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4,404 results for “Digitization”
Multi-temporal digital terrain models of the active deep-seated Vögelsberg landslide (OAL-Austria)
<p>Multi-temporal digital terrain models of the active deep-seated Vögelsberg landslide in OAL Austria (Lat: 47.272°, Lon: 11.597°) with a spatial resolution of 50cm. Raster were derived from classified 3D point clouds acquired with a Riegl VUX-1LR unmanned aerial vehicle laser scanner on August 3<sup>rd</sup> 2018, August 14<sup>th</sup> 2019 and November 6<sup>th</sup> 2020 (Projection: EPSG 31254). Ground classification after Axelsson (2000). Data was used to assess topographic changes at the toe of the active deep-seated Vögelsberg landslide in OAL-Austria.</p>
Historical digital elevation models (DEMs) and orthoimage mosaics for North American Glacier Aerial Photography (NAGAP) program, version 1.0
<p>This data archive contains digital elevation models (DEMs) and orthoimages generated from scanned historical aerial photographs from the North American Glacier Aerial Photography program available from the NSF Arctic Data Center (ADC, arcticdata.io). </p> <p>The scanned images were preprocessed using the <a href="https://github.com/friedrichknuth/hipp">Historical Image Pre-Processing</a> v0.1 software. Photogrammetric processing was performed with the <a href="https://github.com/friedrichknuth/hsfm">Historical Structure from Motion</a> v0.1 software. </p> <p>All DEM and orthoimage products are provided in the UTM Zone 10N (EPSG:32610) projected coordinate system. Elevation values are in meters above the WGS84 ellipsoid. </p> <p>See <a href="https://www.sciencedirect.com/science/article/pii/S0034425722004850">manuscript</a> and <a href="https://ars.els-cdn.com/content/image/1-s2.0-S0034425722004850-mmc1.pdf">supplement</a> for processing details and further dataset description.</p> <p>This release contains data products for two study sites in Washington state, USA:</p> <p><strong>Mount Baker</strong><br> 1970-09-09<br> 1970-09-29<br> 1974-08-10<br> 1977-09-27<br> 1979-10-06<br> 1987-08-21<br> 1990-09-05<br> 1991-09-09<br> 1992-09-15<br> 1992-09-18</p> <p><strong>South Cascade</strong><br> 1967-09-21<br> 1970-09-29<br> 1974-08-10<br> 1977-10-03<br> 1979-08-20<br> 1979-10-06<br> 1984-08-14<br> 1986-09-05<br> 1987-08-21<br> 1990-09-05<br> 1991-09-09<br> 1992-07-28<br> 1992-09-15<br> 1992-09-18<br> 1992-10-06<br> 1994-09-06<br> 1996-09-10<br> 1997-09-23</p> <p>The 00_thumbnails.jpg provides a quicklook overview at both sites.</p> <p><strong>The DEM and ortho file names are structured as follows:</strong><br> hsfm_NAGAP_[site-name]_[date]_[type].tif</p> <p><strong>For example:</strong><br> hsfm_NAGAP_south-cascade_19670921_ortho.tif</p> <p><strong>Where:</strong><br> [site-name] = Either mount-baker or south-cascade<br> [date] = Image acquisition date in YYYYMMDD format<br> [type] = File type</p> <p><strong>For each DEM and ortho pair, we provide the following:</strong><br> _1m_dem.tif = Digital elevation model posted at 1 m resolution <br> _ortho.tif = Orthoimage mosaic posted at the median image ground sample distance, rounded up to the nearest second decimal place.<br> _metadata.tar.gz = Metadata tarball containing:<br> _ortho_footprints.geojson = Orthoimage mosaic footprint polygons provided in GeoJSON format (EPSG:4326)<br> _dem_footprints.geojson = DEM footprint polygons provided in GeoJSON format (EPSG:4326)<br> _cameras.csv = Image file names, positions, and orientations</p>
BigBrain-MR: a new digital phantom with anatomically-realistic magnetic resonance properties at 100-µm resolution
<p><strong>BigBrain-MR</strong> is a novel digital phantom with realistic anatomical detail up to 100-µm resolution, including multiple MRI contrasts and properties that affect image generation. This phantom was generated from the publicly available <a href="https://bigbrainproject.org/">BigBrain histological dataset</a> and from lower-resolution in-vivo 7T-MRI data, using a new image processing framework that allows mapping the general properties of in-vivo data into the fine anatomical scale of BigBrain.