cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.3693750
title: Parti Québécois (PQ) web archive collection derivatives

description: Web archive derivatives of the Parti Québécois (PQ) collection from the Bibliothèque et Archives nationales du Québec. The derivatives were created with the Archives Unleashed Toolkit. Merci beaucoup BAnQ! These derivatives are in the Apache Parquet format, which is a columnar storage format. These derivatives are generally small enough to work with on your local machine, and can be easily converted to Pandas DataFrames. See this notebook for examples. <strong>Domains</strong> <pre><code class="language-java">.webpages().groupBy(ExtractDomainDF($"url").alias("url")).count().sort($"count".desc)</code></pre> Produces a DataFrame with the following columns: domain count <strong>Web Pages</strong> <pre><code class="language-java">.webpages().select($"crawl_date", $"url", $"mime_type_web_server", $"mime_type_tika", RemoveHTMLDF(RemoveHTTPHeaderDF(($"content"))).alias("content"))</code></pre> Produces a DataFrame with the following columns: crawl_date url mime_type_web_server mime_type_tika content <strong>Web Graph</strong> <pre><code class="language-java">.webgraph()</code></pre> Produces a DataFrame with the following columns: crawl_date src dest anchor <strong>Image Links</strong> <pre><code class="language-java">.imageLinks()</code></pre> Produces a DataFrame with the following columns: src image_url <strong>Binary Analysis</strong> Audio Images PDFs Presentation program files Spreadsheets Text files Word processor files
DOI: 10.5281/zenodo.3693751
title: Parti Québécois (PQ) web archive collection derivatives

description: Web archive derivatives of the Parti Québécois (PQ) collection from the Bibliothèque et Archives nationales du Québec. The derivatives were created with the Archives Unleashed Toolkit. Merci beaucoup BAnQ! These derivatives are in the Apache Parquet format, which is a columnar storage format. These derivatives are generally small enough to work with on your local machine, and can be easily converted to Pandas DataFrames. See this notebook for examples. <strong>Domains</strong> <pre><code class="language-java">.webpages().groupBy(ExtractDomainDF($"url").alias("url")).count().sort($"count".desc)</code></pre> Produces a DataFrame with the following columns: domain count <strong>Web Pages</strong> <pre><code class="language-java">.webpages().select($"crawl_date", $"url", $"mime_type_web_server", $"mime_type_tika", RemoveHTMLDF(RemoveHTTPHeaderDF(($"content"))).alias("content"))</code></pre> Produces a DataFrame with the following columns: crawl_date url mime_type_web_server mime_type_tika content <strong>Web Graph</strong> <pre><code class="language-java">.webgraph()</code></pre> Produces a DataFrame with the following columns: crawl_date src dest anchor <strong>Image Links</strong> <pre><code class="language-java">.imageLinks()</code></pre> Produces a DataFrame with the following columns: src image_url <strong>Binary Analysis</strong> Audio Images PDFs Presentation program files Spreadsheets Text files Word processor files
DOI: 10.26300/87mc-rk93
title: Characterizing Emergency Department Use Among Assisted Living Residents
DOI: 10.7910/dvn/mv9c2a
title: Supporting Information - Economic evaluations of human schistosomiasis interventions: a systematic review and identification of associated research needs

description: Supporting Information for the following paper - Economic evaluations of human schistosomiasis interventions: a systematic review and identification of associated research needs
DOI: 10.7910/dvn/mv9c2a/ndmvoz
title: Supporting Infomation - Economic evaluations of human schistosomiasis interventions a systematic review and identification of associated research needs.pdf

description: Supporting Infomation
DOI: 10.5281/zenodo.3693785
title: Spillover of an alien parasite reduces expression of costly behaviour in native host species

