Lower quartile (25th percentile) and lower quintile (20th percentile) gross and disposable (after tax) household income. By Regional Council. Timeseries: Years ending June 2007 – 2020 Source: Stats NZ Household Economic Survey Source: Stats NZ Censuses of Population and Dwellings

Note: In these datasets, a person is defined as up to date if they have received at least one dose of an updated COVID-19 vaccine. The Centers for Disease Control and Prevention (CDC) recommends that certain groups, including adults ages 65 years and older, receive additional doses.

Starting on July 13, 2022, the denominator for calculating vaccine coverage has been changed from age 5+ to all ages to reflect new vaccine eligibility criteria. Previously the denominator was changed from age 16+ to age 12+ on May 18, 2021, then changed from age 12+ to age 5+ on November 10, 2021, to reflect previous changes in vaccine eligibility criteria. The previous datasets based on age 12+ and age 5+ denominators have been uploaded as archived tables.

Starting June 30, 2021, the dataset has been reconfigured so that all updates are appended to one dataset to make it easier for API and other interfaces. In addition, historical data has been extended back to January 5, 2021.

This dataset shows full, partial, and at least 1 dose coverage rates by zip code tabulation area (ZCTA) for the state of California. Data sources include the California Immunization Registry and the American Community Survey’s 2015-2019 5-Year data.

This is the data table for the LHJ Vaccine Equity Performance dashboard. However, this data table also includes ZTCAs that do not have a VEM score.

This dataset also includes Vaccine Equity Metric score quartiles (when applicable), which combine the Public Health Alliance of Southern California’s Healthy Places Index (HPI) measure with CDPH-derived scores to estimate factors that impact health, like income, education, and access to health care. ZTCAs range from less healthy community conditions in Quartile 1 to more healthy community conditions in Quartile 4.

The Vaccine Equity Metric is for weekly vaccination allocation and reporting purposes only. CDPH-derived quartiles should not be considered as indicative of the HPI score for these zip codes. CDPH-derived quartiles were assigned to zip codes excluded from the HPI score produced by the Public Health Alliance of Southern California due to concerns with statistical reliability and validity in populations smaller than 1,500 or where more than 50% of the population resides in a group setting.

These data do not include doses administered by the following federal agencies who received vaccine allocated directly from CDC: Indian Health Service, Veterans Health Administration, Department of Defense, and the Federal Bureau of Prisons.

For some ZTCAs, vaccination coverage may exceed 100%. This may be a result of many people from outside the county coming to that ZTCA to get their vaccine and providers reporting the county of administration as the county of residence, and/or the DOF estimates of the population in that ZTCA are too low. Please note that population numbers provided by DOF are projections and so may not be accurate, especially given unprecedented shifts in population as a result of the pandemic.

Last Version: 3

Authors: Carlota Balsa-Sánchez, Vanesa Loureiro

Date of data collection: 2022/10/28

General description: The publication of datasets according to the FAIR principles, could be reached publishing a data paper (or software paper) in data journals or in academic standard journals. The excel and CSV file contains a list of academic journals that publish data papers and software papers.
File list:

- data_articles_journal_list_v3.xlsx: full list of 124 academic journals in which data papers or/and software papers could be published
- data_articles_journal_list_3.csv: full list of 124 academic journals in which data papers or/and software papers could be published

Relationship between files: both files have the same information. Two different formats are offered to improve reuse

Type of version of the dataset: final processed version

Versions of the files: 3rd version
- Information updated: number of journals, URL, document types associated to a specific journal, publishers normalization and simplification of document types
- Information added : listed in the Directory of Open Access Journals (DOAJ), indexed in Web of Science (WOS) and quartile in Journal Citation Reports (JCR) and/or Scimago Journal and Country Rank (SJR).

Erratum - Data articles in journals Version 3:

Botanical Studies -- ISSN 1999-3110 -- JCR (JIF) Q2
Data -- ISSN 2306-5729 -- JCR (JIF) n/a
Data in Brief -- ISSN 2352-3409 -- JCR (JIF) n/a

Version: 2

Author: Francisco Rubio, Universitat Politècnia de València.

Date of data collection: 2020/06/23

General description: The publication of datasets according to the FAIR principles, could be reached publishing a data paper (or software paper) in data journals or in academic standard journals. The excel and CSV file contains a list of academic journals that publish data papers and software papers.
File list:

- data_articles_journal_list_v2.xlsx: full list of 56 academic journals in which data papers or/and software papers could be published
- data_articles_journal_list_v2.csv: full list of 56 academic journals in which data papers or/and software papers could be published

Relationship between files: both files have the same information. Two different formats are offered to improve reuse

Type of version of the dataset: final processed version

Versions of the files: 2nd version
- Information updated: number of journals, URL, document types associated to a specific journal, publishers normalization and simplification of document types
- Information added : listed in the Directory of Open Access Journals (DOAJ), indexed in Web of Science (WOS) and quartile in Scimago Journal and Country Rank (SJR)

Total size: 32 KB

Version 1: Description

This dataset contains a list of journals that publish data articles, code, software articles and database articles.

