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  • Digital Humanities and Cultural Heritage
  • 2013-2022
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Dupret, Vincent;

    The current data set refers to the study of fossil fish material from Southwest Ireland (Placodermi, Antiarchi; Givetian of the Iveragh Peninsula). The data consist of SEM elemental mapping (section 1), CTscan image stacks and subsequent working files (i.e. segmentation, visualisation files, STLs and 3D PDF files; sections 2-5), as well as phylogenetic analyses related to the genus Bothriolepis studied in the article (section 6). * Zoobank LSID for article: urn:lsid:zoobank.org:pub:0438B3D4-AEAA-4000-A1CB-B5DA0ECA466F * Zoobank LSID for taxon Bothriolepis dairbhrensis: urn:lsid:zoobank.org:act:B577F075-1EF6-48A5-8C7C-E64E36E2BC4E The dataset corresponding to the article Dupret, Byrne, Castro, Hammer, Higgs, Long, Niedźwiedzki, Qvarnström, Stössel & Ahlberg. In Press. The Bothriolepis (Placodermi, Antiarcha) material from the Valentia Slate Formation of the Iveragh Peninsula (middle Givetian, Ireland): morphology, evolutionary and systematic considerations, phylogenetic and palaeogeographic implications. PLOS ONE. with the LSID urn:lsid:zoobank.org:pub:0438B3D4-AEAA-4000-A1CB-B5DA0ECA466F and the species Bothriolepis dairbhrensis Dupret, Byrne, Castro, Hammer, Higgs, Long, Gzegorz Niedźwiedzki, Qvarnström, Stössel & Ahlberg with the LSID urn:lsid:zoobank.org:act:B577F075-1EF6-48A5-8C7C-E64E36E2BC4E is composed of the following files: 1. Elemental analysis (SEM) equipment: Hitachi S–3600N Scanning Electron Microscope (SEM); JPGS are original output. 2. CT-scans datasets In London, the material was CT-scanned with a Nikon HMX ST 225 system, Nikon Metrology, Leuven, Belgium, with a tungsten reflection target. Detailed settings files were adjusted for each specimen and are given in associated documentation "S2 Table-scan properties.xlsx". Two specimens required stitching performed with an in-house NHM script written in Octave. In Oslo, the scanning was carried out with a Nikon Metrology XT H 225 ST microfocus CT instrument at the Natural History Museum, University of Oslo, at 160-220 kV, 1 s exposure time, 3016 projections, and with tin filters of varying thickness. Voxel resolution was 75 µm or better. Detailed settings are given in in associated documentation "S2 Table-scan properties.xlsx". 3. Drishti and Mimics files (segmentation) 4. STL files 5. 3D pdfs In Mimics, each individual structure corresponding to a mask was used to generate a high quality 3D object, itself transformed into an STL file. Each 3D object was duplicated and relocated in the 3D space; once again STLs were generated. The STL files were then imported into Materialise 3-matic (v. 15.0) and were reorganised into anatomical ensembles (head, fin, etc.) in both original and correct positions. Each STL surface was then simplified and corrected using the following functions: Filter Sharp Triangles with filter distance 0.01; Filter Small Edges with filter distance 0.01; Improve Mesh with shape quality high/medium, maximum geometrical error 0.07, and maximal edge length 20.0. A 3D pdf file was finally generated and open in Adobe Acrobat to take pictures used in figures of the current article. for the following specimens a. NMING:F35203-UU210ab_HQ Bothriolepis dairbhrensis sp. nov. Incomplete lateral plate and fragment of indeterminate plate. Segmentation in Mimics, treatment of STLS and 3d PDF exportation in 3-matic. The scale of the reference cube edges is 10 mm. Please note that within the Mimics project files for this specimen µm is incorrectly given as a base of measurement when it should be mm (millimeters). All other processing has been performed treating the source data as being scaled in millimeters. b. NMING:F35229-CH003 Bothriolepis dairbhrensis sp. nov. Assemblage of indeterminate plate and indeterminate scavenging gastropods. Segmentation in Mimics, treatment of STLS and 3d PDF exportation in 3-matic. The scale of the reference cube edges is 10 mm. c. NMING:F35216-UU SFB001 Bothriolepis dairbhrensis sp. nov. Proximal segment of the pectoral fin, with AVL and articular condyle. [ORG] corresponds to plates in original position; [RELOC] corresponds to plates relocated in life position. Segmentation in Mimics, treatment of STLS and 3d PDF exportation in 3-matic. The scale of the reference cube edges is 10 mm. d. NHM P 59677 (complete, ORG end RELOC files) Bothriolepis dairbhrensis sp. nov. Incomplete head (and endocranial processes), ventral body armour and proximal segment of the pectoral fin. [ORG] corresponds to plates in original position; [RELOC] corresponds to plates relocated in life position. Segmentation in Mimics, treatment of STLS and 3d PDF exportation in 3-matic. The scale of the reference cube edges is 10 mm. e. NHM P 59678 Bothriolepis dairbhrensis sp. nov. Incomplete lateral and indeterminate plates of an adult individual. The scale of the reference cube edges is 10 mm. f. NHM P 59679 Bothriolepis dairbhrensis sp. nov. Two indeterminate fragments. The scale of the reference cube edges is 10 mm. g. NHM P 59687 Bothriolepis dairbhrensis sp. nov. Indeterminate fragments and burrows. The scale of the reference cube edges is 10 mm. 6. taxon*character matrices with different sets of analyses (readible in MESQUITE) **LINKS TO PREVIOUSLY MENTIONED SOLUTIONS** MESQUITE (construction of data matrix, visualisation): https://www.mesquiteproject.org/ https://github.com/MesquiteProject/ Maddison, W. P. and D.R. Maddison. 2021. Mesquite: a modular system for evolutionary analysis. Version 3.70 http://www.mesquiteproject.org ZEPHYR (Mesquite package for interacting with external phylogeny inference programs) http://zephyr.mesquiteproject.org/ Maddison, D.R., & W.P. Maddison. 