recruit-jp/japanese-image-classification-evaluation-dataset

  Overview

Developed by: Recruit Co., Ltd. Dataset type: Image Classification Language(s): Japanese LICENSE: CC-BY-4.0

More details are described in our tech blog post.

日本語CLIP学習済みモデルとその評価用データセットの公開

  Dataset Details

This dataset is comprised of four image classification tasks related to concepts and things unique to Japan. Specifically, is consists of the following tasks.

jafood101: Image… See the full description on the dataset page: https://huggingface.co/datasets/recruit-jp/japanese-image-classification-evaluation-dataset.

• The current US Census Bureau world population estimate in June 2019 shows that the current global population is 7,577,130,400 people on Earth, which far exceeds the world population of 7.2 billion in 2015. Our estimate based on UN data shows the world's population surpassing 7.7 billion.
• China is the most populous country in the world with a population exceeding 1.4 billion. It is one of just two countries with a population of more than 1 billion, with India being the second. As of 2018, India has a population of over 1.355 billion people, and its population growth is expected to continue through at least 2050. By the year 2030, India is expected to become the most populous country in the world. This is because India’s population will grow, while China is projected to see a loss in population.
• The following 11 countries that are the most populous in the world each have populations exceeding 100 million. These include the United States, Indonesia, Brazil, Pakistan, Nigeria, Bangladesh, Russia, Mexico, Japan, Ethiopia, and the Philippines. Of these nations, all are expected to continue to grow except Russia and Japan, which will see their populations drop by 2030 before falling again significantly by 2050.
• Many other nations have populations of at least one million, while there are also countries that have just thousands. The smallest population in the world can be found in Vatican City, where only 801 people reside.
• In 2018, the world’s population growth rate was 1.12%. Every five years since the 1970s, the population growth rate has continued to fall. The world’s population is expected to continue to grow larger but at a much slower pace. By 2030, the population will exceed 8 billion. In 2040, this number will grow to more than 9 billion. In 2055, the number will rise to over 10 billion, and another billion people won’t be added until near the end of the century. The current annual population growth estimates from the United Nations are in the millions - estimating that over 80 million new lives are added yearly.
• This population growth will be significantly impacted by nine specific countries which are situated to contribute to the population growth more quickly than other nations. These nations include the Democratic Republic of the Congo, Ethiopia, India, Indonesia, Nigeria, Pakistan, Uganda, the United Republic of Tanzania, and the United States of America. Particularly of interest, India is on track to overtake China's position as the most populous country by 2030. Additionally, multiple nations within Africa are expected to double their populations before fertility rates begin to slow entirely.

Content

• In this Dataset, we have Historical Population data for every Country/Territory in the world by different parameters like Area Size of the Country/Territory, Name of the Continent, Name of the Capital, Density, Population Growth Rate, Ranking based on Population, World Population Percentage, etc. >Dataset Glossary (Column-Wise):
• Rank: Rank by Population.
• CCA3: 3 Digit Country/Territories Code.
• Country/Territories: Name of the Country/Territories.
• Capital: Name of the Capital.
• Continent: Name of the Continent.
• 2022 Population: Population of the Country/Territories in the year 2022.
• 2020 Population: Population of the Country/Territories in the year 2020.
• 2015 Population: Population of the Country/Territories in the year 2015.
• 2010 Population: Population of the Country/Territories in the year 2010.
• 2000 Population: Population of the Country/Territories in the year 2000.
• 1990 Population: Population of the Country/Territories in the year 1990.
• 1980 Population: Population of the Country/Territories in the year 1980.
• 1970 Population: Population of the Country/Territories in the year 1970.
• Area (km²): Area size of the Country/Territories in square kilometers.
• Density (per km²): Population Density per square kilometer.
• Growth Rate: Population Growth Rate by Country/Territories.
• World Population Percentage: The population percentage by each Country/Territories.

Project Tycho datasets contain case counts for reported disease conditions for countries around the world. The Project Tycho data curation team extracts these case counts from various reputable sources, typically from national or international health authorities, such as the US Centers for Disease Control or the World Health Organization. These original data sources include both open- and restricted-access sources. For restricted-access sources, the Project Tycho team has obtained permission for redistribution from data contributors. All datasets contain case count data that are identical to counts published in the original source and no counts have been modified in any way by the Project Tycho team. The Project Tycho team has pre-processed datasets by adding new variables, such as standard disease and location identifiers, that improve data interpretability. We also formatted the data into a standard data format.

Each Project Tycho dataset contains case counts for a specific condition (e.g. measles) and for a specific country (e.g. The United States). Case counts are reported per time interval. In addition to case counts, datasets include information about these counts (attributes), such as the location, age group, subpopulation, diagnostic certainty, place of acquisition, and the source from which we extracted case counts. One dataset can include many series of case count time intervals, such as "US measles cases as reported by CDC", or "US measles cases reported by WHO", or "US measles cases that originated abroad", etc.

