The Experience API (xAPI) is a standardized reporting format for activity metrics to be recorded in a Learning Records Store. This xAPI Profile describes various forms of online teamwork and the associated activities

Getting comfortable with APIs by: understanding how they work; learn how they are used; and gain experience using them.

Borealis Company Export Import Records. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.

The focus of this Profile is on faculty member activities that are mediated electronically because this is more pertinent to the context in which xAPI data is likely to be gathered. Use Case This is for tracking the typical activities that faculty members (not faculties per se) engage in and that might be reported in their annual report, CV. Could also be used by Med Ed Research Centre Directors to provide reporting on their activities.

Borealis Ag Trabrennstrasse Company Export Import Records. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.

Borealis Plastomers Bv Company Export Import Records. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.

This study investigated honey bee abundance and A. borealis parasitism rates in an urban environment in San Francisco, California.

The current dataset contains 237M Tweet IDs for Twitter posts that mentioned "COVID" as a keyword or as part of a hashtag (e.g., COVID-19, COVID19) between March and July of 2020. Sampling Method: hourly requests sent to Twitter Search API using Social Feed Manager, an open source software that harvests social media data and related content from Twitter and other platforms. NOTE: 1) In accordance with Twitter API Terms, only Tweet IDs are provided as part of this dataset. 2) To recollect tweets based on the list of Tweet IDs contained in these datasets, you will need to use tweet 'rehydration' programs like Hydrator (https://github.com/DocNow/hydrator) or Python library Twarc (https://github.com/DocNow/twarc). 3) This dataset, like most datasets collected via the Twitter Search API, is a sample of the available tweets on this topic and is not meant to be comprehensive. Some COVID-related tweets might not be included in the dataset either because the tweets were collected using a standardized but intermittent (hourly) sampling protocol or because tweets used hashtags/keywords other than COVID (e.g., Coronavirus or #nCoV). 4) To broaden this sample, consider comparing/merging this dataset with other COVID-19 related public datasets such as: https://github.com/thepanacealab/covid19_twitter https://ieee-dataport.org/open-access/corona-virus-covid-19-tweets-dataset https://github.com/echen102/COVID-19-TweetIDs

14,478,518 tweet ids for #WomensMarch collected with Documenting the Now's twarc from January 21-28, 2017. Tweets can be “rehydrated” with Documenting the Now’s twarc (https://github.com/DocNow/twarc). twarc.py –hydrate WomensMarch_tweet_ids.txt > WomensMarch.json Also included are the logs files for the Filter API and Search API queries. The Filter API query captures the cumulative number of dropped tweets.

Data Collection: Data was collected using a custom web application (Communalytic, available at: https://communalytic.com/) that used Reddit’s public API (https://www.reddit.com/dev/api/). We sampled one percent of public Reddit comments posted in 2016 from AskScience. Since the dataset was collected retroactively, it does not include comments deleted by authors or moderators. Manual Coding: The sample comments were then manually coded using the 'Leaning in the Wild' Coding Schema by three independent coders, each of whom had first completed a schema tutorial training-module. Each coder (1) reviewed a submission that started a thread and was often framed as a question (see the "submissions_title" column) and then (2) assigned up to three applicable codes to the reply message (see the "text" column). The values stored under columns C1-C8 represent the number of coders who agreed on a given code.

This data includes the python code which accessed the Twitter API to collect all public tweets which used the hashtag #DisabilityDongle. It then includes the excel file with the text of all public tweets, the excel file which excludes tweets from Liz Jackson, the originator of the hashtag and concept of #DisabilityDongle, and a colour coded excel file which identifies the tweets as being of a particular kind. The kinds of tweets and description of sorting and reasons for sorting are presented in the Microsoft Word Document "Disability Dongle Data".

This dataset is a list of journal articles published between 2020-2022 that were funded by the Fonds du Recherche du Québec (FRQ). The list of articles was assembled using Crossref’s public rest API Funder Endpoints.

We are seeking answers to two key questions regarding the influence of marine processes on Arctic climate: 1) How will the increased flow of Pacific waters through the Canadian Archipelago affect the dynamics of climate-active gases in the ocean, and 2) How will these gases be affected by a reduction of sea-ice cover, and increased areas of open water? These questions have been addressed by our multidisciplinary team during two expeditions on the Canadian research ice-breaker Amundsen as part of the International Polar Year. The expeditions took place during the fall of 2007 and 2008. Eleven (2007) and ten (2008) Arctic SOLAS scientists from 7 Canadian institutions participated to these expeditions which allowed a unique and extensive longitudinal survey of these trace gases and aerosols in the High Canadian Arctic, from Baffin Bay to the Beaufort Sea. The missions enabled us to collect new oceanographic and atmospheric data on the distribution and cycling of DMS, N2O, and VOCs across the Canadian Archipelago and to relate these measurements to the distribution and chemical characteristics of aerosol particles. Activities of this program where coordinated with those of the IPY programs CFL, the Canadian program ArcticNet, and the international programs OASIS and SOLAS.

