This dataset contains information about Parks' Special Events, including fitness, sports, dancing, movies, and concerts facilitated by NYC Parks' Public Programs division. These are one-off events that occur a single time - these events are not part of a regularly occurring programming series. Explore the Data Dictionary

Brisbane City Council Events dataset containing dates, costs, booking requirements, venue and location for events listed on the What’s on in Brisbane experience on the Brisbane City Council website.

The dataset includes combined event information from the many different event categories. Active and healthy, Brisbane Botanic Gardens, Creative, and Library event categories are some examples.

The dataset was created using data from an external service called Trumba. The data is a transformed extract created using the Trumba Calendar API XML feed, that is limited to the next 1,000 events. The transformed extract is converted to a CSV file and uploaded into this dataset daily.

To access and view the data using the Source API (Trumba), use the information below and your preferred link in the Data and Resources section. The Source API is available for this dataset in:

Trumba Calendar - API - XML feed is limited to the next 1,000 events

Trumba Calendar - API - RSS feed is limited to the next 1,000 events

Trumba Calendar - API - CSV feed is limited to the next 2,000 events

Trumba Calendar - API - JSON feed is limited to the next 2,000 events.

The Data and resources section of this dataset contains further information for this dataset.

The MIVIA audio events data set is composed of a total of 6000 events for surveillance applications, namely glass breaking, gun shots and screams. The 6000 events are divided into a training set (composed of 4200 events) and a test set (composed of 1800 events).

The present is a manually labeled data set for the task of Event Detection (ED). The task of ED consists of identifying event triggers, the word that most clearly indicates the occurrence of an event.

The present data set consists of 2,200 news extracts from The New York Times (NYT) Annotated Corpus, separated into training (2,000) and testing (200) sets. Each news extract contains the plain text with the labels (event mentions), along with two metadata (publication date and an identifier).

Labels description: We consider as event any ongoing real-world event or situation reported in the news articles. It is important to distinguish those events and situations that are in progress (or are reported as fresh events) at the moment the news is delivered from past events that are simply brought back, future events, hypothetical events, or events that will not take place. In our data set we only labeled as event the first type of event. Based on this criterion, some words that are typically considered as events are labeled as non-event triggers if they do not refer to ongoing events at the time the analyzed news is released. Take for instance the following news extract: "devaluation is not a realistic option to the current account deficit since it would only contribute to weakening the credibility of economic policies as it did during the last crisis." The only word that is labeled as event trigger in this example is "deficit" because it is the only ongoing event refereed in the news. Note that the words "devaluation", "weakening" and "crisis" could be labeled as event triggers in other news extracts, where the context of use of these words is different, but not in the given example.

Further information: For a more detailed description of the data set and the data collection process please visit: https://cs.uns.edu.ar/~mmaisonnave/resources/ED_data.

Data format: The dataset is split in two folders: training and testing. The first folder contains 2,000 XML files. The second folder contains 200 XML files. Each XML file has the following format.

<?xml version="1.0" encoding="UTF-8"?>

The first three tags (pubdate, file-id and sent-idx) contain metadata information. The first one is the publication date of the news article that contained that text extract. The next two tags represent a unique identifier for the text extract. The file-id uniquely identifies a news article, that can hold several text extracts. The second one is the index that identifies that text extract inside the full article.

The last tag (sentence) defines the beginning and end of the text extract. Inside that text are the tags. Each of these tags surrounds one word that was manually labeled as an event trigger.

This collection includes data for 30 different Twitter datasets associated with real world events. The datasets were collected between 2012 and 2016, always using the streaming API with a set of keywords.These datasets are released in accordance with Twitter's TOS, which allows sharing of tweet IDs and are intended for non-commercial research.Note: Twitter's developer policy doesn't allow sharing more than 1,500,000 tweet IDs (https://dev.twitter.com/overview/terms/policy#updated-policy), unless the author is affiliated with an academic institution (which is my case) and tweet IDs are solely used for non-commercial purposes (https://twittercommunity.com/t/policy-update-clarification-research-use-cases/87566). Hence, by downloading these datasets you agree that you will not use it for commercial purposes.Please cite the following paper if you make use of these datasets for your research: https://onlinelibrary.wiley.com/doi/full/10.1002/asi.24026See README file for more details.

Special events permits applied for through the department of Arts, Culture, and Tourism

The NYC Parks Events Listing database is used to store event information displayed on the Parks website, nyc.gov/parks. There are seven related tables that make up the this database:

1. Events_Events table (This is the primary table that contains basic data about every event. Each record is an event.)
2. Events_Categories (Each record is a category describing an event. One event can be in more than one category.)
3. Events_Images (Each record is an image related to an event. One event can have more than one image.)
4. Events_Links (Each record is a link with more information about an event. One event can have more than one link.)
5. Events_Locations (Each record is a location where an event takes place. One event can have more than one location.)
6. Events_Organizers (Each record contains a group or person organizing an event. One event can have more than one organizer.)
7. Events_YouTube (Each record is a link to a YouTube video about an event. One event can have more than one YouTube video.)