Depending on the intended use of a dataset, we recommend a few data processing steps before analysis: - Analyze missing data: Project Tycho datasets do not include time intervals for which no case count was reported (for many datasets, time series of case counts are incomplete, due to incompleteness of source documents) and users will need to add time intervals for which no count value is available. Project Tycho datasets do include time intervals for which a case count value of zero was reported. - Separate cumulative from non-cumulative time interval series. Case count time series in Project Tycho datasets can be "cumulative" or "fixed-intervals". Cumulative case count time series consist of overlapping case count intervals starting on the same date, but ending on different dates. For example, each interval in a cumulative count time series can start on January 1st, but end on January 7th, 14th, 21st, etc. It is common practice among public health agencies to report cases for cumulative time intervals. Case count series with fixed time intervals consist of mutually exclusive time intervals that all start and end on different dates and all have identical length (day, week, month, year). Given the different nature of these two types of case count data, we indicated this with an attribute for each count value, named "PartOfCumulativeCountSeries".

This report surveys the status of NO/sub x/ control for stationary sources in Japan and analyzes applicability of the technology in the US. The principal control methods used in Japan are combustion modification and catalytic reduction using ammonia as the reducing agent. Noncatalytic reduction with ammonia is used to a limited degree. Wet scrubbing methods have been tested but are so unpromising that the development work has practically stopped. The combustion modification developments are applicable in this country but may not be any more effective than methods already under development in the US. Catalytic reduction is fully applicable for oil firing but for coal-fired boilers much more development work is needed to answer the several remaining questions. The needed research is presented in some detail. 16 figures.

Content

More details about each file are in the individual file descriptions.

Context

This is a dataset from the Federal Reserve hosted by the Federal Reserve Economic Database (FRED). FRED has a data platform found here and they update their information according to the frequency that the data updates. Explore the Federal Reserve using Kaggle and all of the data sources available through the Federal Reserve organization page!

• Update Frequency: This dataset is updated daily.

Acknowledgements

This dataset is maintained using FRED's API and Kaggle's API.

Cover photo by Jonny McNee on Unsplash
Unsplash Images are distributed under a unique Unsplash License.

Images trained for my phantom diffusion s2 series. Since they are all AI generated images that are public domain under the US law, I claim it is legal to redistribute them as public domain. However, they might have copyright in your/their original country. Still, many countries including Japan allow us to use them for training an AI under their copyrights law, and because all the artists here are from Japan, I assume it should be allowed to reuse it for training globally.

Dataset Card for ValueConsistency

This is the ValueConsistency data set as introduced in the paper "Are Large Language Models Consistent over Value-laden Questions?".

  Dataset Details







  Dataset Description

ValueConsistency is a dataset of both controversial and uncontroversial questions in English, Chinese, German, and Japanese for topics from the U.S., China, Germany, and Japan. It was generated via prompting by GPT-4 and validated manually. You… See the full description on the dataset page: https://huggingface.co/datasets/jlcmoore/ValueConsistency.

This Gallup poll seeks to collect the opinions of Canadians on several issues of importance to the country as a whole. Included in this survey are discussions on religion, and several questions on foreign trade, including opinion and awareness questions. The specific countries discussed with respect to foreign trade and goods were Germany, Japan, France and Italy. Respondents were also asked questions so that they could be grouped according to geographic, demographic, and social variables. Topics of interest include: American investment in Canada; Canada supporting distressed countries; Canadian businesses; car ownership; Catholic principles which are hard to accept; church attendance; diseases which are most often thought about; diseases which kill the most people; federal elections; buying German goods; the government's overall performance; income tax levels; buying Italian goods; buying Japanese goods; purchasing and opinions of foreign goods; recognition of China's communist government; preferred political parties; Protestant principles which are hard to accept; provincial elections; union membership; voting behaviour; whether women are better looking now than in the past; and whether women should be able to work in the Ministry. Basic demographics variables are also included.

