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115 results for “19th century”
Mid-19th Century Land Use on the Southern New England and New York Coasts 1832-1886
The widespread influence of land use and natural disturbance on population, community, and landscape dynamics and the long-term legacy of disturbance on modern ecosystems requires that a historical, broad-scale perspective become an integral part of modern ecological studies and conservation assessment and planning. In previous studies, the Harvard Forest Long Term Ecological Research (LTER) program has developed an integrated approach of paleoecological and historical reconstruction, meteorological modeling, air photo interpretation, GIS analyses, and field studies of vegetation and soils, to address fundamental ecological questions concerning the rates, direction, and causes of vegetation change, to evaluate controls over modern species and community distributions and landscape patterns, and to provide critical background for conservation and restoration planning. In the current study, we extend this approach to investigate the link between landscape history and the abundance, distribution, and dynamics of species, communities and landscapes of the Cape Cod to Long Island coastal region, including the islands of Martha's Vineyard, Nantucket, and Block Island. The study region includes many areas of high conservation priority that are linked geographically, historically, and ecologically. This data package includes GIS layers digitized by Harvard Forest researchers from copies of the US Coastal Survey “T-Sheet” maps available from the National Archives in College Park, Maryland. The US Coastal Survey, and then the US Coast and Geodetic Survey mapped the region, or specific parts of it, several times between 1832 and the 1960s. In this project we digitized the earliest T-Sheet available for each location. The original maps were surveyed between 1832 and 1886, with most of them made between 1835 to 1855. The original maps showed features such as roads, farm walls, railroads, buildings, some industrial buildings, saltworks, wharfs, and land cover including woodlands,
Diachronic word embeddings from 19th-century newspapers digitised by the British Library (1800-1919)
<p>Word vectors related to the paper <em>Machines in the media: semantic change in the lexicon of mechanization in 19th-century British newspapers </em>by Nilo Pedrazzini and Barbara McGillivray (2022).</p> <p>The embeddings were trained on a 4.2-billion-word corpus of 19th-century British newspapers using Word2Vec and the following parameters:</p> <pre><code>sg = True min_count = 1 window = 3 vector_size = 200 epochs = 5</code></pre> <p>The embeddings are divided into periods of ten years each, with the vectors from each decade aligned to the ones from the most recent decade (1910s) using Orthogonal Procrustes.</p> <p>See related GitHub repository for the full documentation: <a href="https://github.com/Living-with-machines/DiachronicEmb-BigHistData">https://github.com/Living-with-machines/DiachronicEmb-BigHistData</a></p> <p>Project webpage (Living with Machines): <a href="https://livingwithmachines.ac.uk/">https://livingwithmachines.ac.uk/</a></p>
Der königlich sächsische Hausorden der Rautenkrone. Genese, Verfasstheit und Verleihungspraxis eines Hausordens des 19. Jahrhunderts (The Royal Saxon House Order of the Rue Crown. Origin, constitution and award practice of a house order of the 19th century.)
