cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.19653843
title: Figure 1 - Geometric dynamics of midgut morphogenesis -- surface area, volume, length

description: MATLAB data file with fields: <br> centerlineLength = length of the midgut over time for each embryo, as measured by the midgut shape's centerline within the enclosed yolk; centerlineLength_normalized = length normalized to its value at the onset of the first constriction ; volume = volume of the midgut over time for each embryo; volume_normalized = volume normalized to its value at the onset of the first constriction ; surfaceArea : surface area of the midgut over time for each embryo; surfaceArea_normalized : surface area normalized to its value at the onset of the first constriction validLengthIDs = find(any(allL, 2)); validVolumeIDs = find(any(allV, 2)); validAreaIDs = find(any(allV, 2)); <br> Each measurement curve is derived from the extracted inner endoderm surface of a lightsheet dataset of fluorescently labeled midgut cells. Two datasets expressed membrane marker (CAAX), three datasets expressed a nuclear (histone) marker (histone:RFP), and two datasets expressed LifeAct:Ruby. In all datasets tissue specific markers were driven via the GAL4/UAS system with 48Y-GAL4.
DOI: 10.6084/m9.figshare.19653843.v2
title: Figure 1 - Geometric dynamics of midgut morphogenesis -- surface area, volume, length

description: MATLAB data file with fields: <br> centerlineLength = length of the midgut over time for each embryo, as measured by the midgut shape's centerline within the enclosed yolk; centerlineLength_normalized = length normalized to its value at the onset of the first constriction ; volume = volume of the midgut over time for each embryo; volume_normalized = volume normalized to its value at the onset of the first constriction ; surfaceArea : surface area of the midgut over time for each embryo; surfaceArea_normalized : surface area normalized to its value at the onset of the first constriction validLengthIDs = find(any(allL, 2)); validVolumeIDs = find(any(allV, 2)); validAreaIDs = find(any(allV, 2)); <br> Each measurement curve is derived from the extracted inner endoderm surface of a lightsheet dataset of fluorescently labeled midgut cells. Two datasets expressed membrane marker (CAAX), three datasets expressed a nuclear (histone) marker (histone:RFP), and two datasets expressed LifeAct:Ruby. In all datasets tissue specific markers were driven via the GAL4/UAS system with 48Y-GAL4.
DOI: 10.6084/m9.figshare.19653843.v1
title: Geometric dynamics of midgut morphogenesis -- surface area, volume, length

description: MATLAB data file with fields <br> validLengthIDs = find(any(allL, 2)); validVolumeIDs = find(any(allV, 2)); validAreaIDs = find(any(allV, 2)); centerlineLength = length of the midgut over time for each embryo, as measured by the midgut shape's centerline within the enclosed yolk; centerlineLength_normalized = length normalized to its value at the onset of the first constriction ; volume = volume of the midgut over time for each embryo; volume_normalized = volume normalized to its value at the onset of the first constriction ; surfaceArea : surface area of the midgut over time for each embryo; surfaceArea_normalized : surface area normalized to its value at the onset of the first constriction
DOI: 10.6084/m9.figshare.14501955
title: DBS Movie

description: Code to generate video shown here https://www.youtube.com/watch?v=Lwl51aLvDRQ <br> "A Tour Through Brain Circuits" <br> Includes the unedited output video file in high resolution, as well. <br> Needs Lead-DBS as dependency (www.lead-dbs.org).
DOI: 10.6084/m9.figshare.14501955.v1
title: DBS Movie

description: Code to generate video shown here https://www.youtube.com/watch?v=Lwl51aLvDRQ <br> "A Tour Through Brain Circuits" <br> Includes the unedited output video file in high resolution, as well. <br> Needs Lead-DBS as dependency (www.lead-dbs.org).
DOI: 10.6084/m9.figshare.3761562.v2258
title: Online Labour Index: Measuring the Online Gig Economy for Policy and Research

