Valid real estate agent business information with a national real estate agent license

Council-approved licenses to use the whole or part of the public right-of-way. The data excludes terminated licenses and most small cell network nodes. Whenever possible, the City Ordinance is attached to the corresponding feature to provide detailed information about the permitted use, location, and expiration date of the license. The data is updated at the beginning of each month.Facilities and Real Estate Management manages the Real Estate Licenses, and Transportation and Public Works maintains the GIS data. More information on Real Estate Licenses is available at https://dallascityhall.com/departments/building-services/real-estate/Pages/Licenses.aspx.

The IP Licensing industry is growing courtesy of the expansion of fast food and franchise brands. QSR brands like McDonald’s, Chick-fil-A and Raising Cane’s rely significantly on licensing for IP elements such as trademarks, proprietary recipes, operational processes and digital assets. The industry has proven resilient because of operational efficiency, advantageous real estate utilization, the ability to scale rapidly through predefined processes and strong brand recognition. This growth necessitates sophisticated IP management, enforcement and protection services, leading to more advanced tools for digital asset management, contract automation and brand protection. Overall, industry revenue will gain at a CAGR of 3.1% to $69.9 billion through the end of 2025, including a 1.8% climb in 2025 alone. The broader franchising sector relies on an operational duplication model that necessitates effective IP licensing. With digital transformation, both the volume and complexity of IP assets are increasing, leading to diversification of revenue streams. Rising demand for digital content in the entertainment industry fuels the need for robust IP licensing and digital rights management. The increasing prevalence of dynamic and performance-based licensing models is a crucial trend in the industry. According to data from the International Franchise Association and FranData, the number of franchised establishments will climb by 2.5% in 2025. Through the five years to 2030, high-tech sectors like semiconductors and life sciences will significantly contribute to this sector's growth. The rapid pace of innovation and the evolving nature of products in these industries will require specialized expertise and tools. This surge of advancement will necessitate new and dynamic licensing models, as performance-based licensing gains traction. The industry will increasingly embrace the concept of modular and rapid-innovation IP systems, necessitating real-time tracking and updating of IP assets. The sector will develop more advanced tools for IP enforcement and protection, particularly for intangible digital assets, while managing data privacy and cybersecurity challenges. Overall, industry revenue will gain at a CAGR of 1.5% to reach $75.2 billion in 2030.

description: This data contains active Real Estate Salesperson and Broker Licenses from New York State Department of State (DOS). Each line will be either an individual or business licensee which holds business address and license number information. If the license type is an individual, the business name that the individual works for will be listed.; abstract: This data contains active Real Estate Salesperson and Broker Licenses from New York State Department of State (DOS). Each line will be either an individual or business licensee which holds business address and license number information. If the license type is an individual, the business name that the individual works for will be listed.

Licenses and Credentials recorded in Connecticut's eLicensing system.

Updated daily.

Product Overview

You’re a few short steps away from accessing the largest and most comprehensive Pre-Foreclosure and Foreclosure database in the country. Whether you want to conduct property research, data analysis, purchase distressed properties, or market your services, licensing Pre-Foreclosure and Foreclosure Data provides in-depth intelligence on distressed properties across the country that will inform your next move.

What is Foreclosure?

Foreclosure is the legal process of taking possession of a mortgaged property when the borrower fails to keep up with mortgage payments. The foreclosure process varies from state to state, depending on whether the state has a judicial or nonjudicial process. Judicial process requires court action on a foreclosed property, where a nonjudicial process does not.

Foreclosure and Pre-Foreclosure Data Includes:

• 9 Different types of Judicial vs Non-Judicial
• Auctions
• Public Notices
• Lis Pendens
• Releases
• Defendant and Plaintiff Names
• Recording Dates, Published Dates, and Auction Dates
• Original Mortgage Information

Unlock the Potential of U.S. National MLS Real Estate Data

Discover the wealth of information encapsulated in licensing bulk MLS (Multiple Listing Service) data, a cornerstone of the real estate realm. From property particulars to market trends, delve into the significance and multifaceted utility of MLS data across diverse industries.

