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4,404 results for “Digitization”
Digital terrain models derived from UAV overflights of the fifteen NPP study sites at Jornada Basin LTER in 2019
This data package contains digital terrain models (DTMs) of each of the 15 NPP study sites at the Jornada Basin LTER in southern New Mexico, USA. The models were derived from raw images collected during uncrewed aerial vehicle (UAV) overflight missions conducted in late summer and early autumn of 2019 (1 overflight day per site). For each site one or two missions were flown during an afternoon using a DJI Phantom 4 UAV, and between 450 and 1300 12.4 megapixel RGB images were captured. A subset of images captured at each site were loaded into Agisoft Metashape software to derive DTMs using a structure from motion method. These models do not include the elevations of aboveground features such as vegetation and large rocks. The raw images are not provided but can be made available via project PIs. This data package includes one centimeter resolution DTMs of all 15 sites as geotiff raster files. Other derived products from these UAV missions, including orthomosaic photos, digital elevation models, and sparse point clouds, are available in other EDI data packages (knb-lter-jrn.210543001, knb-lter-jrn.210543002, and knb-lter-jrn.210543004, respectively). This study is complete.
Artefact segmentation in digital pathology whole-slide images
<p>Dataset with examples of Artefacts in Digital Pathology.</p> <p>The dataset contains 22 Whole-Slide Images, with H&E or IHC staining, showing various types and levels of defect to the slides. Annotations were made by a biomedical engineer based on examples given by an expert.</p> <p>The dataset is split in different folders:</p> <ul> <li>train <ul> <li>18 whole-slide images (extracted at 1.25x & 2.5x magnification)</li> <li>All from the same Block (colorectal cancer tissue)</li> <li>1/2 with H&E & 1/2 with anti-pan-cytokeratin IHC staining.</li> </ul> </li> <li>validation <ul> <li>3 whole-slide images (1.25x + 2.5x mag)</li> <li>2 from the same Block as the training set (1 IHC, 1 H&E)</li> <li>1 from another Block (IHC anti-pan-cytokerating, gastroesophageal junction lesion)</li> </ul> </li> <li>validation_tiles <ul> <li>patches of varying sizes taken from the 3 validation whole-slide images @1.25x magnification.</li> <li>7 patches from each slide.</li> </ul> </li> <li>test <ul> <li>1 whole-slide image (1.25x + 2.5x mag)</li> <li>From another block: IHC staining (anti-NR2F2), mouth cancer</li> </ul> </li> </ul> <p>For the train, validation and test whole-slide images, each slide has:<br> - The RGB images @1.25x & 2.5x mag<br> - The corresponding background/tissue masks<br> - The corresponding annotation masks containing examples of artefacts (note that a majority of artefacts are not annotated. In total, 918 artefacts are in the train set)</p> <p>For the validation tiles, the following table gives the "patch-level" supervision:</p> <p>tile# Artefact(s)<br> 00 None/Few<br> 01 Tear&Fold<br> 02 Ink<br> 03 None/Few<br> 04 None/Few<br> 05 Tear&Fold<br> 06 Tear&Fold + Blur<br> 07 Knife damage<br> 08 Knife damage<br> 09 Ink<br> 10 None/Few<br> 11 Tear&Fold<br> 12 Tear&Fold<br> 13 None/Few<br> 14 None/Few<br> 15 Knife damage<br> 16 Tear&Fold<br> 17 None/Few<br> 18 None/Few<br> 19 Blur<br> 20 Knife damage</p>
Digital Narratives of Covid-19: a Twitter Dataset
<p>We are releasing a Twitter dataset connected to our project <a href="https://covid.dh.miami.edu/"><em>Digital Narratives of Covid-19</em> </a>(DHCOVID) that -among other goals- aims to explore during one year (May 2020-2021) the narratives behind data about the coronavirus pandemic.</p> <p>In this first version, we deliver a Twitter dataset organized as follows:</p> <ul> <li>Each folder corresponds to daily data (one folder for each day): YEAR-MONTH-DAY</li> <li>In every folder there are 9 different plain text files named with "dhcovid", followed by date (YEAR-MONTH-DAY), language ("en" for English, and "es" for Spanish), and region abbreviation ("fl", "ar", "mx", "co", "pe", "ec", "es"): <ol> <li>dhcovid_YEAR-MONTH-DAY_es_fl.txt: Dataset containing tweets geolocalized in South Florida. The geo-localization is tracked by tweet coordinates, by place, or by user information.</li> <li>dhcovid_YEAR-MONTH-DAY_en_fl.txt: We are gathering only tweets in English that refer to the area of Miami and South Florida. The reason behind this choice is that there are multiple projects harvesting English data, and, our project is particularly interested in this area because of our home institution (University of Miami) and because we aim to study public conversations from a bilingual (EN/ES) point of view.</li> <li>dhcovid_YEAR-MONTH-DAY_es_ar.txt: Dataset containing tweets from Argentina.</li> <li>dhcovid_YEAR-MONTH-DAY_es_mx.txt: Dataset containing tweets from Mexico.</li> <li>dhcovid_YEAR-MONTH-DAY_es_co.txt: Dataset containing tweets from Colombia.</li> <li>dhcovid_YEAR-MONTH-DAY_es_pe.txt: Dataset containing tweets from Perú.</li> <li>dhcovid_YEAR-MONTH-DAY_es_ec.txt: Dataset containing tweets from Ecuador.</li> <li>dhcovid_YEAR-MONTH-DAY_es_es.txt: Dataset containing tweets from Spain.</li> <li>dhcovid_YEAR-MONTH-DAY_es.txt: This dataset contains all tweets in Spanish, regardless of its geolocation.