This dataset is about books. It has 1 row and is filtered where the book is The most dangerous man in the world : the inside story on Julian Assange and the Wikileaks secrets. It features 7 columns including author, publication date, language, and book publisher.

This dataset contains data and analysis from the article Do State Department Travel Warnings Reflect Real Danger?

Key findings

• On the whole, there is a significant relationship between the number of American deaths abroad per capita and the number of travel warnings a country receives
• Mexico, Mali, and Israel have been targeted by the most travel warnings in recent years, but Americans are more likely to be killed in Thailand, Pakistan, and the Philippines
• Several countries with relatively high rates of American death have not been issued a single travel warning in ~7 years, including Belize, Guyana, and Guatemala
• Several countries with relatively low rates of American death have been issued a relatively high number of travel warnings in ~7 years, including Israel, Turkey, and Saudi Arabia
• Overall, countries subject to travel warnings do not see notable declines in American visitors in the 6 months after a warning is issued

Data sources

• BTSOriginUS_10_09_to_06_16.csv Air Carrier Statistics Database export, Bureau of Transportation Statistics
• SDamerican_deaths_abroad_10_09_to_06_16.csv U.S. State Department
• SDwarnings_10_09to06_16.csv U.S. State Department via Internet Archive

Charts / data visualizations

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This dataset is about book subjects. It has 1 row and is filtered where the books is That near-death thing : inside the most dangerous race in the world. It features 10 columns including number of authors, number of books, earliest publication date, and latest publication date.

THIS DATASET WAS LAST UPDATED AT 8:10 AM EASTERN ON AUG. 23

OVERVIEW

2019 had the most mass killings since at least the 1970s, according to the Associated Press/USA TODAY/Northeastern University Mass Killings Database.

In all, there were 45 mass killings, defined as when four or more people are killed excluding the perpetrator. Of those, 33 were mass shootings . This summer was especially violent, with three high-profile public mass shootings occurring in the span of just four weeks, leaving 38 killed and 66 injured.

A total of 229 people died in mass killings in 2019.

The AP's analysis found that more than 50% of the incidents were family annihilations, which is similar to prior years. Although they are far less common, the 9 public mass shootings during the year were the most deadly type of mass murder, resulting in 73 people's deaths, not including the assailants.

One-third of the offenders died at the scene of the killing or soon after, half from suicides.

About this Dataset

The Associated Press/USA TODAY/Northeastern University Mass Killings database tracks all U.S. homicides since 2006 involving four or more people killed (not including the offender) over a short period of time (24 hours) regardless of weapon, location, victim-offender relationship or motive. The database includes information on these and other characteristics concerning the incidents, offenders, and victims.

The AP/USA TODAY/Northeastern database represents the most complete tracking of mass murders by the above definition currently available. Other efforts, such as the Gun Violence Archive or Everytown for Gun Safety may include events that do not meet our criteria, but a review of these sites and others indicates that this database contains every event that matches the definition, including some not tracked by other organizations.

This data will be updated periodically and can be used as an ongoing resource to help cover these events.

Using this Dataset

To get basic counts of incidents of mass killings and mass shootings by year nationwide, use these queries:

Mass killings by year

Mass shootings by year

To get these counts just for your state:

Filter killings by state

Definition of "mass murder"

Mass murder is defined as the intentional killing of four or more victims by any means within a 24-hour period, excluding the deaths of unborn children and the offender(s). The standard of four or more dead was initially set by the FBI.

This definition does not exclude cases based on method (e.g., shootings only), type or motivation (e.g., public only), victim-offender relationship (e.g., strangers only), or number of locations (e.g., one). The time frame of 24 hours was chosen to eliminate conflation with spree killers, who kill multiple victims in quick succession in different locations or incidents, and to satisfy the traditional requirement of occurring in a “single incident.”

