Historical Dataset of Bing Elementary School is provided by PublicSchoolReview and contain statistics on metrics:Total Students Trends Over Years (1993-2023),Total Classroom Teachers Trends Over Years (1993-2023),Distribution of Students By Grade Trends,Student-Teacher Ratio Comparison Over Years (1993-2023),Asian Student Percentage Comparison Over Years (1993-2023),Hispanic Student Percentage Comparison Over Years (1993-2023),Black Student Percentage Comparison Over Years (1993-2023),White Student Percentage Comparison Over Years (1993-2023),Two or More Races Student Percentage Comparison Over Years (2013-2023),Diversity Score Comparison Over Years (1993-2023),Free Lunch Eligibility Comparison Over Years (1993-2023),Reduced-Price Lunch Eligibility Comparison Over Years (1999-2023),Reading and Language Arts Proficiency Comparison Over Years (2011-2022),Math Proficiency Comparison Over Years (2010-2022),Science Proficiency Comparison Over Years (2021-2022),Overall School Rank Trends Over Years (2010-2022)

MEDI+MTEBcls+COVq dataset

This dataset was used in the paper GISTEmbed: Guided In-sample Selection of Training Negatives for Text Embedding Fine-tuning. Refer to https://arxiv.org/abs/2402.16829 for details. The code for generating the data is available at https://github.com/avsolatorio/GISTEmbed.

  Citation

@article{solatorio2024gistembed, title={GISTEmbed: Guided In-sample Selection of Training Negatives for Text Embedding Fine-tuning}, author={Aivin V. Solatorio}… See the full description on the dataset page: https://huggingface.co/datasets/avsolatorio/medi-data-mteb-covid-bing-query-gpt4-avs_triplets.

Historical Dataset of Bing Wong Elementary School is provided by PublicSchoolReview and contain statistics on metrics:Total Students Trends Over Years (2009-2023),Total Classroom Teachers Trends Over Years (2010-2023),Distribution of Students By Grade Trends,Student-Teacher Ratio Comparison Over Years (2010-2023),American Indian Student Percentage Comparison Over Years (2011-2012),Asian Student Percentage Comparison Over Years (2010-2023),Hispanic Student Percentage Comparison Over Years (2009-2023),Black Student Percentage Comparison Over Years (2009-2023),White Student Percentage Comparison Over Years (2009-2023),Two or More Races Student Percentage Comparison Over Years (2009-2023),Diversity Score Comparison Over Years (2009-2023),Free Lunch Eligibility Comparison Over Years (2010-2023),Reduced-Price Lunch Eligibility Comparison Over Years (2010-2023),Reading and Language Arts Proficiency Comparison Over Years (2010-2022),Math Proficiency Comparison Over Years (2010-2022),Overall School Rank Trends Over Years (2010-2022)

Vietnam AWHW: Bing Duong data was reported at 46.400 Hour in 2023. This records a decrease from the previous number of 46.600 Hour for 2022. Vietnam AWHW: Bing Duong data is updated yearly, averaging 48.300 Hour from Dec 2011 (Median) to 2023, with 13 observations. The data reached an all-time high of 51.900 Hour in 2015 and a record low of 39.200 Hour in 2021. Vietnam AWHW: Bing Duong data remains active status in CEIC and is reported by General Statistics Office. The data is categorized under Global Database’s Vietnam – Table VN.G064: Average Weekly Hours Worked: By Provinces: Annual.

Vietnam Unemployment Rate: Urban: WA: Bing Duong data was reported at 1.280 % in 2023. This records an increase from the previous number of 1.230 % for 2022. Vietnam Unemployment Rate: Urban: WA: Bing Duong data is updated yearly, averaging 2.210 % from Dec 2011 (Median) to 2023, with 13 observations. The data reached an all-time high of 3.350 % in 2020 and a record low of 1.230 % in 2022. Vietnam Unemployment Rate: Urban: WA: Bing Duong data remains active status in CEIC and is reported by General Statistics Office. The data is categorized under Global Database’s Vietnam – Table VN.G045: Unemployment Rate: At Working Age: By Provinces: Annual.

Vietnam AWHW: Urban: Female: Bing Duong data was reported at 46.300 Hour in 2023. This records a decrease from the previous number of 46.400 Hour for 2022. Vietnam AWHW: Urban: Female: Bing Duong data is updated yearly, averaging 49.400 Hour from Dec 2011 (Median) to 2023, with 13 observations. The data reached an all-time high of 52.300 Hour in 2015 and a record low of 38.400 Hour in 2021. Vietnam AWHW: Urban: Female: Bing Duong data remains active status in CEIC and is reported by General Statistics Office. The data is categorized under Global Database’s Vietnam – Table VN.G064: Average Weekly Hours Worked: By Provinces: Annual.