Japan JP: Foreign Direct Investment Income: Inward: USD: Total: America data was reported at 14.867 USD bn in 2023. This records an increase from the previous number of 11.519 USD bn for 2022. Japan JP: Foreign Direct Investment Income: Inward: USD: Total: America data is updated yearly, averaging 11.691 USD bn from Dec 2014 (Median) to 2023, with 10 observations. The data reached an all-time high of 14.867 USD bn in 2023 and a record low of 8.926 USD bn in 2015. Japan JP: Foreign Direct Investment Income: Inward: USD: Total: America 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 Japan – Table JP.OECD.FDI: Foreign Direct Investment Income: USD: by Region and Country: OECD Member: Annual. Reverse investment: Netting of reverse investment in equity (when a direct investment enterprise acquires less than 10% equity ownership in its parent) and reverse investment in debt (when a direct investment enterprise extends a loan to its parent) is applied in the recording of total inward and outward FDI transactions and positions. Treatment of debt FDI transactions and positions between fellow enterprises: directional basis according to the residency of the direct investor. FDI financial flows, income flows and positions include, if they exist, resident Special Purpose Entities (SPEs) which cannot be identified separately. Valuation method used for listed inward and outward equity positions: Own funds at book value, Accumulation of FDI equity flows. Valuation method used for unlisted inward and outward equity positions: Own funds at book value, Accumulation of FDI equity flows. Valuation method used for inward and outward debt positions: Nominal value .; FDI statistics are available by geographic allocation, vis-à-vis single partner countries worldwide and geographical and economic zones aggregates. Partner country allocation can be subject to confidentiality restrictions. Geographic allocation of inward and outward FDI transactions and positions is according to the immediate counterparty. Inward FDI positions according to the ultimate counterparty (the ultimate investing country) are also available and publishable. In the dataset 'FDI statistics by parner country and by industry - Summary', inward FDI positions are showed according to the UIC. Intercompany debt between related financial intermediaries, including permanent debt, are excluded from FDI transactions and positions. Direct investment relationships are identified according to the criteria of the Framework for Direct Investment Relationships (FDIR) method. Debt between fellow enterprises are completely covered . Collective investment institutions are covered as direct investment enterprises. Non-profit institutions serving households are covered as direct investors. FDI statistics are available by industry sectors according to ISIC4 classification. Industry sector allocation can be subject to confidentiality restrictions. Inward FDI transactions and positions are allocated to the activity of the resident direct investment enterprise. Outward FDI transactions are allocated according to the activity of the non resident direct investment enterprise. Statistical unit: Enterprise.

Japan JP: Foreign Direct Investment Position: Outward: USD: Total: Northern America data was reported at 737.184 USD bn in 2023. This records an increase from the previous number of 707.118 USD bn for 2022. Japan JP: Foreign Direct Investment Position: Outward: USD: Total: Northern America data is updated yearly, averaging 522.813 USD bn from Dec 2014 (Median) to 2023, with 10 observations. The data reached an all-time high of 737.184 USD bn in 2023 and a record low of 392.280 USD bn in 2014. Japan JP: Foreign Direct Investment Position: Outward: USD: Total: Northern America 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 Japan – Table JP.OECD.FDI: Foreign Direct Investment Position: USD: by Region and Country: OECD Member: Annual. Reverse investment: Netting of reverse investment in equity (when a direct investment enterprise acquires less than 10% equity ownership in its parent) and reverse investment in debt (when a direct investment enterprise extends a loan to its parent) is applied in the recording of total inward and outward FDI transactions and positions. Treatment of debt FDI transactions and positions between fellow enterprises: directional basis according to the residency of the direct investor. FDI financial flows, income flows and positions include, if they exist, resident Special Purpose Entities (SPEs) which cannot be identified separately. Valuation method used for listed inward and outward equity positions: Own funds at book value, Accumulation of FDI equity flows. Valuation method used for unlisted inward and outward equity positions: Own funds at book value, Accumulation of FDI equity flows. Valuation method used for inward and outward debt positions: Nominal value .; FDI statistics are available by geographic allocation, vis-à-vis single partner countries worldwide and geographical and economic zones aggregates. Partner country allocation can be subject to confidentiality restrictions. Geographic allocation of inward and outward FDI transactions and positions is according to the immediate counterparty. Inward FDI positions according to the ultimate counterparty (the ultimate investing country) are also available and publishable. In the dataset 'FDI statistics by parner country and by industry - Summary', inward FDI positions are showed according to the UIC. Intercompany debt between related financial intermediaries, including permanent debt, are excluded from FDI transactions and positions. Direct investment relationships are identified according to the criteria of the Framework for Direct Investment Relationships (FDIR) method. Debt between fellow enterprises are completely covered . Collective investment institutions are covered as direct investment enterprises. Non-profit institutions serving households are covered as direct investors. FDI statistics are available by industry sectors according to ISIC4 classification. Industry sector allocation can be subject to confidentiality restrictions. Inward FDI transactions and positions are allocated to the activity of the resident direct investment enterprise. Outward FDI transactions are allocated according to the activity of the non resident direct investment enterprise. Statistical unit: Enterprise.

