Title of each data set starts with the section number of report, which the data were used in analysis. This dataset is associated with the following publication: Yang, J., H. Wei, X. Wang, S. Buchberger, M. Liang, N. Chang, B. Bierwagen, S. Julius, Z. Li, D. Boccelli, R. Clark, H. Liu, and J. Neal. National Water Infrastructure Adaptation Assessment: Part II, Smart Urban Designer (SUD) and Application Case Studies. U.S. Environmental Protection Agency, Washington, DC, USA, 2020.

Dataset

This dataset was created by People Data Labs

Released under Data files © Original Authors

Contents

Performance, participation, and funding data related to Title III. Data from SY 2010-11 onward.

A listing of transactions associated with changes of vehicle ownership.

A collection of 235 titles from a YouTube channel extracted and cleaned by me.

Unlock powerful insights with McGRAW’s extensive property, mortgage, title, and ownership data. Access over 150M records and 200 attributes for superior decision-making, risk management, and targeted marketing across real estate, mortgage, and title industries.

The Title and Salary Listing is a compilation of job titles under the jurisdiction of the Department of Civil Service.

1. Scientists face an overwhelming number of peer-reviewed publications to read and must choose which to cite. Citation rate is used to measure a scientist's productivity and often affects hiring and promotion. Thus, as the number of scientific publications grows, competition for notice increases. A publication's title is the first step in the filtering process of a reader; the features of a title that are correlated with citation rate have not been explored for entomology journals. 2. We analyzed titles from two entomology and two ecology journals, documenting the presence of Latin names, common names, functional groups, geographic location, question marks, whether the title attempted humor or was divided into two parts, and the number of words in the title. 3. We found that using a Latin name in a title significantly decreases citations. Using Latin names in a title likely causes readers who are not immediately familiar with that name to skip the paper entirely when perusing a journal's table of contents, whereas titles that describe a general research area, without indicating the study organism, draw a wider audience and thus more citations. 4. We found that use of functional group names or geographic location in a title increased citations in entomology journals; however, these patterns were driven by a small portion of the data. Use of common names, presence of punctuation, whether the title attempted humor, and title length had no effect on citation rates. 5. Our findings may help authors to write better titles and therefore improve readership and citation rate.

A "determination of native title" is a decision on whether native title exists in relation to a particular area of land or waters (s 225 of the NTA).

Determinations of native title can be made by agreement (consent determination), without opposition (unopposed determination) or following a trial (litigated determination).

An "approved determination of native title" is a determination of native title made by the Federal Court of Australia, the High Court of Australia, or a recognised State/Territory body within its jurisdictional limits (s 13 of the NTA). Only approved determinations of native title are recorded on the National Native Title Register (s 193 of the NTA).

Note: This dataset also includes representations of determinations of native title that have not yet been entered on the National Native Title Register.

United States Title Insurance: Direct Premiums Written data was reported at 16.286 USD bn in Dec 2024. This records an increase from the previous number of 11.870 USD bn for Sep 2024. United States Title Insurance: Direct Premiums Written data is updated quarterly, averaging 8.849 USD bn from Mar 2012 (Median) to Dec 2024, with 52 observations. The data reached an all-time high of 26.364 USD bn in Dec 2021 and a record low of 2.293 USD bn in Mar 2012. United States Title Insurance: Direct Premiums Written data remains active status in CEIC and is reported by National Association of Insurance Commissioners. The data is categorized under Global Database’s United States – Table US.RG016: Title Insurance: Industry Financial Snapshots.

H-1B visa sponsorship trends for Senior Data Scientist, covering top employers, salary insights, approval rates, and geographic distribution. Explore how job title impacts the U.S. job market under the H-1B program.

Number of vehicle titles issued and fees collected by each county for fiscal year ending 8/31/2021

Trends in Data Science and Software Development - A Dataset of Article Titles from Leading Data Science Blogs

Description: - This dataset comprises article titles collected from three major data science blogs, aiming to serve as a rich resource for understanding current trends and shifts in the data science and software development fields. It was meticulously gathered using Selenium to scrape the websites, ensuring a comprehensive collection of recent articles.

Purpose:

The primary objective of this dataset is to facilitate research and development in Natural Language Processing (NLP) and trend analysis. Content creators, researchers, and data enthusiasts can dive into this dataset to identify emerging topics, gauge the popularity of various concepts over time, and strategize their content creation or academic inquiries accordingly.

