This uniquely granular dataset captures 13,427 development projects worth $843 billion financed by more than 300 Chinese government institutions and state-owned entities across 165 countries in every major region of the world from 2000-2017.

The total population in China was estimated at 1409.7 million people in 2023, according to the latest census figures and projections from Trading Economics. This dataset provides - China Population - actual values, historical data, forecast, chart, statistics, economic calendar and news.

The dataset captures 20,985 projects across 165 low- and middle-income countries supported by loans and grants from official sector institutions in China worth $1.34 trillion. It tracks projects over 22 commitment years (2000-2021) and provides details on the timing of project implementation over a 24-year period (2000-2023).

Abstract

The fourth edition of the Global Findex offers a lens into how people accessed and used financial services during the COVID-19 pandemic, when mobility restrictions and health policies drove increased demand for digital services of all kinds.

The Global Findex is the world's most comprehensive database on financial inclusion. It is also the only global demand-side data source allowing for global and regional cross-country analysis to provide a rigorous and multidimensional picture of how adults save, borrow, make payments, and manage financial risks. Global Findex 2021 data were collected from national representative surveys of about 128,000 adults in more than 120 economies. The latest edition follows the 2011, 2014, and 2017 editions, and it includes a number of new series measuring financial health and resilience and contains more granular data on digital payment adoption, including merchant and government payments.

The Global Findex is an indispensable resource for financial service practitioners, policy makers, researchers, and development professionals.

Geographic coverage

Tibet was excluded from the sample. The excluded areas represent less than 1 percent of the total population of China.

Analysis unit

Individual

Kind of data

Observation data/ratings [obs]

Sampling procedure

In most developing economies, Global Findex data have traditionally been collected through face-to-face interviews. Surveys are conducted face-to-face in economies where telephone coverage represents less than 80 percent of the population or where in-person surveying is the customary methodology. However, because of ongoing COVID-19 related mobility restrictions, face-to-face interviewing was not possible in some of these economies in 2021. Phone-based surveys were therefore conducted in 67 economies that had been surveyed face-to-face in 2017. These 67 economies were selected for inclusion based on population size, phone penetration rate, COVID-19 infection rates, and the feasibility of executing phone-based methods where Gallup would otherwise conduct face-to-face data collection, while complying with all government-issued guidance throughout the interviewing process. Gallup takes both mobile phone and landline ownership into consideration. According to Gallup World Poll 2019 data, when face-to-face surveys were last carried out in these economies, at least 80 percent of adults in almost all of them reported mobile phone ownership. All samples are probability-based and nationally representative of the resident adult population. Phone surveys were not a viable option in 17 economies that had been part of previous Global Findex surveys, however, because of low mobile phone ownership and surveying restrictions. Data for these economies will be collected in 2022 and released in 2023.

In economies where face-to-face surveys are conducted, the first stage of sampling is the identification of primary sampling units. These units are stratified by population size, geography, or both, and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size; otherwise, simple random sampling is used. Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. To increase the probability of contact and completion, attempts are made at different times of the day and, where possible, on different days. If an interview cannot be obtained at the initial sampled household, a simple substitution method is used. Respondents are randomly selected within the selected households. Each eligible household member is listed, and the hand-held survey device randomly selects the household member to be interviewed. For paper surveys, the Kish grid method is used to select the respondent. In economies where cultural restrictions dictate gender matching, respondents are randomly selected from among all eligible adults of the interviewer's gender.

In traditionally phone-based economies, respondent selection follows the same procedure as in previous years, using random digit dialing or a nationally representative list of phone numbers. In most economies where mobile phone and landline penetration is high, a dual sampling frame is used.

The same respondent selection procedure is applied to the new phone-based economies. Dual frame (landline and mobile phone) random digital dialing is used where landline presence and use are 20 percent or higher based on historical Gallup estimates. Mobile phone random digital dialing is used in economies with limited to no landline presence (less than 20 percent).

For landline respondents in economies where mobile phone or landline penetration is 80 percent or higher, random selection of respondents is achieved by using either the latest birthday or household enumeration method. For mobile phone respondents in these economies or in economies where mobile phone or landline penetration is less than 80 percent, no further selection is performed. At least three attempts are made to reach a person in each household, spread over different days and times of day.

Sample size for China is 3500.

Mode of data collection

Mobile telephone

Research instrument

Questionnaires are available on the website.

Sampling error estimates

Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in Demirgüç-Kunt, Asli, Leora Klapper, Dorothe Singer, Saniya Ansar. 2022. The Global Findex Database 2021: Financial Inclusion, Digital Payments, and Resilience in the Age of COVID-19. Washington, DC: World Bank.