</li> </ol> </li> </ul> <p>For English, we collect all tweets with the following keywords and hashtags: covid, coronavirus, pandemic, quarantine, stayathome, outbreak, lockdown, socialdistancing. For Spanish, we search for: covid, coronavirus, pandemia, quarentena, confinamiento, quedateencasa, desescalada, distanciamiento social.</p> <p>The corpus of tweets consists of a list of Tweet Ids; to obtain the original tweets, you can use "<a href="https://github.com/DocNow/hydrator">Twitter hydratator</a>" which takes the id and download for you all metadata in a csv file.</p> <p>We started collecting this Twitter dataset on April 24th, 2020 and we are adding daily data to our GitHub repository. There is a detected problem with file 2020-04-24/dhcovid_2020-04-24_es.txt, which we couldn't gather the data due to technical reasons.</p> <p>For more information about our project visit <a href="https://covid.dh.miami.edu/">https://covid.dh.miami.edu/</a></p> <p>For more updated datasets and detailed criteria, check our GitHub Repository: <a href="https://github.com/dh-miami/narratives_covid19/">https://github.com/dh-miami/narratives_covid19/</a></p>
Towards a generic processingand presentation ofTEI encoded digital editions
<p>This dataset is the basis for the talk given at the TEI Member's Meeting 2014, Evanston, IL</p> <p>The abstract of the paper submitted:</p> <p>The set of XSL stylesheets provided and maintained by the TEI is relatively cautious about processing and presentation of transcriptions and content of digital editions. Only very basic functions are implemented, such as to surround abbreviations with brackets or to process from the element choice in plain mode only those children that represent the "critical" reading. Processing in plain mode means that the elements will be treated as in-line elements.[1]</p> <p>On the other hand the encoding must have been done with a special purpose. A general rule of text encoding is that the editor may encode only those structures and semantic features that he wants to process in the end. The processing might include elaborated examination and analysis of the encoded text or more complex queries as well as a reproduction of visual properties of the original document or provide a (simplified) reading text. Thus the encoding will tell something about the functionalities of the text in processing and presentation.</p> <p>According to Patrick Sahle's "Textrad"[2], "the" text does not exist in a transcription but the encoded text usually represents multiple properties and serves multiple purposes. Whatever the editor might state in some introductory notes and the documentation of the edition which should contain some statements about the encoding used, in the end the encoded text will speak on its own, can be interpreted and will be processed as is.</p> <p>In succession of the modelling of the TEI, realised in the modules, the grouping of elements and of attributes, the semantics of certain elements might let the processor estimate about the foreseen presentation, processing, and use:<br> - The elements <pb>, <lb>, <l>, <lg>, etc. as well as attributes @rend, @rendition or @style represent visual aspects of the text, therefore these might have to be reproduced; users may be given a choice to either see a document-centred view which visualises these aspects or switch to an editorial view on the text which eliminates these properties.<br> - The same applies to the element <choice>: If this is used the editor must have had in mind the opportunity to change the views on the document respectively encoded text.<br> - Entities encoded as <rs>, <name>, <persName>, <placeName>, etc might be referenced, especially if they are accompanied by the related list elements such as <listPerson>, <listPlace>, etc. Additionally, one might assume that there will be norm data available which allows for links into the open.<br> - Bibliographic records (<bibl>, <msDesc>) will serve a similar purpose and will have to be referenced.<br> - Quotations like <cit>, <foreign>, <q>, <quote> etc. will have to be distinguished from the surrounding text.</p> <p>Concerning the overall structure of an (critical) edition one might expect up to three apparatuses: The critical apparatus, the commentary and maybe a bibliographical apparatus. How many of these are present in a given edition is up to the editor but the presence of certain elements and especially of the amount of certain elements will give anybody an idea of how many apparatuses are "appropriate": If the encoding contains editorial elements like <choice>, <abbr>/<expan>, <add>/<del>, etc. the representation of this information in an apparatus will be inevitable. If a certain amount of bibliographic references point to biblical or classical texts the tradition of the publication of editions has provided a separate apparatus as well. Last, editorial notes will have to be distinguished from the former two categories.</p> <p>This paper will examine existing editions with statistical methods and by clustering the elements used it might be possible to assign the encoded text to one or more text types of Sahle's typology. Additionally, the paper shall foster the discussion about the presentation of an edited text according to the intended purpose of the encoding. On the basis of the typology and purpose of the edition it will be more likely that a generic presentation of any edited text is possible. Finally, with some statistical data about the editions some remarks about the interoperability of the TEI-encoded texts shall be possible.</p> <p>[1] e.g. https://github.com/TEIC/Stylesheets/blob/master/html/html_core.xsl</p> <p>[2] Patrick Sahle: Digitale Editionsformen, 3 vols. 2013, esp. vol. 3, p. 9ff.</p>