Japan JP: Foreign Direct Investment Position: Inward: USD: Total: America data was reported at 73.187 USD bn in 2023. This records a decrease from the previous number of 75.510 USD bn for 2022. Japan JP: Foreign Direct Investment Position: Inward: USD: Total: America data is updated yearly, averaging 77.431 USD bn from Dec 2017 (Median) to 2023, with 7 observations. The data reached an all-time high of 97.858 USD bn in 2020 and a record low of 67.867 USD bn in 2018. Japan JP: Foreign Direct Investment Position: Inward: USD: Total: America 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 Japan – Table JP.OECD.FDI: Foreign Direct Investment Position: USD: by Region and Country: OECD Member: Annual. Reverse investment: Netting of reverse investment in equity (when a direct investment enterprise acquires less than 10% equity ownership in its parent) and reverse investment in debt (when a direct investment enterprise extends a loan to its parent) is applied in the recording of total inward and outward FDI transactions and positions. Treatment of debt FDI transactions and positions between fellow enterprises: directional basis according to the residency of the direct investor. FDI financial flows, income flows and positions include, if they exist, resident Special Purpose Entities (SPEs) which cannot be identified separately. Valuation method used for listed inward and outward equity positions: Own funds at book value, Accumulation of FDI equity flows. Valuation method used for unlisted inward and outward equity positions: Own funds at book value, Accumulation of FDI equity flows. Valuation method used for inward and outward debt positions: Nominal value .; FDI statistics are available by geographic allocation, vis-à-vis single partner countries worldwide and geographical and economic zones aggregates. Partner country allocation can be subject to confidentiality restrictions. Geographic allocation of inward and outward FDI transactions and positions is according to the immediate counterparty. Inward FDI positions according to the ultimate counterparty (the ultimate investing country) are also available and publishable. In the dataset 'FDI statistics by parner country and by industry - Summary', inward FDI positions are showed according to the UIC. Intercompany debt between related financial intermediaries, including permanent debt, are excluded from FDI transactions and positions. Direct investment relationships are identified according to the criteria of the Framework for Direct Investment Relationships (FDIR) method. Debt between fellow enterprises are completely covered . Collective investment institutions are covered as direct investment enterprises. Non-profit institutions serving households are covered as direct investors. FDI statistics are available by industry sectors according to ISIC4 classification. Industry sector allocation can be subject to confidentiality restrictions. Inward FDI transactions and positions are allocated to the activity of the resident direct investment enterprise. Outward FDI transactions are allocated according to the activity of the non resident direct investment enterprise. Statistical unit: Enterprise.

For more information, see the Google Cloud Blog . Developed on Google Cloud’s robust infrastructure with guidance from the Harvard Global Health Institute, the COVID-19 Public Forecasts offer a prediction of COVID-19's impact over the next 28 days. The forecasts are generated from a novel time series machine learning approach that combines AI with a robust epidemiological foundation and are trained on public data. The forecasts are maintained by Google Cloud to ensure they remain up-to-date in the changing landscape. For more detail on how the model works, see the White Paper . Forecasts are available for US state and county and Japan prefecture. US User Guide , Japan User Guide ( English and Japanese ). We encourage users who intend to make decisions in part based on these forecasts to closely review the Fairness Analysis . All bytes processed in queries against this dataset will be zeroed out making this part of the query free. Data joined with the dataset will be billed at the normal rate to prevent abuse. After September 2021, queries over these datasets will revert to the normal billing rate. This dataset is hosted in BigQuery and included in BigQuery's 1TB/mo of free tier processing. Each user receives 1TB of free BigQuery processing every month, which can be used to run queries on this public dataset. What is BigQuery?

Japan JP: Foreign Direct Investment Position: Outward: Total: America data was reported at 120,964,566.343 JPY mn in 2023. This records an increase from the previous number of 108,322,733.906 JPY mn for 2022. Japan JP: Foreign Direct Investment Position: Outward: Total: America data is updated yearly, averaging 70,531,479.339 JPY mn from Dec 2014 (Median) to 2023, with 10 observations. The data reached an all-time high of 120,964,566.343 JPY mn in 2023 and a record low of 56,061,540.000 JPY mn in 2014. Japan JP: Foreign Direct Investment Position: Outward: Total: America 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 Japan – Table JP.OECD.FDI: Foreign Direct Investment Position: by Region and Country: OECD Member: Annual. Reverse investment: Netting of reverse investment in equity (when a direct investment enterprise acquires less than 10% equity ownership in its parent) and reverse investment in debt (when a direct investment enterprise extends a loan to its parent) is applied in the recording of total inward and outward FDI transactions and positions. Treatment of debt FDI transactions and positions between fellow enterprises: directional basis according to the residency of the direct investor. FDI financial flows, income flows and positions include, if they exist, resident Special Purpose Entities (SPEs) which cannot be identified separately. Valuation method used for listed inward and outward equity positions: Own funds at book value, Accumulation of FDI equity flows. Valuation method used for unlisted inward and outward equity positions: Own funds at book value, Accumulation of FDI equity flows. Valuation method used for inward and outward debt positions: Nominal value .; FDI statistics are available by geographic allocation, vis-à-vis single partner countries worldwide and geographical and economic zones aggregates. Partner country allocation can be subject to confidentiality restrictions. Geographic allocation of inward and outward FDI transactions and positions is according to the immediate counterparty. Inward FDI positions according to the ultimate counterparty (the ultimate investing country) are also available and publishable. In the dataset 'FDI statistics by parner country and by industry - Summary', inward FDI positions are showed according to the UIC. Intercompany debt between related financial intermediaries, including permanent debt, are excluded from FDI transactions and positions. Direct investment relationships are identified according to the criteria of the Framework for Direct Investment Relationships (FDIR) method. Debt between fellow enterprises are completely covered . Collective investment institutions are covered as direct investment enterprises. Non-profit institutions serving households are covered as direct investors. FDI statistics are available by industry sectors according to ISIC4 classification. Industry sector allocation can be subject to confidentiality restrictions. Inward FDI transactions and positions are allocated to the activity of the resident direct investment enterprise. Outward FDI transactions are allocated according to the activity of the non resident direct investment enterprise. Statistical unit: Enterprise.