2021. Zephyr: a Mesquite package for interacting with external phylogeny inference programs. Version 3.20. http://zephyr.mesquiteproject.org TNT (phylogenetic analysis) https://onlinelibrary.wiley.com/doi/10.1111/j.1096-0031.2008.00217.x Goloboff, P.A., Farris, J.S. and Nixon, K.C. (2008), TNT, a free program for phylogenetic analysis. Cladistics, 24: 774-786. https://doi.org/10.1111/j.1096-0031.2008.00217.x MATERIALISE MIMICS and 3-MATIC (segmentation, 3D modelling): https://www.materialise.com/en/healthcare/mimics-innovation-suite DRISHTI (3D visualisation): https://github.com/nci/drishti Ajay Limaye; Drishti: a volume exploration and presentation tool. Proc. SPIE 8506, Developments in X-Ray Tomography VIII, 85060X (October 17, 2012) Datasetet hänger samman med en studie av fossilt fiskmaterial från sydvästra Irland (Placodermi, Antiarchi; Givetian på Iveragh-halvön). Data består av SEM-elementkartläggning (avsnitt 1), datortomografiska bildstaplar och efterföljande arbetsfiler (dvs. segmentering, visualiseringsfiler, STL-filer och 3D PDF-filer; avsnitt 2-5), samt fylogenetiska analyser relaterade till släktet Bothriolepis som studerats i artikeln (avsnitt 6). * Zoobank LSID för artikeln: urn:lsid:zoobank.org:pub:0438B3D4-AEAA-4000-A1CB-B5DA0ECA466F * Zoobank LSID för taxon Bothriolepis dairbhrensis: urn:lsid:zoobank.org:act:B577F075-1EF6-48A5-8C7C-E64E36E2BC4E Data som motsvarar artikeln Dupret, Byrne, Castro, Hammer, Higgs, Long, Niedźwiedzki, Qvarnström, Stössel & Ahlberg. In Press. The Bothriolepis (Placodermi, Antiarcha) material from the Valentia Slate Formation of the Iveragh Peninsula (middle Givetian, Ireland): morphology, evolutionary and systematic considerations, phylogenetic and palaeogeographic implications. PLOS ONE. med LSID urn:lsid:zoobank.org:pub:0438B3D4-AEAA-4000-A1CB-B5DA0ECA466F och arten Bothriolepis dairbhrensis Dupret, Byrne, Castro, Hammer, Higgs, Long, Gzegorz Niedźwiedzki, Qvarnström, Stössel & Ahlberg med LSID urn:lsid:zoobank.org:act:B577F075-1EF6-48A5-8C7C-E64E36E2BC4E består av följande filer: 1. Elementaranalys (SEM) utrustning: Hitachi S–3600N svepelektronmikroskop (SEM); JPG-filerna är originalutdata. 2. Dataset från datortomografi I London kördes datortomografi på materialet med ett Nikon HMX ST 225-system (Nikon Metrology, Leuven, Belgien), utrustat med ett reflektionsmål av volfram. Detaljerade inställningsfiler justerades för varje exemplar och finns angivna i den tillhörande dokumentationsfilen "S2 Table-scan properties.xlsx". Två exemplar krävde sammanfogning med hjälp av ett särskilt framtaget NHM-skript skrivet i Octave. I Oslo utfördes skanningen med ett Nikon Metrology XT H 225 ST mikrofokus CT-instrument vid Naturhistorisk museum, Universitetet i Oslo, med 160-220 kV, 1 s exponeringstid, 3016 projektioner och med tennfilter av varierande tjocklek. Voxelupplösningen var 75 µm eller bättre. Detaljerade inställningar finns även här angivna i den tillhörande dokumentationsfilen "S2 Table-scan properties.xlsx". 3. Materialise Mimics och Drishti-filer (segmentering) 4. STL-filer 5. 3D PDF-filer I Mimics användes varje enskild struktur som motsvarar en mask för att generera ett högkvalitativt 3D-objekt, som i sig omvandlades till en STL-fil. Varje 3D-objekt duplicerades och positionerades om i 3D, och STL-filer genererades åter. STL-filerna importerades sedan till Materialise 3-matic (v. 15.0) och omorganiserades till anatomiska ensembler (huvud, fena, etc.) i både ursprungliga och korrekta positioner. Varje STL-yta förenklades sedan och korrigerades med hjälp av följande funktioner: "Filter Sharp Triangles" med filter distance 0,01; "Filter Small Edges" med filter distance 0,01; "Improve Mesh" med shape quality high/medium, maximum geometrical error 0,07 och maximal edge length 20,0. En 3D PDF-fil genererades till slut och öppnades i Adobe Acrobat för att ta bilder som används i figurer i den relaterade artikeln. för följande exemplar a. NMING:F35203-UU210ab_HQ Bothriolepis dairbhrensis sp. nov. Ofullständig lateralplatta och fragment av obestämd platta. Segmentering i Mimics, behandling av STL-filer och 3D PDF-export i 3-matic. Referenskubens kanter är 10 mm. Notera att i Mimics-projektfilerna för detta exemplar är µm av misstag angivet som måttreferens när det skall vara mm (millimeter). All annan bearbetning har skett med förutsättningarna att måttreferensen är i millimeter. b. NMING:F35229-CH003 Bothriolepis dairbhrensis sp. nov. Sammansättning av obestämd platta och obestämda asätande gastropoder. Segmentering i Mimics, behandling av STL-filer och 3D PDF-export i 3-matic. Referenskubens kanter är 10 mm. c. NMING:F35216-UU SFB001 Bothriolepis dairbhrensis sp. nov. Proximalt segment av bröstfenan, med AVL och ledkondyl. [ORG] motsvarar plattor i ursprunglig position; [RELOC] motsvarar plattor som flyttats till livsläge. Segmentering i Mimics, behandling av STL-filer och 3D PDF-export i 3-matic. Referenskubens kanter är 10 mm. d. NHM P 59677 (komplett, ORG-slut RELOC-filer) Bothriolepis dairbhrensis sp. nov. Ofullständigt huvud (och endokraniella processer), ventralt kroppspansar och proximalt segment av bröstfenan. [ORG] motsvarar plattor i ursprunglig position; [RELOC] motsvarar plattor som flyttats till livsläge. Segmentering i Mimics, behandling av STL-filer och 3D PDF-export i 3-matic. Referenskubens kanter är 10 mm. e. NHM P 59678 Bothriolepis dairbhrensis sp. nov. Ofullständiga laterala och obestämda plattor av en vuxen individ. Referenskubens kanter är 10 mm. f. NHM P 59679 Bothriolepis dairbhrensis sp. nov. Två obestämda fragment. Referenskubens kanter är 10 mm. g. NHM P 59687 Bothriolepis dairbhrensis sp. nov. Obestämda fragment och hålor. Referenskubens kanter är 10 mm. 6. taxon*karaktär-matriser med olika uppsättningar av analyser (läsbara i MESQUITE) **LÄNKAR TILL ANVÄNDA VERKTYG** MESQUITE (konstruktion av datamatris, visualisering) https://www.mesquiteproject.org/ https://github.com/MesquiteProject/ Maddison, W. P. and D.R. Maddison. 2021. Mesquite: a modular system for evolutionary analysis. Version 3.70 http://www.mesquiteproject.org ZEPHYR (Mesquite-paket för interaktion med externa fylogeni-inferensprogram) http://zephyr.mesquiteproject.org/ Maddison, D.R., & W.P. Maddison. 2021. Zephyr: a Mesquite package for interacting with external phylogeny inference programs. Version 3.20. http://zephyr.mesquiteproject.org TNT (fylogenetisk analys) https://onlinelibrary.wiley.com/doi/10.1111/j.1096-0031.2008.00217.x Goloboff, P.A., Farris, J.S. and Nixon, K.C. (2008), TNT, a free program for phylogenetic analysis. Cladistics, 24: 774-786. https://doi.org/10.1111/j.1096-0031.2008.00217.x MATERIALISE MIMICS and 3-MATIC (segmentering, 3D-modellering): https://www.materialise.com/en/healthcare/mimics-innovation-suite DRISHTI (3D-visualisering): https://github.com/nci/drishti Ajay Limaye; Drishti: a volume exploration and presentation tool. Proc. SPIE 8506, Developments in X-Ray Tomography VIII, 85060X (October 17, 2012)

