New answers tagged data-request
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Wikipedia has a page on COVID-19 related curfews and lockdowns: https://en.wikipedia.org/wiki/COVID-19_related_curfews_and_lockdowns (thanks Willeke for pointing to that resource).
https://www.iatatravelcentre.com/international-travel-document-news/1580226297.htm has a list regarding travel restrictions for all countries in the world.
Both come as ...
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Another dataset for control measures for US States are being collected here
Database: https://tinyurl.com/statepolicies
More info in this tweet and its replies: https://twitter.com/JuliaRaifman/status/1245416835211812875
Interested in #COVID19 policy research? We created a database of the dates of state policy changes for researchers to start ...
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There are a few academic datasets that could be useful. The most common datasets are video though.
The Stanford Drone Dataset
https://cvgl.stanford.edu/projects/uav_data/
The Zurich Urban Micro Aerial Vehicle Dataset
http://rpg.ifi.uzh.ch/zurichmavdataset.html
Small UAV Position and Attitude, Raw Sensor, and Aerial Imagery Data Collected over Farm ...
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There is the Official Government Italian COVID Dataset on Github daily updated (16:00 UTC) in JSON and CSV for Country, Region and Province:
https://github.com/pcm-dpc/COVID-19 (The fields are in Italian but there is an English description)
The hard lock-down start the 10th of March 2020 with this rules:
https://www.ilpost.it/2020/03/10/coronavirus-guida-...
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I have made a repository on github to crawl the data from wikipedia about southeast asia countries (Singapore, Malaysia, Vietnam, Thailand etc), as data for all other countries are widely collected.
https://github.com/caiyundong/covid19-sea
The approach of crawling can be used for other countries, and the data can be generated for API usage or file (json ...
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Many resources in one answer, please scroll through
On data.gov there are several (many?) matching datasets
for example, https://catalog.data.gov/dataset/website-analytics
Web traffic statistics for the several City-Parish websites, brla.gov, city.brla.gov, Red Stick Ready, GIS, Open Data etc. Information provided by Google Analytics.
It's from 1995, ...
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ECDC (European centre for disease prevention & control) world data in CSV format, frequently updated: https://opendata.ecdc.europa.eu/covid19/casedistribution/csv
(From https://www.ecdc.europa.eu/en/publications-data/download-todays-data-geographic-distribution-covid-19-cases-worldwide - there's also xml and json)
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I've also found a fairly detailed dataset on github
https://github.com/beoutbreakprepared/nCoV2019/tree/master/latest_data
This is quite exciting as it holds the following data
Demography: age,sex
Geographic: city, province, country, wuhan(0)_not_wuhan(1), latitude, longitude, geo_resolution, lives_in_Wuhan, location, country_new
Dates: ...
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Index of Countries (community wiki)
Global
Johns Hopkins University
WHO
ECDC
Europe
Belgium
Germany and another Germany
Switzerland
Spain
Italy
United Kingdom
North America
United States
NY Times county level
CDC
Asia
General
China
Oceana
Australia
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Here is an ongoing effort from Switzerland to get this data, which is published by the Federal Government as a "machine readable" PDF. It's not daily but weekly.
https://github.com/statistikZH/covid19monitoring_health_mortality
(source: https://www.bfs.admin.ch/bfs/de/home/statistiken/gesundheit/gesundheitszustand/sterblichkeit-todesursachen.assetdetail....
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Chinese data: https://github.com/Avens666/COVID-19-2019-nCoV-Infection-Data-cleaning-
It is incomplete (from February to March 19th) and the explanations are in Chinese.
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In my study of the same problem, I am using this:
https://archive.ics.uci.edu/ml/datasets/Polish+companies+bankruptcy+data,
which contains 64 attributes and over 40000 records.
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German Covid-19 data from RKI (Robert Koch-Institut) on the state (Bundesländer) and county (Kreise) level can be found here.
