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Context
This list ranks the 40 cities in the Blue Earth County, MN by Non-Hispanic Asian population, as estimated by the United States Census Bureau. It also highlights population changes in each cities over the past five years.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates, including:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the population of Globe by race. It includes the population of Globe across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Globe across relevant racial categories.
Key observations
The percent distribution of Globe population by race (across all racial categories recognized by the U.S. Census Bureau): 58.09% are white, 2.70% are Black or African American, 5.26% are American Indian and Alaska Native, 2.92% are Asian, 0.12% are Native Hawaiian and other Pacific Islander, 11.37% are some other race and 19.54% are multiracial.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Racial categories include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Globe Population by Race & Ethnicity. You can refer the same here
Corn (Zea mays) is one of the most widely grown crops throughout the world. However, many corn fields develop pest problems such as corn borers every year that seriously affect its yield and quality. Corn's response to initial insect damage involves a variety of changes to the levels of defensive enzymes, toxins, and communicative volatiles. Such a dramatic change secondary metabolism necessitates the regulation of gene expression at the transcript level. This Data In Brief paper summarizes the datasets of the transcriptome of corn plants in response to corn stalk borers (Ostrinia furnacalis) and/or methyl jasmonate (MeJA). Altogether, 39, 636 genes were found to be differentially expressed. The sequencing data are available in the NCBI SRA database under accession number SRS965087. This dataset will provide more scientific and valuable information for future work such as the study of the functions of important genes or proteins and develop new insect-resistant maize varieties. Includes supplementary tables and data in fasta and GTF format. Resources in this dataset:Resource Title: Datasets for transcriptomic analyses of maize leaves in response to Asian corn borer feeding and/or jasmonic acid. File Name: Web Page, url: https://www.sciencedirect.com/science/article/pii/S2352340916301792 Data in Brief Article including supplemental data in fasta and GTF format.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Central Asian Food Scenes Dataset
In this work, we propose the first Central Asia Food Scenes Dataset that contains 21,306 images with 69,856 instances across 239 food classes. To make sure that the dataset contains various food items, we took as a benchmark the ontology of Global Individual Food Tool developed by Food and Agriculture Organization (FAO) together with the World Health Organization (WHO) [1]. The dataset contains food items across 18 coarse classes: 🍅 Vegetables •… See the full description on the dataset page: https://huggingface.co/datasets/issai/Central_Asian_Food_Scenes_Dataset.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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We assess the potential impact of international migration on population ageing in Asian countries by estimating replacement migration for the period 2022-2050.
This open data deposit contains the code (R-scripts) and the datasets (csv-files) for the replacement migration scenarios and a zero-migration scenario:
Countries included in the analysis: Armenia, China, Georgia, Hong Kong, Japan, Macao, North Korea, Singapore, South Korea, Taiwan, Thailand.
Please note that for Armenia and Hong Kong (2023) and Georgia (2024) later baseline years are applied due to the UN country-specific assumptions on post-Covid-19 mortality.
For detailed information about the scenarios and parameters:
Dörflinger, M., Potancokova, M., Marois, G. (2024): The potential impact of international migration on prospective population ageing in Asian countries. Asian Population Studies. https://doi.org/10.1080/17441730.2024.2436201
All underlying data (UN World Population Prospects 2022) are openly available at:
https://population.un.org/wpp/Download/Archive
Code
1_Data.R:
2_Scenarios.R:
3_Robustness_checks.R:
Program version used: RStudio "Chocolate Cosmos" (e4392fc9, 2024-06-05). Files may not be compatible with other versions.
Datasets
The datasets contain the key information on population size, the relevant indicators (OADR, POADR, WA, PWA) and replacement migration volumes and rates by country and year. Please see readme_datasets.txt for detailed information.
Acknowledgements
Part of the research was developed in the Young Scientists Summer Program at the International Institute for Applied Systems Analysis, Laxenburg (Austria) with financial support from the German National Member Organization.