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    Swedish National Data Service
    Dataset . 2022
    Data sources: Datacite
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      Swedish National Data Service
      Dataset . 2022
      Data sources: Datacite
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    Afaan Oromo Text to Speech Synthesis dataset is a public domain speech dataset consisting of 8,076 short audio clips of a single male speaker reading sentences collected from legitimate sources such as News Media sources, Non-fiction books, and Afaan Oromo Holy bible. A transcription and its normalized text are provided for each clip. After two weeks of the audio recording process, a total of 17 hours of recorded speech data that corresponded to a total of 8076 recorded .wav files was created.File FormatMetadata is provided in metadata.csv. This file consists of one record per line, delimited by the pipe character. The fields are:ID: this is the name of the corresponding .wav fileTranscription: words spoken by the reader (UTF-8)Normalized Transcription: transcription with numbers, ordinals, and monetary units expanded into full words (UTF-8).Each audio file is a single-channel 16-bit PCM WAV with a sample rate of 22050 Hz. THIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOVE

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    Mendeley Data
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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    Mendeley Data; NARCIS
    Dataset . 2022
    License: CC BY
    Data sources: Datacite; NARCIS
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    DANS-EASY
    Dataset . 2022
    Data sources: B2FIND
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    Mendeley Data
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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      Mendeley Data
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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      Mendeley Data; NARCIS
      Dataset . 2022
      License: CC BY
      Data sources: Datacite; NARCIS
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      DANS-EASY
      Dataset . 2022
      Data sources: B2FIND
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      Mendeley Data
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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    Authors: Haneca; Ervynck;

    In deze zenodo-record zijn de brongegevens terug te vinden waarop de analyses in het hoofdstuk "Kenniswinst archeologieregelgeving 2016-2021" zijn gebaseerd. Dit hoofdstuk maakt deel uit van het onderzoeksrapport "Ameels V, Carpentier F, De Ketelaere S, Ervynck A, Geuens J, Haneca K, Pieters M, Van Looveren J & Verhelst A 2023: Evaluatie archeologie 2016-2021, Onderzoeksrapport Agentschap Onroerend Erfgoed, Brussel.": 1. Een overzicht van alle ingediende eindverslagen (n = 576) en nota's met eindafwerking (n = 26) over de periode 1 april 2016 t.e.m. 31 december 2021 eindverslagen_notas_2016_2021_overzicht.csv (comma-separated values) eindverslagen_notas_2016_2021_overzicht.xlsx (Microsoft Excel Open XML Spreadsheet) eindverslagen_notas_2016_2021_overzicht.shp (ESRI shapefile) (Een overzicht van alle ingediende eindverslagen - vanaf 1 april 2016 tot vandaag - kan je ook downloaden als GIS-bestand op https://geo.onroerenderfgoed.be/downloads.) 2. De resultaten van de inhoudelijke screening (periodisering, materiaalcategorieën, ...) van deze documenten: eindverslagen_notas_2016_2021_screening.csv (comma-separated values) eindverslagen_notas_2016_2021_screening.xlsx (Microsoft Excel Open XML Spreadsheet) eindverslagen_notas_2016_2021_screening.shp (ESRI shapefile)

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    ZENODO
    Dataset . 2022
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2022
    License: CC BY
    Data sources: ZENODO
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      ZENODO
      Dataset . 2022
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      Data sources: Datacite
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      ZENODO
      Dataset . 2022
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    Authors: Li, Weixuan;