Timeseries data from 'Bing Landing' (bing-s-landing-1)

This dataset provides information about the number of properties, residents, and average property values for Bing Place cross streets in Cherry Valley, CA.

This dataset provides information about the number of properties, residents, and average property values for Bing Circle cross streets in Farmington, UT.

Vietnam LFPR: Bing Duong data was reported at 82.600 % in 2023. This records a decrease from the previous number of 83.800 % for 2022. Vietnam LFPR: Bing Duong data is updated yearly, averaging 82.000 % from Dec 2011 (Median) to 2023, with 13 observations. The data reached an all-time high of 87.000 % in 2015 and a record low of 77.600 % in 2018. Vietnam LFPR: Bing Duong data remains active status in CEIC and is reported by General Statistics Office. The data is categorized under Global Database’s Vietnam – Table VN.G026: Labour Force Participation Rate: By Provinces: Annual.

Abstract: CSDMS model. Visit https://dataone.org/datasets/http%3A%2F%2Fget.iedadata.org%2Fmetadata%2Fiso%2F100098 for complete metadata about this dataset.

Dataset contains 613 news of CanalUGR (University of Granada Communication Office) tracked on the main online news aggregators (Google News, Yahoo! News and Bing News). We include: number in CanalUGR, media, country, type.

This dataset contains oceanographic and surface meteorological data in netCDF formatted files, which follow the Climate and Forecast metadata convention (CF) and the Attribute Convention for Data Discovery (ACDD). Florida Department of Environmental Protection collected the data from their in-situ Bing's Landing, Matanzas River station, in the Coastal Waters of Florida. Southeast Coastal Ocean Observing Regional Association (SECOORA), which assembles data from Florida Department of Environmental Protection and other sub-regional coastal and ocean observing systems of the Southeast United States, submitted the data to NCEI as part of the Integrated Ocean Observing System Data Assembly Centers (IOOS DACs) Data Stewardship Program. NCEI updates this dataset when new files are available.

Timeseries data from 'Bing's Landing, Matanzas River' (bing-s-landing-matanzas-river)