description: Data repository for the data underlying the Online Labour Index. See http://ilabour.oii.ox.ac.uk online-labour-index/ for details.
DOI: 10.7278/s50d-k0kv-f0w2
title: Data for Thesis: Mechanisms Governing Ash Aerosol Formation and Deposition during Solid Fuel Combustion
DOI: 10.6084/m9.figshare.19610223
title: AMOC Reversals

description: Mean AMOC structure from an ensemble of 24 North Atlantic simulations. Winds used in forcing the model. AMOC indices timeseries from various runs. All data are in matlab .mat formats.
DOI: 10.6084/m9.figshare.19610223.v1
title: AMOC Reversals

description: Mean AMOC structure from an ensemble of 24 North Atlantic simulations. Winds used in forcing the model. AMOC indices timeseries from various runs. All data are in matlab .mat formats.
DOI: 10.5517/ccdc.csd.cc290llj
title: CCDC 2115737: Experimental Crystal Structure Determination

description: Related Article: Chris Gendy, Juuso Valjus, Roland Roesler, Heikki M. Tuononen|2022|Angew.Chem.,Int.Ed.|61|e202115692|doi:10.1002/anie.202115692
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc290lmk
title: CCDC 2115738: Experimental Crystal Structure Determination

description: Related Article: Chris Gendy, Juuso Valjus, Roland Roesler, Heikki M. Tuononen|2022|Angew.Chem.,Int.Ed.|61|e202115692|doi:10.1002/anie.202115692
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc290lnl
title: CCDC 2115739: Experimental Crystal Structure Determination

description: Related Article: Chris Gendy, Juuso Valjus, Roland Roesler, Heikki M. Tuononen|2022|Angew.Chem.,Int.Ed.|61|e202115692|doi:10.1002/anie.202115692
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc293h86
title: CCDC 2118517: Experimental Crystal Structure Determination

description: Related Article: Jun Zhang, Wataru Kosaka, Yasutaka Kitagawa, Hitoshi Miyasaka|2022|Angew.Chem.,Int.Ed.|61|e202115976|doi:10.1002/anie.202115976
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc293h97
title: CCDC 2118518: Experimental Crystal Structure Determination

description: Related Article: Jun Zhang, Wataru Kosaka, Yasutaka Kitagawa, Hitoshi Miyasaka|2022|Angew.Chem.,Int.Ed.|61|e202115976|doi:10.1002/anie.202115976
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc293hb8
title: CCDC 2118519: Experimental Crystal Structure Determination

description: Related Article: Jun Zhang, Wataru Kosaka, Yasutaka Kitagawa, Hitoshi Miyasaka|2022|Angew.Chem.,Int.Ed.|61|e202115976|doi:10.1002/anie.202115976
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc29fbps
title: CCDC 2127985: Experimental Crystal Structure Determination

description: Related Article: Yongzheng Ding, Hanmin Huang|2022|Chem Cat.|2|1467|doi:10.1016/j.checat.2022.04.021
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc275qsy
title: CCDC 2061090: Experimental Crystal Structure Determination

description: Related Article: Yongzheng Ding, Hanmin Huang|2022|Chem Cat.|2|1467|doi:10.1016/j.checat.2022.04.021
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc275qtz
title: CCDC 2061091: Experimental Crystal Structure Determination

description: Related Article: Yongzheng Ding, Hanmin Huang|2022|Chem Cat.|2|1467|doi:10.1016/j.checat.2022.04.021
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc28jn0h
title: CCDC 2101366: Experimental Crystal Structure Determination

description: Related Article: Yang Xiong, Johannes Großkopf, Christian Jandl, Thorsten Bach|2022|Angew.Chem.,Int.Ed.|61|e202200555|doi:10.1002/anie.202200555
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc28jr6s
title: CCDC 2101465: Experimental Crystal Structure Determination

description: Related Article: Yang Xiong, Johannes Großkopf, Christian Jandl, Thorsten Bach|2022|Angew.Chem.,Int.Ed.|61|e202200555|doi:10.1002/anie.202200555
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.6084/m9.figshare.20132678.v3
title: primary ATRT bulk RNA-seq