Offenders who commit mass murder during a spree (before or after committing additional homicides) are included in the database, and all victims within seven days of the mass murder are included in the victim count. Negligent homicides related to driving under the influence or accidental fires are excluded due to the lack of offender intent. Only incidents occurring within the 50 states and Washington D.C. are considered.

Methodology

Project researchers first identified potential incidents using the Federal Bureau of Investigation’s Supplementary Homicide Reports (SHR). Homicide incidents in the SHR were flagged as potential mass murder cases if four or more victims were reported on the same record, and the type of death was murder or non-negligent manslaughter.

Cases were subsequently verified utilizing media accounts, court documents, academic journal articles, books, and local law enforcement records obtained through Freedom of Information Act (FOIA) requests. Each data point was corroborated by multiple sources, which were compiled into a single document to assess the quality of information.

In case(s) of contradiction among sources, official law enforcement or court records were used, when available, followed by the most recent media or academic source.

Case information was subsequently compared with every other known mass murder database to ensure reliability and validity. Incidents listed in the SHR that could not be independently verified were excluded from the database.

Project researchers also conducted extensive searches for incidents not reported in the SHR during the time period, utilizing internet search engines, Lexis-Nexis, and Newspapers.com. Search terms include: [number] dead, [number] killed, [number] slain, [number] murdered, [number] homicide, mass murder, mass shooting, massacre, rampage, family killing, familicide, and arson murder. Offender, victim, and location names were also directly searched when available.

This project started at USA TODAY in 2012.

Contacts

Contact AP Data Editor Justin Myers with questions, suggestions or comments about this dataset at jmyers@ap.org. The Northeastern University researcher working with AP and USA TODAY is Professor James Alan Fox, who can be reached at j.fox@northeastern.edu or 617-416-4400.

The Armed Conflict Location & Event Data Project (ACLED) is a US-registered non-profit whose mission is to provide the highest quality real-time data on political violence and demonstrations globally. The information collected includes the type of event, its date, the location, the actors involved, a brief narrative summary, and any reported fatalities. ACLED users rely on our robust global dataset to support decision-making around policy and programming, accurately analyze political and country risk, support operational security planning, and improve supply chain management.ACLED’s transparent methodology, expert team composed of 250 individuals speaking more than 70 languages, real-time coding system, and weekly update schedule are unrivaled in the field of data collection on conflict and disorder. Global Coverage: We track political violence, demonstrations, and strategic developments around the world, covering more than 240 countries and territories.Published Weekly: Our data are collected in real time and published weekly. It is the only dataset of its kind to provide such a high update frequency, with peer datasets most often updating monthly or yearly.Historical Data: Our dataset contains at least two full years of data for all countries and territories, with more extensive coverage available for multiple regions.Experienced Researchers: Our data are coded by experienced researchers with local, country, and regional expertise and language skills.Thorough Data Collection and Sourcing: Pulling from traditional media, reports, local partner data, and verified new media, ACLED uses a tailor-made sourcing methodology for individual regions/countries.Extensive Review Process: Our data go through an exhaustive multi-stage quality assurance process to ensure their accuracy and reliability. This process includes both manual and automated error checking and contextual review.Clean, Standardized, and Validated: Our data can be easily connected with internal dashboards through our API or downloaded through the Data Export Tool on our website.Resources Available on ESRI’s Living AtlasACLED data are available through the Living Atlas for the most recent 12 month period. The data are mapped to the centroid of first administrative divisions (“admin1”) within countries (e.g., states, districts, provinces) and aggregated by month. Variables in the data include:The number of events per admin1-month, disaggregated by event type (protests, riots, battles, violence against civilians, explosions/remote violence, and strategic developments)A conservative estimate of reported fatalities per admin1-monthThe total number of distinct violent actors active in the corresponding admin1 for each monthThis Living Atlas item is a Web Map, which provides a pre-configured view of ACLED event data in a few layers:ACLED Event Counts layer: events per admin1-month, styled by predominant event type for each location.ACLED Violent Actors layer: the number of distinct violent actors per admin1-month.ACLED Fatality Estimates layer: the estimated number of fatalities from political violence per admin1-month.These layers are based on the ACLED Conflict and Demonstrations Event Data Feature Layer, which has the same data but only a basic default styling that is similar to the Event Counts layer. The Web Map layers are configured with a time-slider component to account for the multiple months of data per admin1 unit. These indicators are also available in the ACLED Conflict and Demonstrations Data Key Indicators Group Layer, which includes the same preconfigured layers but without the time-slider component or background layers.Resources Available on the ACLED WebsiteThe fully disaggregated dataset is available for download on ACLED's website including:Date (day, month, year)Actors, associated actors, and actor typesLocation information (ADMIN1, ADMIN2, ADMIN3, location and geo coordinates)A conservative fatality estimateDisorder type, event types, and sub-event typesTags further categorizing the data A notes column providing a narrative of the event For more information, please see the ACLED Codebook.To explore ACLED’s full dataset, please register on the ACLED Access Portal, following the instructions available in this Access Guide. Upon registration, you’ll receive access to ACLED data on a limited basis. Commercial users have access to 3 free data downloads company-wide with access to up to one year of historical data. Public sector users have access to 6 downloads of up to three years of historical data organization-wide. To explore options for extended access, please reach out to our Access Team (access@acleddata.com).With an ACLED license, users can also leverage ACLED’s interactive Global Dashboard and check in for weekly data updates and analysis tracking key political violence and protest trends around the world. ACLED also has several analytical tools available such as our Early Warning Dashboard, Conflict Alert System (CAST), and Conflict Index Dashboard.