description: We used a natural experiment of populations of native red squirrels (<em>Sciurus vulgaris</em>) that were colonised by the alien grey squirrel (<em>Sciurus carolinensis</em>), comparing repeated measurements of red squirrel parasite infection and personality with those taken in sites where only the native species occurred.<br> Using data from 323 arena tests across three experimental (native species and IAS) and three control sites (only native species), we found negative correlations between native species’ activity and infection with <em>Strongyloides robustus</em> in the sites invaded by the alien species. Activity was also negatively correlated with infection by its native helminth (<em>Trypanoxyuris sciuri</em>) but only when grey squirrels were present, while in the red-only sites there was no relationship of <em>T. sciuri</em> infection with any of the personality traits. Moreover, individuals that acquired <em>S. robustus</em> during the study reduced their activity after infection, while this was not the case for animals that remained uninfected.
description: Data for manuscript submitted to Journal of Animal Ecology
DOI: 10.5281/zenodo.3693786
title: Spillover of an alien parasite reduces expression of costly behaviour in native host species

description: We used a natural experiment of populations of native red squirrels (<em>Sciurus vulgaris</em>) that were colonised by the alien grey squirrel (<em>Sciurus carolinensis</em>), comparing repeated measurements of red squirrel parasite infection and personality with those taken in sites where only the native species occurred.<br> Using data from 323 arena tests across three experimental (native species and IAS) and three control sites (only native species), we found negative correlations between native species’ activity and infection with <em>Strongyloides robustus</em> in the sites invaded by the alien species. Activity was also negatively correlated with infection by its native helminth (<em>Trypanoxyuris sciuri</em>) but only when grey squirrels were present, while in the red-only sites there was no relationship of <em>T. sciuri</em> infection with any of the personality traits. Moreover, individuals that acquired <em>S. robustus</em> during the study reduced their activity after infection, while this was not the case for animals that remained uninfected.
description: Data for manuscript submitted to Journal of Animal Ecology
DOI: 10.5281/zenodo.3693792
title: Quebec Health Ministry (2013-2018) web archive collection derivatives

description: Web archive derivatives of the Quebec Health Ministry (2013-2018) collection from the Bibliothèque et Archives nationales du Québec. The derivatives were created with the Archives Unleashed Toolkit. Merci beaucoup BAnQ! These derivatives are in the Apache Parquet format, which is a columnar storage format. These derivatives are generally small enough to work with on your local machine, and can be easily converted to Pandas DataFrames. See this notebook for examples. <strong>Domains</strong> <pre><code class="language-java">.webpages().groupBy(ExtractDomainDF($"url").alias("url")).count().sort($"count".desc)</code></pre> Produces a DataFrame with the following columns: domain count <strong>Web Pages</strong> <pre><code class="language-java">.webpages().select($"crawl_date", $"url", $"mime_type_web_server", $"mime_type_tika", RemoveHTMLDF(RemoveHTTPHeaderDF(($"content"))).alias("content"))</code></pre> Produces a DataFrame with the following columns: crawl_date url mime_type_web_server mime_type_tika content <strong>Web Graph</strong> <pre><code class="language-java">.webgraph()</code></pre> Produces a DataFrame with the following columns: crawl_date src dest anchor <strong>Image Links</strong> <pre><code class="language-java">.imageLinks()</code></pre> Produces a DataFrame with the following columns: src image_url <strong>Binary Analysis</strong> Audio Images PDFs Presentation program files Spreadsheets Text files Word processor files
DOI: 10.5281/zenodo.3693791
title: Quebec Health Ministry (2013-2018) web archive collection derivatives

description: Web archive derivatives of the Quebec Health Ministry (2013-2018) collection from the Bibliothèque et Archives nationales du Québec. The derivatives were created with the Archives Unleashed Toolkit. Merci beaucoup BAnQ! These derivatives are in the Apache Parquet format, which is a columnar storage format. These derivatives are generally small enough to work with on your local machine, and can be easily converted to Pandas DataFrames. See this notebook for examples. <strong>Domains</strong> <pre><code class="language-java">.webpages().groupBy(ExtractDomainDF($"url").alias("url")).count().sort($"count".desc)</code></pre> Produces a DataFrame with the following columns: domain count <strong>Web Pages</strong> <pre><code class="language-java">.webpages().select($"crawl_date", $"url", $"mime_type_web_server", $"mime_type_tika", RemoveHTMLDF(RemoveHTTPHeaderDF(($"content"))).alias("content"))</code></pre> Produces a DataFrame with the following columns: crawl_date url mime_type_web_server mime_type_tika content <strong>Web Graph</strong> <pre><code class="language-java">.webgraph()</code></pre> Produces a DataFrame with the following columns: crawl_date src dest anchor <strong>Image Links</strong> <pre><code class="language-java">.imageLinks()</code></pre> Produces a DataFrame with the following columns: src image_url <strong>Binary Analysis</strong> Audio Images PDFs Presentation program files Spreadsheets Text files Word processor files
DOI: 10.5281/zenodo.3693800
title: Quebec Ministry of Tourism (2012 to 2017) web archive collection derivatives