</p> <p>The <strong>dataset</strong> includes:</p> <ul> <li>BigBrain original contrast and a new atlas with 20 ROIs;</li> <li>T<sub>1</sub>-weighted image and T<sub>1</sub> map;</li> <li>T<sub>2</sub>*-weighted images and R<sub>2</sub>* map;</li> <li>Magnetic susceptibility map (QSM);</li> <li>Background magnetic field map;</li> <li>Complex coil sensitivity maps (32ch-receive RF array);</li> <li>Bias field map.</li> </ul> <p>Information about each image/map (including data type and amplitude scaling) is provided in <em>data_info.txt</em>.</p> <p>Additionally, we have included a script with <strong>usage examples</strong> in Python that illustrate how the data can be loaded, processed and combined for diverse simulation purposes.</p> <p>BigBrain-MR is presented, described and tested in the following <strong>peer-reviewed article</strong>:</p> <p>C. Sainz Martinez, M. Bach Cuadra, J. Jorge. <em>BigBrain-MR: a new digital phantom with anatomically-realistic magnetic resonance properties at 100-µm resolution for magnetic resonance methods development</em>. NeuroImage 2023. <strong>DOI:</strong> <a href="https://doi.org/10.1016/j.neuroimage.2023.120074">10.1016/j.neuroimage.2023.120074</a></p> <p> </p>
DATABASE OF THE DIGITAL ELEVATION MODELS OF THE SKEIÐARÁRSANDUR KETTLE-HOLES (S ICELAND), JUNE 2022 - Part II. VIDEO
<p>The database contains 83 video files in .MOV format, shot by a digital camera at 23.98 frames per second. The average length of videos is 100–600 seconds. They are documentation of fieldwork carried out in June 2022, aimed at preparing the footage to generate high-resolution digital elevation models (Part I) using the 'Structure from Motion' technique. The study covered kettle-holes of the glacial flood origin located at Skeiðarársandur in S Iceland.</p>
Survey data on the digitalization of informal businesses in the Global South
<p>During the spring of 2022, the UNDP Accelerator Labs created an online survey to investigate the uptake of digital tools by informal businesses in the Global South. </p> <p>We uploaded the questionnaire onto a digital surveys platform (<a href="https://www.kobotoolbox.org/">https://www.kobotoolbox.org/</a>). We then reached out through UNDP’s network of informal or small businesses in 16 countries, inviting them to complete the questionnaire and spread awareness about it. This implies that respondents are in no way a random sample of the target populations; this choice was made in the interest of speed and cost-effectiveness. We obviously claim no representativity, though we believe that some of our results are strong enough to be considered, to a first approximation, valid as a big picture. </p> <p>1,013 questionnaires from 16 countries, covering all UNDP regions, were completed. In the remaining three countries, we received fewer than 30 completed questionnaire, and decided to discard them. At the country level, the number of respondents ranges from 25 (Ecuador) to 306 (Peru). Our own analysis of the data is published here: <a href="https://doi.org/10.5281/zenodo.7896327">https://doi.org/10.5281/zenodo.7896327</a>.</p>
Graphic materials from the Prus Plus Digital Collection
<p>A digital collection of visual materials (drawings) from 19th-century periodicals held in the resources of the <a href="http://ibl.waw.pl/pl/o-instytucie/biblioteka">IBL PAN Library</a>, prepared for the Prus Plus digital monography (in <a href="https://nplp.pl/kolekcja/prus-plus/">Polish </a>and <a href="http://nplp.pl/en/kolekcja/prus-plus/">English</a>) by the New Panorama of the Polish Literature team.</p> <p>Note: Authors in this case means: people processing, remixing, selecting and analyzing the collection of visual materials (New Panorama of Polish Literature) and the institution curating these resources (IBL PAN Library).</p> <p>Kolekcja materiałów wizualnych (rysunków) z XIX-wiecznych czasopism, znajdujących się w zbiorach <a href="https://ibl.waw.pl/pl/o-instytucie/biblioteka">Biblioteki IBL PAN</a>, przygotowana na potrzeby cyfrowej monografii Prus Plus (w <a href="https://nplp.pl/kolekcja/prus-plus/">języku polskim</a> i <a href="http://nplp.pl/en/kolekcja/prus-plus/">angielskim</a>) przez zespół Nowej Panoramy Literatury Polskiej.</p> <p>Uwaga! Autorzy oznacza w tym przypadku: osoby przetwarzające, remiksujące, selekcjonujące i analizujące kolekcję materiałów wizualnych (Nowa Panorama Literatury Polskiej) oraz instytucję przechowującą zasoby (Biblioteka IBL PAN). </p> <p> </p> <p> </p>
Data for "The Heritage Digital Twin: a bicycle made for two."