Analysis of ‘The Lost Journalists: Dataset of journalist deaths’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/yamqwe/journalist-deathse on 13 February 2022.

--- Dataset description provided by original source is as follows ---

Credit for the original dataset goes to CPJ

About this dataset

In-the-News:

• NRT: AT LEAST 122 MEDIA PROFESSIONALS KILLED GLOBALLY IN 2016
• All Africa: Africa: Journalist Killings Ease From Record Highs As Murders Down, Combat Deaths Up
• BBC: The lost journalists of 2016

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Methodology

CPJ began compiling detailed records on journalist deaths in 1992. We apply strict journalistic standards when investigating a death. One important aspect of our research is determining whether a death was work-related. As a result, we classify deaths as "motive confirmed" or "motive unconfirmed."

We consider a case "confirmed" only if we are reasonably certain that a journalist was murdered in direct reprisal for his or her work; was killed in crossfire during combat situations; or was killed while carrying out a dangerous assignment such as coverage of a street protest. We do not include journalists who are killed in accidents such as car or plane crashes.

We include only confirmed cases in the statistical analyses in this database.

When the motive is unclear, but it is possible that a journalist was killed because of his or her work, CPJ classifies the case as "unconfirmed" and continues to investigate. We regularly reclassify cases based on our ongoing research.

Our archives include narrative capsules of all journalists killed, including the cases in which the motive is unconfirmed. In cases where the place of death is incidental to the journalist's killing, we have listed the country where the fatal attack occurred to be the place of the journalist's death (for example, in a case where a journalist is hit by shrapnel in one country and evacuated to another, where he or she dies, CPJ lists the country in which he or she was hit as the place of death).

CPJ defines journalists as people who cover news or comment on public affairs through any media -- including in print, in photographs, on radio, on television, and online. We take up cases involving staff journalists, freelancers, stringers, bloggers, and citizen journalists. The combination of daily reporting and statistical data forms the basis of our case-driven and long-term advocacy.

In 2003, CPJ began documenting the deaths of media support workers. We did so in recognition of the vital role these individuals play in newsgathering. These workers include translators, drivers, fixers, and administrative workers.

Our archives include narrative capsules for media workers killed on duty. These cases are not included our statistical analyses.

About CPJ

The Committee to Protect Journalists is an independent, nonprofit organization that promotes press freedom worldwide. We defend the right of journalists to report the news without fear of reprisal.