The search strategy in DOAJ and Ulrichsweb was the search for the word data in the title of the journals.
Acknowledgements:
Xaquín Lores Torres for his invaluable help in preparing this dataset.

Updated for 2013-17: US Census American Community Survey data table for: Housing subject area. Provides information about: UPPER VALUE QUARTILE (DOLLARS) for the universe of: Owner-occupied housing units. These data are extrapolated estimates only, based on sampling; they are not actual complete counts. The data is based on 2010 Census Tracts. Table ACS_B25078_UPPERVALUEQUARTILE contains both the Estimate value in the E item for the census topic and an adjacent M item which defines the Margin of Error for the value. The Margin of Error (MOE) is the plus/minus range for the item estimate value, where the range between the Estimate minus the Margin of Error and the Estimate plus the Margin of Error defines the 90% confidence interval of the item value. Many of the Margin of Error values are significant relative to the size of the Estimate value. This table contains 1 item(s) extracted from a larger sequence table. This extracted subset represents that portion of the sequence that is considered high priority. Other portions of this sequence that are not included can be identified in the data dictionary information provided in the Supplemental Information section below. This table information is also provided as a customized layer file: B25078_AREA_UPPERVALUEQUARTILE.lyr where the table information is joined to the 2010 TRACTS_AREA census geography on the GEOID item. Both the table and customized lyr file name do not contain the year descriptor (i.e. 2012-2016) for the current ACS series. This is intentional in order to maintain the same table name in each successive ACS update. The alias of each item's (E)stimate and (M)easure of Error value stores this year date information as beginning YY and ending YY, i.e., 'E1216' and 'M1216' followed by the rest of the alias description. In this way users of the data tables or lyr files that support field aliases can determine which ACS series is being represented by the current table contents.

Median, lower quartile, upper quartile statistics for: • Household income for renters • Rental payments By region (Regional Council, Territorial Authority, Auckland local board) and sector of landlord and household composition. Timeseries: 2001, 2006, 2013, 2018 Source: Stats NZ Censuses of Population and Dwellings

Financial ratios of farms, by farm type and quartile boundary, incorporated and unincorporated sectors, Canada. Data are available on an annual basis.

Data source

Taken from chapter 5 of Machine learning cookbook for cyber security

Data dictionary

number in brackets states the number of described features

"..." - stands for multiple optional names that match the given pattern

.

..._ip, ..._port

(4): IP and port of client / srver

packets_...

(3): Number of packets sent by client / server / both

ack_...

(3): Number of ACK packets sent by client / server / both

packets_A_B_ratio

(1): Ratio between packets sent by client and sent by server

asn_...

(2): Number of autonomous systems served as client, server

push_...

(3): Number of packets with PSH flag sent by client / server / both

bytes_...

(3): Number of bytes sent by client / server / both

reset_...

(3): Number of packets with RST flag sent by client / server / both

bytes_A_B_ratio

(1): Ratio between number of bytes sent and number of bytes received

ssl_count_certificates

(1): Number of SSL certificates

cap_date

(1): date of data capturing start

ssl_count_client_...

(6): Client: Number of supported SSL cipher algorithms / ciphersuites / compressions / eliptic curves / key exchange algorithms / MAC algorithms

country_...

(2): Number of countries systems served as client / server

ssl_count_server_...

(6): Server: Number of supported SSL cipher algorithms / ciphersuites / compressions / eliptic curves / key exchange algorithms / MAC algorithms

daysTime

(1): When during the day communication was established

ssl_dom_server_ciphersuite

(1): Number of SSL versions

dns_alexaRank

(1): DNS response server Alexa rank

ssl_dom_server_compression

(5): Dominated SSL ciphersuite / eliptic curve / server name / server rank / version

dns_count_addresses

(4): Number of adresses / answer / authoritative / additional fields in DNS response

ssl_handshake_duration_...

(10): SSL handshake duration: Minimum value, quartile 1, average, median (quartile 2), sum, quartile 3, maximum value, standard deviation, variance, entropy

dns_count_canon_names

(1): Number of canonical names in DNS response

ssl_ratio_...