<p>The file contains the data used in the case studies of the paper "The Heritage Digital Twin: a bicycle made for two. The integration of digital methodologies into cultural heritage research" published on ORE.</p>
ACM-Digital Library (ACM)
<p>ACM-Digital Library (ACM): a subset of the ACM Digital Library with 24, 897 documents containing articles related to Computer Science. We considered only the first level of the taxonomy adopted by ACM, where each document is assigned to one of 11 classes.</p> <p>The files:<br> texts.txt: Document set (text). One per line.<br> score.txt: Document class whose index is associated with texts.txt<br> split_<k>.pkl: pandas DataFrame with k-cross validation partition.</p> <p>The .zip contains all aforementioned files + the tfidf representation in the CSR matrix format.</p>
Dataset for Appearance evaluation of digital materials in material jetting
<p>Dataset for Appearance evaluation of digital materials in material jetting: Including dataset for gloss, haze, scattering, specular BRDF, reflectance, and transmittance</p>
The e-NDP project : collaborative digital edition of the Chapter registers of Notre-Dame of Paris (1326-1504). Ground-truth for handwriting text recognition (HTR) on late medieval manuscripts.
<p>The <a href="https://endp.hypotheses.org/">e-NDP project</a>, funded by the ANR, is led by the <a href="https://lamop.hypotheses.org/6870">LaMOP</a> (Julie Claustre and Darwin Smith).</p> <p>The project's partners are the Archives nationales, the Bibliothèque nationale de France (Department of Manuscripts, Bibliothèque de l'Arsenal), the École nationale des chartes and the Bibliothèque Mazarine.</p> <p>The e-NDP project aims at renewing our knowledge on <strong>Notre-Dame de Paris cathedral</strong> through the creation of a collaborative digital edition of the registers of its Chapter (1326-1504, <em>AN LL 105-128</em>), the community of 51 canons meeting three times a week on set days to take all administrative, financial and practical decisions pertaining to the cathedral, its estate and the society living in its cloister. This corpus has never been the object of a comprehensive study to understand the workings and history of this urban enclave and powerful community. The collaborative digital edition is based on a process of<strong> handwriting text recognition (HTR)</strong>, tested and supervised by scholars, researchers and engineers combining expertise in Medieval history, paleography, philology and digital humanities. The edition shall allow a better insight into the Chapter’s administration, into its economical and political power within Paris, and the relationships it maintained with other institutions in the city.</p> <p> </p> <p><strong>Section 1 : The e-NDP ground-truth dataset for Handwriting text recognition.</strong></p> <p>The full e-NDP corpus kept today in the French National Archives and was entirely digitized and described in its <a href="https://www.siv.archives-nationales.culture.gouv.fr/siv/rechercheconsultation/consultation/ir/consultationIR.action?formCaller=GENERALISTE&irId=FRAN_IR_059635">catalog</a> in 2022.</p> <p>The first major goal of the e-NDP projet is to propose a first automatic transcription of the 14k pages composing the 26 chapter registers. To achieve this goal representative samples from each one of the volumes were selected and transcribed in order to train a specialized HTR model able to propose a high quality automatic transcription. The collected ground-truth released on this repository currently has <strong>512 pages from the 26 registers</strong> of the cathedral chapter preserved in the National Archives (LL105 - LL128, <strong>1326-1504</strong>). The transcriptions were manually completed in <strong>two rounds</strong> by a group of 12 contributors, historians and paleographers, over the course of 2021-2022 using <a href="https://escriptorium.paris.inria.fr/">eScriptorium </a>as annotation environment. </p> <p> </p> <p><strong>Ground-truth features :</strong></p> <p><br> <em>Number of hands </em>: according to our estimates no fewer than 18 main hands were involved in the writing of the registers during the medieval period. </p> <p><em>Language</em> : More than 98% of the content of the registers was written in Latin, the rest in French. The exact percentage is hard to estimate because the vernacular language is often used in formulae, notes and comments. It is rare to find entire pages or blocks written in French. </p> <p><em>Script family</em> : The registers were written using a Cursive script (ca. late XIIIe - XVIe).</p> <p><em>Documental typology</em> : The volumes containing the chapter conclusions were conceived to serve as memorial records, but above all as documents for regular use and consultation in the daily practice of administration and management. In diplomatics the notion of "documentary manuscripts" is used to describe this kind of sources also by opposition to books and litterary or normative manuscripts.