description: Matrix of raw counts of RNA-seq data from 49 primary ATRT samples were generated using an in-house pipeline developed at the Institut Curie Bioinformatics Core Facility (available at https://github.com/bioinfo-pf-curie/RNA-seq) and the human reference genome hg19. Except, the first column which contains the gene name, columns correspond to samples and named by the patient ID.
DOI: 10.6084/m9.figshare.20132678.v4
title: primary ATRT bulk RNA-seq

description: Matrix of raw counts of RNA-seq data from 49 primary ATRT samples were generated using an in-house pipeline developed at the Institut Curie Bioinformatics Core Facility (available at https://github.com/bioinfo-pf-curie/RNA-seq) and the human reference genome hg19. Except, the first column which contains the gene name, columns correspond to samples and named by the patient ID.
DOI: 10.6084/m9.figshare.20137586
title: SLA_May15_2017

description: SLA from https://cds.climate.copernicus.eu
DOI: 10.6084/m9.figshare.20137586.v1
title: SLA_May15_2017

description: SLA from https://cds.climate.copernicus.eu
DOI: 10.6084/m9.figshare.20137589.v1
title: SLA_Oct15_2017

description: SLA from https://cds.climate.copernicus.eu
DOI: 10.6084/m9.figshare.20137589
title: SLA_Oct15_2017

description: SLA from https://cds.climate.copernicus.eu
DOI: 10.5683/sp2/d44qie
title: Library and Archives Canada

description: Manuals that Library and Archives Canada provided.
DOI: 10.5281/zenodo.6671371
title: HiPACE++ input scripts for "Self-stabilizing positron acceleration in a plasma column"

description: This dataset presents the HiPACE++ input scripts required to re-create the data of Fig. 2 and 4 in the article "Self-stabilizing positron acceleration in a plasma column" by S. Diederichs, C. Benedetti, M. Thévenet, E. Esarey, J. Osterhoff, and C. B. Schroeder.
DOI: 10.5281/zenodo.6671370
title: HiPACE++ input scripts for "Self-stabilizing positron acceleration in a plasma column"

description: This dataset presents the HiPACE++ input scripts required to re-create the data of Fig. 2 and 4 in the article "Self-stabilizing positron acceleration in a plasma column" by S. Diederichs, C. Benedetti, M. Thévenet, E. Esarey, J. Osterhoff, and C. B. Schroeder.
DOI: 10.6084/m9.figshare.20137583
title: Questionnaires with English loanwords (translation study).xlsx

description: List of English words used in the study on the strategies employed by Croatian students when translating the most frequent English loanwords in Croatian.
DOI: 10.6084/m9.figshare.20137562
title: Supplemental Table 1 - Evaluating Methods Reporting in Langendorff Technique

description: This is the complete dataset accompanying the manuscript " <strong>Re-evaluating methods reporting practices to improve reproducibility: an analysis of methodological rigor for the Langendorff whole-heart technique</strong> " published in AJP-Heart and Circ.
DOI: 10.6084/m9.figshare.20137562.v1
title: Supplemental Table 1 - Evaluating Methods Reporting in Langendorff Technique

description: This is the complete dataset accompanying the manuscript " <strong>Re-evaluating methods reporting practices to improve reproducibility: an analysis of methodological rigor for the Langendorff whole-heart technique</strong> " published in AJP-Heart and Circ.
DOI: 10.5683/sp/v0zift
title: Twitter data related to Canada at the Rio 2016 Olympics and Paralympics

description: Tweet IDs for tweets containing hashtags related to Canada at the 2016 Rio Olympics and Paralympics, held Aug. 5-21 and Sept. 7-18 respectively. These were captured as part of a larger web archiving project focused on Canada's involvement in the Rio Games. Tweet IDs can be hydrated using Ed Summers' twarc (https://github.com/edsu/twarc). Hydrating will recreate the original tweet(s) in json format, provided the content is still available on Twitter. / Tweets were collected July 29 - Sept. 23. Several hashtags were tracked, with new ones added as they were identified: Added July 29: #teamcanada,#equipecanada / Added Aug. 3: #CAN, #CanadaRED, #CanWNT / Added Aug. 8: #GoCanadaGo / Added Aug. 10: #LetsGoCanada, #Canadaolympics, #Flytheflag / Added Aug. 12: #Pennyoleksiak / Added Sept. 6: #Paratough, #Parafort /
DOI: 10.5683/sp/djlhsb
title: The fall of Aleppo tweets; Aleppo 2016-12-13 through 2016-12-29