The number of smartphone users in Southeast Asia was forecast to continuously increase between 2024 and 2029 by in total 105.9 million users (+23.9 percent). After the nineteenth consecutive increasing year, the smartphone user base is estimated to reach 548.92 million users and therefore a new peak in 2029. Notably, the number of smartphone users of was continuously increasing over the past years.Smartphone users here are limited to internet users of any age using a smartphone. The shown figures have been derived from survey data that has been processed to estimate missing demographics.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the number of smartphone users in countries like Western Asia and Southern Asia.
Open Database License (ODbL) v1.0https://www.opendatacommons.org/licenses/odbl/1.0/
License information was derived automatically
By Health [source]
This dataset contains data on the modes of transportation used by California residents aged 16 and older to commute to work. It includes data from the U.S. Census Bureau, Decennial Census and American Community Survey, covering all regions, counties, cities/towns, and census tracts in California. With each region showing detailed information regarding how its population travels to work (modes of transportation used), this dataset provides vital insight into the development of transport infrastructure in California over the past decade.
Unlike other states where private cars constitute an overwhelming majority of daily commuters (over 79% nationwide according to a 2015 survey), Californians have built up varied commuting habits – bicycles are commonly reported 5%, public transit stands at 15%, walking alone 4%, and carpooling is at 11%. Commuting plays a significant role on overall health—active modes such as biking or walking lead to healthier lifestyles that lower heart disease risks, obesity rates, diabetes prevalence; passengers on public transport also have a lower chance of injury in collisions compared with pedestrians or cyclists.
The consequences of inadequate planning for human mobility extend beyond physical health – it can also cause huge disparities between different racial groups such as Native Americans who experience four times higher death rate from pedestrian-car collisions than Whites or Asians; African-Americans and Latinos suffer twice as much as White people do when driving privately in their own cars due to air pollution hazards or lack thereof access to reliable public transportation system that could provide them with healthier alternatives. It is our hope that policymakers will use this dataset prominently stated by the Healthy Communities Data & Indicators Project - part of the Office Of Health Equity - while ensuring every resident’s right for safe mobility no matter their background!
For more datasets, click here.
- 🚨 Your notebook can be here! 🚨!
This dataset contains information on the percent of Californians aged 16 and older who use different modes of transportation to get to work. The data is collected from the U.S. Census Bureau and American Community Survey, and covers all counties, cities/towns and census tracts in California.
In this dataset, there are several columns of data such as mode (mode of transport), race_eth_name (name of the race/ethnicity), region_code (code for the region) and pop_total (total population). This makes it possible to look at relations between transportation choice and demographic factors like gender or ethnicity, or comparison between regions within California regarding commuting habits.
The purpose of this dataset is to provide information on how Californians travel to their jobs with respect to both geographical area as well as demographic characteristics. It allows studies into why certain areas might have higher usage rates for specific types of transport compared with others, how gender affects travel decisions, or which regions have access issues with public transit compared with driving for example.
To use this dataset you should start by familiarizing yourself with descriptive statistics such as percentages, hazard ratios etc., in order to understand each variable's contribution towards commuting trends more effectively. It might also help if you filter data by geographic area or personal characteristics first before performing more detailed analysis for more insightful results that can be used in policy-making when planning effective infrastructure investments related to transportation options over time or among differing populations within California state population levels noted here year-by-year across a decade period provided here
- Creating interactive maps to visualize and compare the transportation methods of different race/ethnicities in California.
- Analyzing the transportation trends across regions, counties, cities/towns, and census tracts to forecast and plan for infrastructure investments.
- Comparing the risk ratio of pedestrian-car fatalities across different ethnic groups in order to address safety issues within underserved populations
If you use this dataset in your research, please credit the original authors. Data Source
**License: [Open Database License (ODbL) v1.0](https://opendatacommons.org/lice...
Success.ai’s Import Export Data for Import, Export & Trade Professionals in Asia delivers a comprehensive dataset tailored for businesses aiming to connect with key players in Asia’s dynamic trade industry. Covering professionals involved in import/export operations, international logistics, and supply chain management, this dataset provides verified contact details, firmographic insights, and actionable professional data.
With access to over 700 million verified global profiles and 70 million business datasets, Success.ai ensures your outreach, market research, and trade strategies are powered by accurate, continuously updated, and AI-validated data. Supported by our Best Price Guarantee, this solution is essential for navigating the complexities of global trade in Asia.