</p> <table align="center"> <caption><strong>Ground truth statistics</strong></caption> <tbody> <tr> <th>Text units</th> <th>Count</th> </tr> <tr> <td>Pages</td> <td>512</td> </tr> <tr> <td>Annotated regions (see section 2)</td> <td>2448</td> </tr> <tr> <td>Lines of text</td> <td>34231</td> </tr> <tr> <td>Tokens</td> <td>205083</td> </tr> <tr> <td>Characters</td> <td>3320407</td> </tr> </tbody> </table> <p> </p> <p><strong>Rules of transcription :</strong></p> <ul> <li>The abbreviations have been resolved, both those by suspension (<code>facimꝰ</code> ---> <code>facimus</code>) and by contraction (<code>dñi</code> --> <code>domini</code>). Likewise, those using conventional signs (<code>⁊</code> --> <code>et</code> ; <code>ꝓ</code> --> <code>pro</code>) have been resolved. </li> <li>The named entities (names of persons, places and institutions) have been <code>capitalized</code>. The beginning of a block of text as well as the original capitals used by the notary are also capitalized.</li> <li>The consonantal <code>i</code> and <code>u</code> characters have been transcribed as <code>j</code> and <code>v</code> in both French and Latin.</li> <li>The punctuation marks used in the text: <code>.</code> and <code>/</code> have been transcribed, but the transcription has not been standardized with modern punctuation.</li> <li>Corrections and words that appear cancelled in the manuscript have been transcribed surrounded by the sign <code>$</code> at the beginning and at the end.</li> <li>More specific transcription rules can be found into the file <code>transcription_guidelines.pdf</code></li> </ul> <p> </p> <p><strong>Section 2. e-NDP Layout Segmentation.</strong></p> <p>Layout segmentation is a compulsory step before HTR recognition in order to distinguish sections and regions inside a document. This process intend to separate interdependant page zones to produce a recognition in a section-sequence order and not in a line-sequence order which mix textual and peri-textual content.</p> <p>The regions of 364 pages (see <code>GT-layout_list</code>) of the e-NDP corpus were annotated using a 5 sections vocabulary (see <code>endp_layout_regions</code>) in order to describe the page distribution in all the 26 volumes :</p> <ol> <li><em>Block</em> : All the central text blocks, that normally corresponds to the main content called "conclusions" in registers.</li> <li><em>Liste</em> : List of names of the canons who were present during the meeting. Normally located before the <em>conclusions</em>.</li> <li><em>Entrée</em> : Marginal notes or entries to inform about the content of <em>conclusions</em>.</li> <li><em>Date</em> : Paragraph contending the date. Normally at the head of a <em>conclusion</em>, but separate of the main body.</li> <li><em>Numérotation</em> : Page numbers in roman or arabic. Usually appear in the top corners of the pages.</li> </ol> <table align="center"> <caption><strong>Layout GT statistics</strong></caption> <tbody> <tr> <th>Region</th> <th>Count</th> </tr> <tr> <td>block</td> <td>833</td> </tr> <tr> <td>liste</td> <td>431</td> </tr> <tr> <td>date</td> <td>448</td> </tr> <tr> <td>entrée</td> <td>205</td> </tr> <tr> <td>numérotation</td> <td>531</td> </tr> </tbody> </table> <p> </p> <p><strong>Section 3. The e-NDP HTR modeling.</strong></p> <p>The e-NDP project has progressively trained several HTR models adapted to work on late medieval cursive in order to accelerate the production of ground truth. Currently the best model delivers an average <strong>CER (Character error ratio) of 9.7%</strong> in handwriting recognition on the 26 registers (see <code>endp_learning_curve</code>) and can serve as generalist model for other manuscripts of the same period and similar script family. These models and their training implementation details can be found in the project's github <a href="https://github.com/chartes/e-NDP_HTR">repository</a>. </p> <p>Additionally, the automatic HTR transcriptions of the 26 registers (14k pages, 4.5M tokens) enriched with lexical and semantical information has been the subject of a first <a href="https://nosketch-engine.lamop.fr/#dashboard?corpname=endp">online publication</a> using the NoSketch engine that allows advanced data mining based on the combination of data, metadata and NLP features. </p> <p> </p> <p><strong>Section 4. Dataset content.</strong></p> <p>This zip dataset contains :</p> <p>- <code>HTR_ground_truth</code> : Two folders containing the jpg / jpeg images and their curated transcriptions in PAGE XML format.</p> <p>- <code>images_docs</code> : 4 files illustrating the different phases of the project (list of GT for layout segmentation, layout ontologie, transcription guideline and HTR evaluation curves)</p>
Digital Aristoteles Latinus Environment 2.1