Data on the county level include patient information such as age group and gender. County level data can be merged with county level information from the INKAR database via county id (Kreiskennziffer).
Update (2020-03-30): There is ...
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The Anthem XPRIZE Pandemic Alliance has pledged the availability of such de-identified data including data on previous outbreaks (i.e. swine-flu, influenza, SARS etc.) It is unclear, however, how soon the datasets will be released to researchers as it was just announced.
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My take on UK data: https://github.com/sainnr/covid19-uk-data-capture. The goal is to represent daily updates published by UK official bodies in the machine-readable format.
Currently, it consists mainly of two parts:
number of cases within the UK (fatal/recovered/positive/total) from 30 Jan till today
number of confirmed positive cases within regions (...
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I suggest Damegender as Python Tool for this taks. This software shares very good open datasets (USA, UK, Spain, Uruguay, ...) and it is giving support to machine learning features to guess gender in names if it doesn't appear in the dataset with good results.
https://pypi.org/project/damegender/
https://github.com/davidam/damegender
For instance,
$ ...
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There are now some fairly complete and up to date such datasets.
An Oxford University group - Future of Humanity Institute - has gathered these data:
https://storage.googleapis.com/static-covid/Containment%20measures/COVID-19%20containment%20measures.zip
Almost simultaneously, a different department, the Blavatnik School of Government from the same ...
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What about this database? It includes government measures...
ACAPS COVID-19: Government Measures Dataset
The COVID-19 Government Measures Dataset puts together all the measures implemented by governments worldwide in response to the Coronavirus pandemic. Data collection includes secondary data review. The researched information available falls into five ...
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We started a worldwide crowdsourcing data collection on policy measures, including lockdowns at the admin1 level (region) and the country level. Currently we coded data for ~13 countries and are continously expanding. You can access the data here:
Collaborative Google Sheets on Policy Measures Against Covid19.
These data are free to use for anybody. We rely ...
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OpenStreetMap has the data, specifically 70k+ entries with the tag "man_made=petroleum_well" (also the less used "man_made=pumping_rig". Here's how they look on the map:
There are many tools to export all the data for a set of tags. In particular, start with manual searches using the OverPass-Turbo API, to see if this tag has good coverage for places you ...
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As Barry Carter explained, parcel data in the US is generally maintained at the county level. Unfortunately this means you usually have to download it from a separate source for each county. Here's a quick explanation of how to find parcel data downloads.
Usually the parcel data can be found by searching for the county auditor's website. Be sure to include ...
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check out the Florida Dept of Revenue FTP site here:
ftp://sdrftp03.dor.state.fl.us/Map%20Data/
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Cafe, library etc are known in the audio research communities as "scenes". Automatically classifying based on the audio from which scene it is from is known as "Acoustic Scene Classification". So those are good keywords when searching for this.
This task has been recurring at the DCASE Machine Learning challenge. So you can find several datasets there:
...
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Spain data can be found here:
https://www.mscbs.gob.es/profesionales/saludPublica/ccayes/alertasActual/nCov-China/situacionActual.htm
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German data can be found here:
https://www.rki.de/DE/Content/InfAZ/N/Neuartiges_Coronavirus/Fallzahlen.html
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The CDC has US-wide cases, per date
https://www.cdc.gov/coronavirus/2019-ncov/cases-updates/testing-in-us.html
It's an HTML table, and I haven't found a more machine readable source. But with Python & Pandas you can easily read the data into a dataframe
import pandas as pd
df = pd.read_html('https://www.cdc.gov/coronavirus/2019-ncov/cases-updates/...
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I successfully parse WHO situation reports and convert them to CSV, from march 1. Older reports are too unstructured.
See here: https://github.com/gibello/whocovid19 (reports in data/csv).
On the site, also links to ECDC and Johns Hopkins data.
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Actions taken in Switzerland are available with machine-readable CSV
Repo 1: https://github.com/zdavatz/covid19_ch#data-on-the-measures-taken-against-covid2019
Repo 2: https://github.com/baffelli/covid-2019-measures
Here we collect a timeline of all containment and public health measure taken in the course of the covid2019 pandemics.