Video Games Sales Dataset

About Dataset

This Dataset provides up-to-date information on the sales performance and popularity of various video games worldwide. The data includes the name, platform, year of release, genre, publisher, and sales in North America, Europe, Japan, and other regions. It also features scores and ratings from both critics and users, including average critic score, number of critics reviewed, average user score, number of users reviewed, developer, and rating. This comprehensive and essential dataset offers valuable insights into the global video game market and is a must-have tool for gamers, industry professionals, and market researchers. by source

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Columns

Research Ideas / Data Use

• Market Analysis: The video game sales data can be used to analyze market trends and identify popular genres, platforms, and publishers. This can be useful for industry professionals to make informed decisions about game development and marketing strategies.
• Sales Forecasting: The sales data can be used to forecast future trends and predict the success of upcoming games.
• Consumer Insights: The data can be analyzed to gain insights into consumer preferences and buying habits, which can be used to tailor marketing strategies and improve customer satisfaction.
• Comparison of Competitors: The data can be used to compare the sales performance of competing video games and identify market leaders.
• Gaming Industry Performance: The data can be used to evaluate the overall performance of the gaming industry and track its growth over time.
• Gaming Popularity by Region: The data can be analyzed to determine which regions are the largest markets for video games and which genres are most popular in each region.
• Impact of Reviews: The data can be used to study the impact of critic and user reviews on sales and the relationship between scores and sales performance.
• Gaming Trends over Time: The data can be used to identify trends in the gaming industry over time and to track the evolution of the market.
• Gaming Demographics: The data can be used to analyze the demographic makeup of the gaming audience, including age, gender, and income.
• Impact of Gaming Industry on the Economy: The data can be used to evaluate the impact of the gaming industry on the economy and to assess its contribution to job creation and economic growth.

Acknowledgements

if this dataset was used in your work or studies, please credit the original source Please Credit ↑ ⠀⠀⠀

This dataset presents information on historical central government revenues for 31 countries in Europe and the Americas for the period from 1800 (or independence) to 2012. The countries included are: Argentina, Australia, Austria, Belgium, Bolivia, Brazil, Canada, Chile, Colombia, Denmark, Ecuador, Finland, France, Germany (West Germany between 1949 and 1990), Ireland, Italy, Japan, Mexico, New Zealand, Norway, Paraguay, Peru, Portugal, Spain, Sweden, Switzerland, the Netherlands, the United Kingdom, the United States, Uruguay, and Venezuela. In other words, the dataset includes all South American, North American, and Western European countries with a population of more than one million, plus Australia, New Zealand, Japan, and Mexico. The dataset contains information on the public finances of central governments. To make such information comparable cross-nationally we have chosen to normalize nominal revenue figures in two ways: (i) as a share of the total budget, and (ii) as a share of total gross domestic product. The total tax revenue of the central state is disaggregated guided by the Government Finance Statistics Manual 2001 of the International Monetary Fund (IMF) which provides a classification of types of revenue, and describes in detail the contents of each classification category. Given the paucity of detailed historical data and the needs of our project, we combined some subcategories. First, we are interested in total tax revenue (centaxtot), as well as the shares of total revenue coming from direct (centaxdirectsh) and indirect (centaxindirectsh) taxes. Further, we measure two sub-categories of direct taxation, namely taxes on property (centaxpropertysh) and income (centaxincomesh). For indirect taxes, we separate excises (centaxexcisesh), consumption (centaxconssh), and customs(centaxcustomssh).

For a more detailed description of the dataset and the coding process, see the codebook available in the .zip-file.

Purpose:

This dataset presents information on historical central government revenues for 31 countries in Europe and the Americas for the period from 1800 (or independence) to 2012. The countries included are: Argentina, Australia, Austria, Belgium, Bolivia, Brazil, Canada, Chile, Colombia, Denmark, Ecuador, Finland, France, Germany (West Germany between 1949 and 1990), Ireland, Italy, Japan, Mexico, New Zealand, Norway, Paraguay, Peru, Portugal, Spain, Sweden, Switzerland, the Netherlands, the United Kingdom, the United States, Uruguay, and Venezuela. In other words, the dataset includes all South American, North American, and Western European countries with a population of more than one million, plus Australia, New Zealand, Japan, and Mexico. The dataset contains information on the public finances of central governments. To make such information comparable cross-nationally we have chosen to normalize nominal revenue figures in two ways: (i) as a share of the total budget, and (ii) as a share of total gross domestic product. The total tax revenue of the central state is disaggregated guided by the Government Finance Statistics Manual 2001 of the International Monetary Fund (IMF) which provides a classification of types of revenue, and describes in detail the contents of each classification category. Given the paucity of detailed historical data and the needs of our project, we combined some subcategories. First, we are interested in total tax revenue (centaxtot), as well as the shares of total revenue coming from direct (centaxdirectsh) and indirect (centaxindirectsh) taxes. Further, we measure two sub-categories of direct taxation, namely taxes on property (centaxpropertysh) and income (centaxincomesh). For indirect taxes, we separate excises (centaxexcisesh), consumption (centaxconssh), and customs(centaxcustomssh).