    Abraham Bredius’ seminal work Künstler-Inventare contains over 150 inventories of artists’ possessions in the Dutch Republic. However, this rich source has never been fully transformed into datasets, partially because Bredius was selective in his transcriptions of artists’ inventories with a focus on paintings. To fill this gap and to overcome Bredius’ biases, the Virtual Interior project assembled and transcribed 46 inventories of artists’ and art dealers’ homes in 17th-century Amsterdam. The selection of the inventories was based on three criteria: 1) The artists’ and art dealers’ inventories in my sample were drawn up during an artist’s lifetime or shortly after his death; 2) the inventories listed goods arranged by room; 3) the original documents of the inventories can still be traced in the Amsterdam City Archives. Forty-six inventories were selected and transcribed from the original sources or copied from existing publications. The majority of my samples can be found in the notarial archives (Archive nr. 5075) and the rest in the Archive of the Chamber of Insolvency (Desolate Boedel kamer, Archive nr. 5072), both preserved in the Amsterdam City Archives. Starting with the published inventories, Bart Reuvekamp from our project team traced them back to the original sources in the archive, transcribed centuries-old handwritten pages, and compiled the listed objects in digital form. In this way, our database is able to encompass all belongings present in painters’ workshops, filling in the blanks that Bredius and other authors neglected or chose to leave out – the missing information that once hindered our comprehension of how artists organized their studios. The dataset is organized as follows: 1_Intro_and_data_explanation.xlsx introduces the dataset and explains the columns in the following files 2_Inventory_list.csv hosts the details of the inventories in this dataset 3_Inventory_items.csv contains the full transcriptions and categorical data of the objects in the inventories 4_Inventory_relationships.csv captures all the people mentioned in the inventories in the pre- or postscript and/or as debtors or creditors 5_Inventory_category_reference.csv provides a reference table for the ‘object_type’ and ‘object_category’ columns in 3_Inventory_items.csv 6_Inventory_subjectmatter_reference.csv offers a reference table for the ‘painting_subject’ and ‘painting_genre’ columns in 3_Inventory_items.csv NB: This Künstler-Inventare database is a provisional version. The correction and final data process has not been fully finished in Version 1. The transcriptions might contain errors and need to be treated with caution. This project is financed by NWO Smart Culture - Big Data / Digital Humanities grant

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    ZENODO
    Dataset . 2022
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    Data sources: Datacite
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      ZENODO
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    Authors: Keshav Santhanam, Jon Saad-Falcon, Martin Franz, Omar Khattab, Avirup Sil, Radu Florian, Md Arafat Sultan, Salim Roukos, Matei Zaharia, Christopher Potts;

    XOR TyDi query and document files for running PLAID-ColBERTv2 experiments from "Moving Beyond Downstream Task Accuracy for Information Retrieval Benchmarking".

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    ZENODO
    Dataset . 2022
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2022
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      ZENODO
      Dataset . 2022
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2022
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    Authors: Berger, Michael; Bolte, Henrike; Führer, Veronika; Hausleitner, Felix; +9 Authors

    This is ground truth for the vast collection of sermons of Nikolaus von Dinkelsbühl (ca. 1360 to 17th March 1433), translated and reorganised by a German redactor, from the 15th century has never been edited until now. It consists of 361 folios of parchment and paper. The text speaks about various topics such as fasting and other religious practices. Being one of the leading intellectuals of his time, Nikolaus von Dinkelsbühl also contributed to the development of the University of Vienna. The manuscript was probably produced in the vicinity of Klosterneuburg in Austria and is still kept there today (Shelfmark: Cod. 48). Data collection and ground truth creation: The edition at hand was produced by an international team of researchers from various fields in the context of the Vienna HTR Winter School 2022 with the help of Transkribus Expert Client. We uploaded the images of the manuscript into the Transkribus platform, applied the line recognition tool and manually copied the transcribed text lines into the recognised line boxes. Various models were trained with the ground truth (20% of the entire codex) created by the team. Images of the Klosterneuburg, Augustiner-Chorherrenstift, Cod. 48 are available at: https://manuscripta.at/diglit/AT5000-48/0001

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    ZENODO
    Dataset . 2022
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2022
    License: CC BY
    Data sources: ZENODO
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      ZENODO
      Dataset . 2022
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2022
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    Authors: Ina Serif;

    The database derives from my research for my PhD, which I conducted between 2013 and 2017 at the University of Freiburg (Germany). The thesis was defended in summer 2018 and published in 2020 with De Gruyter: Ina Serif: Geschichte aus der Stadt. Überlieferung und Aneignungsformen der deutschen Chronik Jakob Twingers von Königshofen. Berlin/Boston 2020. I have been using nodegoat for several years now as my working and data storing environment. As it is a relational database, the export for this repository consists of two files: the main file, manuscripts.csv, which contains the manuscripts and their metadata, and a content file, content.csv, which contains the relations between texts and manuscripts, using "nodegoat_ID" as identifier. As of 2022, the main file consists of 128 records, the content file of 1220 entries. You should be able to import it to the software you prefer, linking the content to the manuscripts through "nodegoat_ID". The metadata fields for the manuscripts are the following: nodegoat ID, Institution, Call no., Sigle, Folio no., Material, Language, illustrated, Exact date of origin, Date of origin, Place of origin, Place certain, Chronicle Version, Additional info. The information about the single codices derives from manuscript catalogues, research articles, and own analyses. For a complete bibliography of the used literature see my thesis, pp. 215–245. As this is a finished research project, the database gets updated only on an irregular basis. I am also maintaining an online article about the known manuscripts and existing digital versions: Ina Serif: Der zerstreute Chronist. Zur Überlieferung der deutschsprachigen Chronik Jakob Twingers von Königshofen, in: Mittelalter. Interdisziplinäre Forschung und Rezeptionsgeschichte, 2/2015, last update 10/2021, https://mittelalter.hypotheses.org/7063. The record for the chronicle in the Handschriftencensus does not list all manuscripts that I consider to be textual witnesses (as of October 2021, it lists 115 manuscripts), but contains additional information regarding single codices.

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    ZENODO
    Dataset . 2022
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    Data sources: Datacite
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    ZENODO
    Dataset . 2022
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      ZENODO
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      ZENODO
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    Authors: Berg, Johanna; Aasa, Carl Ollvik; Appelgren Thorell, Björn; Aits, Sonja;