Additional Reading
Investigative journalism in Africa – “Walking through a minefield at midnight”
Iraq: The deadliest war for journalists
Being a journalist in Mexico is getting even more dangerous

Source: Committee to Protect Journalists

This dataset was created by Journalism, News, and Media and contains around 2000 samples along with Date, Unnamed: 18, technical information and other features such as: - Local/ Foreign - Unnamed: 20 - and more.

How to use this dataset

• Analyze Coverage in relation to Taken Captive
• Study the influence of Organization on Unnamed: 21
• More datasets

Acknowledgements

If you use this dataset in your research, please credit Journalism, News, and Media

Start A New Notebook!

--- Original source retains full ownership of the source dataset ---

This article examines the effects of the militarization of public security and the conflicts it triggers on a central democratic institution – press freedom. We focus on Mexico, which experienced multiple waves of assassination of local journalists after the federal government declared a War on Drugs against the country’s main cartels and deployed the military to the country’s most conflictive regions. We argue that violence against journalists is tied to the outbreak of criminal wars – the multiple localized turf wars and power struggles unleashed by the federal military intervention. Subnational politicians and their security forces are at the center of these conflicts because they partner with drug lords to enable local operations of the transnational drug trafficking industry. To defend their interests, they have individual and shared incentives to prevent city- and town-level journalists from (or punish them for) publishing fine-grained information that may compromise their criminal and political survival and their quest for local control. We compiled the most comprehensive dataset available on lethal attacks on journalists from 1994 to 2019 to test our claims. Using a difference-in-differences design, we show that violence against local journalists substantially increased in militarized regions, where the military decapitated the cartels and fragmented the criminal underworld, triggering violent competition for criminal governance – de facto rule over territories, people, and illicit economies. Evidence from original focus groups and interviews with at-risk reporters suggests that governors, mayors, and their police forces possibly joined cartels in murdering journalists to mitigate the risks of unwanted information and to minimize the costs of criminal governance by silencing the press and society. Our study offers a sobering lesson of how the militarization of anti-crime policy and the onset of criminal wars can undermine local journalism, press freedom, and democracy.

The general purpose of my model is to identify three snake species in Australia. I will first use the Oxyuranus microlepidotus Taipan, which is referred to as the Inland Taipan (Billabong Sanctuary, n.d). I will then use the Oxyuranus scutellatus Taipan, which is referred to as the Coastal Taipan (Beatson, n.d). My third classification I will be using is the Pseudonaja textilis Brown-Snake, which is referred to as the Eastern-Brown-Snake (Wikipedia, 2024). I have created an object detection model. My data was derived from Google Images and iNaturalist. When searching for each snake, I typed in the name of the snake for each class. I mainly focused on getting clear-cut images that mainly focus on the head of the snake, since most of the differences between each focus there. I am hoping this project will reach out to audiences, such as any student interested in science, any professors that may be interested or be teaching Environmental Studies courses, and overall anyone interested in learning more about Australian snake species, since each of these species is some of the most dangerous in the world. My model will be valuable in being able to distinguish between the species, since each looks very similar. So, my overall goal of the project is to be able to identify the physical differences between the snakes, so scientists and educators can use this model to detect dangerous snakes in Australia. This model was created for a class assignment in AI and Natural History at St. Mary’s College of Maryland.

References: Beatson, A. C. (n.d.). Coastal Taipan. The Australian Museum. https://australian.museum/learn/animals/reptiles/coastal-taipan/#:~:text=Scientific%20name%3A%20Oxyuranus%20scutellatus,mungkan%20people%20of%20Cape%20York. Billabong Sanctuary. (n.d.). Discover the deadly beauty of the inland taipan. https://www.billabongsanctuary.com.au/inland-taipan/ Wikimedia Foundation. (2024b, March 13). Eastern Brown snake. Wikipedia. https://en.wikipedia.org/wiki/Eastern_brown_snake#:~:text=The%20eastern%20brown%20snake%20(Pseudonaja,snake%20in%20the%20family%20Elapidae.

