You can check the fields description in the documentation: current Keyword database: https://docs.dataforseo.com/v3/databases/google/keywords/?bash; Historical Keyword database: https://docs.dataforseo.com/v3/databases/google/history/keywords/?bash. You don’t have to download fresh data dumps in JSON or CSV – we can deliver data straight to your storage or database. We send terrabytes of data to dozens of customers every month using Amazon S3, Google Cloud Storage, Microsoft Azure Blob, Eleasticsearch, and Google Big Query. Let us know if you’d like to get your data to any other storage or database.

You can check the fields description in the documentation: current Full database: https://docs.dataforseo.com/v3/databases/google/full/?bash; Historical Full database: https://docs.dataforseo.com/v3/databases/google/history/full/?bash.

Full Google Database is a combination of the Advanced Google SERP Database and Google Keyword Database.

Google SERP Database offers millions of SERPs collected in 67 regions with most of Google’s advanced SERP features, including featured snippets, knowledge graphs, people also ask sections, top stories, and more.

Google Keyword Database encompasses billions of search terms enriched with related Google Ads data: search volume trends, CPC, competition, and more.

This database is available in JSON format only.

You don’t have to download fresh data dumps in JSON – we can deliver data straight to your storage or database. We send terrabytes of data to dozens of customers every month using Amazon S3, Google Cloud Storage, Microsoft Azure Blob, Eleasticsearch, and Google Big Query. Let us know if you’d like to get your data to any other storage or database.

Belarus Internet Usage: Search Engine Market Share: Desktop: StartPagina (Google) data was reported at 0.000 % in 09 Mar 2025. This records a decrease from the previous number of 0.030 % for 08 Mar 2025. Belarus Internet Usage: Search Engine Market Share: Desktop: StartPagina (Google) data is updated daily, averaging 0.070 % from Mar 2025 (Median) to 09 Mar 2025, with 9 observations. The data reached an all-time high of 0.070 % in 05 Mar 2025 and a record low of 0.000 % in 09 Mar 2025. Belarus Internet Usage: Search Engine Market Share: Desktop: StartPagina (Google) data remains active status in CEIC and is reported by Statcounter Global Stats. The data is categorized under Global Database’s Belarus – Table BY.SC.IU: Internet Usage: Search Engine Market Share.

Business Listings Database is the source of point-of-interest data and can provide you with all the information you need to analyze how specific places are used, what kinds of audiences they attract, and how their visitor profile changes over time.

The full fields description may be found on this page: https://docs.dataforseo.com/v3/databases/business_listings/?bash

The Global Power Plant Database is a comprehensive, open source database of power plants around the world. It centralizes power plant data to make it easier to navigate, compare and draw insights. Each power plant is geolocated and entries contain information on plant capacity, generation, ownership, and fuel type. As …

The Ultimate Arabic News Dataset is a collection of single-label modern Arabic texts that are used in news websites and press articles.

Arabic news data was collected by web scraping techniques from many famous news sites such as Al-Arabiya, Al-Youm Al-Sabea (Youm7), the news published on the Google search engine and other various sources.

• The data we collect consists of two Primary files:

UltimateArabic: A file containing more than 193,000 original Arabic news texts, without pre-processing. The texts contain words, numbers, and symbols that can be removed using pre-processing to increase accuracy when using the dataset in various Arabic natural language processing tasks such as text classification.

UltimateArabicPrePros: It is a file that contains the data mentioned in the first file, but after pre-processing, where the number of data became about 188,000 text documents, where stop words, non-Arabic words, symbols and numbers have been removed so that this file is ready for use directly in the various Arabic natural language processing tasks. Like text classification.

• We add two samples of data collected by web scraping techniques:

Sample_Youm7_Politic: An example of news in the "Politic" category collected from the Youm7 website.

Sample_alarabiya_Sport: An example of news in the "Sport" category collected from the Al-Arabiya website.