    Electronic health records (EHRs) are a rich source of information for medical research and public health monitoring. Information systems based on EHR data could also assist in patient care and hospital management. However, much of the data in EHRs is in the form of unstructured text, which is difficult to process for analysis. Natural language processing (NLP), a form of artificial intelligence, has the potential to enable automatic extraction of information from EHRs and several NLP tools adapted to the style of clinical writing have been developed for English and other major languages. In contrast, the development of NLP tools for less widely spoken languages such as Swedish has lagged behind. A major bottleneck in the development of NLP tools is the restricted access to EHRs due to legitimate patient privacy concerns. To overcome this issue we have generated a citizen science platform for collecting artificial Swedish EHRs with the help of Swedish physicians and medical students. These artificial EHRs describe imagined but plausible emergency care patients in a style that closely resembles EHRs used in emergency departments in Sweden. In the pilot phase, we collected a first batch of 50 artificial EHRs, which has passed review by an experienced Swedish emergency care physician. We make this dataset publicly available as OpenChart-SE corpus (version 1) under an open-source license for the NLP research community. The project is now open for general participation and Swedish physicians and medical students are invited to submit EHRs on the project website (https://github.com/Aitslab/openchart-se), where additional batches of quality-controlled EHRs will be released periodically. Dataset content OpenChart-SE, version 1 corpus (txt files and and dataset.csv) The OpenChart-SE corpus, version 1, contains 50 artificial EHRs (note that the numbering starts with 5 as 1-4 were test cases that were not suitable for publication). The EHRs are available in two formats, structured as a .csv file and as separate textfiles for annotation. Note that flaws in the data were not cleaned up so that it simulates what could be encountered when working with data from different EHR systems. All charts have been checked for medical validity by a resident in Emergency Medicine at a Swedish hospital before publication. Codebook.xlsx The codebook contain information about each variable used. It is in XLSForm-format, which can be re-used in several different applications for data collection. suppl_data_1_openchart-se_form.pdf OpenChart-SE mock emergency care EHR form. suppl_data_3_openchart-se_dataexploration.ipynb This jupyter notebook contains the code and results from the analysis of the OpenChart-SE corpus. More details about the project and information on the upcoming preprint accompanying the dataset can be found on the project website (https://github.com/Aitslab/openchart-se). Acknowledgement We thank all citizen scientists for contributing artificial EHRs and all members of our research groups, who provided helpful comments throughout the development of this project. This study was supported by a grant to Science for Life Laboratory from the Knut and Alice Wallenberg (KAW) Foundation (S.A. 2020.0182), which was distributed through the SciLifeLab and KAW National COVID-19 Research Program. The project is conducted in the AI Lund research environment at Lund University.

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    ZENODO
    Dataset . 2022
    License: CC BY
    Data sources: Datacite
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    ZENODO
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    Authors: Dhrangadhariya, Anjani; Müller, Henning;

    This upload contains four main zip files. ds_cto_dict.zip: This zip file contains the four distant supervision dictionaries (P: participant.txt, I = intervention.txt, intervetion_syn.txt, O: outcome.txt) generated from clinicaltrials.gov using the Methodology described in Distant-CTO (https://aclanthology.org/2022.bionlp-1.34/). These dictionaries were used to create distant supervision labelling functions as described in the Labelling sources subsection of the Methodology. The data was derived from https://clinicaltrials.gov/ handcrafted_dictionaries.zip: This zip folder contains three files 1) gender_sexuality.txt: a list of possible genders and sexual orientations found across the web. The list needs to be more comprehensive. 2) endpoints_dict.txt: contains outcome names and the names of questionnaires used to measure outcomes assembled from PROM questionnaires and PROMs. and 3) comparator_dict: contains a list of idiosyncratic comparator terms like a sham, saline, placebo, etc., compiled from the literature search. The list needs to be more comprehensive. test_ebm_correctedlabels.tsv: EBM-PICO is a widely used dataset with PICO annotations at two levels: span-level or coarse-grained and entity-level or fine-grained. Span-level annotations encompass the full information about each class. Entity-level annotations cover the more fine-grained information at the entity level, with PICO classes further divided into fine-grained subclasses. For example, the coarse-grained Participant span is further divided into participant age, gender, condition and sample size in the randomised controlled trial. This dataset comes pre-divided into a training set (n=4,933) annotated through crowd-sourcing and an expert annotated gold test set (n=191) for evaluation. The EBM-PICO annotation guidelines caution about variable annotation quality. Abaho et al. developed a framework to post-hoc correct EBM-PICO outcomes annotation inconsistencies. Lee et al. studied annotation span disagreements suggesting variability across the annotators. Low annotation quality in the training dataset is excusable, but the errors in the test set can lead to faulty evaluation of the downstream ML methods. We evaluate 1% of the EBM-PICO training set tokens to gauge the possible reasons for the fine-grained labelling errors and use this exercise to conduct an error-focused PICO re-annotation for the EBM-PICO gold test set. The file 'test_ebm_correctedlabels.tsv' has error corrected EBM-PICO gold test set. This dataset could be used as a complementary evalution set along with EBM-PICO test set. error_analysis.zip: This .zip file contains three .tsv files for each PICO class to identify possible errors in about 1% (about 12,962 tokens) of the EBM-PICO training set. Objective: PICO (Participants, Interventions, Comparators, Outcomes) analysis is vital but time-consuming for conducting systematic reviews (SRs). Supervised machine learning can help fully automate it, but a lack of large annotated corpora limits the quality of automated PICO recognition systems. The largest currently available PICO corpus is manually annotated, which is an approach that is often too expensive for the scientific community to apply. Depending on the specific SR question, PICO criteria are extended to PICOC (C-Context), PICOT (T-timeframe), and PIBOSO (B-Background, S-Study design, O-Other) meaning the static hand-labelled corpora need to undergo costly re-annotation as per the downstream requirements. We aim to test the feasibility of designing a weak supervision system to extract these entities without hand-labelled data. Methodology: We decompose PICO spans into its constituent entities and re-purpose multiple medical and non-medical ontologies and expert-generated rules to obtain multiple noisy labels for these entities. These labels obtained using several sources are then aggregated using simple majority voting and generative modelling approaches. The resulting programmatic labels are used as weak signals to train a weakly-supervised discriminative model and observe performance changes. We explore mistakes in the currently available PICO corpus that could have led to inaccurate evaluation of several automation methods. Results: We present Weak-PICO, a weakly-supervised PICO entity recognition approach using medical and non-medical ontologies, dictionaries and expert-generated rules. Our approach does not use hand-labelled data. Conclusion: Weak supervision using weak-PICO for PICO entity recognition has encouraging results, and the approach can potentially extend to more clinical entities readily. All the datasets could be opened using text editors or Google sheets. The .zip files in the dataset can be opened using the archive utility on Mac OS and unzip functionality in Linux. (All Windows and Apple operating systems support the use of ZIP files without additional third-party software)

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    Authors: Leonardo Santiago Benitez Pereira;

    Collection of 300 support tickets manually labeled for semantic similarity, obtained from a IT support company in the Florianópolis (Brazil) region. Each ticket is represented by an unstructured text field, which is typed by the user that opened the call. The labeling process was performed in 2022 by three IT support professionals. The corpus contains tickets in many languages, mainly English, German, Portuguese and Spanish. All Personal Identifiable Information (PII) and sensitive information were removed (substituted by a tag indicating the original content, for instance: the sentence "this text was written by Leonardo" is converted to "this text was written by [NAME]"). The removal was performed in three steps: first, the automated machine learning-based tool AWS Comprehend PII Removal was used; then, a sequence of custom regular expressions was applied; last, the entire corpus was manually verified.