Why Choose Success.ai’s Import Export Data?
Verified Contact Data for Effective Engagement
Comprehensive Coverage of Asian Trade Markets
Continuously Updated Datasets
Ethical and Compliant
Data Highlights:
Key Features of the Dataset:
Professional Profiles in Import/Export and Logistics
Firmographic and Geographic Insights
Advanced Filters for Precision Campaigns
AI-Driven Enrichment
Strategic Use Cases:
Sales and Business Development
Market Research and Competitive Analysis
Partnership Development and Trade Collaboration
Recruitment and Talent Acquisition
Why Choose Success.ai?
Best Price Guarantee
Seamless Integration
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Three-dimensional (3D) urban structures play a critical role in informing climate mitigation strategies aimed at the built environment and facilitating sustainable urban development. Regrettably, there exists a significant gap in detailed and consistent data on 3D building space structures with global coverage due to the challenges inherent in the data collection and model calibration processes. In this study, we constructed a global urban structure dataset (GUS-3D), including building volume, height, and footprint information, at a 500 m spatial resolution using extensive satellite observation products and numerous reference building samples. Our analysis indicated that the total volume of buildings worldwide in 2015 exceeded 1 × 1012 m3. Over the 1985 to 2015 period, we observed a slight increase in the magnitude of 3D building volume growth (i.e., it increased from 166.02 km3 during the 1985–2000 period to 175.08 km3 during the 2000–2015 period), while the expansion magnitudes of the two-dimensional (2D) building footprint (22.51 × 103 km2 vs. 13.29 × 103 km2) and urban extent (157 × 103 km2 vs. 133.8 × 103 km2) notably decreased. This trend highlights the significant increase in intensive vertical utilization of urban land. Furthermore, we identified significant heterogeneity in building space provision and inequality across cities worldwide. This inequality is particularly pronounced in many populous Asian cities, which has been overlooked in previous studies on economic inequality. The GUS-3D dataset shows great potential to deepen our understanding of the urban environment and creates new horizons for numerous 3D urban studies.
The third wave of the Asian Barometer survey (ABS) conducted in 2010 and the database contains nine countries and regions in East Asia - the Philippines, Taiwan, Thailand, Mongolia, Singapore, Vietnam, Indonesia, Malaysia and South Korea. The ABS is an applied research program on public opinion on political values, democracy, and governance around the region. The regional network encompasses research teams from 13 East Asian political systems and 5 South Asian countries. Together, this regional survey network covers virtually all major political systems in the region, systems that have experienced different trajectories of regime evolution and are currently at different stages of political transition.
The mission and task of each national research team are to administer survey instruments to compile the required micro-level data under a common research framework and research methodology to ensure that the data is reliable and comparable on the issues of citizens' attitudes and values toward politics, power, reform, and democracy in Asia.
The Asian Barometer Survey is headquartered in Taipei and co-hosted by the Institute of Political Science, Academia Sinica and The Institute for the Advanced Studies of Humanities and Social Sciences, National Taiwan University.
13 East Asian political systems: Japan, Mongolia, South Koreas, Taiwan, Hong Kong, China, the Philippines, Thailand, Vietnam, Cambodia, Singapore, Indonesia, and Malaysia; 5 South Asian countries: India, Pakistan, Bangladesh, Sri Lanka, and Nepal
-Individuals
Sample survey data [ssd]
Compared with surveys carried out within a single nation, cross-nation survey involves an extra layer of difficulty and complexity in terms of survey management, research design, and database modeling for the purpose of data preservation and easy analysis. To facilitate the progress of the Asian Barometer Surveys, the survey methodology and database subproject is formed as an important protocol specifically aiming at overseeing and coordinating survey research designs, database modeling, and data release.
As a network of Global Barometer Surveys, Asian Barometer Survey requires all country teams to comply with the research protocols which Global Barometer network has developed, tested, and proved practical methods for conducting comparative survey research on public attitudes.
Research Protocols:
A model Asian Barometer Survey has a sample size of 1,200 respondents, which allows a minimum confidence interval of plus or minus 3 percent at 95 percent probability.