Dataset do DH2020 [The Lusophone Digital Humanities and What they (we) are doing from the South: textual corpus analysis and FAIR principles to tackle Hegemony]
<p>Planilha de dados recuperados do Google Scholar utilizado na análise e apresentação da pesquisa empírica intitulada - <strong>The Lusophone Digital Humanities and What they (we) are doing from the South: textual corpus analysis and FAIR principles to tackle Hegemony </strong>- no evento <strong>DH2020 Ottawa</strong>: <a href="https://hcommons.org/deposits/item/hc:32051/">https://hcommons.org/deposits/item/hc:32051/</a></p>
Dataset for Overscan Detection in Digitized Analog Films by Precise Sprocket Hole Segmentation
<p>This repo includes the self-generated dataset as well as the pre-trained models .</p> <p>ISVC 2020 - 15th International Symposium on Visual Computing</p> <p>Paper: Overscan Detection in Digitized Analog Filmsby Precise Sprocket Hole Segmentation</p> <p> </p> <p>Acknowledgement:</p> <p>Visual History of the Holocaust: Rethinking Curation in the Digital Age. This project has received funding from the European Union’s Horizon 2020 research and innovation program under the Grant Agreement 822670.</p> <p>https://www.vhh-project.eu</p> <p> </p>
List of Links to Digital Resources for Latin and Ancient Greek
<p>List of Links to Digital Resources for Latin and Ancient Greek</p> <p>The list was produced as an appendix to the German publication "Wie die Digitalisierung unseren Umgang mit den Alten Sprachen verändert hat" (How Digitization Changed the Way We Deal with Latin and Ancient Greek) in the journal "Forum Classicum", scheduled for release at the end of the year 2020.</p> <p>It contains references to various resources, such as text editions, databases, teaching materials, newspaper articles, tools for natural language processing and more. Most of them are available in English, some only in German. The list is sorted by the appearance of links in the article.</p> <p>Changelog:</p> <p>Version 2.0: Added headings from the paper to indicate topics for each part of the link list. English translations for the German headings are given in brackets.</p> <p>The list:</p> <p>Wie die Digitalisierung unseren Umgang mit den Alten Sprachen verändert hat / Linkliste (How Digitization Changed the Way We Deal with Latin and Ancient Greek / Link List)<br>A. Umgang mit der Literatur und anderen Wissensbeständen (Dealing with Literature and Other Data Collections)<br>1. Digitale Textsammlungen sind schnell verfügbar und unterstützen Lehre und Forschung. (Digital text collections are quickly accessible and support teaching as well as research.)<br>https://www.degruyter.com/view/db/btltll <br>http://stephanus.tlg.uci.edu/ <br>https://cil.bbaw.de/ <br>https://latin.packhum.org/ <br>http://cite-architecture.org/cts/ <br>https://referenceworks.brillonline.com/entries/brill-s-new-pauly/ancient-authors-and-titles-of-works-Ancient_Authors_and_Titles_of_Works <br>http://www.perseus.tufts.edu/hopper/collection?collection=Perseus:collection:Greco-Roman <br>https://tesserae.caset.buffalo.edu/<br>2. Digitale Datenbanken ermöglichen schnelle systematische Suchanfragen in großen Text- oder Informationsbeständen, auch über disziplinäre Grenzen hinweg. (Digital databases enable quick systematic queries for large collections of texts and other information, even beyond disciplinary boundaries.)<br>https://about.brepolis.net/lannee-philologique-aph/ <br>https://www.gbd.digital/metaopac/start.do?View=gnomon <br>https://referenceworks.brillonline.com/browse/brill-s-new-pauly <br>https://www.navigium.de/ <br>https://www.navigium.de/latein-unterrichten.html <br>http://lehrerportal.ccbuchner.de/Textanalyse/Default.aspx <br>https://open-educational-resources.de/ <br>https://github.com/sommerschield/ancient-text-restoration <br>3. Digitale Datenbestände werden vernetzt und für neue Anwendungszwecke kombiniert. (Digital data collections can be interconnected and combined for new use cases.)<br>https://www.w3.org/standards/semanticweb/data <br>https://lila-erc.eu/ <br>https://peripleo.pelagios.org/ <br>https://medium.com/pelagios/linked-open-data-to-navigate-the-past-using-peripleo-in-class-4286b3089bf3 <br>https://topostext.org/ <br>4. Die maschinelle sprachliche Vorverarbeitung antiker Texte erleichtert den Zugang für Lernende und Forschende. (Natural language processing of ancient texts facilitates access for both teachers and researchers.)<br>http://www.lemlat3.eu/ <br>https://d.iogen.es/ <br>https://alpheios.net/</p> <p>B. Umgang mit dem Spracherwerb (Dealing with Language Acquisition)<br>5. Die Digitalisierung fördert einen multimodalen und inklusiven Spracherwerb. (Digitization supports multimodal and inclusive language acquisition.)<br>https://www.hearinglink.org/living/loops-equipment/hearing-loops/what-is-a-hearing-loop/<br>http://www.cross-plus-a.com/balabolka.htm<br>https://propylaeum.de/e-learning/historische-aussprache-des-lateinischen-und-altgriechischen<br>https://www.youtube.com/watch?v=R5vdg_2i_pU<br>https://www.lesediagnostik.de/eye-tracking/<br>https://www.youtube.com/watch?v=8QocWsWd7fc<br>https://www.speechtexter.com/<br>https://etherpad.org/<br>https://moodle.org<br>6. Der Spracherwerb kann flexibel und personalisiert gestaltet werden. (Language acquisition can be designed in a flexible and personalized manner.)