(7): Ratio between ssl sessions and: expired certificates / client cipher algorithms / ciphersuits / eliptic curves / client key exchange algorithms / client MAC algorithms / server names

dns_flag

(1): DNS response flags combinations

ssl_req_bytes_...

(10): Number of request bytes: Minimum value, quartile 1, average, median (quartile 2), sum, quartile 3, maximum value, standard deviation, variance, entropy

dns_host_name

(1): DNS host name

ssl_resp_bytes_...

(10): Number of response bytes: Minimum value, quartile 1, average, median (quartile 2), sum, quartile 3, maximum value, standard deviation, variance, entropy

dns_min_ttl

(1): DNS response minimal time-to-live

start

(1): session start (date-time)

dns_pre_bad_requests

(1): Number of preceding bad DNS responses

tcp_analysis_...

(6): TCP: Number of packets with Keep Alive packets / lost segments / packets received out of order / retransmitted packets / reused ports / duplicake ACKs

dns_time

(1): Time took to receive DNS response

ttl_A_...

(10): TCP packet time-to-live sent by client: Minimum value, quartile 1, average, median (quartile 2), sum, quartile 3, maximum value, standard deviation, variance, entropy

ds_field_...

(2): Differentiated Services (DS) field sent by client / server

ttl_...

(10): TCP packet time-to-live: Minimum value, quartile 1, average, median (quartile 2), sum, quartile 3, maximum value, standard deviation, variance, entropy

duration

(1): Session duration

ttl_B_...

(10): TCP packet time-to-live sent by server: Minimum value, quartile 1, average, median (quartile 2), sum, quartile 3, maximum value, standard deviation, variance, entropy

http_bytes_...

(10): Number of bytes sent by client over HTTP: Minimum value, quartile 1, average, median (quartile 2), sum, quartile 3, maximum value, standard deviation, variance, entropy.

urg_...

(3): Packets with URG flag sent by client / server / both

http_cookie_count

(1): Total number of cookie values

weekDay

(1): day of week (Sunday, Monday, …)

http_cookie_values_...

(10): Number of cookie values: Minimum value, quartile 1, average, median (quartile 2), sum, quartile 3, maximum value, standard deviation, variance, entropy

domain / subdomain / suffix

(3): Dminated host's URL: domain / subdomain / suffix

http_count_...

(6): HTTP: Number of hosts / unique content types used in request / unique response codes / unique response content types / transactions / unique user agents

is_ad_http

(1): subdomain of HTTP dominated host includes ad-related keywords

http_dom_...

(8): Dominated HTTP: browser / browser version / host / host Alexa rank / operating system / operating system version / request contetn type / response code / response contetn type /

is_cdn_http

(1): subdomain of HTTP dominated host includes CDN-related keywords

http_dom_is_bot

(1): Is most of HTTP connections created by known bot

is_cloud_http

(1): subdomain of HTTP dominated host includes cloud-related keywords

http_GET

(1): Number of HTTP requests submited with GET method

is_...

(3): session protocol is DNS / HTTP / SSL

http_has_...

(4): Does HTTP request have a location / referrer / content type / user agent field

is_g_http

(1): subdomain of HTTP dominated host includes g-related keywords

http_has_resp_content_type

(1): Does HTTP response have a content type field

is_img_http

(1): subdomain of HTTP dominated host includes image-related keywords

http_inter_arrivel_...

(10): HTTP request-response inter arrival time: Minimum value, quartile 1, average, median (quartile 2), sum, quartile 3, maximum value, standard deviation, variance, entropy

is_m_http

(1): subdomain of HTTP dominated host includes mobile-related keywords

http_POST

(1): Number of HTTP requests submited with POST method

is_maker_site_http

(1): subdomain of HTTP dominated host is of a maker's site

http_req_bytes_...

(10): HTTP request bytes: Minimum value, quartile 1, average, median (quartile 2), sum, quartile 3, maximum value, standard deviation, variance, entropy

is_media_http

(1): subdomain of HTTP dominated host includes media-related keywords

http_resp_bytes_...

(10): HTTP response bytes: Minimum value, quartile 1, average, median (quartile 2), sum, quartile 3, maximum value, standard deviation, variance, entropy

is_numeric_url_http

(1): subdomain of HTTP dominated host is numeric

http_time_...

(10): Time took to HTTP server to return response: Minimum value, quartile 1, average, median (quartile 2), sum, quartile 3, maximum value, standard deviation, variance, entropy

is_numeric_url_with_port_http

(1): subdomain of HTTP dominated host is numeric plus port name

label

(1): malware label

is_tv_http

(1): HTTP dominated host has TV-related keywords

labelSS

(1): malware label

B_is_system_port

(1): destination port is in the range of [1, 1023]

packet_inter_arrivel_A_...

