Explore the progression of average salaries for graduates in Gis from 2020 to 2023 through this detailed chart. It compares these figures against the national average for all graduates, offering a comprehensive look at the earning potential of Gis relative to other fields. This data is essential for students assessing the return on investment of their education in Gis, providing a clear picture of financial prospects post-graduation.

Explore the progression of average salaries for graduates in Geography Focus Gis from 2020 to 2023 through this detailed chart. It compares these figures against the national average for all graduates, offering a comprehensive look at the earning potential of Geography Focus Gis relative to other fields. This data is essential for students assessing the return on investment of their education in Geography Focus Gis, providing a clear picture of financial prospects post-graduation.

This dataset has been published by the Human Resources Department of the City of Virginia Beach and data.virginiabeach.gov. The mission of data.virginiabeach.gov is to provide timely and accurate City information to increase government transparency and access to useful and well organized data by the general public, non-governmental organizations, and City of Virginia Beach employees.Distributed bydata.virginiabeach.gov2405 Courthouse Dr.Virginia Beach, VA 23456EntityEmployee SalariesPoint of ContactHuman ResourcesSherri Arnold, Human Resources Business Partner IIIsharnold@vbgov.com757-385-8804Elda Soriano, HRIS Analystesoriano@vbgov.com757-385-8597AttributesColumn: DepartmentDescription: 3-letter department codeColumn: Department DivisionDescription: This is the City Division that the position is assigned to.Column: PCNDescription: Tracking number used to reference each unique position within the City.Column: Position TitleDescription: This is the title of the position (per the City’s pay plan).Column: FLSA Status Description: Represents the position’s status with regards to the Fair Labor Standards Act (FLSA) “Exempt” - These positions do not qualify for overtime compensation – Generally, a position is classified as FLSA exempt if all three of the following criteria are met: 1) Paid at least $47,476 per year ($913 per week); 2) Paid on a salary basis - generally, salary basis is defined as having a guaranteed minimum amount of pay for any work week in which the employee performs any work; 3) Perform exempt job duties - Job duties are split between three classifications: executive, professional, and administrative. All three have specific job functions which, if present in the employee’s regular work, would exempt the individual from FLSA. Employees may also be exempt from overtime compensation if they are a “highly compensated employee” as defined by the FLSA or the position meets the criteria for other enumerated exemptions in the FLSA.“Non-exempt” – These positions are eligible for overtime compensation - positions classified as FLSA non-exempt if they fail to meet any of exempt categories specified in the FLSA. Column: Initial Hire DateDescription: This is the date that the full-time employee first began employment with the City.Column: Date in TitleDescription: This is the date that the full-time employee first began employment in their current position.Column: SalaryDescription: This is the annual salary of the full-time employee or the hourly rate of the part-time employee.Frequency of dataset updateMonthly

Explore the progression of average salaries for graduates in Transportation And Gis from 2020 to 2023 through this detailed chart. It compares these figures against the national average for all graduates, offering a comprehensive look at the earning potential of Transportation And Gis relative to other fields. This data is essential for students assessing the return on investment of their education in Transportation And Gis, providing a clear picture of financial prospects post-graduation.

The County of Suffolk Annual Salaries File for the Year 2021 is a yearly summary of Payroll Data for all Suffolk County employees. This file contains the Employee Names and Hired Date along with their most recent Job Title and Department. In addition, the file contains the Employee’s Regular Pay Rate (Hourly, Biweekly or Annual Salary), the Year to Date Regular Earnings, Longevity Pay, Overtime Pay, and Other Payments (comprised of Holiday Pay, Night Differential Pay, Cleaning and Clothing Allowances, Taxable Legal Benefit Amounts, etc.). If an employee has been terminated or has separated from County employment, the Separation Payment Amount (if applicable), and Termination Date is also included.

Classification establishes and maintains the County's job classifications and compensation systems and practices, with equity, consistency, and due regard for pay competitiveness. Positions are analyzed and assigned to appropriate job classificationsJob Descriptions -- Frequently Asked Questions -- Classification and Compensation Documents

A dataset that explores Green Card sponsorship trends, salary data, and employer insights for gis in the U.S.

General Mills reported $625.6M in Net Income for its fiscal quarter ending in February of 2025. Data for General Mills | GIS - Net Income including historical, tables and charts were last updated by Trading Economics this last June in 2025.

Table contains count and percentage of households with an annual household income of less than $100,000. Data are presented at county, city, zip code and census tract level. Data are presented for zip codes (ZCTAs) fully within the county. Source: U.S. Census Bureau, 2016-2020 American Community Survey 5-year estimates, Table B19001; data accessed on May 16, 2022 from https://api.census.gov. The 2020 Decennial geographies are used for data summarization.METADATA:notes (String): Lists table title, notes, sourcesgeolevel (String): Level of geographyGEOID (Numeric): Geography IDNAME (String): Name of geographytotalHH (Numeric): Total householdslt100k (Numeric): Number of households with less than $100,000 annual incomepct_lt100k (Numeric): Percent of households with less than $100,000 annual income

Explore the progression of average salaries for graduates in Cartology And Gis from 2020 to 2023 through this detailed chart. It compares these figures against the national average for all graduates, offering a comprehensive look at the earning potential of Cartology And Gis relative to other fields. This data is essential for students assessing the return on investment of their education in Cartology And Gis, providing a clear picture of financial prospects post-graduation.