• The data is divided into 10 different categories: Culture, Diverse, Economy, Sport, Politic, Art, Society, Technology, Medical and Religion.

Singapore Internet Usage: Search Engine Market Share: Tablet: StartPagina (Google) data was reported at 0.000 % in 11 Dec 2024. This stayed constant from the previous number of 0.000 % for 10 Dec 2024. Singapore Internet Usage: Search Engine Market Share: Tablet: StartPagina (Google) data is updated daily, averaging 0.060 % from Dec 2024 (Median) to 11 Dec 2024, with 9 observations. The data reached an all-time high of 0.060 % in 07 Dec 2024 and a record low of 0.000 % in 11 Dec 2024. Singapore Internet Usage: Search Engine Market Share: Tablet: StartPagina (Google) data remains active status in CEIC and is reported by Statcounter Global Stats. The data is categorized under Global Database’s Singapore – Table SG.SC.IU: Internet Usage: Search Engine Market Share.

You can check the fields description in the documentation: regular SERP: https://docs.dataforseo.com/v3/databases/google/serp_regular/?bash; Advanced SERP: https://docs.dataforseo.com/v3/databases/google/serp_advanced/?bash; Historical SERP: https://docs.dataforseo.com/v3/databases/google/history/serp_advanced/?bash You don’t have to download fresh data dumps in JSON or CSV – we can deliver data straight to your storage or database. We send terrabytes of data to dozens of customers every month using Amazon S3, Google Cloud Storage, Microsoft Azure Blob, Eleasticsearch, and Google Big Query. Let us know if you’d like to get your data to any other storage or database.

Nowadays web portals play an essential role in searching and retrieving information in the several fields of knowledge: they are ever more technologically advanced and designed for supporting the storage of a huge amount of information in natural language originating from the queries launched by users worldwide. A good example is given by the WorldWideScience search engine: The database is available at http://worldwidescience.org/. It is based on a similar gateway, Science.gov, which is the major path to U.S. government science information, as it pulls together Web-based resources from various agencies. The information in the database is intended to be of high quality and authority, as well as the most current available from the participating countries in the Alliance, so users will find that the results will be more refined than those from a general search of Google. It covers the fields of medicine, agriculture, the environment, and energy, as well as basic sciences. Most of the information may be obtained free of charge (the database itself may be used free of charge) and is considered ‘‘open domain.’’ As of this writing, there are about 60 countries participating in WorldWideScience.org, providing access to 50+databases and information portals. Not all content is in English. (Bronson, 2009) Given this scenario, we focused on building a corpus constituted by the query logs registered by the GreyGuide: Repository and Portal to Good Practices and Resources in Grey Literature and received by the WorldWideScience.org (The Global Science Gateway) portal: the aim is to retrieve information related to social media which as of today represent a considerable source of data more and more widely used for research ends. This project includes eight months of query logs registered between July 2017 and February 2018 for a total of 445,827 queries. The analysis mainly concentrates on the semantics of the queries received from the portal clients: it is a process of information retrieval from a rich digital catalogue whose language is dynamic, is evolving and follows – as well as reflects – the cultural changes of our modern society.

Montenegro Internet Usage: Search Engine Market Share: Desktop: StartPagina (Google) data was reported at 0.000 % in 05 Oct 2024. This stayed constant from the previous number of 0.000 % for 04 Oct 2024. Montenegro Internet Usage: Search Engine Market Share: Desktop: StartPagina (Google) data is updated daily, averaging 0.000 % from Sep 2024 (Median) to 05 Oct 2024, with 9 observations. The data reached an all-time high of 0.050 % in 01 Oct 2024 and a record low of 0.000 % in 05 Oct 2024. Montenegro Internet Usage: Search Engine Market Share: Desktop: StartPagina (Google) data remains active status in CEIC and is reported by Statcounter Global Stats. The data is categorized under Global Database’s Montenegro – Table ME.SC.IU: Internet Usage: Search Engine Market Share.