description: Web archive derivatives of the Quebec Ministry of Tourism (2012 to 2017) collection from the Bibliothèque et Archives nationales du Québec. The derivatives were created with the Archives Unleashed Toolkit. Merci beaucoup BAnQ! These derivatives are in the Apache Parquet format, which is a columnar storage format. These derivatives are generally small enough to work with on your local machine, and can be easily converted to Pandas DataFrames. See this notebook for examples. <strong>Domains</strong> <pre><code class="language-java">.webpages().groupBy(ExtractDomainDF($"url").alias("url")).count().sort($"count".desc)</code></pre> Produces a DataFrame with the following columns: domain count <strong>Web Pages</strong> <pre><code class="language-java">.webpages().select($"crawl_date", $"url", $"mime_type_web_server", $"mime_type_tika", RemoveHTMLDF(RemoveHTTPHeaderDF(($"content"))).alias("content"))</code></pre> Produces a DataFrame with the following columns: crawl_date url mime_type_web_server mime_type_tika content <strong>Web Graph</strong> <pre><code class="language-java">.webgraph()</code></pre> Produces a DataFrame with the following columns: crawl_date src dest anchor <strong>Image Links</strong> <pre><code class="language-java">.imageLinks()</code></pre> Produces a DataFrame with the following columns: src image_url <strong>Binary Analysis</strong> Audio Images PDFs Presentation program files Spreadsheets Text files Videos Word processor files
DOI: 10.5281/zenodo.3693801
title: Quebec Ministry of Tourism (2012 to 2017) web archive collection derivatives

description: Web archive derivatives of the Quebec Ministry of Tourism (2012 to 2017) collection from the Bibliothèque et Archives nationales du Québec. The derivatives were created with the Archives Unleashed Toolkit. Merci beaucoup BAnQ! These derivatives are in the Apache Parquet format, which is a columnar storage format. These derivatives are generally small enough to work with on your local machine, and can be easily converted to Pandas DataFrames. See this notebook for examples. <strong>Domains</strong> <pre><code class="language-java">.webpages().groupBy(ExtractDomainDF($"url").alias("url")).count().sort($"count".desc)</code></pre> Produces a DataFrame with the following columns: domain count <strong>Web Pages</strong> <pre><code class="language-java">.webpages().select($"crawl_date", $"url", $"mime_type_web_server", $"mime_type_tika", RemoveHTMLDF(RemoveHTTPHeaderDF(($"content"))).alias("content"))</code></pre> Produces a DataFrame with the following columns: crawl_date url mime_type_web_server mime_type_tika content <strong>Web Graph</strong> <pre><code class="language-java">.webgraph()</code></pre> Produces a DataFrame with the following columns: crawl_date src dest anchor <strong>Image Links</strong> <pre><code class="language-java">.imageLinks()</code></pre> Produces a DataFrame with the following columns: src image_url <strong>Binary Analysis</strong> Audio Images PDFs Presentation program files Spreadsheets Text files Videos Word processor files
DOI: 10.15468/gib2j4
title: L’apport du registre paléogène d’Amazonie sur la diversification initiale des Caviomorpha (Hystricognathi, Rodentia): implications phylogénétiques, macroévolutives et paléobiogéographiques

description: This dataset contains the digitized treatments in Plazi based on the original journal article Boivin, Myriam, Marivaux, Laurent, Antoine, Pierre-Olivier (2019): L’apport du registre paléogène d’Amazonie sur la diversification initiale des Caviomorpha (Hystricognathi, Rodentia): implications phylogénétiques, macroévolutives et paléobiogéographiques. Geodiversitas 41 (4): 143-245, DOI: 10.5252/geodiversitas2019v41a4
DOI: 10.3886/e117974v1-22727
title: Jacob Kaplan's Concatenated Files: Uniform Crime Reporting (UCR) Program Data: Human Trafficking 2013-2018