As one of the richest biodiversity countries in the world, China has carried out the work of specimen digitalization for many years. And it has also shared millions of specimens for several times and get good results from data application and international influence in recent years. Now, it continuely makes a big publication of plant specimens this time.

The region of present-day China has historically been the most populous region in the world; however, its population development has fluctuated throughout history. In 2022, China was overtaken as the most populous country in the world, and current projections suggest its population is heading for a rapid decline in the coming decades. Transitions of power lead to mortality The source suggests that conflict, and the diseases brought with it, were the major obstacles to population growth throughout most of the Common Era, particularly during transitions of power between various dynasties and rulers. It estimates that the total population fell by approximately 30 million people during the 14th century due to the impact of Mongol invasions, which inflicted heavy losses on the northern population through conflict, enslavement, food instability, and the introduction of bubonic plague. Between 1850 and 1870, the total population fell once more, by more than 50 million people, through further conflict, famine and disease; the most notable of these was the Taiping Rebellion, although the Miao an Panthay Rebellions, and the Dungan Revolt, also had large death tolls. The third plague pandemic also originated in Yunnan in 1855, which killed approximately two million people in China. 20th and 21st centuries There were additional conflicts at the turn of the 20th century, which had significant geopolitical consequences for China, but did not result in the same high levels of mortality seen previously. It was not until the overlapping Chinese Civil War (1927-1949) and Second World War (1937-1945) where the death tolls reached approximately 10 and 20 million respectively. Additionally, as China attempted to industrialize during the Great Leap Forward (1958-1962), economic and agricultural mismanagement resulted in the deaths of tens of millions (possibly as many as 55 million) in less than four years, during the Great Chinese Famine. This mortality is not observable on the given dataset, due to the rapidity of China's demographic transition over the entire period; this saw improvements in healthcare, sanitation, and infrastructure result in sweeping changes across the population. The early 2020s marked some significant milestones in China's demographics, where it was overtaken by India as the world's most populous country, and its population also went into decline. Current projections suggest that China is heading for a "demographic disaster", as its rapidly aging population is placing significant burdens on China's economy, government, and society. In stark contrast to the restrictive "one-child policy" of the past, the government has introduced a series of pro-fertility incentives for couples to have larger families, although the impact of these policies are yet to materialize. If these current projections come true, then China's population may be around half its current size by the end of the century.

Introduction

Welcome to the Mandarin Chinese General Conversation Speech Dataset — a rich, linguistically diverse corpus purpose-built to accelerate the development of Mandarin speech technologies. This dataset is designed to train and fine-tune ASR systems, spoken language understanding models, and generative voice AI tailored to real-world Mandarin Chinese communication.

Curated by FutureBeeAI, this 30 hours dataset offers unscripted, spontaneous two-speaker conversations across a wide array of real-life topics. It enables researchers, AI developers, and voice-first product teams to build robust, production-grade Mandarin speech models that understand and respond to authentic Chinese accents and dialects.

Speech Data

The dataset comprises 30 hours of high-quality audio, featuring natural, free-flowing dialogue between native speakers of Mandarin Chinese. These sessions range from informal daily talks to deeper, topic-specific discussions, ensuring variability and context richness for diverse use cases.

Topic Diversity

The dataset spans a wide variety of everyday and domain-relevant themes. This topic diversity ensures the resulting models are adaptable to broad speech contexts.

Transcription

Each audio file is paired with a human-verified, verbatim transcription available in JSON format.

These transcriptions are production-ready, enabling seamless integration into ASR model pipelines or conversational AI workflows.

Metadata

The dataset comes with granular metadata for both speakers and recordings:

Such metadata helps developers fine-tune model training and supports use-case-specific filtering or demographic analysis.

Usage and Applications

This dataset is a versatile resource for multiple Mandarin speech and language AI applications:

Abstract copyright UK Data Service and data collection copyright owner. Beginning in January 1999, this project started by gathering basic information on immigration, through-migration and employment patterns in selected European countries (Britain, Germany, France, the Netherlands, Italy, Spain, Hungary, Romania and Russia). Subsequently, exploratory research in Fujian province was carried out, including a survey conducted in Mingxi village, the summarised results of which are included in this data collection. During the second phase of the research from September 1999 until April 2001, the project focused on three countries in Europe (Britain, Hungary and Italy) selected on the basis of the exploratory research of the first phase. Interviews were conducted with persons of Fujianese origin living in these countries, the transcripts of which form the bulk of the data collection. Some interviews were also conducted with persons resident in Germany and the USA. Britain, Hungary and Italy occupy a prominent place on the Fujianese map of Europe. Britain, with the oldest and largest of the Chinese communities, became the destination of choice to many Fujianese in the 1990s. Its close links with other Anglophone countries that are major destinations for Fujianese migrants, such as the US and Australia, also ensured its popularity. Hungary, a gateway into southern and western Europe, occupies a pivotal place in the exploration of eastern Europe by Chinese migrants. Especially in the wake of the fall of the Soviet bloc in 1989-1990. Italy became the main Chinese destination country in southern Europe in the 1980s, also attracting many Fujianese in the 1990s. Its current transition to a much more restrictive 'northern European' immigration regime provides a template for developments elsewhere in what, to Chinese migrants, is the European periphery in the future. Main Topics: Topics covered in the interviews include: personal and family background, migrations within China, time and direction of migration(s) and decision making, development of occupation and/or entrepreneurship after migration, economic situation over time, employment patterns, distribution of family members abroad and family migration strategies, contacts with family members and friends abroad, boundaries of social space and identity, remittances to family at home and evaluation of the impact of migration. Reading notes collected by the researchers are also included in the data collection, which cover relevant documents, newspapers and secondary literature. They form a useful background to the project and provide further information on Fujianese immigration issues. Purposive selection/case studies Face-to-face interview Telephone interview Observation Compilation or synthesis of existing material

China Proportion of People Living Below 50 Percent Of Median Income: % data was reported at 11.600 % in 2021. This records a decrease from the previous number of 11.900 % for 2020. China Proportion of People Living Below 50 Percent Of Median Income: % data is updated yearly, averaging 15.100 % from Dec 1990 (Median) to 2021, with 19 observations. The data reached an all-time high of 19.500 % in 2010 and a record low of 8.900 % in 1990. China Proportion of People Living Below 50 Percent Of Median Income: % data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s China – Table CN.World Bank.WDI: Social: Poverty and Inequality. The percentage of people in the population who live in households whose per capita income or consumption is below half of the median income or consumption per capita. The median is measured at 2017 Purchasing Power Parity (PPP) using the Poverty and Inequality Platform (http://www.pip.worldbank.org). For some countries, medians are not reported due to grouped and/or confidential data. The reference year is the year in which the underlying household survey data was collected. In cases for which the data collection period bridged two calendar years, the first year in which data were collected is reported.;World Bank, Poverty and Inequality Platform. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are mostly from the Luxembourg Income Study database. For more information and methodology, please see http://pip.worldbank.org.;;The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).

Exports in China increased to 325.18 USD Billion in June from 316.10 USD Billion in May of 2025. This dataset provides - China Exports - actual values, historical data, forecast, chart, statistics, economic calendar and news.

China Population: Average Household Size data was reported at 2.800 Person in 2023. This records an increase from the previous number of 2.760 Person for 2022. China Population: Average Household Size data is updated yearly, averaging 3.150 Person from Dec 1982 (Median) to 2023, with 31 observations. The data reached an all-time high of 4.430 Person in 1982 and a record low of 2.620 Person in 2020. China Population: Average Household Size data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GA: Population: No of Person per Household.

China Population: Prefecture Level City data was reported at 1,291,941.900 Person th in 2015. This records an increase from the previous number of 1,289,538.000 Person th for 2014. China Population: Prefecture Level City data is updated yearly, averaging 1,194,579.100 Person th from Dec 1996 (Median) to 2015, with 20 observations. The data reached an all-time high of 1,291,941.900 Person th in 2015 and a record low of 897,719.200 Person th in 1997. China Population: Prefecture Level City data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GE: Population: Prefecture Level City.

This series of 11 datasets is drawn from Rhoads, Edward J. M. Stepping Forth into the World: The Chinese Educational Mission to the United States, 1872-81. Hong Kong University Press, 2011. They document the 120 young Chinese who participated in the pioneering Chinese Educational Mission (CEM) in the United States (1872-1881). The first 8 files are drawn directly from the tables in Rhoads: Table 2.1 CEM students, by detachment (p.14-17) Table 5.1. Initial host family assignments (p.51-54) Table 7.1. CEM students in middle schools (by state and locality) (p. 90-94) Table 7.2 CEM students in public high schools (by state and locality) (p.96-99) Table 7.3 CEM students in private academies (by state and locality) (p.99-100) Table 8.1 CEM students in colleges (by academic year of enrollment) (p.116-118) Table 9.1 Deaths, dismissals, and withdrawals from the CEM (by date) (p.136) Table 9.2 CEM students in the June 1880 census (p.138-142) Based on these tables, I created three synthetic datasets which can be used for statistical and network analyses: cem_attributes: students' vital attributes, including their multiple names and transliteration, date and place of birth, and other attribute data (one row for each individual). cem_host: students' host families in the United States cem_education: students' educational curricula Each file contains two tabs, one for the data (data), one for the description of variables (key). Grey columns refer to the unstructured information given in the original source.