1. Repeatability is the cornerstone of science and it is particularly important for systematic reviews. However, little is known on how researchers' choice of database and search platform influence the repeatability of systematic reviews. Here, we aim to unveil how the computer environment and the location where the search was initiated from influence hit results.

2. We present a comparative analysis of time-synchronized searches at different institutional locations in the world, and evaluate the consistency of hits obtained within each of the search terms using different search platforms.

3. We revealed a large variation among search platforms and showed that PubMed and Scopus returned consistent results to identical search strings from different locations. Google Scholar and Web of Science's Core Collection varied substantially both in the number of returned hits and in the list of individual articles depending on the search location and computing environment. Inconsistency in Web of Science results has most likely emerged from the different licensing packages at different institutions.

4. To maintain scientific integrity and consistency, especially in systematic reviews, action is needed from both the scientific community and scientific search platforms to increase search consistency. Researchers are encouraged to report the search location and the databases used for systematic reviews, and database providers should make search algorithms transparent and revise access rules to titles behind paywalls. Additional options for increasing the repeatability and transparency of systematic reviews are storing both search metadata and hit results in open repositories and using Application Programming Interfaces (APIs) to retrieve standardized, machine-readable search metadata.

This project aims to use remote sensing data from the Landsata database from Google Earth Engine to evaluate the spatial extent changes in the Bear Lake located between the US states of Utah and Idaho. This work is part of a term project submitted to Dr Alfonso Torres-Rua as a requirment to pass the Remote Sensing of Land Surfaces class (CEE6003). More information about the course is provided below. This project uses the geemap Python package (https://github.com/giswqs/geemap) for dealing with the google earth engine datasets. The content of this notebook can be used to:

learn how to retrive the Landsat 8 remote sensed data. The same functions and methodology can also be used to get the data of other Landsat satallites and other satallites such as Sentinel-2, Sentinel-3 and many others. However, slight changes might be required when dealing with other satallites then Landsat. Learn how to create time lapse images that visulaize changes in some parameters over time. Learn how to use supervised classification to track the changes in the spatial extent of water bodies such as Bear Lake that is located between the US states of Utah and Idaho. Learn how to use different functions and tools that are part of the geemap Python package. More information about the geemap Pyhton package can be found at https://github.com/giswqs/geemap and https://github.com/diviningwater/RS_of_Land_Surfaces_laboratory Course information:

Name: Remote Sensing of Land Surfaces class (CEE6003) Instructor: Alfonso Torres-Rua (alfonso.torres@usu.edu) School: Utah State University Semester: Spring semester 2023

Luxembourg Internet Usage: Search Engine Market Share: Mobile: StartPagina (Google) data was reported at 0.000 % in 07 Oct 2024. This records a decrease from the previous number of 0.030 % for 06 Oct 2024. Luxembourg Internet Usage: Search Engine Market Share: Mobile: StartPagina (Google) data is updated daily, averaging 0.000 % from Oct 2024 (Median) to 07 Oct 2024, with 6 observations. The data reached an all-time high of 0.030 % in 06 Oct 2024 and a record low of 0.000 % in 07 Oct 2024. Luxembourg Internet Usage: Search Engine Market Share: Mobile: StartPagina (Google) data remains active status in CEIC and is reported by Statcounter Global Stats. The data is categorized under Global Database’s Luxembourg – Table LU.SC.IU: Internet Usage: Search Engine Market Share.

Harvester is a Web-based tool that bulk-collects bioinformatic data on human proteins from various databases and prediction servers. It is a meta search engine for gene and protein information. It searches 16 major databases and prediction servers and combines the results on pregenerated HTML pages. In this way Harvester can provide comprehensive gene-protein information from different servers in a convenient and fast manner. As full text meta search engine, similar to Google trade mark, Harvester allows screening of the whole genome proteome for current protein functions and predictions in a few seconds. With Harvester it is now possible to compare and check the quality of different database entries and prediction algorithms on a single page. Sponsors: This work has been supported by the BMBF with grants 01GR0101 and 01KW0013.