Potential Applications:

1. Trend Analysis: Examine the rise and fall of data science and software development topics over time to understand the evolving landscape.
2. Content Strategy Development: Aid content creators in strategizing their articles or posts based on trending topics and audience interests.
3. NLP and Machine Learning Models: Serve as a training set for models focused on text generation, title recommendation systems, or topic modeling.

Dataset Structure: 1. Title 2. Date 3. Subtitle

Data Collection: The data was collected using Selenium, a robust tool for web scraping. Each title has been carefully extracted from the respective blog pages, ensuring accuracy and relevance.

Usage Guidelines: This dataset is open for academic and personal use. If you're employing it in your research or project, a citation would be appreciated. We encourage users to explore diverse applications and share insights or models developed using this dataset.

Contribution: Feel free to contribute by suggesting additional sources, improvements, or potential uses. Your feedback and contributions will help enhance this dataset for the broader community.

Content

The Title and Salary Listing is a compilation of job titles under the jurisdiction of the Department of Civil Service.

Context

This is a dataset hosted by the State of New York. The state has an open data platform found here and they update their information according the amount of data that is brought in. Explore New York State using Kaggle and all of the data sources available through the State of New York organization page!

• Update Frequency: This dataset is updated annually.

Acknowledgements

This dataset is maintained using Socrata's API and Kaggle's API. Socrata has assisted countless organizations with hosting their open data and has been an integral part of the process of bringing more data to the public.

This dataset provides information about the number of properties, residents, and average property values for Ancient Title Court cross streets in Walnut, CA.

Dataset

This dataset was created by Gary Davis

Released under Data files © Original Authors

Contents

This table provides information on Records of Title that are live and part-cancelled.

This table contains top level, general title data only, such as the title number, type (e.g. Freehold, Unit Title, Cross Lease etc) and status.

A Record of Title is a record of a property's owners, legal description and the rights and responsibilities registered against the title.

If you need more detailed title data such as the legal description, please refer to the NZ Property Titles Estate List table.

This table does not contain ownership data. This is available in the NZ Property Title Owners List table. This is a restricted access dataset and requires you to agree to the LINZ Licence for Personal Data.

For title data that is directly linked to parcel shapes (property boundaries) refer to NZ Property Titles or NZ Property Titles Including Owners. Please note that these datasets are much larger to download, contain duplicated parcel shapes (one for each title that relates to the parcel) and does not contain all of the columns that this table has.

For more information about this table, other property datasets, and how to relate them to each other, refer to the Property Boundary and Ownership Data Dictionary.

List of Civil Service title codes and title descriptions used by City of New York agencies

The Title and Salary Listing is a compilation of job titles under the jurisdiction of the Department of Civil Service.

EDFacts Title I, 2010-11 (EDFacts T1:2010-11), is one of 17 'topics' identified in the EDFacts documentation (in this database, each 'topic' is entered as a separate study); program data is available since 2005 at . EDFacts T1:2010-11 (ed.gov/about/inits/ed/edfacts) annually collects cross-sectional data from states about student participants and staff of Title I, Part A of the Elementary and Secondary Act (ESEA), as amended, at the school, LEA, and state levels. EDFacts T1:2010-11 data were collected using the EDFacts Submission System (ESS), a centralized portal and their submission by states is mandatory and required for benefits. Not submitting the required reports by a state constitutes a failure to comply with law and may have consequences for federal funding to the state. Key statistics produced from EDFacts T1:2010-11 are from 18 data groups with information on Economically Disadvantaged Students, School Poverty Indicator, Public School Choice - Eligible, Public School Choice - Applied for Transfer, Public School Choice - Transferred, Public School Choice - Implementation, Public School Choice - 20% Transportation Reservation, Public School Choice - Funds Spent, SES - Applied to Receive Services, SES - Eligible to Receive Services, SES - Funds Spent, SES - Per Pupil Expenditure, SES - Received Services, Title I Part A Participation, Title I Status, Title I Part A SWP/TAS Participation, Title I TAS Staff Funded (FTE), Title I Part A TAS. For the purposes of this system, data groups are referred to as 'variables', as a result of the structure and format of EDFacts' data.