In the past decades, numerous clinical researches have been conducted to illuminate the effects of traditional Chinese medicine for better inheritance and promotion of it, which are mostly clinical trials designed from the doctor's point of view. This large-scale data mining study was conducted from real-world point of view in up to 10 years' big data sets of Traditional Chinese Medicine (TCM) in China, including both medical visits to hospital and cyberspace and contemporaneous social survey data. Finally, some important and interesting findings appear: (1) More Criticisms vs. More Visits. The intensity of criticism increased by 2.33 times over the past 10 years, while the actual number of visits increased by 2.41 times. (2) The people of younger age, highly educated and from economically developed areas have become the primary population for utilizing TCM, which is contrary to common opinions on the characteristics of TCM users. The discovery of this phenomenon indicates that TCM deserves further study on how it treats illness and maintains health.

Chinese Domestic Databases Market Outlook

The Chinese Domestic Databases market size is set for robust growth, projected to grow from USD 2 billion in 2023 to USD 6.5 billion by 2032, reflecting an impressive CAGR of 13.5%. This growth is driven by the increasing demand for data sovereignty, technological advancements, and regulatory support from the Chinese government. The market is primed for expansion, propelled by factors such as the burgeoning digital economy, increased cloud adoption, and the strategic focus on indigenous technological advancements.

One of the primary growth factors for the Chinese Domestic Databases market is the increasing emphasis on data sovereignty and security. With the Chinese government imposing stringent regulations on data storage and management, domestic companies are compelled to utilize local databases to ensure compliance. This has created a favorable environment for the growth of domestic database providers who are tailored to meet these unique requirements. Additionally, the rise in cyber threats has further driven the need for secure and reliable database solutions, contributing significantly to market growth.

Technological advancements and innovation within the database industry are also pivotal growth drivers. The rapid development of Artificial Intelligence (AI) and Machine Learning (ML) technologies has allowed for more efficient and intelligent database management systems. Innovations in data handling, processing speed, and storage capabilities provide a significant competitive edge to domestic databases over international counterparts. Furthermore, the integration of AI and ML with databases enables advanced analytics and insights, helping businesses make more informed decisions, thus driving the market forward.

The digital transformation across various sectors in China has also fueled the demand for robust database solutions. Sectors such as finance, healthcare, and retail are increasingly relying on digital platforms for their operations, necessitating sophisticated and reliable databases to manage vast amounts of data. The push towards a digital economy by the Chinese government, coupled with initiatives like the "New Infrastructure" program, which focuses on the development of digital infrastructure including big data centers, has significantly boosted the demand for domestic databases.

Regionally, East China dominates the market due to the presence of major economic hubs like Shanghai and Hangzhou, which are home to numerous technology companies and data centers. North China, with Beijing as its central hub, also plays a significant role in the market due to the concentration of governmental bodies and financial institutions that demand secure and compliant database solutions. South China, particularly Shenzhen, is another critical region, given its prominence as a technology and innovation hub. Central China and other regions are gradually catching up as investments in digital infrastructure spread across the country. Overall, the regional dynamics of the Chinese Domestic Databases market present a diverse and rapidly evolving landscape.

Type Analysis

The Chinese Domestic Databases market comprises various types, including Relational Databases, NoSQL Databases, NewSQL Databases, and others. Relational Databases have been the cornerstone of the database industry for decades, offering structured data storage and easy retrieval through SQL queries. Despite their age, they remain highly relevant due to their robustness, reliability, and the vast ecosystems that have developed around them. In China, relational databases continue to be widely adopted across various industries, particularly in sectors like finance and government, where data accuracy and consistency are paramount.

NoSQL Databases have gained significant traction in recent years due to their flexibility, scalability, and ability to handle unstructured data. Unlike traditional relational databases, NoSQL databases can seamlessly manage large volumes of diverse data types, making them ideal for applications in big data and real-time web applications. In China, the adoption of NoSQL databases is particularly prominent in the e-commerce and social media sectors, where the ability to scale out horizontally and handle high-velocity data is crucial.