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    ZENODO
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    ZENODO
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Dupret, Vincent;

    The current data set refers to the study of fossil fish material from Southwest Ireland (Placodermi, Antiarchi; Givetian of the Iveragh Peninsula). The data consist of SEM elemental mapping (section 1), CTscan image stacks and subsequent working files (i.e. segmentation, visualisation files, STLs and 3D PDF files; sections 2-5), as well as phylogenetic analyses related to the genus Bothriolepis studied in the article (section 6). * Zoobank LSID for article: urn:lsid:zoobank.org:pub:0438B3D4-AEAA-4000-A1CB-B5DA0ECA466F * Zoobank LSID for taxon Bothriolepis dairbhrensis: urn:lsid:zoobank.org:act:B577F075-1EF6-48A5-8C7C-E64E36E2BC4E The dataset corresponding to the article Dupret, Byrne, Castro, Hammer, Higgs, Long, Niedźwiedzki, Qvarnström, Stössel & Ahlberg. In Press. The Bothriolepis (Placodermi, Antiarcha) material from the Valentia Slate Formation of the Iveragh Peninsula (middle Givetian, Ireland): morphology, evolutionary and systematic considerations, phylogenetic and palaeogeographic implications. PLOS ONE. with the LSID urn:lsid:zoobank.org:pub:0438B3D4-AEAA-4000-A1CB-B5DA0ECA466F and the species Bothriolepis dairbhrensis Dupret, Byrne, Castro, Hammer, Higgs, Long, Gzegorz Niedźwiedzki, Qvarnström, Stössel & Ahlberg with the LSID urn:lsid:zoobank.org:act:B577F075-1EF6-48A5-8C7C-E64E36E2BC4E is composed of the following files: 1. Elemental analysis (SEM) equipment: Hitachi S–3600N Scanning Electron Microscope (SEM); JPGS are original output. 2. CT-scans datasets In London, the material was CT-scanned with a Nikon HMX ST 225 system, Nikon Metrology, Leuven, Belgium, with a tungsten reflection target. Detailed settings files were adjusted for each specimen and are given in associated documentation "S2 Table-scan properties.xlsx". Two specimens required stitching performed with an in-house NHM script written in Octave. In Oslo, the scanning was carried out with a Nikon Metrology XT H 225 ST microfocus CT instrument at the Natural History Museum, University of Oslo, at 160-220 kV, 1 s exposure time, 3016 projections, and with tin filters of varying thickness. Voxel resolution was 75 µm or better. Detailed settings are given in in associated documentation "S2 Table-scan properties.xlsx". 3. Drishti and Mimics files (segmentation) 4. STL files 5. 3D pdfs In Mimics, each individual structure corresponding to a mask was used to generate a high quality 3D object, itself transformed into an STL file. Each 3D object was duplicated and relocated in the 3D space; once again STLs were generated. The STL files were then imported into Materialise 3-matic (v. 15.0) and were reorganised into anatomical ensembles (head, fin, etc.) in both original and correct positions. Each STL surface was then simplified and corrected using the following functions: Filter Sharp Triangles with filter distance 0.01; Filter Small Edges with filter distance 0.01; Improve Mesh with shape quality high/medium, maximum geometrical error 0.07, and maximal edge length 20.0. A 3D pdf file was finally generated and open in Adobe Acrobat to take pictures used in figures of the current article. for the following specimens a. NMING:F35203-UU210ab_HQ Bothriolepis dairbhrensis sp. nov. Incomplete lateral plate and fragment of indeterminate plate. Segmentation in Mimics, treatment of STLS and 3d PDF exportation in 3-matic. The scale of the reference cube edges is 10 mm. Please note that within the Mimics project files for this specimen µm is incorrectly given as a base of measurement when it should be mm (millimeters). All other processing has been performed treating the source data as being scaled in millimeters. b. NMING:F35229-CH003 Bothriolepis dairbhrensis sp. nov. Assemblage of indeterminate plate and indeterminate scavenging gastropods. Segmentation in Mimics, treatment of STLS and 3d PDF exportation in 3-matic. The scale of the reference cube edges is 10 mm. c. NMING:F35216-UU SFB001 Bothriolepis dairbhrensis sp. nov. Proximal segment of the pectoral fin, with AVL and articular condyle. [ORG] corresponds to plates in original position; [RELOC] corresponds to plates relocated in life position. Segmentation in Mimics, treatment of STLS and 3d PDF exportation in 3-matic. The scale of the reference cube edges is 10 mm. d. NHM P 59677 (complete, ORG end RELOC files) Bothriolepis dairbhrensis sp. nov. Incomplete head (and endocranial processes), ventral body armour and proximal segment of the pectoral fin. [ORG] corresponds to plates in original position; [RELOC] corresponds to plates relocated in life position. Segmentation in Mimics, treatment of STLS and 3d PDF exportation in 3-matic. The scale of the reference cube edges is 10 mm. e. NHM P 59678 Bothriolepis dairbhrensis sp. nov. Incomplete lateral and indeterminate plates of an adult individual. The scale of the reference cube edges is 10 mm. f. NHM P 59679 Bothriolepis dairbhrensis sp. nov. Two indeterminate fragments. The scale of the reference cube edges is 10 mm. g. NHM P 59687 Bothriolepis dairbhrensis sp. nov. Indeterminate fragments and burrows. The scale of the reference cube edges is 10 mm. 6. taxon*character matrices with different sets of analyses (readible in MESQUITE) **LINKS TO PREVIOUSLY MENTIONED SOLUTIONS** MESQUITE (construction of data matrix, visualisation): https://www.mesquiteproject.org/ https://github.com/MesquiteProject/ Maddison, W. P. and D.R. Maddison. 2021. Mesquite: a modular system for evolutionary analysis. Version 3.70 http://www.mesquiteproject.org ZEPHYR (Mesquite package for interacting with external phylogeny inference programs) http://zephyr.mesquiteproject.org/ Maddison, D.R., & W.P. Maddison. 