A dataset that explores Green Card sponsorship trends, salary data, and employer insights for geographic information systems gis in the U.S.

As of January 7, 2025, several Miami-Dade County departments transitioned to become independent constitutional offices. These offices include:Sheriff's OfficeSupervisor of ElectionsProperty AppraiserOffice of the Tax CollectorClerk of the Court and ComptrollerEmployees from these departments are now employed directly by their respective constitutional offices, with their positions, pay, benefits, and seniority carrying over without interruption. Participation in the Florida Retirement System (FRS) and the Deferred Retirement Option Program (DROP) continues seamlessly.Miami-Dade County provides a public Employee Salary Search tool that allows you to view county employee compensation details, including bi-weekly gross pay, annual salary, and year-to-date totals. You can search by employee name, title, department or salary.Please note that while the constitutional offices are now independent, they may still provide access to similar salary information through their own channels. For the most accurate and up-to-date information, it's advisable to contact the specific constitutional office directly.

General Mills comprehensive income for the quarter ending February 28, 2025 was $-2.474B, a 7.71% increase year-over-year. General Mills comprehensive income for 2024 was $-2.52B, a 10.66% increase from 2023. General Mills comprehensive income for 2023 was $-2.277B, a 15.55% increase from 2022. General Mills comprehensive income for 2022 was $-1.971B, a 18.88% decline from 2021.

This layer shows median household income by race and by age of householder. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. Median income and income source is based on income in past 12 months of survey. This layer is symbolized to show median household income. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2018-2022ACS Table(s): B19013B, B19013C, B19013D, B19013E, B19013F, B19013G, B19013H, B19013I, B19049, B19053Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 7, 2023The United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2022 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters).The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

NFCorpus: 20 generated queries (BEIR Benchmark)

This HF dataset contains the top-20 synthetic queries generated for each passage in the above BEIR benchmark dataset.

DocT5query model used: BeIR/query-gen-msmarco-t5-base-v1 id (str): unique document id in NFCorpus in the BEIR benchmark (corpus.jsonl). Questions generated: 20 Code used for generation: evaluate_anserini_docT5query_parallel.py

Below contains the old dataset card for the BEIR benchmark.

  Dataset Card for BEIR… See the full description on the dataset page: https://huggingface.co/datasets/income/cqadupstack-gis-top-20-gen-queries.

The County of Suffolk Annual Salaries File for the Year 2018 is a yearly summary of Payroll Data for all Suffolk County employees. This file contains the Employee Names and Hired Date along with their most recent Job Title and Department. In addition, the file contains the Employee’s Regular Pay Rate (Hourly, Biweekly or Annual Salary), the Year to Date Regular Earnings, Longevity Pay, Overtime Pay, and Other Payments (comprised of Holiday Pay, Night Differential Pay, Cleaning and Clothing Allowances, Taxable Legal Benefit Amounts, etc.). If an employee has been terminated or has separated from County employment, the Separation Payment Amount (if applicable), and Termination Date is also included.

Additional information about the Dataset Attributes are listed below. Please feel free to contact us if you have any questions about this dataset.

Year: Year of employment Last Name: Employee Last Name First Name: Employee First Name Department: Department Name Job Title: Job Title Bargaining Unit Number: Bargaining Unit Bargaining Unit Name: Bargaining Unit Name Salary: Regular Salary Earnings for the Year Longevity Pay: Longevity Pay Overtime Pay: Overtime Pay Separation Pay: Separation Payment of Sick, Vacation and Personal Time Accruals Other Pay: Special Payments - Holiday Pay, Night Differential, Cleaning Clothing Tool Allowance, Legal Benefit Total Earnings: Total Earnings for the Year Separation Date: Date of Termination/Separation from Suffolk County

This layer shows income data in Tucson by neighborhood, aggregated from block level data, between 2010-2019. For questions, contact GIS_IT@tucsonaz.gov. The data shown is from Esri's 2019 Updated Demographic estimates.Esri's U.S. Updated Demographic (2019/2024) Data - Population, age, income, sex, race, home value, and marital status are among the variables included in the database. Each year, Esri's Data Development team employs its proven methodologies to update more than 2,000 demographic variables for a variety of U.S. geographies.Additional Esri Resources:Esri DemographicsU.S. 2019/2024 Esri Updated DemographicsEssential demographic vocabularyPermitted use of this data is covered in the DATA section of the Esri Master Agreement (E204CW) and these supplemental terms.

Metro Nashville general government employees’ titles and base annual salaries. This dataset is updated annually.Source Link: https://www.nashville.gov/departments/human-resourcesMetadata Document: General Government-Employees-Titles-and-Base-Annual-Salaries-Metadata.pdfContact Data Owner: opendata@nashville.gov

A dataset that explores Green Card sponsorship trends, salary data, and employer insights for forest engineering (gis) in the U.S.

Starting from July 2022, the dataset provides the monthly number of Old Age Security (OAS) pension and Guaranteed Income Supplement (GIS) beneficiaries and the amount of benefits paid. The data is provided by age groups 65-74 and 75 and over. The data is presented by gender (male and female) and by province/territory. Nunavut is included in Northwest territories due to current data limitations. Beneficiaries paid under an International Agreement (IA) may be located in Canada or abroad, but are presented as a separate category due to current data limitations.