</p> <p>C. Umgang mit der Öffentlichkeit (Dealing with the Public)<br>https://www.che.de/third-mission/<br>7. Social Media ermöglichen eine schnelle Interessens- und Wissensvernetzung innerhalb und vor allem außerhalb einer definierten Gemeinschaft. (Social Media enable us to quickly connect interests and knowledge inside and especially outside of a specific community.)<br>https://la.wikipedia.org/wiki/Vicipaedia_Latina<br>http://forum.latein24.de/<br>https://twitter.com/RomAthen<br>https://www.projekte.hu-berlin.de/de/callidus/blog-2017-2018<br>https://www.superprof.de/blog/lateinische-begriffe-im-deutschen/<br>https://www.facebook.com/klassphil/?__tn__=%2Cd%2CP-R&eid=ARDXqBAnvPxAePqFMxWrKxnFG2nfqqzKDWdoHdSg1CBNwBmcZbHwF5f8IWuQZXEODH6VKzqzWvUvUzfU<br>https://www.instagram.com/fs_klassphil_tuebingen/<br>https://hu-berlin.academia.edu/MarkusAsper<br>https://www.researchgate.net/profile/Monica_Berti<br>https://www.br.de/alphalernen/faecher/latein/latein-einfach-erklaert-100.html<br>https://www.pinterest.de/pin/5418462037462026/<br>https://www.youtube.com/channel/UChB8TYnAEtSIL1mY7FuBoqA<br>https://learnattack.de/latein/saetze-uebersetzen?utm_campaign=Learnattack_Kanal&utm_source=youtube.com&utm_medium=social&utm_content=saetze-uebersetzen-latein&kanal=youtube#video-wie-du-einen-lateinischen-satz-%C3%BCbersetzt<br>https://vimeo.com/276706092<br>8. Der digitale weltweite Zugang zu und Austausch von Wissen fördert das informelle Lernen und die Open-Science-Bewegung. (The worldwide digital access to and exchange of knowledge supports informal learning and the Open Science movement.)<br>https://www.udemy.com/course/an-introduction-to-classical-latin/<br>https://www.coursera.org/learn/roman-architecture<br>https://www.coursera.org/learn/plato<br>https://www.youtube.com/channel/UCNW1n7ctSkW3cgYFCzKPK3A/videos<br>https://scholar.google.de/<br>https://www.kim.uni-konstanz.de/openscience/onlinekurs-open-science-von-daten-zu-publikationen/<br>https://www.go-fair.org/fair-principles/<br>https://zenodo.org/record/3601182<br>https://zenodo.org/record/3816709<br>https://scm.cms.hu-berlin.de/callidus<br>https://www.ianus-fdz.de/<br>https://opr.degruyter.com/<br>http://ahropenreview.com/<br>https://arxiv.org/help/trackback<br>https://www.propylaeum.de/<br>https://journals.ub.uni-heidelberg.de/index.php/dco/index<br>http://www.pegasus-onlinezeitschrift.de/<br>https://www.schule-bw.de/faecher-und-schularten/sprachen-und-literatur/latein<br>https://www.schule-bw.de/faecher-und-schularten/sprachen-und-literatur/griechisch<br>https://www.bmbf.de/de/citizen-science-wissenschaft-erreicht-die-mitte-der-gesellschaft-225.html<br>https://pleiades.stoa.org/home</p> <p>Fazit (Conclusion)<br>http://pom.bbaw.de/cmg/</p>
Harnessing the power of digitized natural history collections to visualize spatiotemporal patterns in native and non-native bee flight phenology
<p>What time of year are bees flying, where are they flying, and how do biogeographical factors, sex, and native status affect flight phenology? Consistent monitoring along with creating spatially and temporally explicit visualizations using large openly available data sets enhance our understanding of trends in flight time phenology and shape our understanding of bee-plant interactions, including shifts in the phenology of bee pollinators.</p> <p>Species occurrence data from digitized collection networks (iNaturalist, Global Biodiversity Information Faculty (GBIF), Integrated Digitized Biocollections (iDigBio), Symbiota Collections of Arthropods Network (SCAN), and UC Santa Barbara Collection Network) are part of an effort to improve our understanding of bees in coastal Santa Barbara County, including the California Channel Islands. New inventory collections combined with historical data from over 11 natural history museums and 2 observation networks are used in an effort to examine patterns and changes in phenology of native and non-native bee species, and create updated species inventories.</p> <p>Synthesizing species observation data from digitized natural history collections makes use of a wealth of existing data and multiplies the analytical power of isolated observations, but it is not without limitations and challenges. By exploring novel techniques to generate clear and accurate visualizations to communicate bee flight time, we present our key initial findings and identify geographic, temporal, and taxonomic gaps, which will lead to further focused inventory projects of coastal Santa Barbara County, improved data quality for phenological analyses, and reusable methods for visualizing insect phenology data across taxa or geography.</p> <p><strong>The attached files include the R code and some of the .csv files used to produce the figures in my poster that was available on demand at the Entomology Society of America 2020 virtual meeting. </strong></p>
An open, collaborative, and scholarly digital edition of Anṭūn al-Jumayyil's monthly journal "al-Zuhūr" (Cairo, 1910--1913)
<p>This release has been necessitated by the need for documenting changes and improvements that took place over the last two years:</p> <ol> <li>New sets of facsimiles have been added using IIIF</li> <li>The TEI Boilerplate has been updated to the latest version</li> <li>The mark-up of entities and their links to our authority files have been much improved</li> </ol>
