifood Sector for Healthier Diets: Exploring the Links between Agrifood Public Support and Diet Quality (World Bank, 2024) and the included README file. | This dataset contains important information and resources. For comprehensive details, documentation, and inquiries, please contact fdizon@worldbank.org. Additional metadata and related resources are available on this page.

The zip file contains the benchmark data used for the TIPP3 simulation study. See the README file for more information.