Japan JP: Foreign Direct Investment Financial Flows: Outward: USD: Total: ODA Recipients - America data was reported at 6.291 USD bn in 2023. This records a decrease from the previous number of 6.530 USD bn for 2022. Japan JP: Foreign Direct Investment Financial Flows: Outward: USD: Total: ODA Recipients - America data is updated yearly, averaging 4.411 USD bn from Dec 2014 (Median) to 2023, with 10 observations. The data reached an all-time high of 6.530 USD bn in 2022 and a record low of 53.282 USD mn in 2017. Japan JP: Foreign Direct Investment Financial Flows: Outward: USD: Total: ODA Recipients - America 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 Japan – Table JP.OECD.FDI: Foreign Direct Investment Financial Flows: USD: by Region and Country: OECD Member: Annual. Reverse investment: Netting of reverse investment in equity (when a direct investment enterprise acquires less than 10% equity ownership in its parent) and reverse investment in debt (when a direct investment enterprise extends a loan to its parent) is applied in the recording of total inward and outward FDI transactions and positions. Treatment of debt FDI transactions and positions between fellow enterprises: directional basis according to the residency of the direct investor. FDI financial flows, income flows and positions include, if they exist, resident Special Purpose Entities (SPEs) which cannot be identified separately. Valuation method used for listed inward and outward equity positions: Own funds at book value, Accumulation of FDI equity flows. Valuation method used for unlisted inward and outward equity positions: Own funds at book value, Accumulation of FDI equity flows. Valuation method used for inward and outward debt positions: Nominal value .; FDI statistics are available by geographic allocation, vis-à-vis single partner countries worldwide and geographical and economic zones aggregates. Partner country allocation can be subject to confidentiality restrictions. Geographic allocation of inward and outward FDI transactions and positions is according to the immediate counterparty. Inward FDI positions according to the ultimate counterparty (the ultimate investing country) are also available and publishable. In the dataset 'FDI statistics by parner country and by industry - Summary', inward FDI positions are showed according to the UIC. Intercompany debt between related financial intermediaries, including permanent debt, are excluded from FDI transactions and positions. Direct investment relationships are identified according to the criteria of the Framework for Direct Investment Relationships (FDIR) method. Debt between fellow enterprises are completely covered . Collective investment institutions are covered as direct investment enterprises. Non-profit institutions serving households are covered as direct investors. FDI statistics are available by industry sectors according to ISIC4 classification. Industry sector allocation can be subject to confidentiality restrictions. Inward FDI transactions and positions are allocated to the activity of the resident direct investment enterprise. Outward FDI transactions are allocated according to the activity of the non resident direct investment enterprise. Statistical unit: Enterprise.; Countries from AMERICA recipients of Offical Development Assistance (ODA), 30 countries: Chile, Mexico , Antigua and Barbuda, Cuba, Dominica, Dominican Republic, Grenada, Haiti, Jamaica, Montserrat, Saint Lucia, Saint Vincent and the Grenadines, Belize, Costa Rica, El Salvador, Guatemala, Honduras, Nicaragua, Panama, Argentina, Bolivia, Brazil, Colombia, Ecuador, Guyana, Paraguay, Peru, Suriname, Uruguay, Venezuela