Lipschitz quaternions in the range [−10, 10]^4, which induce bijective 3D digitized rotations
<p>The file contains Lipschitz quaternions in the range [−10, 10]^4, such that they induce bijective 3D digitized rotations. It is a comma-separated values file format such that each line contains a different quaternion. This is an updated version which contains 576 more quaternions with respect to the previous version. These 576 quaternions where previously certified as ones which do not lead to bijective digitized rotations due to a bug in the used implementation of the algorithm described in:</p> <p>Pluta K., Romon P., Kenmochi Y., Passat N. (2016) Bijectivity Certification of 3D Digitized Rotations. In: Bac A., Mari JL. (eds) Computational Topology in Image Context. CTIC 2016. Lecture Notes in Computer Science, vol 9667. Springer, pp 30-41, doi:10.1007/978-3-319-39441-1_4</p> <p> </p> <p><strong>Acknowledgements:</strong><br> Special thanks for Victor Ostromoukhov and David Cœurjolly of University of Lyon 1, LIRIS, France, for finding the bug.</p>
Developing Digital Image Processing methods to quantify internal and interfacial convection in the Hele-Shaw cell, with applications to the laboratory ice-ocean boundary layer
<p>This dataset provides the video and image files obtained from Schlieren optical experiment 3 performed in the <span>Laboratoire de Glaciologie (GLACIOL)</span> at the Universite de libre Bruxelles. A document detailing the visual data and supporting figures is presented (DataOverview.pdf). </p>
Circularity3 DDOMP - Project tracksheets: scholarly publications, non-peer-reviewed digital outputs, dataset log, and software log.
<p>Project tracking sheets for the Circularity3 project. </p> <p>The following tracking sheets are provided:</p> <ol> <li>Scholarly Publications </li> <li>Non-peer-reviewed digital outputs</li> <li>Dataset log </li> <li>Software log </li> </ol> <p>For further specifications and explanations of the tracking sheets refer to the Circularity3 DDOMP here: https://doi.org/10.5281/zenodo.11047951</p> <p> </p> <p>This tracking sheets reference widely the PARSEC research teams tracking sheets, to whom we are very grateful for their transparent and insightful documentation.</p> <p>Stall, Shelley, Specht, Alison, Corrêa, Pedro Luiz Pizzigatti, David, Romain, Edmunds, Rorie, Mabile, Laurence, Machicao, Jeaneth, Miyairi, Nobuko, Murayama, Yasuhiro, O'Brien, Margaret, Wyborn, Lesley, & Vellenich, Danton Ferreira. (2023). PARSEC Data and Digital Output Management Plan and Workbook. Zenodo. <a href="https://doi.org/10.5281/zenodo.3891426">https://doi.org/10.5281/zenodo.3891426</a></p>
Alteromonas Digital Organism Databases
<p>This is the home of the database for the <i>Alteromonas</i> Digital Organism, one of C-CoMP's collaborative efforts. This database was created in anvi'o (anvio-dev) primarily by Michelle DeMers (Massachusetts Institute of Technology) and Rogier Braakman (Massachusetts Institute of Technology), with significant help from members of the Meren Lab (A. Murat Eren, Iva Veseli, and Matthew Schechter) and Moran Lab (Zac Cooper and Mary Ann Moran). This version upload consists of:</p><p>Alteromonas_Pangenome_v2.1.1.md: A reproducible workflow that details the additions made to this version of the pangenome since v2.1.0.</p><p>Alteromonas2.1.1dbs.tar.gz: Collection of all updated contigs databases and genomes storage database.</p><p>external-genomes-v2.txt: Text file consisting of a list of the genomes used in this digital organism with ID, strain, and source information.</p><p>Alteromonas2.1.1pangenome.db.tar.gz: Compressed file containing the <i>Alteromonas</i> pangenome (digital organism).</p><p>Alteromonas2.1.1pangenomefiles.tar.gz: Compressed directory containing any information that anvi'o created when forming the pangenome.</p><p>Alteromonas2.1.1ANI.tar.gz: Compressed directory containing all output files from assessing genome similarity.</p><p>bayesian_2_1_concatenated_proteins*: Concatenated core protein files made from bayesian core gene sets.</p><p>RAxML_*boots: New RAxML tree artifacts produced for this version of the pangenome, with bootstrap values. Includes midpoint rooted tree.</p><p>layer_orders.txt: Tab-delimited file used to import newick tree into the pangenome.</p><p>view.txt: Tab-delimited file containing isolate and strain names.</p>
The Curated Courier: Digital Text Corpora from the UNESCO Courier (1948–2020)
<p>Founded in 1948 as the official magazine of the United Nations Educational, Scientific and Cultural Organization, <i>The UNESCO Courier</i> represents an extraordinary resource for research on global themes in the humanities. The complete <a href="https://en.unesco.org/courier/archives">archive of the magazine</a> is available in PDF form through UNESCO. These files make it possible for users anywhere to read individual issues, but it does not allow for full-text searching, much less any of the computational text analysis methods that have recently made important advances in humanities research.