Background

​Annually in the UK, around 60,000 people develop a pulmonary embolism (PE) and 200,000 a deep vein thrombosis (DVT) and the number of emergency admissions for suspected PE and DVT is increasing. Diagnosing PE and DVT remains a challenge due to the non-specific nature of presenting symptoms. Further tests are often required and each year the number of CTPAs and USS performed for suspected VTE increases.

There is great interest in finding better tools to identify those with the highest likelihood of a DVT and PE, so that precious screening services can be focused where needed most. A number of tools have been suggested but few have been adopted in clinical practice.

Methods such as age-adjusted D-dimer tests and 4PEPs and 4D scores aim to predict PE and DVT more accurately. Implementing a more precise system could revolutionise how we diagnose and treat these dangerous conditions. This dataset enables an exploration of VTE to better understand disease, identify patients at most risk of the poorest outcomes and to improve health services through the development of new prognostic tools.

PIONEER geography: The West Midlands (WM) has a population of 5.9 million & includes a diverse ethnic & socio-economic mix. UHB is one of the largest NHS Trusts in England, providing direct acute services & specialist care across four hospital sites, with 2.2 million patient episodes per year, and 2,750 beds. UHB runs a fully electronic healthcare record (EHR) (PICS; Birmingham Systems), a shared primary & secondary care record (Your Care Connected) & a patient portal “My Health.” 

Methodology: A specific pipeline was designed for the generation of the synthetic version of thromboembolic events dataset including data pre-processing, synthetising, and post-process steps. In brief, a generative adversarial network model (CTGAN) in the SDV package (N. Patki, 2016) was employed to generate synthetic dataset which is statistically equivalent to a real dataset. Pre-process and post-process steps were customised to improve the realisticity of the synthetic data.

Scope: Enabling data-driven research and machine learning models towards improving the diagnosis of Thromboembolic events (PE/DVT). Real-world dataset linked. The dataset includes large patient demographics, clinical scores, and medical conditions for PE/DVT patients, alongside outcomes taken from ICD-10 & SNOMED-CT codes.

Available supplementary data: real-world PE/DVT cohort.

Available supplementary support: Analytics, model build, validation & refinement; A.I.; Data partner support for ETL (extract, transform & load) process, Clinical expertise, Patient & end-user access, Purchaser access, Regulatory requirements, Data-driven trials, “fast screen” services.

National Geographic article under Wildlife Watch, concerning illegal logging in Cambodia

CONTEXT

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F21407317%2Fe141f4f5a4155a96827db4c23bb27eba%2FToutatis.jpg?generation=1721308000774356&alt=media" alt=""> (Asteroid (4179) Tautatis is a potentially dangerous object passing at a distance of 2.3 times the distance from the Moon. (available in our dataset))

There are many dangerous bodies in space, one of them is N.E.O. - "Nearest Earth Objects". Some such bodies really pose a danger to the planet Earth, NASA classifies them as "is_hazardous". This dataset contains ALL NASA observations of similar objects from 1910 to 2024!!!

There are 338,199 records of N.E.O. in the Dataset!

Try to predict "is_hazardous" as accurately as possible! (otherwise we will not be ready for an asteroid attack)

SOURCES

NASA Open API

Wikipedia

Inspirer

Latin America is the most violent region in the world, with many countries also suffering from high levels of criminality and the presence of powerful criminal organizations. Identifying government responses that improve citizen security is imperative. Existing research argues that improving intergovernmental coordination helps the state combat criminality, but has limited its analysis to political factors that affect coordination. I study the impact of increasing intergovernmental coordination between law enforcement agencies. Using the generalized synthetic control method, original data on the staggered implementation of a police reform that increased intergovernmental police coordination and detailed data on criminal organizations and criminality in Guanajuato, Mexico, I find that the reform weakened criminal organizations and reduced violent crime, but increased violence.