Face-to-face [f2f]
A standard questionnaire instrument containing a core module of identical or functionally equivalent questions. Wherever possible, theoretical concepts are measured with multiple items in order to enable testing for construct validity. The wording of items is determined by balancing various criteria, including: the research themes emphasized in the survey, the comprehensibility of the item to lay respondents, and the proven effectiveness of the item when tested in previous surveys.
Survey Topics: 1.Economic Evaluations: What is the economic condition of the nation and your family: now, over the last five years, and in the next five years? 2.Trust in institutions: How trustworthy are public institutions, including government branches, the media, the military, and NGOs. 3.Social Capital: Membership in private and public groups, the frequency and degree of group participation, trust in others, and influence of guanxi. 4.Political Participatio: Voting in elections, national and local, country-specific voting patterns, and active participation in the political process as well as demonstrations and strikes. Contact with government and elected officials, political organizations, NGOs and media. 5.Electoral Mobilization: Personal connections with officials, candidates, and political parties; influence on voter choice. 6.Psychological Involvement and Partisanship: Interest in political news coverage, impact of government policies on daily life, and party allegiance. 7.Traditionalism: Importance of consensus and family, role of the elderly, face, and woman in theworkplace. 8.Democratic Legitimacy and Preference for Democracy: Democratic ranking of present and previous regime, and expected ranking in the next five years; satisfaction with how democracy works, suitability of democracy; comparisons between current and previous regimes, especially corruption; democracy and economic development, political competition, national unity, social problems, military government, and technocracy. 9.Efficacy, Citizen Empowerment, System Responsiveness: Accessibility of political system: does a political elite prevent access and reduce the ability of people to influence the government. 10.Democratic vs. Authoritarian Values: Level of education and political equality, government leadership and superiority, separation of executive and judiciary. 11.Cleavage: Ownership of state-owned enterprises, national authority over local decisions, cultural insulation, community and the individual. 12.Belief in Procedural Norms of Democracy: Respect of procedures by political leaders: compromise, tolerance of opposing and minority views. 13.Social-Economic Background Variables: Gender, age, marital status, education level, years of formal education, religion and religiosity, household, income, language and ethnicity. 14.Interview Record: Gender, age, class, and language of the interviewer, people present at the interview; did the respondent: refuse, display impatience, and cooperate; the language or dialect spoken in interview, and was an interpreter present.
Quality checks are enforced at every stage of data conversion to ensure that information from paper returns is edited, coded, and entered correctly for purposes of computer analysis. Machine readable data are generated by trained data entry operators and a minimum of 20 percent of the data is entered twice by independent teams for purposes of cross-checking. Data cleaning involves checks for illegal and logically inconsistent values.
Attribution-NonCommercial 4.0 (CC BY-NC 4.0)https://creativecommons.org/licenses/by-nc/4.0/
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The dataset contains an up-to-date list of species of genera Semagystia Schoorl and Dyspessa Hubner (Lepidoptera, Cossidae) in Asian part of Russia and Central Asia. The dataset is intended to provide all interested users of GBIF with information on the distribution of the genera within the Asian part of Russia and Central Asia, identifying the locations of storage of material in world collections and other types of analyzes (taxonomic, phenological, etc.) using the available datasets in GBIF.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset provides values for GDP PER CAPITA reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset tracks annual asian student percentage from 1989 to 2023 for Starbuck - An Ib World School vs. Wisconsin and Racine Unified School District
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset tracks annual asian student percentage from 2011 to 2023 for Global Technology Preparatory vs. New York and New York City Geographic District # 4 School District
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset tracks annual asian student percentage from 1992 to 2023 for Lake Arrowhead Elementary School vs. California and Rim Of The World Unified School District
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset tracks annual asian student percentage from 1996 to 2023 for Brooks Global Elementary School vs. North Carolina and Guilford County Schools School District
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Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
This list ranks the 40 cities in the Blue Earth County, MN by Non-Hispanic Asian population, as estimated by the United States Census Bureau. It also highlights population changes in each cities over the past five years.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates, including:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.