Database of Service Provider Names, Websites, Mission, Location by Country, and Service Type who participated in the SelectUSA 2017 and 2018 Investment Summits

This dataset is about book subjects. It has 5 rows and is filtered where the books is Database-driven web sites. It features 10 columns including number of authors, number of books, earliest publication date, and latest publication date.

NCBI, National Center for Biotechnology Information; KEGG, Kyoto Encyclopedia of Genes and Genomes.

A complete list of live websites using the db-ip technology, compiled through global website indexing conducted by WebTechSurvey.

Product provided by Wappalyzer. Instant access to website technology stacks.

Lookup API Perform near-instant technology lookups with the Lookup API. Results are fetched from our comprehensive database of millions of websites. If we haven't seen a domain before, we'll index it immediately and report back within minutes.

For each hospital web page, we only recorded data requests that initiated data transfers to third-party domains. We then used the webXray database to determine the corporation associated with the third-party domain and the majority owner of the corporation (i.e., the “parent company”) at the time the study occurred (August 2021). For example, the corporation associated with the third-party domain doubleclick.net was determined to be Google, which is majority owned by Alphabet.

Our research does not indicate that the corporations or parent companies listed in our report received data from hospital website browsing; rather, the parent companies listed owned a corporation affiliated with the third-party domains initiating these data requests. We observed only data transfers from the browser to the domain; we did not observe the subsequent use of the data. We do not claim that any third-party domain listed was requesting or receiving this data in a manner that violated applicable laws or regulations governing consumer data privacy.

Below is a table that lists each parent company and the listed domains associated with a corporation owned by such parent company.

.WEBSITE Whois Database, discover comprehensive ownership details, registration dates, and more for .WEBSITE TLD with Whois Data Center.

A database and storage service resource which allows users to create, view, share, and download information from companion websites. RunMyCode allows users to create companion websites for their scientific publications. Users can share and download computer code and data from companion websites made with RunMyCode. Any software and data format is compatible with RunMyCode.

The organizations that contribute to the longevity of 67 long-lived molecular biology databases published in Nucleic Acids Research (NAR) between 1991-2016 were identified to address two research questions 1) which organizations fund these databases? and 2) which organizations maintain these databases? Funders were determined by examining funding acknowledgements in each database's most recent NAR Database Issue update article published (prior to 2017) and organizations operating the databases were determine through review of database websites.

1. Website usage instructions2. Website usage case instructions3. Website unit introduction

Salient Features of Dentists Email Addresses

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1. 1.2 million phone calls per month as a part of a data verification
2. 85% telephone and email verified Dentist Mailing Lists
3. Quarterly SMTP and NCOA verified to keep data fresh and active
4. 15 million verification messages sent every month to validate email addresses
5. Connect with top Dentists across the US, Canada, UK, Europe, EMEA, Australia, APAC and many more countries.
6. egularly updated and cleansed databases to keep it free of duplicate and inaccurate data

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We provide a variety of methods for marketing your dental appliances or products to the top-rated dentists in the United States. Take a glance at some of the available channels:

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Data Sources

The contact details of your targeted healthcare professionals are compiled from highly credible resources like: • Websites • Medical seminars • Medical records • Trade shows • Medical conferences

What’s in for you? Over choosing us, here are a few advantages we authenticate- • Locate, target, and prospect leads from 170+ countries • Design and execute ABM and multi-channel campaigns • Seamless and smooth pre-and post-sale customer service • Connect with old leads and build a fruitful customer relationship • Analyze the market for product development and sales campaigns • Boost sales and ROI with increased customer acquisition and retention

Our security compliance

We use of globally recognized data laws like –

GDPR, CCPA, ACMA, EDPS, CAN-SPAM and ANTI CAN-SPAM to ensure the privacy and security of our database. We engage certified auditors to validate our security and privacy by providing us with certificates to represent our security compliance.

Our USPs- what makes us your ideal choice?

At DataCaptive™, we strive consistently to improve our services and cater to the needs of businesses around the world while keeping up with industry trends.

• Elaborate data mining from credible sources • 7-tier verification, including manual quality check • Strict adherence to global and local data policies • Guaranteed 95% accuracy or cash-back • Free sample database available on request

Guaranteed benefits of our Dentists email database!

85% email deliverability and 95% accuracy on other data fields

We understand the importance of data accuracy and employ every avenue to keep our database fresh and updated. We execute a multi-step QC process backed by our Patented AI and Machine learning tools to prevent anomalies in consistency and data precision. This cycle repeats every 45 days. Although maintaining 100% accuracy is quite impractical, since data such as email, physical addresses, and phone numbers are subjected to change, we guarantee 85% email deliverability and 95% accuracy on other data points.