The Events_Events table is the primary table. All other tables can be related by joining on the event_id. This data contains records from 2013 and on. For a complete list of related datasets, please follow This Link

This dataset contains events according to the formal open standard.

Browse LSEG's Events , discover our range of data, indices & benchmarks. Our Data Catalogue offers unrivalled data and delivery mechanisms.

EventWiki is a knowledge base of major events happening throughout mankind history. It contains 21,275 events of 95 types. The details of event entries can be found in our paper submission and documentation file. Data in the knowledge base is mainly harvested from Wikipedia.As Wikipedia, this resource can be distributed and shared under CC-BY 3.0 license.

Techsalerator’s News Event Data in Asia offers a detailed and expansive dataset designed to provide businesses, analysts, journalists, and researchers with comprehensive insights into significant news events across the Asian continent. This dataset captures and categorizes major events reported from a diverse range of news sources, including press releases, industry news sites, blogs, and PR platforms, offering valuable perspectives on regional developments, economic shifts, political changes, and cultural occurrences.

Key Features of the Dataset: Extensive Coverage:

The dataset aggregates news events from a wide range of sources such as company press releases, industry-specific news outlets, blogs, PR sites, and traditional media. This broad coverage ensures a diverse array of information from multiple reporting channels. Categorization of Events:

News events are categorized into various types including business and economic updates, political developments, technological advancements, legal and regulatory changes, and cultural events. This categorization helps users quickly find and analyze information relevant to their interests or sectors. Real-Time Updates:

The dataset is updated regularly to include the most current events, ensuring users have access to the latest news and can stay informed about recent developments as they happen. Geographic Segmentation:

Events are tagged with their respective countries and regions within Asia. This geographic segmentation allows users to filter and analyze news events based on specific locations, facilitating targeted research and analysis. Event Details:

Each event entry includes comprehensive details such as the date of occurrence, source of the news, a description of the event, and relevant keywords. This thorough detailing helps users understand the context and significance of each event. Historical Data:

The dataset includes historical news event data, enabling users to track trends and perform comparative analysis over time. This feature supports longitudinal studies and provides insights into the evolution of news events. Advanced Search and Filter Options:

Users can search and filter news events based on criteria such as date range, event type, location, and keywords. This functionality allows for precise and efficient retrieval of relevant information. Asian Countries and Territories Covered: Central Asia: Kazakhstan Kyrgyzstan Tajikistan Turkmenistan Uzbekistan East Asia: China Hong Kong (Special Administrative Region of China) Japan Mongolia North Korea South Korea Taiwan South Asia: Afghanistan Bangladesh Bhutan India Maldives Nepal Pakistan Sri Lanka Southeast Asia: Brunei Cambodia East Timor (Timor-Leste) Indonesia Laos Malaysia Myanmar (Burma) Philippines Singapore Thailand Vietnam Western Asia (Middle East): Armenia Azerbaijan Bahrain Cyprus Georgia Iraq Israel Jordan Kuwait Lebanon Oman Palestine Qatar Saudi Arabia Syria Turkey (partly in Europe, but often included in Asia contextually) United Arab Emirates Yemen Benefits of the Dataset: Strategic Insights: Businesses and analysts can use the dataset to gain insights into significant regional developments, economic conditions, and political changes, aiding in strategic decision-making and market analysis. Market and Industry Trends: The dataset provides valuable information on industry-specific trends and events, helping users understand market dynamics and identify emerging opportunities. Media and PR Monitoring: Journalists and PR professionals can track relevant news across Asia, enabling them to monitor media coverage, identify emerging stories, and manage public relations efforts effectively. Academic and Research Use: Researchers can utilize the dataset for longitudinal studies, trend analysis, and academic research on various topics related to Asian news and events. Techsalerator’s News Event Data in Asia is a crucial resource for accessing and analyzing significant news events across the continent. By offering detailed, categorized, and up-to-date information, it supports effective decision-making, research, and media monitoring across diverse sectors.

NIGENS (Neural Information Processing group GENeral sounds) is a database provided for sound-related modeling in the field of computational auditory scene analysis, particularly for sound event detection, that has emerged from the Two!Ears project.

It contains 1017 wav files of various lengths (between 1s and 5mins), in total comprising 4h:46m of sound material. Mostly, sounds are provided with 32-bit precision and 44100 Hz sampling rate. The files contain sound events in isolation, i.e. without superposition of ambient or other foreground sources.