</p><p>The Curated Courier 1.0 is a package of digital text corpora, text analysis tools, and supplementary materials that makes the complete archive of <i>The UNESCO Courier</i> from 1948 to 2020 machine-readable, accessible, and reusable for digital text analysis. </p><p>Here on Zenodo we publish two <i>Courier</i> corpora. The first corpus (curated_courier_article_corpus) consists of the texts of all articles published in the English-language edition of <i>The UNESCO Courier</i> between 1948 and 2020. For this corpus we have extracted and reconstructed the complete text of all articles, for example by pulling together non-contiguous pages where necessary and by removing non-article text (masthead, photo captions, letters to the editor, and so on). We have linked each article to a comprehensive curated metadata index, included in the download (document_index.csv).</p><p>The second corpus (curated_issues) compiles the complete text of all <i>Courier</i> issues (English-language edition), 1948-2020. To prepare this corpus we extracted text from <a href="https://en.unesco.org/courier/archives">the PDFs that UNESCO has made available</a>, used multiple modes of OCR, and rendered each issue as a simple text file. Our test of the OCR quality finds an average error rate of 0.7 %, which should be considered good quality.</p><p>Working data from the process can be found in our <a href="https://github.com/inidun/tagged_courier">GitHub repository "tagged Courier."</a> The products, text analysis tools, and additional documentation are in the <a href="https://github.com/inidun/curated_courier">repository "Curated Courier."</a></p><p>The text of <i>The UNESCO Courier</i> is <a href="https://courier.unesco.org/en/about">available in Open Access</a> under the Attribution-ShareAlike 3.0 IGO (CC-BY-SA 3.0 IGO) license, in the context of <a href="https://en.unesco.org/open-access/">UNESCO's open access publications policy</a>. This dataset is published under the most recent version of the same license: Attribution-ShareAlike 4.0 International (<a href="https://creativecommons.org/licenses/by-sa/4.0/deed.en">CC BY-SA 4.0 Deed</a>).</p><p>These datasets was developed as part of the research project "International Ideas at UNESCO: Digital Approaches to Global Conceptual History" (INIDUN), led by Benjamin G. Martin at Uppsala University and funded by a grant from the Swedish Research Council (Vetenskapsrådet), 2020-2024. For more information, see: <a href="https://inidun.github.io">https://inidun.github.io</a>, as well as the<a href="https://github.com/inidun"> project repository on GitHub</a>, which includes documentation and files related to the curating process.</p>
Digital Elevation Models (DEMs) and lava outlines from the 2023 Litla-Hrútur eruption, Iceland, from Pléiades satellite stereoimages
<p><strong>Introduction:</strong></p><p>On the 10th of July 2023, at 16:40, an eruption started in the Reykjanes Peninsula, Iceland, next to the mountain "Litla-Hrútur". As part of the response, the CIEST2 french initiative was activated (Gouhier et al., 2022). Once activated, Pléiades stereoimages were tasked and scheduled for fast delivery within the area of Interest. On the 20th of August 2023 an additional stereopair of images from Pléiades was acquired and processed after the eruption had stopped.</p><p>Once acquired and delivered, the Pléiades images were processed following the methods described in the section below. This repository contains the near-real time results of DEMs, difference maps compared to a pre-eruption DEM, and lava outlines digitized from the difference map and the orthoimage.</p><p> </p><p><strong>Methods</strong>:</p><p>The Pléiades stereoimages were processed using the Ames StereoPipeline (ASP, Shean et al., 2016, see ASP branch in repository), yielding a DEM in 2x2m GSD and an orthoimage in 0.5x0.5m GSD. The processing was done using as only input the stereoimages and their orientation information, as Rational Polynomial Coefficients (RPCs). The <i>parallel_stereo </i>routine performs all the steps needed in the correlation of the stereoimages, yielding a pointcloud which is then interpolated using the routine <i>point2dem</i>. Besides default parameters, the <i>parallel_stereo</i> parameters used for creation of the DEMs were the standard parameters, plus the following ones: </p><p><i>--stereo-algorithm asp_mgm --corr-tile-size 300 --corr-timeout 900 --cost-mode 3 --subpixel-mode 9 --corr-kernel 7 7 --subpixel-kernel 15 15</i></p><p>Once the DEM was created, DEM co-registration was applying in order to align and minimize positional biases between the pre-eruption DEM and the Pléiades DEMs. We followed the co-registration method of Nuth & Kääb (2011), implemented by David Shean's co-registration routines (<a href="https://github.com/dshean/demcoreg">https://github.com/dshean/demcoreg</a>, Shean et al., 2016). The co-registration involved a horizontal and vertical shift of the Pléiades DEMs, as well as a planar tilt correction. The horizontal offset obtained from the DEM co-registration was also applied to the Pléiades orthoimages.</p><p>The pre-eruption DEM used for this study is a survey done on the 27th of September 2022, data collected Birgir Óskarsson and Robert A. Askew (Icelandic Institute of Natural History) and processed by Sydney R. Gunnarsson and Joaquín M.C. Belart (National Land Survey of Iceland). Metadata of this dataset is available here: https://gatt.lmi.is/geonetwork/srv/eng/catalog.search#/metadata/c59da6cf-18ee-44af-a085-afbad0de029a</p><p>Lava outlines were manually digitized from the co-registered Pléiades orthoimages, The lava outlines are available as GeoPackages in the "GPKG" branch of the repository.