NewSQL Databases represent a hybrid approach that combines the best features of traditional relational databases and NoSQL databases. They offer the scalability and flexibility of NoSQL while maintaining the ACID (Atomicity, Consistency, Isolation, Durability) prope

The Gross Domestic Product (GDP) in China was worth 18743.80 billion US dollars in 2024, according to official data from the World Bank. The GDP value of China represents 17.65 percent of the world economy. This dataset provides - China GDP - actual values, historical data, forecast, chart, statistics, economic calendar and news.

China % of Population with Access to Water: City data was reported at 99.433 % in 2023. This records an increase from the previous number of 99.387 % for 2022. China % of Population with Access to Water: City data is updated yearly, averaging 96.120 % from Dec 1985 (Median) to 2023, with 31 observations. The data reached an all-time high of 99.433 % in 2023 and a record low of 63.900 % in 2000. China % of Population with Access to Water: City data remains active status in CEIC and is reported by Ministry of Housing and Urban-Rural Development. The data is categorized under China Premium Database’s Utility Sector – Table CN.RCA: Percentage of Population with Access to Water.

COVID-19 is a global pandemic. In response to this unprecedented crisis, Chinese government formulated a series of policies. This research is dedicated to exploring the dynamic evolution of China’s policy mix in response to COVID-19 in different crisis response stages from a network perspective. First, a three-dimensional analysis framework of “policy subject-policy target-policy instrument” was developed. Then, based on the data sets collected by textual analysis, the dynamic evolution of policy subject, policy target, policy instrument in China’s policy mix in response to COVID-19 was discussed by using the method of SNA. This study concluded that the core policy subject, policy instrument, and policy target of China’s response to COVID-19 changed with time. National Health Commission (NHC), Ministry of Finance (MOF), Ministry of Transport (MOT) and Ministry of Human Resources and Social Security (MHRSS) have important influences in the network of policy subjects. Other subjects are more at the edge of the network, and there are few joint issuances among policy subjects. The study also found that the core policy target was adjusted over time, with phased dynamic characteristics. At the initial stage of China’s response to COVID-19, “reduce infection and mortality” and “steadily carry out economic and social work” were the core policy targets. With the COVID-19 under control, “enterprise development and work resumption” becomes a new core policy target. In addition, this study also revealed the dynamic evolution and unbalanced use of China’s policy instruments in response to COVID-19 in different stages. The combination of policy instruments is mainly composed of “mandatory administration instruments” and “economic incentive instruments”, and supplemented by “health promotion instruments” and “voluntary plan instruments”. These findings may enrich the literature on COVID-19 policy to help researchers understand the dynamics of policy from a network perspective. Moreover, these findings may provide several valuable implications for policymakers and other countries to formulate more effective policies for epidemic response.

China Total Employment data was reported at 733,510.000 Person th in 2022. This records a decrease from the previous number of 746,520.000 Person th for 2021. China Total Employment data is updated yearly, averaging 746,470.000 Person th from Dec 1990 (Median) to 2022, with 33 observations. The data reached an all-time high of 763,490.000 Person th in 2014 and a record low of 647,490.000 Person th in 1990. China Total Employment data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s China – Table CN.OECD.MSTI: Population, Labour Force and Employment: Non OECD Member: Annual.

The national breakdown by source of funds does not fully match with the classification defined in the Frascati Manual. The R&D financed by the government, business enterprises, and by the rest of the world can be retrieved but part of the expenditure has no specific source of financing, i.e. self-raised funding (in particular for independent research institutions), the funds from the higher education sector and left-over government grants from previous years.

The government and higher education sectors cover all fields of NSE and SSH while the business enterprise sector only covers the fields of NSE. There are only few organisations in the private non-profit sector, hence no R&D survey has been carried out in this sector and the data are not available.

From 2009, researcher data are collected according to the Frascati Manual definition of researcher. Beforehand, this was only the case for independent research institutions, while for the other sectors data were collected according to the UNESCO concept of “scientist and engineer”.

In 2009, the survey coverage in the business and the government sectors has been expanded.

Before 2000, all of the personnel data and 95% of the expenditure data in the business enterprise sector are for large and medium-sized enterprises only. Since 2000 however, the survey covers almost all industries and all enterprises above a certain threshold. In 2000 and 2004, a census of all enterprises was held, while in the intermediate years data for small enterprises are estimated.

Due to the reform of the S&T system some government institutions have become enterprises, and their R&D data have been reflected in the Business Enterprise sector since 2000.

Unemployment Rate in China increased to 5.20 percent in July from 5 percent in June of 2025. This dataset provides - China Unemployment Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.