2021. Zephyr: a Mesquite package for interacting with external phylogeny inference programs. Version 3.20. http://zephyr.mesquiteproject.org TNT (phylogenetic analysis) https://onlinelibrary.wiley.com/doi/10.1111/j.1096-0031.2008.00217.x Goloboff, P.A., Farris, J.S. and Nixon, K.C. (2008), TNT, a free program for phylogenetic analysis. Cladistics, 24: 774-786. https://doi.org/10.1111/j.1096-0031.2008.00217.x MATERIALISE MIMICS and 3-MATIC (segmentation, 3D modelling): https://www.materialise.com/en/healthcare/mimics-innovation-suite DRISHTI (3D visualisation): https://github.com/nci/drishti Ajay Limaye; Drishti: a volume exploration and presentation tool. Proc. SPIE 8506, Developments in X-Ray Tomography VIII, 85060X (October 17, 2012) Datasetet hänger samman med en studie av fossilt fiskmaterial från sydvästra Irland (Placodermi, Antiarchi; Givetian på Iveragh-halvön). Data består av SEM-elementkartläggning (avsnitt 1), datortomografiska bildstaplar och efterföljande arbetsfiler (dvs. segmentering, visualiseringsfiler, STL-filer och 3D PDF-filer; avsnitt 2-5), samt fylogenetiska analyser relaterade till släktet Bothriolepis som studerats i artikeln (avsnitt 6). * Zoobank LSID för artikeln: urn:lsid:zoobank.org:pub:0438B3D4-AEAA-4000-A1CB-B5DA0ECA466F * Zoobank LSID för taxon Bothriolepis dairbhrensis: urn:lsid:zoobank.org:act:B577F075-1EF6-48A5-8C7C-E64E36E2BC4E Data som motsvarar artikeln Dupret, Byrne, Castro, Hammer, Higgs, Long, Niedźwiedzki, Qvarnström, Stössel & Ahlberg. In Press. The Bothriolepis (Placodermi, Antiarcha) material from the Valentia Slate Formation of the Iveragh Peninsula (middle Givetian, Ireland): morphology, evolutionary and systematic considerations, phylogenetic and palaeogeographic implications. PLOS ONE. med LSID urn:lsid:zoobank.org:pub:0438B3D4-AEAA-4000-A1CB-B5DA0ECA466F och arten Bothriolepis dairbhrensis Dupret, Byrne, Castro, Hammer, Higgs, Long, Gzegorz Niedźwiedzki, Qvarnström, Stössel & Ahlberg med LSID urn:lsid:zoobank.org:act:B577F075-1EF6-48A5-8C7C-E64E36E2BC4E består av följande filer: 1. Elementaranalys (SEM) utrustning: Hitachi S–3600N svepelektronmikroskop (SEM); JPG-filerna är originalutdata. 2. Dataset från datortomografi I London kördes datortomografi på materialet med ett Nikon HMX ST 225-system (Nikon Metrology, Leuven, Belgien), utrustat med ett reflektionsmål av volfram. Detaljerade inställningsfiler justerades för varje exemplar och finns angivna i den tillhörande dokumentationsfilen "S2 Table-scan properties.xlsx". Två exemplar krävde sammanfogning med hjälp av ett särskilt framtaget NHM-skript skrivet i Octave. I Oslo utfördes skanningen med ett Nikon Metrology XT H 225 ST mikrofokus CT-instrument vid Naturhistorisk museum, Universitetet i Oslo, med 160-220 kV, 1 s exponeringstid, 3016 projektioner och med tennfilter av varierande tjocklek. Voxelupplösningen var 75 µm eller bättre. Detaljerade inställningar finns även här angivna i den tillhörande dokumentationsfilen "S2 Table-scan properties.xlsx". 3. Materialise Mimics och Drishti-filer (segmentering) 4. STL-filer 5. 3D PDF-filer I Mimics användes varje enskild struktur som motsvarar en mask för att generera ett högkvalitativt 3D-objekt, som i sig omvandlades till en STL-fil. Varje 3D-objekt duplicerades och positionerades om i 3D, och STL-filer genererades åter. STL-filerna importerades sedan till Materialise 3-matic (v. 15.0) och omorganiserades till anatomiska ensembler (huvud, fena, etc.) i både ursprungliga och korrekta positioner. Varje STL-yta förenklades sedan och korrigerades med hjälp av följande funktioner: "Filter Sharp Triangles" med filter distance 0,01; "Filter Small Edges" med filter distance 0,01; "Improve Mesh" med shape quality high/medium, maximum geometrical error 0,07 och maximal edge length 20,0. En 3D PDF-fil genererades till slut och öppnades i Adobe Acrobat för att ta bilder som används i figurer i den relaterade artikeln. för följande exemplar a. NMING:F35203-UU210ab_HQ Bothriolepis dairbhrensis sp. nov. Ofullständig lateralplatta och fragment av obestämd platta. Segmentering i Mimics, behandling av STL-filer och 3D PDF-export i 3-matic. Referenskubens kanter är 10 mm. Notera att i Mimics-projektfilerna för detta exemplar är µm av misstag angivet som måttreferens när det skall vara mm (millimeter). All annan bearbetning har skett med förutsättningarna att måttreferensen är i millimeter. b. NMING:F35229-CH003 Bothriolepis dairbhrensis sp. nov. Sammansättning av obestämd platta och obestämda asätande gastropoder. Segmentering i Mimics, behandling av STL-filer och 3D PDF-export i 3-matic. Referenskubens kanter är 10 mm. c. NMING:F35216-UU SFB001 Bothriolepis dairbhrensis sp. nov. Proximalt segment av bröstfenan, med AVL och ledkondyl. [ORG] motsvarar plattor i ursprunglig position; [RELOC] motsvarar plattor som flyttats till livsläge. Segmentering i Mimics, behandling av STL-filer och 3D PDF-export i 3-matic. Referenskubens kanter är 10 mm. d. NHM P 59677 (komplett, ORG-slut RELOC-filer) Bothriolepis dairbhrensis sp. nov. Ofullständigt huvud (och endokraniella processer), ventralt kroppspansar och proximalt segment av bröstfenan. [ORG] motsvarar plattor i ursprunglig position; [RELOC] motsvarar plattor som flyttats till livsläge. Segmentering i Mimics, behandling av STL-filer och 3D PDF-export i 3-matic. Referenskubens kanter är 10 mm. e. NHM P 59678 Bothriolepis dairbhrensis sp. nov. Ofullständiga laterala och obestämda plattor av en vuxen individ. Referenskubens kanter är 10 mm. f. NHM P 59679 Bothriolepis dairbhrensis sp. nov. Två obestämda fragment. Referenskubens kanter är 10 mm. g. NHM P 59687 Bothriolepis dairbhrensis sp. nov. Obestämda fragment och hålor. Referenskubens kanter är 10 mm. 6. taxon*karaktär-matriser med olika uppsättningar av analyser (läsbara i MESQUITE) **LÄNKAR TILL ANVÄNDA VERKTYG** MESQUITE (konstruktion av datamatris, visualisering) https://www.mesquiteproject.org/ https://github.com/MesquiteProject/ Maddison, W. P. and D.R. Maddison. 2021. Mesquite: a modular system for evolutionary analysis. Version 3.70 http://www.mesquiteproject.org ZEPHYR (Mesquite-paket för interaktion med externa fylogeni-inferensprogram) http://zephyr.mesquiteproject.org/ Maddison, D.R., & W.P. Maddison. 2021. Zephyr: a Mesquite package for interacting with external phylogeny inference programs. Version 3.20. http://zephyr.mesquiteproject.org TNT (fylogenetisk analys) https://onlinelibrary.wiley.com/doi/10.1111/j.1096-0031.2008.00217.x Goloboff, P.A., Farris, J.S. and Nixon, K.C. (2008), TNT, a free program for phylogenetic analysis. Cladistics, 24: 774-786. https://doi.org/10.1111/j.1096-0031.2008.00217.x MATERIALISE MIMICS and 3-MATIC (segmentering, 3D-modellering): https://www.materialise.com/en/healthcare/mimics-innovation-suite DRISHTI (3D-visualisering): https://github.com/nci/drishti Ajay Limaye; Drishti: a volume exploration and presentation tool. Proc. SPIE 8506, Developments in X-Ray Tomography VIII, 85060X (October 17, 2012)