100% replacement in case of hard bounces

Every data point is meticulously verified and then re-verified to ensure you get the best. Data Accuracy is paramount in successfully penetrating a new market or working within a familiar one. We are committed to precision. However, in an unlikely event where hard bounces or inaccuracies exceed the guaranteed percentage, we offer replacement with immediate effect. If need be, we even offer credits and/or refunds for inaccurate contacts.

Other promised benefits

• Contacts are for the perpetual usage • The database comprises consent-based opt-in contacts only • The list is free of duplicate contacts and generic emails • Round-the-clock customer service assistance • 360-degree database solutions

A complete list of live websites using the Name Directory technology, compiled through global website indexing conducted by WebTechSurvey.

The RAD-IT database, based on version 8.1 of RAD-IT and ARC-IT, is available for download, and includes the interconnect details of the ITS elements and data flows. Interconnect diagrams developed from this database are used throughout the laconnect-it.com website.

This screenshot to save the website of project implementation database at the sub-national level in Cambodia.

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 have added two folders containing additional detailed datasets:

1- Sample: This folder contains samples of the results of web-scraping techniques for two popular Arab websites in two different news categories, Sports and Politics. this folder contain two datasets:

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.

2- Dataset Versions: This volume contains four different versions of the original data set, from which the appropriate version can be selected for use in text classification techniques. The first data set (Original) contains the raw data without pre-processing the data in any way, so the number of tokens in the first data set is very high. In the second data set (Original_without_Stop) the data was cleaned, such as removing symbols, numbers, and non-Arabic words, as well as stop words, so the number of symbols is greatly reduced. In the third dataset (Original_with_Stem) the data was cleaned, and text stemming technique was used to remove all additions and suffixes that might affect the accuracy of the results and to obtain the words roots. In the 4th edition of the dataset (Original_Without_Stop_Stem) all preprocessing techniques such as data cleaning, stop word removal and text stemming technique were applied, so we note that the number of tokens in the 4th edition is the lowest among all releases.

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

Gain exclusive access to verified Shopify store owners with our premium Shopify Users Email List. This database includes essential data fields such as Store Name, Website, Contact Name, Email Address, Phone Number, Physical Address, Revenue Size, Employee Size, and more on demand. Leverage real-time, accurate data to enhance your marketing efforts and connect with high-value Shopify merchants. Whether you're targeting small businesses or enterprise-level Shopify stores, our database ensures precision and reliability for optimized lead generation and outreach strategies. Key Highlights: ✅ 3.9M+ Shopify Stores ✅ Direct Contact Info of Shopify Store Owners ✅ 40+ Data Points ✅ Lifetime Access ✅ 10+ Data Segmentations ✅ FREE Sample Data

Dataset of 700,000 restaurants in the United States complete with detailed contact and geolocation data. The database includes multiple data points such as restaurant name, address, phone number, website, email, opening hours, latitude, longitude, and cuisine.

The USDA Branded Food Database was integrated as part of FoodData Central on April 2019. For more information on FoodData Central and the USDA Branded Food Database: Website: https://fdc.nal.usda.gov/ Ag Data Commons link: https://data.nal.usda.gov/dataset/fooddata-central

This dataset covers all relevant information on every Afrotropical moth species. The zoogeographic area covered can be defined as the Africa continent south of the Sahara (i.e. excl. Morocco, Algeria, Tunisia, Libya and Egypt), the islands in the Atlantic Ocean: Amsterdam Island, Ascension, Cape Verde Archipelago, Inaccessible Island, St. Helena, São Tomé and Principe, Tristan da Cunha, and the islands in the Indian Ocean: Comores (Anjouan, Grande Comore, Mayotte, Mohéli), Madagascar, Mascarene Islands (La Réunion, Mauritius, Rodrigues), Seychelles (Félicité, Mahé, Praslin, Silhouette, a.o.). Furthermore, also those moth species occurring in the transition zone to the Palaearctic fauna have been included, namely most of the Arabia Peninsula (Kuwait, Oman, Saudi Arabia, United Arab Emirates, Yemen with Socotra) but not Iraq, Jordan and further north. Also, some Saharan species have been included (e. g. Hoggar Mts. in Algeria, Tibesti Mts. in South Libya). Utmost care was taken that the data incorporated in the database are correct. We decline any responsibility in case of damage to soft- or hardware based on information used in this website. Persons retrieving information from this website for their own research or for applied aspects such as pest control programmes, should acknowledge the usage of data from this website in the following format: De Prins, J. & De Prins, W. 2011. Afromoths, online database of Afrotropical moth species (Lepidoptera). World Wide Web electronic publication (www.afromoths.net)

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