United States agricultural researchers have many options for making their data available online. This dataset aggregates the primary sources of ag-related data and determines where researchers are likely to deposit their agricultural data. These data serve as both a current landscape analysis and also as a baseline for future studies of ag research data. Purpose As sources of agricultural data become more numerous and disparate, and collaboration and open data become more expected if not required, this research provides a landscape inventory of online sources of open agricultural data. An inventory of current agricultural data sharing options will help assess how the Ag Data Commons, a platform for USDA-funded data cataloging and publication, can best support data-intensive and multi-disciplinary research. It will also help agricultural librarians assist their researchers in data management and publication. The goals of this study were to establish where agricultural researchers in the United States-- land grant and USDA researchers, primarily ARS, NRCS, USFS and other agencies -- currently publish their data, including general research data repositories, _domain-specific databases, and the top journals compare how much data is in institutional vs. _domain-specific vs. federal platforms determine which repositories are recommended by top journals that require or recommend the publication of supporting data ascertain where researchers not affiliated with funding or initiatives possessing a designated open data repository can publish data Approach The National Agricultural Library team focused on Agricultural Research Service (ARS), Natural Resources Conservation Service (NRCS), and United States Forest Service (USFS) style research data, rather than ag economics, statistics, and social sciences data. To find _domain-specific, general, institutional, and federal agency repositories and databases that are open to US research submissions and have some amount of ag data, resources including re3data, libguides, and ARS lists were analysed. Primarily environmental or public health databases were not included, but places where ag grantees would publish data were considered. Search methods We first compiled a list of known _domain specific USDA / ARS datasets / databases that are represented in the Ag Data Commons, including ARS Image Gallery, ARS Nutrition Databases (sub-components), SoyBase, PeanutBase, National Fungus Collection, i5K Workspace @ NAL, and GRIN. We then searched using search engines such as Bing and Google for non-USDA / federal ag databases, using Boolean variations of “agricultural data” /“ag data” / “scientific data” + NOT + USDA (to filter out the federal / USDA results). Most of these results were _domain specific, though some contained a mix of data subjects. We then used search engines such as Bing and Google to find top agricultural university repositories using variations of “agriculture”, “ag data” and “university” to find schools with agriculture programs. Using that list of universities, we searched each university web site to see if their institution had a repository for their unique, independent research data if not apparent in the initial web browser search. We found both ag specific university repositories and general university repositories that housed a portion of agricultural data. Ag specific university repositories are included in the list of _domain-specific repositories. Results included Columbia University – International Research Institute for Climate and Society, UC Davis – Cover Crops Database, etc. If a general university repository existed, we determined whether that repository could filter to include only data results after our chosen ag search terms were applied. General university databases that contain ag data included Colorado State University Digital Collections, University of Michigan ICPSR (Inter-university Consortium for Political and Social Research), and University of Minnesota DRUM (Digital Repository of the University of Minnesota). We then split out NCBI (National Center for Biotechnology Information) repositories. Next we searched the internet for open general data repositories using a variety of search engines, and repositories containing a mix of data, journals, books, and other types of records were tested to determine whether that repository could filter for data results after search terms were applied. General subject data repositories include Figshare, Open Science Framework, PANGEA, Protein Data Bank, and Zenodo. Finally, we compared scholarly journal suggestions for data repositories against our list to fill in any missing repositories that might contain agricultural data. Extensive lists of journals were compiled, in which USDA published in 2012 and 2016, combining search results in ARIS, Scopus, and the Forest Service's TreeSearch, plus the USDA web sites Economic Research Service (ERS), National Agricultural Statistics Service (NASS), Natural Resources and Conservation Service (NRCS), Food and Nutrition Service (FNS), Rural Development (RD), and Agricultural Marketing Service (AMS). The top 50 journals' author instructions were consulted to see if they (a) ask or require submitters to provide supplemental data, or (b) require submitters to submit data to open repositories. Data are provided for Journals based on a 2012 and 2016 study of where USDA employees publish their research studies, ranked by number of articles, including 2015/2016 Impact Factor, Author guidelines, Supplemental Data?, Supplemental Data reviewed?, Open Data (Supplemental or in Repository) Required? and Recommended data repositories, as provided in the online author guidelines for each the top 50 journals. Evaluation We ran a series of searches on all resulting general subject databases with the designated search terms. From the results, we noted the total number of datasets in the repository, type of resource searched (datasets, data, images, components, etc.), percentage of the total database that each term comprised, any dataset with a search term that comprised at least 1% and 5% of the total collection, and any search term that returned greater than 100 and greater than 500 results. We compared _domain-specific databases and repositories based on parent organization, type of institution, and whether data submissions were dependent on conditions such as funding or affiliation of some kind. Results A summary of the major findings from our data review: Over half of the top 50 ag-related journals from our profile require or encourage open data for their published authors. There are few general repositories that are both large AND contain a significant portion of ag data in their collection. GBIF (Global Biodiversity Information Facility), ICPSR, and ORNL DAAC were among those that had over 500 datasets returned with at least one ag search term and had that result comprise at least 5% of the total collection. Not even one quarter of the _domain-specific repositories and datasets reviewed allow open submission by any researcher regardless of funding or affiliation. See included README file for descriptions of each individual data file in this dataset. Resources in this dataset:Resource Title: Journals. File Name: Journals.csvResource Title: Journals - Recommended repositories. File Name: Repos_from_journals.csvResource Title: TDWG presentation. File Name: TDWG_Presentation.pptxResource Title: Domain Specific ag data sources. File Name: domain_specific_ag_databases.csvResource Title: Data Dictionary for Ag Data Repository Inventory. File Name: Ag_Data_Repo_DD.csvResource Title: General repositories containing ag data. File Name: general_repos_1.csvResource Title: README and file inventory. File Name: README_InventoryPublicDBandREepAgData.txt

Dataset

This dataset was created by Antonio Rueda-Toicen

Contents

Vietnam AWHW: Rural: Male: Bing Duong data was reported at 45.800 Hour in 2023. This records a decrease from the previous number of 46.800 Hour for 2022. Vietnam AWHW: Rural: Male: Bing Duong data is updated yearly, averaging 46.800 Hour from Dec 2011 (Median) to 2023, with 13 observations. The data reached an all-time high of 50.900 Hour in 2019 and a record low of 40.400 Hour in 2021. Vietnam AWHW: Rural: Male: Bing Duong data remains active status in CEIC and is reported by General Statistics Office. The data is categorized under Global Database’s Vietnam – Table VN.G064: Average Weekly Hours Worked: By Provinces: Annual.

This dataset provides information about the number of properties, residents, and average property values for Bing Court cross streets in Pickerington, OH.

This dataset provides information about the number of properties, residents, and average property values for Bing Court cross streets in Kalispell, MT.

Bing Maps is a free online map service from Microsoft that allows you to view various spatial data and use spatial services. It is a further development of the MSN Virtual Earth and is part of the search engine Bing. The data and services are provided through the Bing Maps for Enterprise platform and include satellite and aerial images. In the so-called transit area (for public transport connections), stops and timetables of the Wiener Linien as well as several hundred other transport companies and networks in the world are mapped to form the largest existing transit network. In the future, the mapping of real-time connections is also planned in this context.