Japan JP: Foreign Direct Investment Financial Flows: Outward: Total: ODA Recipients - America data was reported at 883,891.468 JPY mn in 2023. This records an increase from the previous number of 858,253.677 JPY mn for 2022. Japan JP: Foreign Direct Investment Financial Flows: Outward: Total: ODA Recipients - America data is updated yearly, averaging 478,480.930 JPY mn from Dec 2014 (Median) to 2023, with 10 observations. The data reached an all-time high of 883,891.468 JPY mn in 2023 and a record low of 5,977.390 JPY mn in 2017. Japan JP: Foreign Direct Investment Financial Flows: Outward: Total: ODA Recipients - America 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 Japan – Table JP.OECD.FDI: Foreign Direct Investment Financial Flows: by Region and Country: OECD Member: Annual. Reverse investment: Netting of reverse investment in equity (when a direct investment enterprise acquires less than 10% equity ownership in its parent) and reverse investment in debt (when a direct investment enterprise extends a loan to its parent) is applied in the recording of total inward and outward FDI transactions and positions. Treatment of debt FDI transactions and positions between fellow enterprises: directional basis according to the residency of the direct investor. FDI financial flows, income flows and positions include, if they exist, resident Special Purpose Entities (SPEs) which cannot be identified separately. Valuation method used for listed inward and outward equity positions: Own funds at book value, Accumulation of FDI equity flows. Valuation method used for unlisted inward and outward equity positions: Own funds at book value, Accumulation of FDI equity flows. Valuation method used for inward and outward debt positions: Nominal value .; FDI statistics are available by geographic allocation, vis-à-vis single partner countries worldwide and geographical and economic zones aggregates. Partner country allocation can be subject to confidentiality restrictions. Geographic allocation of inward and outward FDI transactions and positions is according to the immediate counterparty. Inward FDI positions according to the ultimate counterparty (the ultimate investing country) are also available and publishable. In the dataset 'FDI statistics by parner country and by industry - Summary', inward FDI positions are showed according to the UIC. Intercompany debt between related financial intermediaries, including permanent debt, are excluded from FDI transactions and positions. Direct investment relationships are identified according to the criteria of the Framework for Direct Investment Relationships (FDIR) method. Debt between fellow enterprises are completely covered . Collective investment institutions are covered as direct investment enterprises. Non-profit institutions serving households are covered as direct investors. FDI statistics are available by industry sectors according to ISIC4 classification. Industry sector allocation can be subject to confidentiality restrictions. Inward FDI transactions and positions are allocated to the activity of the resident direct investment enterprise. Outward FDI transactions are allocated according to the activity of the non resident direct investment enterprise. Statistical unit: Enterprise.; Countries from AMERICA recipients of Offical Development Assistance (ODA), 30 countries: Chile, Mexico , Antigua and Barbuda, Cuba, Dominica, Dominican Republic, Grenada, Haiti, Jamaica, Montserrat, Saint Lucia, Saint Vincent and the Grenadines, Belize, Costa Rica, El Salvador, Guatemala, Honduras, Nicaragua, Panama, Argentina, Bolivia, Brazil, Colombia, Ecuador, Guyana, Paraguay, Peru, Suriname, Uruguay, Venezuela

Japan JP: Foreign Direct Investment Financial Flows: Outward: USD: Total: Central America and Caribbean Countries data was reported at 7.409 USD bn in 2023. This records a decrease from the previous number of 7.886 USD bn for 2022. Japan JP: Foreign Direct Investment Financial Flows: Outward: USD: Total: Central America and Caribbean Countries data is updated yearly, averaging 9.488 USD bn from Dec 2014 (Median) to 2023, with 10 observations. The data reached an all-time high of 25.455 USD bn in 2016 and a record low of 2.717 USD bn in 2014. Japan JP: Foreign Direct Investment Financial Flows: Outward: USD: Total: Central America and Caribbean Countries 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 Japan – Table JP.OECD.FDI: Foreign Direct Investment Financial Flows: USD: by Region and Country: OECD Member: Annual. Reverse investment: Netting of reverse investment in equity (when a direct investment enterprise acquires less than 10% equity ownership in its parent) and reverse investment in debt (when a direct investment enterprise extends a loan to its parent) is applied in the recording of total inward and outward FDI transactions and positions. Treatment of debt FDI transactions and positions between fellow enterprises: directional basis according to the residency of the direct investor. FDI financial flows, income flows and positions include, if they exist, resident Special Purpose Entities (SPEs) which cannot be identified separately. Valuation method used for listed inward and outward equity positions: Own funds at book value, Accumulation of FDI equity flows. Valuation method used for unlisted inward and outward equity positions: Own funds at book value, Accumulation of FDI equity flows. Valuation method used for inward and outward debt positions: Nominal value .; FDI statistics are available by geographic allocation, vis-à-vis single partner countries worldwide and geographical and economic zones aggregates. Partner country allocation can be subject to confidentiality restrictions. Geographic allocation of inward and outward FDI transactions and positions is according to the immediate counterparty. Inward FDI positions according to the ultimate counterparty (the ultimate investing country) are also available and publishable. In the dataset 'FDI statistics by parner country and by industry - Summary', inward FDI positions are showed according to the UIC. Intercompany debt between related financial intermediaries, including permanent debt, are excluded from FDI transactions and positions. Direct investment relationships are identified according to the criteria of the Framework for Direct Investment Relationships (FDIR) method. Debt between fellow enterprises are completely covered . Collective investment institutions are covered as direct investment enterprises. Non-profit institutions serving households are covered as direct investors. FDI statistics are available by industry sectors according to ISIC4 classification. Industry sector allocation can be subject to confidentiality restrictions. Inward FDI transactions and positions are allocated to the activity of the resident direct investment enterprise. Outward FDI transactions are allocated according to the activity of the non resident direct investment enterprise. Statistical unit: Enterprise.