Twenty-four unique tools mapped to the six-step approach in the conceptual framework to support the implementation of hand hygiene recommendations in community settings (one tool can be relevant to more than one step and key action).

BackgroundMultiple sclerosis (MS) is one of the most common neurological disorders and is one of the main causes of disability. The prevalence and incidence of MS in Iran is reported to range from 5.3 to 89/ 100,000and 7 to 148.1/ 100,000, respectively. There are no systematic and meta-analysis studies on MS in Iran. Therefore, this study was conducted to investigate the prevalence and incidence of MS in Iran using meta-analysis.MethodA systematic review of the present study focused on MS epidemiology in Iran based on PRISMA guidelines for systematic review and meta-analysis. We searched eight international databases including Scopus, PubMed, Science Direct, Cochrane Library, Web of Science, EMBASE, PsycINFO, Google Scholar search engine and six Persian databases for peer-reviewed studies published without time limit until May 2018. Data were analyzed using Comprehensive meta-analysis ver. 2 software. The review protocol has been registered in PROSPERO with ID: CRD42018114491.ResultsAccording to searching on different databases, 39 (15%) articles finalized. The prevalence of MS in Iran was estimated 29.3/ 100,000 (95%CI: 25.6–33.5) based on random effects model. The prevalence of MS in men and women was estimated to be 16.5/ 100,000 (95%CI: 13.7–23.4) and 44.8/ 100,000 (95%CI: 36.3–61.6), respectively. The incidence of MS in Iran was estimated to be 3.4/ 100,000 (95%CI: 1.8–6.2) based on random effects model. The incidence of MS in men was estimated to be 16.5/ 100,000 (95%CI: 13.7–23.4) and the incidence of MS in women was 44.8/ 100,000 (95%CI: 36.3–61.6). The meta-regression model for prevalence and incidence of MS was significantly higher in terms of year of study (p

Andorra Internet Usage: Search Engine Market Share: Desktop: StartPagina (Google) data was reported at 0.000 % in 06 Oct 2024. This stayed constant from the previous number of 0.000 % for 05 Oct 2024. Andorra Internet Usage: Search Engine Market Share: Desktop: StartPagina (Google) data is updated daily, averaging 0.000 % from Jun 2024 (Median) to 06 Oct 2024, with 18 observations. The data reached an all-time high of 0.360 % in 07 Jun 2024 and a record low of 0.000 % in 06 Oct 2024. Andorra Internet Usage: Search Engine Market Share: Desktop: StartPagina (Google) data remains active status in CEIC and is reported by Statcounter Global Stats. The data is categorized under Global Database’s Andorra – Table AD.SC.IU: Internet Usage: Search Engine Market Share.

Yahoo's share in the mobile search engine market across India was about 0.03 percent in February 2024. This was a fall in market share compared to its standing of 0.24 percent in September 2018. The immense popularity and database of Google has left little to gain for other search engine operators in India.

Contains the annotations (WDPA polygons).. Visit https://dataone.org/datasets/sha256%3A5f2db5b57ae438910a1f32601d0dac34209304d5044969710343ed21a6a06a2a for complete metadata about this dataset.

The geoBoundaries Global Database of Political Administrative Boundaries Database is an online, open license resource of boundaries (i.e., state, county) for every country in the world. Currently 199 total entities are tracked, including all 195 UN member states, Greenland, Taiwan, Niue, and Kosovo. Comprehensive Global Administrative Zones (CGAZ) is a set of global composites for administrative boundaries. Disputed areas are removed and replaced with polygons following US Department of State definitions. It has three boundary levels ADM0, ADM1, and ADM2, clipped to international boundaries (US Department of State), with gaps filled between borders. This dataset is part of CGAZ. It was ingested from version 6.0.0 of Global Composite Files with DBF_DATE_LAST_UPDATE=2023-09-13. It shows boundaries at level ADM0 (country-level boundaries).