(10): Client packets inter arival time: Minimum value, quartile 1, average, median (quartile 2), sum, quartile 3, maximum value, standard deviation, variance, entropy

B_is_user_port

(1): destination port is in the range of [1024, 49151]

packet_inter_arrivel_...

(10): Packets inter arival time: Minimum value, quartile 1, average, median (quartile 2), sum, quartile 3, maximum value, standard deviation, variance, entropy

B_is_dynamic_and_or_private_port

(1): destination port is in the range of [49152, 65535]

packet_inter_arrivel_B_...

(10): Server packets inter arival time: Minimum value, quartile 1, average, median (quartile 2), sum, quartile 3, maximum value, standard deviation, variance, entropy

B_port_is_...

(10): Destination port is one of recent top 10 most frequent: 80, 23, etc.

packet_size_A_...

(10): Client packets size: Minimum value, quartile 1, average, median (quartile 2), sum, quartile 3, maximum value, standard deviation, variance, entropy

subdomain_is_...

(10): subdomain of HTTP dominated host is one of recent top 10 most frequent

packet_size_...

(10): Packets size: Minimum value, quartile 1, average, median (quartile 2), sum, quartile 3, maximum value, standard deviation, variance, entropy

domain_is_...

(10): domain of HTTP dominated host is one of recent top 10 most frequent

packet_size_B_...

(10): Server packets size: Minimum value, quartile 1, average, median (quartile 2), sum, quartile 3, maximum value, standard deviation, variance, entropy

suffix_is_...

(4): suffix of HTTP dominated host is one of recent top 4most frequent: com, net, etc.

Canadian Internet use survey, household access to the Internet at home, by household income quartile for Canada and provinces from 2010 and 2012.

Percentage of Internet users by selected Internet service and technology, such as; home Internet access, use of smart home devices, use of smartphones, use of social networking accounts, use or purchase of streaming services, use of government services online and online shopping.

In 2020, 59 percent of high school graduates from families in the lowest income quartile in the United States enrolled in college. This was a decrease of one percent from the previous year.

Affordability ratios calculated by dividing house prices by gross annual workplace-based earnings. Based on the median and lower quartiles of both house prices and earnings in England and Wales.

Conferences are an essential tool for scientific communication. In disciplines such as Computer Science, over 50% of original research results are published in conference proceedings. In this dataset, there is is a list of conference proceedings, categorized Q1 - Q4 by analogy with SJR journal quartiles. We have analyzed the role of conference proceedings in various disciplines and propose an alternative approach to research evaluation based on conference proceedings and Scimago Journal Rank (SJR). Comparison of the resulting list in Computer Science with the CORE ranking showed a 62% match, as well as an average rank correlation of the distribution by category.

This dataset contains gender pay gap figures for all employees in London and large employers in London. The pay gap figures for GLA group organisations can be found on their respective websites. The gender pay gap is the difference in the average hourly wage of all men and women across a workforce. If women do more of the less well paid jobs within an organisation than men, the gender pay gap is usually bigger. The UK government publish gender pay gap figures for all employers with 250 or more employees. A cut of this dataset that only shows employers that are registered in London can be found below. Read a report by the Local Government Association (LGA) that summarises the mean and median pay gaps in local authorities, as well as the distribution of staff across pay quartiles. This dataset is one of the Greater London Authority's measures of Economic Fairness. Click here to find out more. This dataset is one of the Greater London Authority's measures of Economic Development strategy. Click here to find out more.

Affordability ratios calculated by dividing house prices by gross annual residence-based earnings. Based on the median and lower quartiles of both house prices and earnings in England and Wales.

Dataset contains patient identification from 1 to 82 (ID), steatosis grade (Steatosis), inflammation grade (Inflammation), fibrosis stage (Fibrosis), point shear wave elasticity (pSWE), μn = mean intensity normalized by its maximal value (munMean), 1/α = reciprocal of the scatterer clustering parameter (ialphaMean), k = coherent-to-diffuse signal ratio (kMean), 1/(k + 1) = diffuse-to-total signal power ratio (ikappaMean), mean intensity normalized by its maximal value inter-quartile range (munIQR), reciprocal of the scatterer clustering parameter inter-quartile range (ialphaIQR), coherent-to-diffuse signal ratio inter-quartile range (kIQR), diffuse-to-total signal power ratio inter-quartile range (ikappaIQR),total attenuation coefficient slope (TotalACS), local attenuation coefficient slope (LocalACS). (XLSX)