MLS Real Estate Data includes:

• Property Information: Address, size, layout, condition, amenities, and more.
• Price History: Historical price changes, listing dates, and sales dates.
• Geographic Insights: Location, neighborhood information, school districts, and proximity to amenities.
• Property Photos: MLS images of properties (see the condition of a property inside and out.)
• Agent/Broker Information: Certain details about the listing agent or broker as well as their notes on properties.
• Market Dynamics: Data on local real estate market conditions, including inventory levels, price trends, and days on the market.

This paper investigates in an exploratory manner the licensing strategies pursued by firms whose business model is based on developing and licensing out their intellectual property rights (IPRs). These are not traditional suppliers, since they do not engage in production or commercialization, but focus solely on invention. While considerable anecdotal evidence exists about these IP vendors, there has been no systematic investigation of how they use licensing to appropriate value from their investments in R&D. In this paper, we suggest that the licensing strategies they pursue can be differentiated along two main dimensions: whether the driving force behind the inventive process is "technology push" or "market pull", and the degree to which the innovative activities carried out by the IP vendor are mutually dependent upon the innovative activities of the other relevant market players. On this basis, four main licensing strategies are identified. We investigate the relative benefits and costs of these four strategies, and the factors affecting licensing choices. Key words: Intellectual property, licensing, strategy JEL Codes: O31, O32, O34

Review of Economics and Statistics: Forthcoming. Visit https://dataone.org/datasets/sha256%3A9c6288386b701f85f40331c69dffd08e1abb80882c862f912312dedaf8a8037f for complete metadata about this dataset.

All Active Short-Term Licenses. This dataset includes Commercial, Non-Commercial, and Operator Licenses, as well as listings for lodging providers exempt from STR licensing (i.e., licensed Hotels, Motels, and Bed and Breakfasts who may list their properties on Short-Term Rental platforms).

This data contains information for all currently active Real Estate Appraiser licensees. Each record will be for an individual licensee, and will contain their Name, Unique Identification Number, License Type, Original Certification Date, Current Certification and Expiration Dates, Reciprocal State (if any), the Name of the Business they are associated with, and the Business’s Address.

For over years we've been providing real estate licensee data for residential real estate, commercial real estate, and investors with active licenses.

We provide Name, Brokerage, License and Contact details for all the licensees, standardized to a common set of values.

Common use cases include: - Compliance use cases ensuring agents and brokers maintain an active license - Viewing market agent movement - Assessing Agent Count by Brokerage across States - Marketing to agents and brokers by specialization - Recruiting new agents - Monitoring agent growth

Record counts by province are as follows:

Alberta ~516 records British Columbia ~2,283 records Manitoba ~1,472 records New Brunswick ~16,191 records Newfoundland & Labrador ~828 records Nova Scoatia ~3,461 records Ontario ~105,214 records Prince Edward Island ~29,946 records Quebec ~1,951 records Saskatchewan ~17,852 records

United States - Governmental Taxes and License Fees for Real Estate, All Establishments, Employer Firms (DISCONTINUED) was 23122.00000 Mil. of $ in January of 2017, according to the United States Federal Reserve. Historically, United States - Governmental Taxes and License Fees for Real Estate, All Establishments, Employer Firms (DISCONTINUED) reached a record high of 23122.00000 in January of 2017 and a record low of 16893.00000 in January of 2010. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Governmental Taxes and License Fees for Real Estate, All Establishments, Employer Firms (DISCONTINUED) - last updated from the United States Federal Reserve on June of 2025.

United States - Sources of Revenue: Licensing of Right to Use Intellectual Property for Internet Publishing and Broadcasting and Web Search Portals, All Establishments, Employer Firms was 4814.00000 Mil. of $ in January of 2021, according to the United States Federal Reserve. Historically, United States - Sources of Revenue: Licensing of Right to Use Intellectual Property for Internet Publishing and Broadcasting and Web Search Portals, All Establishments, Employer Firms reached a record high of 4840.00000 in January of 2019 and a record low of 1320.00000 in January of 2010. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Sources of Revenue: Licensing of Right to Use Intellectual Property for Internet Publishing and Broadcasting and Web Search Portals, All Establishments, Employer Firms - last updated from the United States Federal Reserve on June of 2025.