<p>DALE 2.1 is the first release of DALE on GitHub. It contains the current documentation file of the project, the current RELAXNG schema, and the XML files I created based on the schema.</p>
Stefan Zweig digital
<p>DER NACHLASS STEFAN ZWEIGS UND SEINE ÜBERLIEFERUNG</p> <p>Der österreichische Schriftsteller Stefan Zweig (1881–1942) erlangte insbesondere mit seinen Novellen und Biographien Weltruhm. Nicht zuletzt durch seinen Gang ins Exil ergab sich für seinen schriftlichen Nachlass eine Verteilung auf zahlreiche öffentliche und private Sammlungen und somit eine komplizierte und teilweise unübersichtliche Überlieferungslage. Aufgrund dessen standen Originalmanuskripte und weitere Materialien eines der auflagenstärksten und meistübersetzten deutschsprachigen Autoren des 20. Jahrhunderts trotz anhaltendem Interesse an seinem Werk bisher nur eingeschränkt zur Verfügung.</p> <p>Das Literaturarchiv Salzburg bewahrt seit 2014 eine der größten Sammlungen von Materialien aus dem Nachlass Stefan Zweigs auf, darunter über 50 Manuskripte und Typoskripte sowie mehr als ein Dutzend Werknotizbücher und seine sämtlichen bekannten Tagebücher. Dieser wertvolle Bestand wird nun im Rahmen des Projekts STEFAN ZWEIG DIGITAL einer weltweiten Öffentlichkeit zugänglich gemacht. Mit der Einrichtung dieser erweiterbaren digitalen Präsentation ist zugleich die Basis für zukünftige Transkriptionen und wissenschaftliche Bearbeitungen des Quellenmaterials geschaffen. Gleichzeitig sind auch Werkmanuskripte und Typoskripte Stefan Zweigs aus den umfangreichen Sammlungen der Daniel A. Reed Library der State University of New York in Fredonia und der National Library of Israel in das System aufgenommen worden. Damit ist der auf diese Institutionen aufgeteilte literarische Nachlass Zweigs, der all jene Dokumente umfasst, die sich bis zu seinem Tod in seinem Besitz befanden, erstmals in seiner Gesamtheit katalogisiert und erschlossen worden.</p> <p>INHALTE UND ZUGÄNGE</p> <p>Das in STEFAN ZWEIG DIGITAL unter Verwendung etablierter Katalogisierungsstandards für Archive und Bibliotheken erfasste Material ist mit weitreichenden Beschreibungen und Verknüpfungen versehen, die ganz unterschiedliche Zugänge zur Beantwortung wissenschaftlicher Fachfragen wie auch für die interessierte Öffentlichkeit bieten. So stehen für die Recherche neben den Katalogen eine biographische Übersicht sowie ein Index der Personen und Standorte mit über 700 Einträgen zur Verfügung. Hinzu kommt das Verzeichnis der erhaltenen Bücher aus Zweigs Bibliothek, das einen wichtigen Einblick in die von ihm wahrgenommene, gelesene und als Quelle für seine Werke genutzte Literatur bietet. Zusätzlich werden hochwertige digitale Faksimiles der Werke und Lebensdokumente zur Verfügung gestellt, die online durchblättert werden können.</p> <p>Während klassische archivarische und bibliothekarische Erschließungsmaßnahmen im Hinblick auf die Komplexität von Schriftstellernachlässen oftmals an Grenzen stoßen, sind die Kontextualisierung und Semantisierung der Objekte in STEFAN ZWEIG DIGITAL potentiell immer weiter ausbaubar und flexibel verknüpfbar. Das Einbinden der Daten und Metadaten aus verschiedenen Sammlungen wird schließlich eine weitreichendere virtuelle Rekonstruktion des Gesamtnachlasses ermöglichen, welche die Originalquellen und ihren ursprünglichen Entstehungszusammenhang in einzigartiger Breite und Tiefe erfahrbar macht.</p>
Dataset for BRDF representation in response to the build orientation in 3D-printed digital materials
<p>This dataset folder contains data for the project "BRDF representation in response to the build orientation in 3D-printed digital materials"<br> For more information please contact Ali Payami Golhin (payami.ag@gmail.com)</p> <p>Abbreviations:<br> C:Cyan; M:Magenta; Y:Yellow; K:Black<br> GoG: Glossy on Glossy finish; GoM: Glossy on Matte finish</p> <p>Folder "Color values": presents data for CIEXYZ, CIELab, CIELCh for 328 measurement geometries for each CMYK resins<br> Folder "Spectral data": presents reflctance data for 328 measurement geometries for each CMYK resins. The first column in each file represent wavelength (nm) and the second column contains spectral data<br> File "PCA.xlsx": presents PCA (PC1) scores for CMYK colors</p>
1805-1898 Census Records of Lausanne : a Long Digital Dataset for Demographic History