A list of 10,538 Twitter IDs for tweets harvested between 4 January at 11am and 9 January at 11am using Social Feed Manager. As this used the search API, the 4 January at 11am crawl went back about 5-9 days. Tweet IDs included, as is a log of the decisions made to curate this dataset.

Model outputs and configuration files associated with the paper "ExoPlaSim: Extending the Planet Simulator for Exoplanets". Contained are netCDF files for the synchronous rotation experiments, as well as CFG files (plain-text) which can be loaded by ExoPlaSim to replicate model runs (only available for models produced after the ExoPlaSim python API was developed; part of the pN2 experiment, the THAI comparison, and the HZ experiment). File names are descriptive, with CO2 in microbars, pN2 in bars, flux in W/m^2, effective temperature in K, and (if specified) rotation period in days.

A list of occurrence data on calls for service in the City of Guelph in the 2016 calendar year was obtained from the Guelph Police Open Data portal. An OpenStreetMap based API was used to generate latitude and longitude coordinates for the occurrence data.

As part of our ongoing research on misinformation and disinformation of various types, we conducted an exploratory analysis of tweets discussing an unverified report that Russian forces engaged in a chemical attack in Mariupol, Ukraine. This claim was made on April 11 by Ukraine’s Azov regiment. At the time when this claim was first reported, Mariupol was surrounded by Russian troops, making it difficult, if not nearly impossible, for journalists to gain access to the city and to interview local sources. We were interested in examining how this claim was discussed on social media because if it was true, it had the potential to galvanize the world’s sentiments in support of Ukraine and against Russia. Using Twitter’s Academic Track API, we retroactively collected 246,189 public tweets posted between April 6 and 13, 2022 to analyze how Twitter users were discussing this claim. We collected tweets related to this case a few days before and after April 11 to capture speculation before the accusation, and the reaction to it. We used the search query “chemical (weapons OR weapon) (Mariupol OR Ukraine)” to collect data. (For data completeness, we kept 12,193 tweets referenced by one of the tweets in the search results.)

2,661,117 tweet ids for #healthcanada #NACI #fordnation #medicalfreedom #covid19 #covid19vaccines #protectourfamilies #protectyourchildren #holdtheline tweets, collected with Documenting the Now's twarc. Tweets can be “rehydrated” with Documenting the Now’s twarc, or Hydrator. twarc hydrate tweet-ids.txt > tweets.jsonl ID files are available for all hashtags or some individual hashtags: covid19-ids.txt covid19vaccines-ids.txt fordnation-ids.txt healthcanada-ids.txt healthcanada-NACI-fordnation-medicalfreedom-covid19-covid19vaccines-protectourfamilies-protectyourchildren-holdtheline-ids.txt holdtheline-ids.txt medicalfreedom-ids.txt NACI-ids.txt protectyourchildren-ids.txt Tweets were collected via the Standard Search API on: November 18, 2021 November 21, 2021 November 26, 2021 December 1, 2021

Data collection: Using Twitter's Search API, we collected 363,706 public tweets (in English) mentioning #elxn43 and directed at 1,116 candidates running for office during the 2019 Federal election in Canada. Tweets were collected between September 29 and October 28, 2019. Manual coding: The data set contains a random sample of 3,637 tweets (1% sample) hand coded as either 'toxic' or 'insulting' by using three coders. Only tweets that were flagged by all three coders were considered as either 'toxic' (TOXICITY_3CODERS_AGREE=1) or 'insulting' (INSULT_3CODERS_AGREE = 1).

Description: Tweet ids for 1288882 tweets for the following hashtags “#onpoli, #ONexln, #ontariovotes, #wynne, #DougFord, #fordnation, #KathleenWynne, #AndreaHorwath, #Horwath, #MikeSchreiner collected using the Twitter Search (every 5 days) and Filter API (every 15 minutes) from May 9 2018 to June 14 2018 via Ed Summers’ twarc tool : https://github.com/DocNow/twarc.