Graph and download economic data for Employed full time: Wage and salary workers: Data entry keyers occupations: 16 years and over: Men (LEU0254609800A) from 2000 to 2024 about occupation, full-time, males, salaries, workers, 16 years +, wages, employment, and USA.

This is the new 311 call center data from MyKCMO, which replaced PeopleSoft CRM on March 4th, 2021. For now this dataset is updated manually, several times a day.

For older data from PS CRM, please see https://data.kcmo.org/311/311-Call-Center-Service-Requests-2007-March-2021/7at3-sxhp

An Open Context "predicates" dataset item. Open Context publishes structured data as granular, URL identified Web resources. This "Variables" record is part of the "Oracle Bones in East Asia" data publication.

This is a PDF document created by the Department of Information Technology (DoIT) and the Governor's Office of Performance Improvement to assist training Maryland state employees on use of the Open Data Portal, https://opendata.maryland.gov. This document covers direct data entry, uploading Excel spreadsheets, connecting source databases, and transposing data. Please note that this tutorial is intended for use by state employees, as non-state users cannot upload datasets to the Open Data Portal.

Base de datos actualizada de licitaciones públicas con código CPV 72312000 (Data entry services). Estadísticas, gráficos y licitaciones actualizadas a Agosto de 2025.

Rolling three year performance measures for RASKC

https://kingcounty.gov/depts/regional-animal-services/about-us/stats-at-a-glance.aspx

This data aligns with WWC Certification requirements, and serves as the basis for our data warehouse and open data roadmap. It's a continual work in progress across all departments.Louisville Metro Technology Services builds data and technology platforms to ready our government for our community’s digital future.Data Dictionary: Field Name Description Dataset Name The official title of the dataset as listed in the inventory. Brief Description of Data A short summary explaining the contents and purpose of the dataset. Data Source The origin or system from which the data is collected or generated. Home Department The primary department responsible for the dataset. Home Department Division The specific division within the department that manages the dataset. Data Steward (Business) Name The name of person responsible for the dataset’s accuracy and relevance. Data Custodian (Technical) Name) The technical contact responsible for maintaining and managing the dataset infrastructure. Data Classification The sensitivity level of the data (e.g., Public, Internal, Confidential) Data Format The file format(s) in which the dataset is available (e.g., CSV, JSON, Shapefile). Frequency of Data Change How often the dataset is updated (e.g., Daily, Weekly, Monthly, Annually). Time Spam The overall time period the dataset covers. Start Date The beginning date of the data collection period. End Date The end date of the data collection period Geographic Coverage The geographic area that the dataset pertains to (e.g., Louisville Metro). Geographic Granularity The level of geographic detail (e.g., parcel, neighborhood, ZIP code). Link to Existing Publication A URL linking to the dataset’s public-facing page or open data portal entry.

description: The dataset is known as Border Crossing/Entry Data. The Bureau of Transportation Statistics (BTS) Border Crossing/Entry Data provides summary statistics to the public for incoming crossings at the U.S.-Canadian and the U.S.-Mexican border at the port level. Data are available for trucks, trains, containers, buses, personal vehicles, passengers, and pedestrians. Data fields are numeric counts and textual sequences. These data are collected by U.S. Customs and Border Protection (CBP) at individual ports of entry, then compiled and tabulated by staff of CBP's Office of Field Operations. CBP uses a mixture of manual and automated procedures to collect the data. The data reflect the number of vehicles, containers, passengers or pedestrians entering the United States. U.S. Customs and Border Protection does not collect comparable data on outbound crossings.; abstract: The dataset is known as Border Crossing/Entry Data. The Bureau of Transportation Statistics (BTS) Border Crossing/Entry Data provides summary statistics to the public for incoming crossings at the U.S.-Canadian and the U.S.-Mexican border at the port level. Data are available for trucks, trains, containers, buses, personal vehicles, passengers, and pedestrians. Data fields are numeric counts and textual sequences. These data are collected by U.S. Customs and Border Protection (CBP) at individual ports of entry, then compiled and tabulated by staff of CBP's Office of Field Operations. CBP uses a mixture of manual and automated procedures to collect the data. The data reflect the number of vehicles, containers, passengers or pedestrians entering the United States. U.S. Customs and Border Protection does not collect comparable data on outbound crossings.