<p><strong>Context. </strong>This historical dataset stems from the project of automatic extraction of 72 census records of Lausanne, Switzerland. The complete dataset covers a century of historical demography in Lausanne (1805-1898), which corresponds to 18,831 pages, and nearly 6 million cells.</p> <p><strong>Content.</strong> The data published in this repository correspond to a first release, i.e. a diachronic slice of one register every 8 to 9 years. Unfortunately, the remaining data are currently under embargo. Their publication will take place as soon as possible, and at the latest by the end of 2023. In the meantime, the data presented here correspond to a large subset of 2,844 pages, which already allows to investigate most research hypotheses.</p> <p><strong>Description. </strong>The population censuses, digitized by the <a href="https://www.lausanne.ch/vie-pratique/culture/bibliotheques-et-archives/archives.html">Archives of the city of Lausanne</a>, continuously cover the evolution of the population in Lausanne throughout the 19th century, starting in 1805, with only one long interruption from 1814 to 1831. Highly detailed, they are an invaluable source for studying migration, economic and social history, and traces of cultural exchanges not only with Bern, but also with France and Italy. Indeed, the system of tracing family origin, specific to Switzerland, allows to follow the migratory movements of families long before the censuses appeared. The bourgeoisie is also an essential economic tracer. In addition, censuses extensively describe the organization of the social fabric into family nuclei, around which gravitate various boarders, workers, servants or apprentices, often living in the same apartment with the family.</p> <p><strong>Production. </strong>The structure and richness of censuses have also provided an opportunity to develop automatic methods for processing structured documents. The processing of censuses includes several steps, from the identification of text segments to the restructuring of information as digital tabular data, through Handwritten Text Recognition and the automatic segmentation of the structure using neural networks. Please note that the detailed extraction methodology, as well as the complete evaluation of performance and reliability is published in:</p> <ul> <li>Petitpierre R., Rappo L., Kramer M. (2023). <em>An end-to-end pipeline for historical censuses processing</em>. International Journal on Document Analysis and Recognition (IJDAR). doi: <a href="https://doi.org/10.1007/s10032-023-00428-9">10.1007/s10032-023-00428-9</a></li> </ul> <p><strong>Data structure.</strong> The data are structured in rows and columns, with each row corresponding to a household. Multiple entries in the same column for a single household are separated by vertical bars ⟨|⟩. The center point ⟨·⟩ indicates an empty entry. For some columns (e.g., street name, house number, owner name), an empty entry indicates that the last non-empty value should be carried over. The page number is in the last column.</p> <p><strong>Liability. </strong>The data presented here are not curated nor verified. They are the raw results of the extraction, the reliability of which was thoroughly assessed in the above-mentioned publication. We insist on the fact that for any reuse of this data for research purposes, the implementation of an appropriate methodology is necessary. This may typically include string distance heuristics, or statistical methodologies to deal with noise and uncertainty.</p>
Digital Elevation Models, orthoimages and lava outlines of the 2021 Fagradalsfjall eruption: Results from near real-time photogrammetric monitoring
<p>This repository contains the data behind the work described in Pedersen et al (in review), specifically the Digital Elevation Models (DEMs), orthoimages and lava outlines created as part of the near-real time monitoring of the Fagradalsfjall 2021 eruption (SW-Iceland).</p> <p>The processing of the data is explained in detail in the Supplement S2 of Pedersen et al (2022).</p> <p>The data derived from Pléiades surveys includes only the DEMs and the lava outlines. The Pléiades-based orthoimages are subject to license. Please contact the authors for further information about this.</p> <p><strong>Convention for file naming:</strong></p> <p>Data: DEM, Ortho, Outline</p> <p>YYYYMMDD_HHMM: Date of acquisition</p> <p>Platform used: Helicopter (HEL), Pléiades (PLE), Hasselblad A6D (A6D)</p> <p>Origin of elevations in DEMs: meters above ellipsoid (zmae)</p> <p>Ground Sampling Distance: 2x2m (DEM) and 30x30cm (Ortho)</p> <p>Cartographic projection: isn93 (see cartographic specifications for further details)</p> <p> </p> <p><strong>Cartographic specifications:</strong></p> <p>Cartographic projection: ISN93/Lambert 1993 (EPSG: 3057, https://epsg.io/3057)</p> <p>Horizontal and vertical reference frame: The surveys after 18 April 2021 are in ISN2016/ISH2004, updated locally around the study area in April 2021 (after pre-eruptive deformations occurred). The rest of the surveys of late March and early April were created using several floating reference systems (see Supplement S3 for details), since no ground surveys were available during the first weeks of the data collection. The surveys of 23 March 2021, 31 March 2021 were re-procesed in Gouhier et al., 2022, using the survey done on 18 May 2021 as reference.</p> <p>Origin of elevations: Ellipsoid WGS84</p> <p>Raster data format: GeoTIFF</p> <p>Raster compression system: ZSTD (http://facebook.github.io/zstd/)</p> <p>Vector data format: GeoPackage (https://www.geopackage.org/)</p>