Fourteen distinct sound classes are included: alarm, crying baby, crash, barking dog, running engine, burning fire, footsteps, knocking on door, female and male speech, female and male scream, ringing phone, piano. Additionally, there is the general (“anything else”) class. Care has been taken to select sound classes representing different features, like noise-like or pronounced, discrete or continuous.

The general class is a pool of sound events different than the 14 distuingished target sound classes, containing as heterogeneous sounds as possible (303 in total). For example, it includes nature sounds such as wind, rain, or animals, sounds from human-made environments such as honks, doors, or guns, as well as human sounds like coughs. These sounds are intended both as ``disturbance'' sound events (superposing) and as counterexamples to target sound classes.

Wav files are accompanied by annotation (.txt) files that include perceptual on- and offset times of the file's sound events.

You are free to use this database non-commercially under Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 license.

If you use this data set, please cite as:

Ivo Trowitzsch, Jalil Taghia, Youssef Kashef, and Klaus Obermayer (2019). The NIGENS general sound events database. Technische Universität Berlin, Tech. Rep. arXiv:1902.08314 [cs.SD]

In [1], we have developed and analyzed a robust binaural sound event detection training scheme using NIGENS. In [2], we have extended it to join sound event detection and localization through spatial segregation.

[1] Trowitzsch, I., Mohr, J., Kashef, Y., Obermayer, K. (2017). Robust detection of environmental sounds in binaural auditory scenes. IEEE/ACM Transactions on Audio, Speech, and Language Processing 25(6).

[2] Trowitzsch, I., Schymura, C., Kolossa, D., Obermayer, K. (2019). Joining Sound Event Detection and Localization Through Spatial Segregation. accepted for publication in IEEE/ACM Transactions on Audio, Speech, and Language Processing. DOI: 10.1109/TASLP.2019.2958408. E-Preprint: arXiv:1904.00055 [cs.SD].

This operations dashboard shows historic and current data related to this performance measure.The performance measure dashboard is available at 3.19 Value of Special Events. Data Dictionary

This dataset is available on Brisbane City Council’s open data website – data.brisbane.qld.gov.au. The site provides additional features for viewing and interacting with the data and for downloading the data in various formats.

Brisbane City Council Events dataset containing dates, costs, booking requirements, venue and location for events listed on the What’s on in Brisbane experience on the Brisbane City Council website.

The dataset includes combined event information from the many different event categories. Active and healthy, Brisbane Botanic Gardens, Creative, and Library event categories are some examples.

The dataset was created using data from an external service called Trumba. The data is a transformed extract created using the Trumba Calendar API XML feed, that is limited to the next 1,000 events. The transformed extract is converted to a CSV file and uploaded into this dataset daily.

To access and view the data using the Source API (Trumba), use the information below and your preferred link in the Data and Resources section. The Source API is available for this dataset in:

• Trumba Calendar - API - XML feed is limited to the next 1,000 events
• Trumba Calendar - API - RSS feed is limited to the next 1,000 events
• Trumba Calendar - API - CSV feed is limited to the next 2,000 events
• Trumba Calendar - API - JSON feed is limited to the next 2,000 events.

The Data and resources section of this dataset contains further information for this dataset.

This is a list of all Major Safety and Security Events from January of 2014 to the most recently published data within the Federal Transit Administration's major event time series: https://www.transit.dot.gov/ntd/data-product/safety-security-major-only-time-series-data

Monthly Safety and Security data are released to this dataset within three months of being submitted to the NTD. Generally, there will be at least 90-day lag between when the event occurs and when it is included in this data set.

This dataset shows list of MIMOS organized events for external visitors and participated events

Storm Data is provided by the National Weather Service (NWS) and contain statistics on personal injuries and damage estimates. Storm Data covers the United States of America. The data began as early as 1950 through to the present, updated monthly with up to a 120 day delay possible. NCDC Storm Event database allows users to find various types of storms recorded by county, or use other selection criteria as desired. The data contain a chronological listing, by state, of hurricanes, tornadoes, thunderstorms, hail, floods, drought conditions, lightning, high winds, snow, temperature extremes and other weather phenomena.

Excel CSV files showing events in Plymouth between 2017 and 2025 on a yearly basis. Department abbreviations: PCC - Plymouth City Council PCCC - Plymouth City Centre Company PWP - Plymouth Waterfront Partnership

New York City Department of Transportation hosts various safety events throughout New York City at schools, community centers, senior centers and local playground or parks. Types of events includes child passenger safety, bike safety and helmet distribution, public outreach and more to spread safety awareness.

The GLM Events and Flashes Data consist of the size and number of lightning flashes and events. The data were collected from the Geostationary Lightning Mapper (GLM) instrument on the GOES-16 and GOES-17 satellites and are available as L1b events (raw) and L2 flashes (processed). They are available from March 15, 2021, through March 18, 2021, in netCDF-4 and HDF-5 formats.