</p><p>At the moment, the results from Pléiades are used by the Institute of Earth Sciences of the Univesity of Iceland (Jarðvisindustofnun Háskoli Íslands) to estimate lava volumes and effusion rate, following the methods described in Pedersen et al. (2022). Please contact the authors if these data are intended to be used for a similar purpose, in order to avoid conflict of interests or duplicate work. We encourage collaboration and data sharing for the purpose of the monitoring of the eruption and for research applications.</p><p><strong>Data naming convention:</strong></p><p>faf_YYYYMMDD_hhmmss_hhmmss_*align.tif: DEM obtained from the processing, co-registered to the reference pre-eruption DEM.</p><p>faf_YYYYMMDD_hhmmss_hhmmss_*align_diff.tif: Difference of elevation between the Pléiades DEM and the pre-eruption DEM.</p><p>faf_YYYYMMDD_hhmm.gpkg: Polygon containing the lava outlines, extracted from the Pléiades orthoimage and the map of elevation difference.</p><p>0_faf_YYYYMMDD_hhmmss_hhmmss_*fig.png: A figure showing the latest map of elevation difference, overlaid with a hillshade of the latest Pléiades DEM and the latest lava outlines, result of the processing of the Pléiades stereoimages. The figure was created using the tool imviewer.py from the GitHub repository https://github.com/dshean/imview (Shean et al., 2016).</p><p><strong>Data Specifications:</strong></p><ul><li>Cartographic projection: ISN93 / Lambert 1993 (EPSG:3057, <a href="http://https:/epsg.io/3057">https://epsg.io/3057</a>)</li><li>Origin of Elevation: meters above GRS80 ellipsoid (WGS84)</li><li>Raster data format: GeoTIFF</li><li>Raster compression system: LZW</li><li>Vector data format: GeoPackage (<a href="https://www.geopackage.org/">https://www.geopackage.org/</a>)</li><li>Pléiades dataset includes only DEMs because the Pléiades ortho imagery is for licensed use only. Please contact the authors for further information on this.</li></ul><p><strong>Acknowledgements</strong>: </p><p>Pléiades images from July 2023 were provided under the CIEST² initiative (CIEST2 is part of ForM@Ter (<a href="https://en.poleterresolide.fr/">https://en.poleterresolide.fr/</a>). Pléiades images from August 2023 were provided under the CEOS Volcano Supersite (https://ceos.org/ourwork/workinggroups/disasters/gsnl/). Image Pléiades©CNES2023, distribution AIRBUS DS.</p><p><strong>Dataset Attribution</strong>:</p><p>This dataset is licensed under a <a href="https://creativecommons.org/licenses/by-nc/4.0/">Creative Commons CC BY-NC 4.0 International License</a> (Attribution-NonCommercial).</p><p><strong>Citation:</strong></p><p>Please cite this repository as described below:</p><p>Joaquin M.C. Belart, Virginie Pinel, Hannah. I. Reynolds, Etienne Berthier, & Sydney R. Gunnarson. (2023). Digital Elevation Models (DEMs) and lava outlines from the 2023 Litla-Hrútur eruption, Iceland, from Pléiades satellite stereoimages (1) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.10133203</p>
Data for "Demographic inequalities in digital spaces in China: The case of Weibo"
<p>These data underlie the results and figures used in the article "Demographic inequalities in digital spaces in China: The case of Weibo" (https://doi.org/10.36190/2023.01). This research was presented at the ICWSM workshop "Data for the wellbeing of the most vulnerable" on June 5, 2023.</p><p>The corresponding workflow can be found in the linked repository.</p><p>`README.md` provides more details.</p>
BST/NOAA PSL Level 2 UAS Soil Moisture, Digital Elevation, Normalized Difference Vegetative Index, and Surface Temperature for SPLASH
<p>This dataset contains uncrewed aircraft systems (UAS) high-resolution data of soil moisture at the 0-5 cm soil depth, normalized difference vegetation index (NDVI), surface temperature, and digital elevation for the Study of Precipitation, the Lower Atmosphere, and Surface for Hydrology (SPLASH) campaign sponsored by the National Oceanic and Atmospheric Administration (NOAA). These data were collected near Avery Picnic (38.972425 degrees N,106.996855 degrees W) and Kettle Ponds (38.942005 degrees N,106.973006 degrees W) in the East River Watershed in Colorado from a series of flights starting on June 1st, 2022 and ending October 18th, 2023. Soil moisture measurements were retrieved using the Lobe Differencing Correlation Radiometer (LDCR) which is a L-Band (1-2 GHz) microwave radiometer and was flown on the E2 and S2 aerial platforms operated by Black Swift Technologies LLC. </p> <p> </p> <p>Each zip file contains a set of four Level 2 NetCDF files which provides the highest spatial resolution available for each of four products for a given flight location. With the Level 2 data, each flight location and variable can have different spatial resolutions depending on the sensor type, retrieval algorithm, and flight altitude. The file name convention for the zip files is as follows.</p> <p> </p> <p>uas_L2_yyyymmdd_hhmmss_vX.X.zip </p> <p>where</p> <p>L2 = Level 2 data </p> <p>yyyymmdd = year,month,day</p> <p>hhmmss = hour,minute,second</p> <p>vX.X = version number</p> <p>Time is the flight start time in UTC.</p> <p> </p> <p>The NetCDF file format contained in the zip files has a similar format to the zip files with convention</p> <p> </p> <p>uas_<var>_L2_yyyymmdd_hhmmss.nc </p> <p>where</p> <p><var> = vsm, dem, ndvi, or stmp</p> <p>vsm = volumetric soil moisture</p> <p>dem = digital elevation</p> <p>ndvi = normalized difference vegetation index</p> <p>stmp = surface temperature</p> <p> </p> <p>Note that each flight location using the E2 aerial platform required two flights so starting flight times for the soil moisture NetCDF files are different from the other three products.</p> <p><strong>November 2023 update</strong>: Version 2.0 added flight data from 2023. Version 2.0 includes an updated calibration of the soil moisture retrieval that has been applied to 2023 data, and a mask was applied to the soil moisture retrieval over water surfaces for both 2022 and 2023 data.</p> <p><strong>December 2023 update</strong>: Version 2.1 updated soil moisture data with a wet bias in v2.0 for flights #2 (17:40:35 UTC) and #3 (19:24:45 UTC) on July 27, 2022.</p>