Columns in the CSV ...
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The DCASE2017 challenge, task: Rare Sound Event Detection has a dataset which contains baby cry (as well as glass breaking and gunshot). The target sounds were collected from the FreeSound database.
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Several places for data of Switzerland Covid-19 cases
quasi-official: https://github.com/openZH/covid_19
unofficial: https://github.com/daenuprobst/covid19-cases-switzerland
Comparison between Swiss sources, including links to sources : https://observablehq.com/@republik/sars-cov-2-covid-19-data
more to come (hopefully data, not cases)
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The Italian data from the Civil Protection Agency is updated daily at
https://github.com/pcm-dpc/COVID-19
There are a few data sets (CSV) in there. Aggregated data is published at http://opendatadpc.maps.arcgis.com/apps/opsdashboard/index.html#/b0c68bce2cce478eaac82fe38d4138b1
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Wikidata has a nickname property https://www.wikidata.org/wiki/Property:P1449
which can be used with given names https://www.wikidata.org/wiki/Q202444 or https://www.wikidata.org/wiki/Q82799
which you can query with SPARQL https://query.wikidata.org
This approach may give you a more "real-life" dataset, and statistics about how many nicknames map back to ...
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Two more hypocorism (=diminutive form of a name) datasets:
https://github.com/brianary/Lingua-EN-Nickname/blob/master/nicknames.txt
https://github.com/jonathanhar/diminutives.db:
https://github.com/jonathanhar/diminutives.db/blob/master/female_diminutives.csv
https://github.com/jonathanhar/diminutives.db/blob/master/male_diminutives.csv
Related: large (...
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You can get PM10 and other air pollution measurement data from multiple locations in the city of Zürich, Switzerland
https://data.stadt-zuerich.ch/dataset?q=luftqualit%C3%A4t
The data comes either as
hourly, for the last 24 hours, updated every hour
daily, for the last 30 days, updated every day
daily, going back to 2012 (and also 1983-2011), updated ...
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At this point Wikipedia will have most of the information but not yet machine readable. For a broad data-request on global lockdowns of varying degree, and for an ongoing event, I can't image a machine readable dataset yet.
https://en.wikipedia.org/wiki/2019%E2%80%9320_coronavirus_pandemic
One example would be using school closures, for which there is a ...
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The best that I have found so far is https://opensky-network.org/ It even offers antonymous access to data, but why not join? The REST API is at https://opensky-network.org/apidoc/rest.html
https://www.adsbexchange.com/data/# offers free for non-commercial use data. However, it requires you to set up alive feed of your own data, to share it with others....
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I'm not aware of any definitive source, but this is doable piece-meal I think.
New York Data starting from 2009-2010.
Google has a lot from FluTrends.
Trends in Recorded Influenza Mortality: United States, 1900–2004; I'm assuming datasets are cited/linked to here.
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The paper you posted a link to literally states:
The dataset introduced in this paper is available upon request.
and all of the email addresses of the authors are on the title page. In general, for specific and academic datasets, make the request to the researcher first.
Note: one author has a download page, but it seems this dataset is not there. http:/...
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That was long ago and I doubt you'd find it. Write to the bea directly and see if they can help. It is likely a analog microfiche lost in some cabinet. Good luck. Most data before the eighties was never digitized. You will need to travel to it.
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Instagram is a start. Just scrape and use opencv or similar to identify faces. Or, manually sort faces.
Instagram is a simple http site that can be crawled recursively. It's a matter of counting the images so tweak it and find a good balance. Nobody is going to take 1000 pictures of the same face so dont expect perfection.
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It would be easy if data was available. You are paid to clean it. If you provide your own clean database then people will pay for it if its important.
The cleaning is left up to private data vendors. Gov only provides raw data. It's better because less errors. No reason for them to add complexity.
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