Local digital elevation model for the Ayeyarwady Delta in Myanmar (AD-DEM) derived from digitised spot and contour heights of topographic maps
<p><strong>Title:</strong></p> <p>Local digital elevation model for the Ayeyarwady Delta in Myanmar (AD-DEM) derived from digitised spot and contour heights of topographic maps</p> <p><strong>Citation:</strong></p> <p>Seeger, K.; Minderhoud, P. S. J., Peffeköver, A., Vogel, A., Brückner, H., Kraas, F., Nay Win Oo, Brill, D. (2023): Local digital elevation model for the Ayeyarwady Delta in Myanmar (AD-DEM) derived from digitised spot and contour heights of topographic maps. Zenodo, <a href="https://doi.org/10.5281/zenodo.7875965">https://doi.org/10.5281/zenodo.7875965</a>.</p> <p><strong>Supplement to:</strong></p> <p>Seeger, K., Minderhoud, P. S. J., Peffeköver, A., Vogel, A., Brückner, H., Kraas, F., Nay Win Oo, and Brill, D. (2023): Assessing land elevation in the Ayeyarwady Delta (Myanmar) and its relevance for studying sea level rise and delta flooding. EGUsphere [preprint], <a href="https://doi.org/10.5194/egusphere-2022-1425">https://doi.org/10.5194/egusphere-2022-1425</a>.</p> <p><strong>Abstract:</strong></p> <p>The local digital elevation model (DEM) of the Ayeyarwady Delta, referred to as AD-DEM, was generated based on elevation data of topographic maps at scale of 1:50,000 published in 2014 while source data was compiled between 2000 and 2004. Empirical Bayesian Kriging with empirical data transformation and exponential modelling was applied to interpolate ~5100 elevation points (spot heights) and ~13600 elevation points extracted from contour data of the topographic maps. Elevation values higher than 10 m were excluded from interpolation and the SRTM water body mask created in 2000 was applied to the processed AD-DEM. The AD-DEM was transformed from its original vertical reference of local mean sea level at Kyaikkhami tide gauge to continuous mean sea level based on the mean dynamic topography data (CNES-CLS18 dataset of Mulet et al. (2021; <a href="https://doi.org/10.5194/os-17-789-2021">https://doi.org/10.5194/os-17-789-2021</a>) that we transposed to EGM96) in order to account for sea level variations along the Myanmar coast.</p> <p>The AD-DEM contains itself some uncertainty due to the lack of evenly distributed spot heights in areas of the upper delta, for which a separate shapefile is provided. However, we highlight to consider the AD-DEM as being the currently best available model against the background of the lacking possibility of ground truthing and being independent from satellite-based measurements.</p> <p>For further information on data processing, including DEM interpolation, determination of local mean sea level and vertical datum conversions, as well as DEM performance, see the corresponding paper and supplementary material.</p> <p>File name: ADDEM_Con250m_lesseq10_MDT_AD_MMR2000_masked_maskedSRTM.tif</p> <p>File format: GEOTIFF file</p> <p>Spatial reference: MMR2000_46N</p> <p>Vertical reference: local continuous mean sea level, i.e., mean dynamic topography (CNES-CLS18 dataset of Mulet et al. (2021; <a href="https://doi.org/10.5194/os-17-789-2021">https://doi.org/10.5194/os-17-789-2021</a>) transposed to EGM96</p> <p>Cell size: 750 × 750 m</p> <p>File name: DataPoorAreas_MMR2000.shp</p> <p>File format: ESRI Shapefile</p> <p>Spatial reference: MMR2000_46N</p>
Dataset for the evaluation of the scalability of a primary school Digital Education curricular reform
<p>Dataset for the evaluation of the scalability of a primary school Digital Education curricular reform<br> =======================================================</p> <p>• If you publish material based on this dataset, please cite the following :</p> <p> • The Zenodo repository : Laila El-Hamamsy, Barbara Bruno, Jessica Dehler Zufferey, & Francesco Mondada (2023). Dataset for the evaluation of the scalability of a primary school Digital Education curricular reform [Data set]. Zenodo. https://doi.org/10.5281/zenodo.7912941</p> <p><br> • The corresponding article : El-Hamamsy, L.*, Monnier, E.-C. *, Chessel-Lazzarotto F., Liégeois G., Bruno, B., Dehler Zufferey, J., and Mondada, F. (2023). An Adapted Cascade Model to Scale Primary School Digital Education Curricular Reforms and Teacher Professional Development Programs. arXiv. https://doi.org/10.48550/arXiv.2306.02751</p> <p><br> • License: This work is licensed under a Creative Commons Attribution 4.0 International license (CC-BY-4.0)</p> <p>• Creator: El-Hamamsy, L., Bruno, B., Dehler Zufferey, J., and Mondada, F.