Ruegeria pomeroyi digital microbe databases
<p>These databases consolidate a variety of datasets related to the model organism Ruegeria pomeroyi DSS-3. The data were primarily generated by members of the Moran Lab at the University of Georgia, and put together in this format using anvi'o v7.1-dev through the collaborative efforts of Zac Cooper, Sam Miller, and Iva Veseli (special thanks to Christa Smith and Lidimarie Trujillo Rodriguez for their help with gene annotations). The data includes:</p> <p>- (R_POM_DSS3-contigs.db) the complete genome and megaplasmid sequence of R. pomeroyi, along with highly-curated gene annotations established by the Moran Lab and automatically-generated annotations from NCBI COGs, KEGG KOfam/BRITE, Pfams, and anvi'o single-copy core gene sets. It also contains annotations for the Moran Lab's TnSeq mutant library (<a href="https://doi.org/10.1101/2022.09.11.507510">https://doi.org/10.1101/2022.09.11.507510</a>; <a href="https://doi.org/10.1038/s43705-023-00244-6">https://doi.org/10.1038/s43705-023-00244-6</a>).</p> <p>- (PROFILE-VER_01.db) read-mapping data from multiple transcriptome and metatranscriptome samples generated by the Moran lab to the R. pomeroyi genome. Some coverage data is stored in the AUXILIARY-DATA.db file. This data can be visualized using anvi-interactive. Publicly-available samples are labeled with their SRA accession number.</p> <p>- (DEFAULT-EVERYTHING.db) gene-level coverage data from the transcriptome and meta-transcriptomes samples stored in the profile database, as well as per-gene normalized spectral abundance counts from proteomes matched to a subset of the transcriptomes and gene mutant fitness data from <a href="https://doi.org/10.1073/pnas.2217200120">https://doi.org/10.1073/pnas.2217200120</a>. This data can also be visualized using anvi-interactive (see instructions below). The proteome data layers are labeled according to their matching transcriptome samples.</p> <p>- (R_pom_reproducible_workflow.md) a reproducible workflow describing how the databases were generated.</p> <p><em>Please note that using these databases requires the development version of anvi'o `v8-dev`, or a later version of anvi'o if available. They are not usable with anvi'o `v8` or earlier.</em></p> <p>Instructions for <strong>visualizing the genes database</strong> in the anvi'o interactive interface: Anvi'o expects genes databases to be located in a folder called `GENES`, so in order to use the specific database included in this datapack, you must move it to the expected location by running the following commands in your terminal:</p> <blockquote> <p>mkdir GENES<br>mv DEFAULT-EVERYTHING.db GENES/<br> </p> </blockquote> <p>Once that is done, you can use the following command to visualize the gene-level information:</p> <blockquote> <p>anvi-interactive -c R_POM_DSS3-contigs.db -p PROFILE-VER_01.db -C DEFAULT -b EVERYTHING --gene-mode</p> </blockquote> <p>To view <strong>only the proteomic data</strong> and its matched transcriptomes, you can add the flag `--state-autoload proteomes` to the above command.</p> <p>To view all transcriptomes and the proteomes <strong>organized by study of origin</strong>, you can add the flag `--state-autoload figure` to the above command.</p>
Example data from a virtual mass comparison using the Digital Calibration Certificate (DCC) scheme
<p><strong>The example data is an outcome of a project on a fully automated evaluation of a virtual mass comparison using the Digital Calibration </strong><strong>Certificate (DCC) schema.</strong></p> <p>We present the proof of concept for the first fully automated evaluation of a virtual mass comparison. The focus of this comparison is to demonstrate a possibility of digital transformation in metrology using an automated evaluation chain of different tools as well as machine-interpretable files for data transfer and final report. This publication provides the example data being used as input and output of the automated comparison evaluation tool.</p>
Accelerating Digital Skills for Music Researchers - Processing Text-Based Corpora for Musical Discourse Analysis - Episode 5
<p>Dataset containing four .xlsx and .csv files for the exercises in Episode 5 of the <a href="https://acceleratingdigitalskills.github.io/Processing-Text-Based-Corpora/">Processing Text-Based Corpora for Musical Discourse Analysis</a> lesson of the <a href="https://acceleratingdigitalskills.org/">Accelerating Digital Skills for Music Researchers</a> project. The original data was collected from <a href="https://boomkat.com/">Boomkat.com</a> with permission.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.