The global market for number pads for data entry is experiencing steady growth, driven by increasing demand in sectors such as finance, accounting, and data processing. While precise figures are unavailable, leveraging publicly available data on related peripherals and extrapolating from general market trends suggests a 2025 market size of approximately $1.5 billion USD. This is based on reasonable estimations considering the growth of related markets like computer peripherals and the ongoing digitization of various industries. The market is segmented by application (online and offline sales) and type (wired and wireless). Wireless number pads are witnessing a surge in popularity due to their portability and ease of use, fueling the overall market growth. This trend is further reinforced by the increasing adoption of cloud-based applications and remote work environments. Major players like Microsoft, Lenovo, Logitech, and others are actively competing, driving innovation in features and design. The North American and European regions currently hold significant market share, though the Asia-Pacific region is anticipated to exhibit substantial growth in the coming years due to rapid economic development and increasing computer penetration. However, factors such as the increasing use of touchscreen devices and integrated keyboards could act as potential restraints to the market's growth. The forecast period (2025-2033) is projected to see a Compound Annual Growth Rate (CAGR) of approximately 5%, primarily driven by the adoption of new technologies and improving ergonomics in number pad design. The market's future trajectory is closely tied to technological advancements. The integration of ergonomic designs, enhanced connectivity options (e.g., Bluetooth 5.0 and above), and improved battery life in wireless models will be crucial for attracting new consumers and maintaining growth. Furthermore, the development of specialized number pads for specific industry applications (like those with dedicated accounting functions) could create niche segments and drive further market expansion. The competitive landscape is characterized by established players and new entrants vying for market share through product differentiation, pricing strategies, and brand recognition. A continued focus on user experience and adapting to evolving technological landscapes will be pivotal for companies to maintain their competitive edge in this dynamic market.

Graph and download economic data for Employed full time: Median usual weekly nominal earnings (second quartile): Wage and salary workers: Data entry keyers occupations: 16 years and over (LEU0254556400A) from 2000 to 2024 about second quartile, occupation, full-time, salaries, workers, earnings, 16 years +, wages, median, employment, and USA.

Concept: Number of singular free-entry credit unions Source: Information System on Entities Related to the BCB 25513-singular-free-entry-credit-unions 25513-singular-free-entry-credit-unions

This is the entry site to the collection of public data files from legacy Replicationdomain.comThe data consists of4DN data setsHuman data setsMouse data setsAs FigShare allows only up to 100 files/entry, Human and Mouse data sets are divided into multiple entries according to the sample/assay types. To find the BigWig files you need, please refer to the Word file "Data file location".

The GAPs Data Repository provides a comprehensive overview of available qualitative and quantitative data on national return regimes, now accessible through an advanced web interface at https://data.returnmigration.eu/.

This updated guideline outlines the complete process, starting from the initial data collection for the return migration data repository to the development of a comprehensive web-based platform. Through iterative development, participatory approaches, and rigorous quality checks, we have ensured a systematic representation of return migration data at both national and comparative levels.

The Repository organizes data into five main categories, covering diverse aspects and offering a holistic view of return regimes: country profiles, legislation, infrastructure, international cooperation, and descriptive statistics. These categories, further divided into subcategories, are based on insights from a literature review, existing datasets, and empirical data collection from 14 countries. The selection of categories prioritizes relevance for understanding return and readmission policies and practices, data accessibility, reliability, clarity, and comparability. Raw data is meticulously collected by the national experts.

The transition to a web-based interface builds upon the Repository’s original structure, which was initially developed using REDCap (Research Electronic Data Capture). It is a secure web application for building and managing online surveys and databases.The REDCAP ensures systematic data entries and store them on Uppsala University’s servers while significantly improving accessibility and usability as well as data security. It also enables users to export any or all data from the Project when granted full data export privileges. Data can be exported in various ways and formats, including Microsoft Excel, SAS, Stata, R, or SPSS for analysis. At this stage, the Data Repository design team also converted tailored records of available data into public reports accessible to anyone with a unique URL, without the need to log in to REDCap or obtain permission to access the GAPs Project Data Repository. Public reports can be used to share information with stakeholders or external partners without granting them access to the Project or requiring them to set up a personal account. Currently, all public report links inserted in this report are also available on the Repository’s webpage, allowing users to export original data.