</p> <p>• Date: May 9th 2023</p> <p>• Subject: Educational change, Scalability, Professional Development, Digital Education, Curricular<br> Reform, Primary School</p> <p>• Dataset format: CSV</p> <p>• Dataset collection: September 2018 to September 2022</p> <p>• Dataset size : < 100 kB</p> <p>• Dataset content : one excel file with detailed description below. Please note that the spreadsheet may contain missing values due to teachers either choosing not to respond to the questions or the questions not being presented at each of the training sessions. To have access to the specific survey questions please refer to the associated publication [a].</p> <p>• Abbreviations :<br> - DE : Digital Education<br> - PD : Professional Development</p> <p>• Funding : This work was funded by the the NCCR Robotics, a National Centre of Competence in Research, funded by the Swiss National Science Foundation (grant number 51NF40_185543)</p> <p># References</p> <p>[a] El-Hamamsy, L.*, Monnier, E.-C. *, Chessel-Lazzarotto F., Liégeois G., Bruno, B., Dehler Zufferey, J., and Mondada, F. (2023). An Adapted Cascade Model to Scale Primary School Digital Education Curricular Reforms and Teacher Professional Development Programs. arXiv. https://doi.org/10.48550/arXiv.2306.02751</p>
High-Resolution Heterogeneous Digital PET [18F]FDG Brain Phantom based on the BigBrain Atlas
<p>We present the design of a digital phantom that tries to overcome the problems of the current PET digital brain phantoms, particularly for the simulation of simultaneous PET-MRI data sets. We propose a new brain digital brain phantom based on the BigBrain atlas, a free, publicly available tool that provides considerable neuroanatomical insight into the human brain with an ultrahigh-resolution 3D model of a human brain at nearly cellular resolution of 20 micrometers. We used the histology maps, the classified tissue maps and the MRI image of the BigBrain atlas, as well as the Hammersmith atlas and a PET [18F]FDG template as inputs to create an instance of this ultra high-resolution heterogeneous PET-MRI phantom.</p> <p>Full details of this phantom in Medical Physics: "Technical Note: Ultra high‐resolution radiotracer‐specific digital pet brain phantoms based on the BigBrain atlas", <a href="https://doi.org/10.1002/mp.14218">10.1002/mp.14218.</a></p> <p>You can find codes examples for reading the data at https://github.com/mabelzunce/PETBrainPhantoms </p> <p>Please cite this paper if you use this phantom in your work:</p> <p>Belzunce, M.A. and Reader, A.J. (2020), Technical Note: Ultra high‐resolution radiotracer‐specific digital pet brain phantoms based on the BigBrain atlas. Med. Phys., 47: 3356-3362. doi:<a href="https://doi.org/10.1002/mp.14218">10.1002/mp.14218</a></p>
DECISO Digital Ecosystem overview
<p>The Digital Ecosystem is part of the overall exosystemic approach used within the DECISO project, which implies the stakeholders' engagement at different levels and different scales in the face2face, virtual and hybrid activities of the project, but also after the end of the project for exploiting the results and share experiences and the knowledge produced by the consortium. The DECISO Digital Ecosystem will facilitate organizing events and sharing content using a participatory approach, i.e., each partner can directly upload and manage content related to events. The Digital Ecosystem is directly accessible from the DECISO Digital Ecosystem section of the DECISO website and has been designed by CNR starting from the experience of the MARINA and BIOVOICES platforms.</p>
Digital Assets for "Morphological Parameters and Associated Uncertainties for 8 Million Galaxies in the Hyper Suprime-Cam Wide Survey"
<p>These are morphological catalogs and trained <a href="https://github.com/aritraghsh09/GaMPEN">GaMPEN</a> models for Hyper Suprime-Cam galaxies. Please refer to <a href="https://gampen.readthedocs.io/en/latest/Public_data.html">https://gampen.readthedocs.io/en/latest/Public_data.html</a> and <a href="https://arxiv.org/abs/2212.00051">https://arxiv.org/abs/2212.00051</a> for more details about this data release. </p> <p> </p> <p><strong>Catalog Files</strong></p> <ol> <li>g_0_025_preds_summary.csv --> Structural parameter catalog for z < 0.25 HSC g-band galaxies </li> <li>r_025_050_preds_summary.csv --> Structural parameter catalog for 0.25 < z < 0.50 HSC r-band galaxies </li> <li>i_050_075_preds_summary.csv --> Structural parameter catalog for 0.50 < z < 0.75 HSC i-band galaxies </li> </ol> <p> </p> <p><strong>Trained PyTorch Model Files</strong></p> <ol> <li>g_0_025_real_data.pt --> Trained Model for z < 0.25 HSC g-band galaxies </li> <li>r_025_050_real_data.pt --> Trained Model for 0.25 < z < 0.50 HSC r-band galaxies </li> <li>i_050_075_real_data.pt --> Trained Model for 0.50 < z < 0.75 HSC i-band galaxies </li> <li>sim_g_0_025.pt --> Trained Model for Simulated z < 0.25 HSC g-band galaxies </li> <li>sim_r_025_050.pt --> Trained Model for Simulated 0.25 < z < 0.50 HSC r-band galaxies </li> <li>sim_i_050_075.pt --> Trained Model for Simulated 0.50 < z < 0.75 HSC i-band galaxies </li> </ol>
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.