description: 8,595,589 tweet ids for aleppo tweets captured during the fall of Aleppo in December 2016. Tweets can be "rehydrated" with Documenting the Now's twarc (https://github.com/DocNow/twarc). twarc.py --hydrate aleppo_tweet_ids.txt &gt; aleppo.json
DOI: 10.5683/sp/ngmqnx
title: Tweet ids for final Tragically Hip concert

description: 228,086 tweet ids for "TheHip, hipinkingston" captured during the Tragically Hip's final concert in Kingston, Ontario in August 2016. Tweets can be "rehydrated" with Documenting the Now's twarc (https://github.com/DocNow/twarc). twarc.py --hydrate th_final_concert_kingston_tweet_ids.txt &gt; th_final_concert_kingston.json
DOI: 10.5683/sp/cfvf1f
title: American Historical Association 2017 Conference Tweets

description: 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.
DOI: 10.5683/sp/zel1q6
title: #WomensMarch tweets January 12-28, 2017

description: 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 &gt; 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.
DOI: 10.5683/sp/7bc9v1
title: #MarchForScience tweets April 12-26, 2017

description: 1,276,220 tweet ids for #MarchForScience collected with Documenting the Now's twarc from January 22-26, 2017. Tweets can be “rehydrated” with Documenting the Now’s twarc (https://github.com/DocNow/twarc). twarc.py hydrate MarchForScience_tweet-ids.txt &gt; MarchForScience.json.
DOI: 10.5683/sp/kzzvzw
title: #climatemarch tweets April 19-May 3, 2017

description: 681,668 tweet ids for #climate collected with Documenting the Now's twarc from January 22-26, 2017. Tweets can be “rehydrated” with Documenting the Now’s twarc (https://github.com/DocNow/twarc). twarc.py hydrate climatemarch_tweet_ids.txt &gt; climatemarch.json.
DOI: 10.5683/sp/d7r2wb
title: #paradisepapers tweets

description: 1,797,260 tweet ids for #paradisepapers collected with Documenting the Now's twarc from November 5-26, 2017. Tweets can be “rehydrated” with Documenting the Now’s twarc (https://github.com/DocNow/twarc). twarc.py hydrate paradisepapers_ids.txt &gt; paradisepapers.json. Or with Documenting the Now's Hydrator: https://github.com/DocNow/hydrator
DOI: 10.5683/sp/8bavqm
title: Tweets to Donald Trump (@realDonaldTrump)

description: 362,464,578 tweet ids for tweets directed at Donald Trump (@realDonaldTrump), collected with Documenting the Now's twarc. Tweets can be “rehydrated” with Documenting the Now’s twarc, or Hydrator. twarc hydrate to_realdonaldtrump_20210120_ids.txt &gt; to_realdonaldtrump_20210120.jsonl. Collection notes: Tweets from May 7, 2017 - October 16, 2018 of the dataset used a combination of the Filter (Streaming) API and Search API. The Filter API failed on June 21, 2017. From June 23, 2017 forward only the Search API was used to collect. Collection was done every 5 days on a cron job, and periodically deduplicated. There is a data gap from Tue Jul 28 13:53:50 +0000 2020 through Thu Aug 06 09:36:23 +0000 2020 due to a collection error. This dataset also includes a number of derivative csv files from the original jsonl collected. This includes: A user csv file created with jq (see below). twut userInfo twut language twut times twut sources twut hashtags twut urls twut animatedGifUrls twut imageUrls twut mediaUrls twut videoUrls User csv: jq -r '[.id_str, .created_at, .user.screen_name, .retweeted_status != null] | @csv' to_realdonaldtrump_20190130.jsonl &gt; to_realdonaldtrump_20190130_users.jsonl
DOI: 10.5683/sp/mq3y99
title: #JeffSessions tweets