This report also includes a detailed codebook to help users understand the structure, variables, and methodologies used in data collection and organization. This addition ensures transparency and provides a comprehensive framework for researchers and practitioners to effectively interpret the data.

The GAPs Data Repository is committed to providing accessible, well-organized, and reliable data by moving to a centralized web platform and incorporating advanced visuals. This Repository aims to contribute inputs for research, policy analysis, and evidence-based decision-making in the return and readmission field.

Explore the GAPs Data Repository at https://data.returnmigration.eu/.

Temporary vehicle entry system

This data entry contains annotated mouse data from the DeepLabCut Nature Neuroscience paper.

This data entry contains a public release of annotated mouse data from the DeepLabCut paper. The trail-tracking behavior is part of an investigation into odor guided navigation, where one or multiple wildtype (C57BL/6J) mice are running on a paper spool and following odor trails. These experiments were carried out by Alexander Mathis & Mackenzie Mathis in the Murthy lab at Harvard University.

Data was recorded by two different cameras (640×480 pixels with Point Grey Firefly (FMVU-03MTM-CS), and at approximately 1,700×1,200 pixels with Grasshopper 3 4.1MP Mono USB3 Vision (CMOSIS CMV4000-3E12)) at 30 Hz. The latter images were cropped around mice to generate images that are approximately 800×800.

Here we share 1066, frames from multiple experimental sessions observing 7 different mice. Pranav Mamidanna labeled the snout, the tip of the left and right ear as well as the base of the tail in the example images. The data is organized in DeepLabCut 2.0 project structure with images and annotations in the labeled-data folder. The names are pseudocodes indicating mouse id and session id, e.g. m4s1 = mouse 4 session 1.

Code for loading, visualizing & training deep neural networks available at https://github.com/DeepLabCut/DeepLabCut.

Spain Fixed Income Trading: Central Book-Entry Office System (CBE): Public Debt data was reported at 5,328,908.000 EUR mn in 2017. This records a decrease from the previous number of 5,875,113.000 EUR mn for 2016. Spain Fixed Income Trading: Central Book-Entry Office System (CBE): Public Debt data is updated yearly, averaging 2,441,413.000 EUR mn from Dec 1997 (Median) to 2017, with 21 observations. The data reached an all-time high of 6,820,935.000 EUR mn in 2011 and a record low of 1,639,773.000 EUR mn in 2000. Spain Fixed Income Trading: Central Book-Entry Office System (CBE): Public Debt data remains active status in CEIC and is reported by Spanish Exchanges. The data is categorized under Global Database’s Spain – Table ES.Z009: Fixed Income Market: Public Debt.

Estimated total HCW generation rate per year in the study public health centres, Addis Ababa City Government, February 2018.

The City of Surrey CKAN extension enhances a CKAN instance with customizations tailored for the City of Surrey's open data portal. This extension provides theming, custom pages, controlled data access, and pre-defined metadata fields, streamlining data publication and discovery for both internal users and the public. Designed for CKAN 2.2, the extension incorporates customizations such as custom CSS, additions to the portal front-end, license management, and dataset access controls. Key Features: Custom CSS and Templates: Allows theming and visual adjustments of the CKAN instance using a custom CSS file and template overrides to match the City of Surrey’s branding. Custom Pages: Implements custom pages like contact forms, dataset suggestion forms, a follow page, FAQ, glossary, Open Government Licence page, & City of Surrey Open Data API page, utilizing iRoutes. Custom Licence: Integrates a custom licence option for datasets managed within the CKAN instance, allowing for more precise control over data usage rights. Predefined Extra Fields: Adds predefined extra fields at the dataset level, ensuring consistent data quality and simplifying data entry for data managers.