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    Swedish National Data Service
    Dataset . 2022
    Data sources: Datacite
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      Swedish National Data Service
      Dataset . 2022
      Data sources: Datacite
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    Afaan Oromo Text to Speech Synthesis dataset is a public domain speech dataset consisting of 8,076 short audio clips of a single male speaker reading sentences collected from legitimate sources such as News Media sources, Non-fiction books, and Afaan Oromo Holy bible. A transcription and its normalized text are provided for each clip. After two weeks of the audio recording process, a total of 17 hours of recorded speech data that corresponded to a total of 8076 recorded .wav files was created.File FormatMetadata is provided in metadata.csv. This file consists of one record per line, delimited by the pipe character. The fields are:ID: this is the name of the corresponding .wav fileTranscription: words spoken by the reader (UTF-8)Normalized Transcription: transcription with numbers, ordinals, and monetary units expanded into full words (UTF-8).Each audio file is a single-channel 16-bit PCM WAV with a sample rate of 22050 Hz. THIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOVE

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Mendeley Dataarrow_drop_down
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    Mendeley Data
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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    Mendeley Data; NARCIS
    Dataset . 2022
    License: CC BY
    Data sources: Datacite; NARCIS
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    DANS-EASY
    Dataset . 2022
    Data sources: B2FIND
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    Mendeley Data
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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      Mendeley Data
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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      Mendeley Data; NARCIS
      Dataset . 2022
      License: CC BY
      Data sources: Datacite; NARCIS
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      DANS-EASY
      Dataset . 2022
      Data sources: B2FIND
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      Mendeley Data
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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    Authors: Haneca; Ervynck;

    In deze zenodo-record zijn de brongegevens terug te vinden waarop de analyses in het hoofdstuk "Kenniswinst archeologieregelgeving 2016-2021" zijn gebaseerd. Dit hoofdstuk maakt deel uit van het onderzoeksrapport "Ameels V, Carpentier F, De Ketelaere S, Ervynck A, Geuens J, Haneca K, Pieters M, Van Looveren J & Verhelst A 2023: Evaluatie archeologie 2016-2021, Onderzoeksrapport Agentschap Onroerend Erfgoed, Brussel.": 1. Een overzicht van alle ingediende eindverslagen (n = 576) en nota's met eindafwerking (n = 26) over de periode 1 april 2016 t.e.m. 31 december 2021 eindverslagen_notas_2016_2021_overzicht.csv (comma-separated values) eindverslagen_notas_2016_2021_overzicht.xlsx (Microsoft Excel Open XML Spreadsheet) eindverslagen_notas_2016_2021_overzicht.shp (ESRI shapefile) (Een overzicht van alle ingediende eindverslagen - vanaf 1 april 2016 tot vandaag - kan je ook downloaden als GIS-bestand op https://geo.onroerenderfgoed.be/downloads.) 2. De resultaten van de inhoudelijke screening (periodisering, materiaalcategorieën, ...) van deze documenten: eindverslagen_notas_2016_2021_screening.csv (comma-separated values) eindverslagen_notas_2016_2021_screening.xlsx (Microsoft Excel Open XML Spreadsheet) eindverslagen_notas_2016_2021_screening.shp (ESRI shapefile)

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    ZENODO
    Dataset . 2022
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2022
    License: CC BY
    Data sources: ZENODO
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      ZENODO
      Dataset . 2022
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2022
      License: CC BY
      Data sources: ZENODO