Showing 481-488 of 573 results
Snap Political Ads Library

Snap Political Ads Library

Stefan
Open Dataset
Creators: Snapchat
Publication Date: 2024
Creators: Snapchat

The Political and Advocacy Ads Library is an important step in our efforts to increase the level of transparency around political and issue advertising on. The dataset includes advertisements from 2018 through 2025 with a total size of 538,8 kB. It offers detailed insights into political advertising on Snapchat, including:​

  • Ad Content: Access to the creative content of each advertisement through unique URLs.​

  • Financial Information: Details on the amount spent on each ad campaign, specified in the local currency.​

  • Impressions: Data on the number of times each ad was viewed by Snapchat users.​

  • Targeting Criteria: Information on the demographic and geographic targeting parameters used in each campaign.

These features enable researchers, policymakers, and the public to analyze the reach, expenditure, and strategies of political advertisers on Snapchat.

IMINTREG data

IMINTREG data

Stefan
Open Dataset
Creators: Zuber, Christina Isabel
Publication Date: 2011
Creators: Zuber, Christina Isabel

IMINTREG offers data on immigrant integration policies of Italian regions, Spanish autonomous communities and German Länder. You can download the original regional integration laws, as well as measures of in- vs. exclusiveness of regional integration policies based on my coding of the laws here. The dataset has a size of 84,2 kB and entails the following aspects:

  • Regional Integration Laws: The dataset includes the original texts of regional integration laws from the specified regions, allowing for direct analysis of legislative content.​

  • Inclusiveness Measures: It provides coded measures assessing the inclusiveness of these policies, facilitating comparative studies across different regions.​

  • Comparative Scope: By covering multiple countries with varying approaches to integration, the dataset offers a unique opportunity to study the effects of regional policies within different national contexts.​

CVE List

CVE List

Stefan
Open Dataset
Creators: CVE
Publication Date: 2024
Creators: CVE

The mission of the CVE® Program is to identify, define, and catalog publicly disclosed cybersecurity vulnerabilities identified from 1999 through June 25, 2024, providing a historical perspective on the evolution of cybersecurity threats over a span of 25 years. Its primary purpose is to standardize the identification of vulnerabilities across various platforms and security tools, facilitating consistent and efficient communication within the cybersecurity community. As of June 25, 2024, the CVE List comprises 269,759 records with a size of 36,3 kB.

Each CVE entry includes several key components:​

  • CVE Identifier (CVE ID): A unique alphanumeric code assigned to each vulnerability, following the format “CVE-YYYY-NNNN,” where “YYYY” denotes the year of identification, and “NNNN” is a sequential number.​

  • Description: A brief summary outlining the nature of the vulnerability, including affected software or hardware, potential impacts, and any known exploits.​

  • References: Links to external resources such as security advisories, vendor bulletins, or detailed analyses that provide additional context or mitigation information.

Soccer Power Index (SPI) Ratings

Soccer Power Index (SPI) Ratings

Stefan
Open Dataset
Creators: FiveThirtyEight
Publication Date: 2022
Creators: FiveThirtyEight

This file contains links to the data behind our Club Soccer Predictions and Global Club Soccer Rankings. These data analyse soccer team performances worldwide,  providing valuable insights into team strengths and match outcomes.

The SPI database covers data up to the year 2022 with a total size of 52,6 kB and includes the following metrics:​

  • SPI Rating: An overall measure of a team’s strength, combining offensive and defensive capabilities.​

  • Offensive and Defensive Ratings: Separate evaluations of a team’s attacking and defensive proficiencies.​

  • Match Probabilities: Predicted probabilities for home win, away win, and draw outcomes, offering insights into expected match results.​

  • Projected Scores: Anticipated goal counts for both home and away teams, aiding in match analysis and forecasting.

 

Netflix Prize Data Set

Netflix Prize Data Set

Stefan
Open Dataset
Creators: Netflix
Publication Date: 2009
Creators: Netflix

This dataset was constructed to support participants in the Netflix Prize. See [Web Link] for details about the prize.

There are over 480,000 customers in the dataset, each identified by a unique integer id.

The title and release year for each movie is also provided. There are over 17,000 movies in the dataset, each identified by a unique integer id.

The dataset contains over 100 million ratings and has a size of 7,7 kB. The ratings were collected between October 1998 and December 2005 and reflect the distribution of all ratings received during this period. Each rating has a customer id, a movie id, the date of the rating, and the value of the rating.

As part of the original Netflix Prize a set of ratings was identified whose rating values were not provided in the original dataset. The object of the Prize was to accurately predict the ratings from this ‘qualifying’ set. These missing ratings are now available in the grand_prize.tar.gz dataset file.

New York Prison Employee Discipline Data

New York Prison Employee Discipline Data

Stefan
Open Dataset
Creators: The Mashall Project
Publication Date: 2023
Creators: The Mashall Project

The Marshall Project examined 12 years of employee discipline data and hundreds of prisoner lawsuits. The Marshall Project requested this data via New York’s Freedom of Information Law in the summer of 2020. We asked for: “An electronic copy of the database maintained by the Bureau of Labor Relations to document disciplinary cases and their resolutions involving alleged misconduct by DOCCS employees from January 1, 2010 to present.” We later asked for a second batch of data covering the time period up until the spring of 2022. By doing so, we prove an in-depth look into the internal disciplinary processes of the New York prison system, offering insights into the nature and frequency of infractions committed by prison staff, the outcomes of disciplinary proceedings, and patterns that may exist within the system. Such detailed information is typically challenging to access, making this dataset particularly valuable for research and analysis in criminal justice and institutional accountability. The dataset has a size of 1,2 MB.

Project Foundations of Legal Data Science I

Project Foundations of Legal Data Science I

Stefan
Open Dataset
Creators: Fobbe, Seán
Publication Date: 2019
Creators: Fobbe, Seán

the first two of a new series of open and high-quality international legal data sets: comprehensive, fully reproducible, human- and machine-readable open access collections covering one hundred years of case law of the primary judicial organs of the United Nations and the League of Nations: the Corpus of Decisions: International Court of Justice (CD-ICJ) and the Corpus of Decisions: Permanent Court of International Justice(CD-PCIJ).

National Zoning and Land Use Database

National Zoning and Land Use Database

Stefan
Open Dataset
Creators: Desmond, Matthew; Mleczko: Matthew
Publication Date: 2023
Creators: Desmond, Matthew; Mleczko: Matthew

We constructed a National Zoning and Land Use Database using natural language processing techniques on publicly available administrative data. We created the National Zoning and Land Use Database (NZLUD) to provide national zoning and land use data for the 2019-2022 time period. We supply our source code to enable timely access to publicly available zoning information. Users can rerun our code at regular intervals to create panel zoning data moving forward. Users can also expand to additional municipalities or additional zoning and land use measures not currently captured by our process. The intent is for this code to further automate the process of building national zoning and land use information in an open source way. Overall, the dataset has a size of 82,2 kB and is structured into:

  • Municipal-Level Data: The file contains zoning and land use information for individual municipalities. This includes various measures extracted using NLP techniques from municipal codes, focusing on aspects such as zoning regulations and land use policies. ​

  • MSA-Level Data: This file aggregates the municipal-level data to the MSA level, providing a broader view of zoning and land use patterns across metropolitan areas. ​

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