Japan JP: Foreign Direct Investment Position: Inward: % of Total (FDI) Foreign Direct Investment: Total: Northern America data was reported at 30.197 % in 2023. This records a decrease from the previous number of 30.554 % for 2022. Japan JP: Foreign Direct Investment Position: Inward: % of Total (FDI) Foreign Direct Investment: Total: Northern America data is updated yearly, averaging 30.554 % from Dec 2017 (Median) to 2023, with 7 observations. The data reached an all-time high of 36.110 % in 2017 and a record low of 28.800 % in 2021. Japan JP: Foreign Direct Investment Position: Inward: % of Total (FDI) Foreign Direct Investment: Total: Northern America 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 Japan – Table JP.OECD.FDI: Foreign Direct Investment: % of Total FDI: by Region and Country: OECD Member: Annual. Reverse investment: Netting of reverse investment in equity (when a direct investment enterprise acquires less than 10% equity ownership in its parent) and reverse investment in debt (when a direct investment enterprise extends a loan to its parent) is applied in the recording of total inward and outward FDI transactions and positions. Treatment of debt FDI transactions and positions between fellow enterprises: directional basis according to the residency of the direct investor. FDI financial flows, income flows and positions include, if they exist, resident Special Purpose Entities (SPEs) which cannot be identified separately. Valuation method used for listed inward and outward equity positions: Own funds at book value, Accumulation of FDI equity flows. Valuation method used for unlisted inward and outward equity positions: Own funds at book value, Accumulation of FDI equity flows. Valuation method used for inward and outward debt positions: Nominal value .; FDI statistics are available by geographic allocation, vis-à-vis single partner countries worldwide and geographical and economic zones aggregates. Partner country allocation can be subject to confidentiality restrictions. Geographic allocation of inward and outward FDI transactions and positions is according to the immediate counterparty. Inward FDI positions according to the ultimate counterparty (the ultimate investing country) are also available and publishable. In the dataset 'FDI statistics by parner country and by industry - Summary', inward FDI positions are showed according to the UIC. Intercompany debt between related financial intermediaries, including permanent debt, are excluded from FDI transactions and positions. Direct investment relationships are identified according to the criteria of the Framework for Direct Investment Relationships (FDIR) method. Debt between fellow enterprises are completely covered . Collective investment institutions are covered as direct investment enterprises. Non-profit institutions serving households are covered as direct investors. FDI statistics are available by industry sectors according to ISIC4 classification. Industry sector allocation can be subject to confidentiality restrictions. Inward FDI transactions and positions are allocated to the activity of the resident direct investment enterprise. Outward FDI transactions are allocated according to the activity of the non resident direct investment enterprise. Statistical unit: Enterprise.

Aim The Hemiptera is the fifth-largest insect order but comprises more established non-native insect species than any other insect order. This over-representation may result from high propagule pressure or from high species invasiveness. Here, we assess the reasons for over-representation in this group by analyzing geographical, temporal and taxonomic variation in numbers of historical invasions. Location Global Method We assembled lists of historical Hemiptera invasions in 12 world regions, countries or islands (Australia, Chile, Europe, New Zealand, North America, South Africa, South Korea, Japan, and the Galapagos, Hawaiian, Okinawa, and Ogasawara Islands) and border interception data from 9 countries (Australia, Canada, European Union, United Kingdom, Hawaii, Japan, New Zealand, South Korea, USA mainland, South Africa). Using these data, we identified hemipteran superfamilies that are historically over-represented among established non-native species, and superfamilies that are over-represented among arrivals (proxied by interceptions). We also compared temporal patterns of establishments among hemipteran suborders and among regions. Results Across all regions, patterns of over- and under-representation were similar. The Aphidoidea, Coccoidea, Aleyrodoidea, Cimicoidea and Phylloxeroida were over-represented among non-native species. These same superfamilies were not consistently over-represented among intercepted species indicating that propagule pressure does not completely explain the tendency of some Hemiptera to be over-represented among invasions. Asexual reproduction is common in nearly all over-represented superfamilies and this trait may be key to explaining the exceptional invasion success of these superfamilies. Geographical and temporal patterns of historical numbers of species established per decade mirror trends of naturalization of non-native plants. Conclusions We conclude that both propagule pressure and species invasiveness traits are drivers of the exceptional invasion success of the Sternorrhyncha suborder and Hemiptera in general. Most Hemiptera are plant-feeding; we conclude that non-native plant invasions provide ecological niches for non-native Hemiptera and play a role in driving their invasions worldwide. Methods These data list individual non-native Hemiptera species established in 12 regions around the globe: Australia, Chile, Europe (including its major islands and the European part of Russia), the Galapagos Archipelago, the Hawaiian Archipelago, Japan (excluding outlying islands), New Zealand, Okinawa (Nansei Islands), North America (Canada, continental USA), the Ogasawara Islands (also known as Bonin Islands, Japan), South Africa, and South Korea. Family, superfamily and the year of initial discovery in each region where it is present are included for records when these data are available. This dataset was assembled from various sources by an interdisciplinary scientific working group. Most of the records here are also included in Turner, R., Blake, R., & Liebhold, A. M. (2021). International Non-native Insect Establishment Data (0.1) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.5245302. Data have been cleaned of most typographic and taxonomic errors using the code in the R package insectcleanr: Initial release (DOI: 10.5281/zenodo.4555787), which is based on the Global Biodiversity Information Facility (GBIF) taxonomic backbone (GBIF Secretariat (2021). GBIF Backbone Taxonomy. Checklist dataset https://doi.org/10.15468/39omei accessed via GBIF.org on 2022-02-09, i.e. the https://doi.org/10.15468/43g7-9874 backbone).