description: For any questions about this data please email me at jacob@crimedatatool.com. If you use this data, please cite it.<br>This Human Trafficking data set is an FBI data set that is part of the annual Uniform Crime Reporting (UCR) Program data. This data contains information about human trafficking offenses reported in the United States. There are two crimes that are included in this data set: commercial sex acts and involuntary servitude. The information is the number of these crimes that are reported, to have actually occurred (based upon an investigation into the report), to not have occurred ("unfounded"), cleared by arrest of at least one person, and cleared by arrest where all offenders are under the age of 18.<br> The data sets here combine data from the years 2013-2018 (the only years available) into a single file for annual data and a single file for monthly data (data does not get more precise than monthly counts). I also added state, county, and place FIPS code from the LEAIC (crosswalk). <br><br>All the data was is from the FBI and read into R using the package asciiSetupReader. All work to clean the data and save it in various file formats was also done in R. For the R code used to clean this data, see here. https://github.com/jacobkap/crime_data. The raw (in fixed-width ASCII format) was downloaded on the FBI's website here: https://crime-data-explorer.fr.cloud.gov/downloads-and-docs<br><br>The following definitions are from the FBI's UCR manual which is included in each zip file available to download. Please see pages 55-58 of that manual for more information, including examples of each offense.<br>Human Trafficking - Commercial Sex Acts: Inducing a person by force, fraud, or coercion to participate in commercial sex acts, or in which the person induced to perform such act(s) has not attained 18 years of age.<br>Human Trafficking - Involuntary Servitude: The obtaining of a person(s) through recruitment, harboring, transportation, or provision, and subjecting such persons by force, fraud, or coercion into involuntary servitude, peonage, debt bondage, or slavery (not to include commercial sex acts).
description: Smallest Geographic Unit: Police agency
DOI: 10.25386/genetics.11889189
title: Supplemental Material for Vissers et al., 2020

description: Supplementary Data<br>
DOI: 10.25386/genetics.11889189.v1
title: Supplemental Material for Vissers et al., 2020

description: Supplementary Data<br>
DOI: 10.21227/88nv-vb54
title: Twitter Sentiment Analysis Data

description: Each database (*.db) contain three columns. First column: date and time of the tweet, second column: tweet, third column: sentiment score for the particular tweet within the range [-1,1] with -1 being the most negative, 0 being the neutral and +1 being the most positive sentiment.The tweets have been collected by the LSTM model deployed here at sentiment.live[1]. The last column, viz. sentiment score, is not the score estimated by the model. The LSTM model is still in the pre-alpha phase. Therefore, to make it easy for the NLP researchers to get access to the sentiment analysis of each collected tweet, the sentiment score out of TextBlob [2] has been appended as the last column. The sentiment scores produced by our model will be made public after the project is completely open-sourced.####status/latest addition: March 02, 2020####Tweets containing the term "corona": 2.3 million-plus (first collection)Tweets containing the term "republic day": 0.37 million-plusTweets containing the term "samsung": 1.20 million-plusTweets containing the term "facebook": 0.77 million-plusTweets containing the term "android": 0.88 million-plusTweets containing the term "oneplus": 15 thousand-plusTweets containing the term "messi": 225 thousand-plusTweets containing the term "housefull 4": 346 thousand-plusTweets containing the term "the joker": 1 million-plusTweets containing the term "iphone 11": 2 million-plus##################References:[1]https://sentiment.live/ [2]https://textblob.readthedocs.io/en/dev/
DOI: 10.21227/99xj-1193
title: Twitter Sentiment Analysis Data