description: 2,278,757 tweet ids for #JeffSessions collected with Documenting the Now's twarc. Tweets can be “rehydrated” with Documenting the Now’s twarc, or Hydrator. twarc hydrate to_realdonaldtrump_ids.txt &gt; to_donaltrump.jsonl.
DOI: 10.5683/sp2/qamppi
title: #elxn43 tweets (43rd Canadian Federal Election)

description: 2,944,525 tweet ids for #elxn43 tweets, collected with Documenting the Now's twarc. Tweets can be “rehydrated” with Documenting the Now’s twarc, or Hydrator. twarc hydrate elxn43-ids.txt &gt; elxn43.jsonl. Tweets were collected via the Standard Search API on a cron job every five days from September 9, 2019 - November 23, 2019.
DOI: 10.5683/sp2/z68evj
title: Avery Library Historic Preservation and Urban Planning web archive collection derivatives

description: Web archive derivatives of the Avery Library Historic Preservation and Urban Planning collection from Columbia University Libraries. The derivatives were created with the Archives Unleashed Toolkit and Archives Unleashed Cloud. The cul-1757-parquet.tar.gz 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. Domains .webpages().groupBy(ExtractDomainDF($"url").alias("url")).count().sort($"count".desc) Produces a DataFrame with the following columns: domain count Web Pages .webpages().select($"crawl_date", $"url", $"mime_type_web_server", $"mime_type_tika", RemoveHTMLDF(RemoveHTTPHeaderDF(($"content"))).alias("content")) Produces a DataFrame with the following columns: crawl_date url mime_type_web_server mime_type_tika content Web Graph .webgraph() Produces a DataFrame with the following columns: crawl_date src dest anchor Image Links .imageLinks() Produces a DataFrame with the following columns: src image_url The cul-1757-auk.tar.gz derivatives are the standard set of web archive derivatives produced by the Archives Unleashed Cloud. Gephi file, which can be loaded into Gephi. It will have basic characteristics already computed and a basic layout. Raw Network file, which can also be loaded into Gephi. You will have to use that network program to lay it out yourself. Full text file. In it, each website within the web archive collection will have its full text presented on one line, along with information around when it was crawled, the name of the domain, and the full URL of the content. Domains count file. A text file containing the frequency count of domains captured within your web archive. Due to file size restrictions in Scholars Portal Dataverse, each of the derivative files needed to be split into 1G parts. These parts can be joined back together with cat. For example: cat cul-1757-parquet.tar.gz.part* &gt; cul-1757-parquet.tar.gz
DOI: 10.5683/sp2/fqr2ck
title: Tyendinaga tweet ids

description: 80,264 tweet ids for Tyendinaga tweets, collected with Documenting the Now's twarc. Tweets can be “rehydrated” with Documenting the Now’s twarc, or Hydrator. twarc hydrate tyendinaga-20210115-ids.txt &gt; tyendinaga.jsonl. Tweets were collected via the Standard Search API on a cron job every five days beginning on February 24, 2020. Collection is ongoing. The account that was used to collect these Tweets failed to collect Tweets for the period from Sun Jul 26 03:46:41 +0000 2020 through Fri Aug 07 20:33:27 +0000 2020.
DOI: 10.5683/sp2/c0kftf
title: Wet'suwet'en tweet ids

description: 425,227 tweet ids for Wet'suwet'en tweets, collected with Documenting the Now's twarc. Tweets can be “rehydrated” with Documenting the Now’s twarc, or Hydrator. twarc hydrate wetsuweten-20210115-ids.txt &gt; wetsuweten.jsonl Tweets were collected via the Standard Search API on a cron job every five days beginning on February 18, 2020. Collection is ongoing. The account that was used to collect these Tweets failed to collect Tweets for the period from Sun Jul 26 02:00:21 +0000 2020 through Fri Aug 07 20:05:54 +0000 2020.