BatchData's property listings data provides comprehensive insights with over 140 data points and nationwide listing data inclusive of For Sale By Owner (FSBO) listings across the United States. Updated daily in most markets, the data includes:

• Listing Details: property listings descriptions, property characteristics, pricing, days on market, and more.
• Agent Information: agent names, license numbers, contact details, listing counts, and listing histories.
• Broker Information: Broker names, locations, URLs, emails, phone numbers, and licensing information.
• Additional Details: Information about schools, neighborhoods, subdivisions, and tax data.

Common Use Cases: - Recruiting Teams: Enhance talent acquisition by analyzing agents' listing counts, close rates, property types, and client profiles. - Proptech Software & Marketplaces: Integrate current and historical listings to create detailed property profiles, advanced search features, and robust analytics. - Home Service Providers: Target marketing and outreach efforts to homeowners, whether they are preparing to move or have recently relocated. - Real Estate Agents & Investors: Identify undervalued properties, connect with buyers/sellers based on activity, analyze market trends, and develop effective marketing strategies.

Our property listings data can be delivered in a variety of formats to suit your needs. Choose from API integration for seamless, real-time data access, bulk data delivery for extensive datasets, S3 bucket storage for scalable cloud solutions, and more. This flexibility ensures that you can incorporate our comprehensive property information into your systems efficiently and effectively, whether you're building a new platform, enhancing existing tools, or conducting in-depth analyses.

Data Description: This data set contains all license & use permits issued by City of Cincinnati departments (including Buildings & Inspections; Cincinnati Fire Department; Cincinnati Health Department; Transportation & Engineering; and Finance Department). Licenses range from food service operation, to open flame permits, to swimming pool licenses. This data set also contains licenses & use permits issued by other Hamilton County jurisdictions.

Data Creation: All data is input by the respective licensing agencies, and stored by Cincinnati Area Geographic Information Systems (CAGIS). This data is also available on the CAGIS Property Activity Report website: http://cagismaps.hamilton-co.org/PropertyActivity/cagisreport

Data Created By: CAGIS

Refresh Frequency: Daily

Data Dictionary: A data dictionary providing definitions of columns and attributes is available as an attachment to this data set.

Processing: The City of Cincinnati is committed to providing the most granular and accurate data possible. In that pursuit the Office of Performance and Data Analytics facilitates standard processing to most raw data prior to publication. Processing includes but is not limited: address verification, geocoding, decoding attributes, and addition of administrative areas (i.e. Census, neighborhoods, police districts, etc.).

Data Usage: For directions on downloading and using open data please visit our How-to Guide: https://data.cincinnati-oh.gov/dataset/Open-Data-How-To-Guide/gdr9-g3ad

This consists of a discussion in three sections: • Intellectual property rights in data: Copyright and Database Rights. • Trends in legal certainty: Open Data Licensing. • “Informal” Openness and Open License Limitations. (PDF)

We introduce a large-scale dataset of the complete texts of free/open source software (FOSS) license variants. To assemble it we have collected from the Software Heritage archive���the largest publicly available archive of FOSS source code with accompanying development history���all versions of files whose names are commonly used to convey licensing terms to software users and developers. The dataset consists of 6.5 million unique license files that can be used to conduct empirical studies on open source licensing, training of automated license classifiers, natural language processing (NLP) analyses of legal texts, as well as historical and phylogenetic studies on FOSS licensing. Additional metadata about shipped license files are also provided, making the dataset ready to use in various contexts; they include: file length measures, detected MIME type, detected SPDX license (using ScanCode), example origin (e.g., GitHub repository), oldest public commit in which the license appeared. The dataset is released as open data as an archive file containing all deduplicated license blobs, plus several portable CSV files for metadata, referencing blobs via cryptographic checksums. For more details see the included README file and companion paper: Stefano Zacchiroli. A Large-scale Dataset of (Open Source) License Text Variants. In proceedings of the 2022 Mining Software Repositories Conference (MSR 2022). 23-24 May 2022 Pittsburgh, Pennsylvania, United States. ACM 2022. If you use this dataset for research purposes, please acknowledge its use by citing the above paper.

Courses approved to meet licensing requirements

Graph and download economic data for Sources of Revenue: Licensing of Right to Use Intellectual Property for Scientific Research and Development Services, Establishments Exempt from Federal Income Tax Employer Firms (REVLIPEF5417TAXEPT) from 2013 to 2022 about tax exempt, licenses, R&D, science, used, intellectual property, employer firms, accounting, revenue, establishments, tax, services, and USA.