description: Each database (*.db) contain three columns. First column: date and time of the tweet, second column: tweet, third column: sentiment score for the particular tweet within the range [-1,1] with -1 being the most negative, 0 being the neutral and +1 being the most positive sentiment.The tweets have been collected by the LSTM model deployed here at sentiment.live[1]. The last column, viz. sentiment score, is not the score estimated by the model. The LSTM model is still in the pre-alpha phase. Therefore, to make it easy for the NLP researchers to get access to the sentiment analysis of each collected tweet, the sentiment score out of TextBlob [2] has been appended as the last column. The sentiment scores produced by our model will be made public after the project is completely open-sourced.####status/latest addition: March 02, 2020####Tweets containing the term "corona": 1.5 million-plus (second collection)Tweets containing the term "corona": 2.3 million-plus (first collection)Tweets containing the term "republic day": 0.37 million-plusTweets containing the term "samsung": 1.20 million-plusTweets containing the term "facebook": 0.77 million-plusTweets containing the term "android": 0.88 million-plusTweets containing the term "oneplus": 15 thousand-plusTweets containing the term "messi": 225 thousand-plusTweets containing the term "housefull 4": 346 thousand-plusTweets containing the term "the joker": 1 million-plusTweets containing the term "iphone 11": 2 million-plus##################References:[1]https://sentiment.live/ [2]https://textblob.readthedocs.io/en/dev/
DOI: 10.5281/zenodo.3694084
title: DataHawk2 files from LAPSE-RATE

description: This dataset includes measurements obtained using the University of Colorado DataHawk2 UAS during the 2018 LAPSE-RATE (Lower Atmospheric Profiling Studies at Elevation - a Remotely-piloted Aircraft Team Experiment) field campaign. This campaign took place in the San Luis Valley of Colorado between 14-21 July, 2018. <strong>All parties downloading the data are asked to cite the original research team and funding body when appropriate, and when using images and data in publications, presentations or other public displays. The DOI for the current dataset, and associated articles should be referenced whenever the dataset is used for scientific analysis.</strong>
description: Funding supported by the US National Science Foundation (AGS 1807199) and the US Department of Energy (DE-SC0018985).
DOI: 10.5281/zenodo.3694100
title: TTWISTOR files from LAPSE-RATE

description: This dataset includes measurements obtained using the University of Colorado TTwistor UAS during the 2018 LAPSE-RATE (Lower Atmospheric Profiling Studies at Elevation - a Remotely-piloted Aircraft Team Experiment) field campaign. This campaign took place in the San Luis Valley of Colorado between 14-21 July, 2018. <strong>All parties downloading the data are asked to cite the original research team and funding body when appropriate, and when using images and data in publications, presentations or other public displays. The DOI for the current dataset, and associated articles should be referenced whenever the dataset is used for scientific analysis.</strong>
description: Funding supported by the US National Science Foundation (AGS 1807199) and the US Department of Energy (DE-SC0018985).
DOI: 10.5519/qd.801qwc1n
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (4565 records)
DOI: 10.5519/qd.jrtgkokk
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (224 records)
DOI: 10.5519/qd.1dy0w3bl
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (24898 records)
DOI: 10.5519/qd.3rsjvfx3
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (52998 records)
DOI: 10.5519/qd.644suz6o
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (10755 records)
DOI: 10.5519/qd.d5lvzv7f
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (267 records)
DOI: 10.5519/qd.erizftd1
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1549 records)
DOI: 10.25387/g3.8343863
title: Supplementary Material for Chandler, Mammel and Dworkin, 2019

description: Supplementary Materials
DOI: 10.3886/e117987
title: What Makes Them Persist? Expectancy-Value Beliefs and the Math Participation, Performance, and Preparedness of Hispanic Youth

description: This study examined the longitudinal associations of Hispanic youths’ 9th-grade math expectancy-values and their sub- sequent participation (course taking and advanced course taking), performance, and preparedness (high school graduation and university eligibility) across 9th to 12th grades. Gender moderation associations of expectancy-value and participation, performance, and preparedness were evaluated. Students’ socio-demographic characteristics and previous math experiences (achievement and curricular track) were controlled. The study sample (n = 1,116) was 53% female, 46% English learner, and 84% low income. Males reported higher expectancy, interest, attainment, and cost values. Females completed more math courses and advanced courses, achieved stronger course grades, and were more likely to complete math preparation requirements for high school graduation and college. Associations of expectancy-value, and participation and performance were observed along with gender-moderated associations with preparedness. The odds of graduation preparedness were increased for females with high attainment value, whereas the odds of university prepared- ness were increased for males with high utility value.