<p>This data set was produced as part of a <a href="https://www.academia.edu/86314498/Der_königlich_sächsische_Hausorden_der_Rautenkrone_Genese_Verfasstheit_und_Verleihungspraxis_eines_Hausordens_des_19_Jahrhunderts">bachelor's thesis on the Royal Saxon House Order of the Rue Crown</a> (<em>Orden der Rautenkrone</em>) at the University of Greifswald. The thesis examines the award practices of the Grand Masters of the Order and attempts to draw conclusions about social circumstances. </p> <p>For the work, a data set was created that includes all knights of the Order of the Rue Crown in the period from 1807 to 1918. The names of the beloved were expanded to include a standardised name (GND) and their life data, GND/Wikidata identifier and main geographical affiliation as well as rank and profession. </p> <p>The data here are provided as Numbers and Excel files. Furthermore, the individual tables have been exported into CSV format (Note: in Excel, the CSV files may be displayed incorrectly despite UTF-8 encoding - especially with special characters and umlauts)</p> <p>The dates are not yet completely accurate. For example, in the case of the standardised names, since the persons concerned may have received the corresponding status (king, etc.) only later after the award. The data sets are in constant development. If you have additional information about an entry or have discovered an error, please feel free to contact me. </p>
Decade-level Word2Vec models from automatically transcribed 19th-century newspapers digitised by the British Library (1800-1919)
<p>Word embeddings trained on a 4.2-billion-word corpus of 19th-century British newspapers using Word2Vec and the following parameters:</p> <pre><code>sg = True min_count = 5 window = 5 vector_size = 100 epochs = 5</code></pre> <p>The embeddings are divided into periods of ten years each. Unlike those in <a href="https://doi.org/10.5281/zenodo.7181682">this repository</a>, these were not aligned and OCR errors skimmed from the vocabulary. </p> <p>See related GitHub repository for the full documentation: <a href="https://github.com/Living-with-machines/DiachronicEmb-BigHistData">https://github.com/Living-with-machines/DiachronicEmb-BigHistData</a></p> <p>Project website (Living with Machines): <a href="https://livingwithmachines.ac.uk/">https://livingwithmachines.ac.uk/</a></p>
PARESv3 : PArish REgistry Survey − Historical Census Table Dataset (19th, 20th centuries) − France
<h2>PARES Dataset v3</h2> <p>PARES (PArish REcord Survey) contains<strong> 535 images of handwritten census tables</strong> for years ranging from around <strong>1650 A.D. until 1850 A.D.</strong>.They come from two <strong>French cities</strong>, Vic-sur-Seille (French department of Moselle) and Echevronne (French department of Côte d'Or). While they mention very ancient times, the documents are handwritten transcriptions of even older documents and are quite recent, copied from original documents during the 1950's and 1960's for demographic studies led by the INED in France (<em>Institut National des études démographiques</em> − National Institute for Demographic Studies). These copies were made by only a few different writers.</p> <p>In this updated version of the dataset, each table row has been carefully annotated and transcribed. Please note that for each row transcription, we have specified the attribute to which each value corresponds.</p> <p>We published a paper, <a href="https://link.springer.com/article/10.1007/s10032-025-00531-z">The PARES Database: Information Extraction over Historical Parish Records,</a> in which we better describe the dataset and the tasks it's possible to run on it.</p> <p> </p>
Cultures of Suntanning in late-19th to mid-20th century Britain
<p>Data collected in the project "Cultures of Suntanning in late 19th to mid-20th century Britain", British Academy Mid-Career Fellowship award number MCFSS22\220038.</p><p>Archive Dataset lists identifying details for all archive resources that were consulted during the project, with a note as to whether data was collected from each source.</p><p>Literary dataset lists identifying details for all literary resources consulted during the project, including digital concordances where used, with a note as to whether data was collected from each source.</p><p>The raw data collected cannot be made open access due to archive/copyright restrictions. The identifying details provide enough supplementary information for researchers to locate these resources.</p>
An Annotated Corpus of Tonal Piano Music from the Long 19th Century
<p>This corpus has been created within the <a href="https://github.com/DCMLab/dcml_corpora">DCML corpus initiative</a> and employs the <a href="https://github.com/DCMLab/standards">DCML harmony annotation standard</a>.</p> <p><strong>Version 1</strong> has been released for submitting it as part of the data report <code>Hentschel, J., Rammos, Y., Neuwirth, M., Rohrmeier, M. (forthcoming). An Annotated Corpus of Tonal Piano Music from the Long 19th Century</code> that accompanies nine corpora grouped under the DOI <a href="https://doi.org/10.5281/zenodo.7483349">10.5281/zenodo.7483349</a>.</p> <p><strong>Version 1.1</strong> comes with a complete set of metadata and score headers. Among more accurate composition dates, the metadata now include URIs that identify the compositions in terms of the <a href="https://viaf.org/">Virtual International Authority File (VIAF)</a>, <a href="https://www.wikidata.org/">Wikidata</a>, <a href="https://imslp.org/">IMSLP</a> and <a href="https://musicbrainz.org/">MusicBrainz</a>. The data has been re-extracted from the scores using <a href="https://pypi.org/project/ms3/">ms3 1.1.1</a>.</p> <p>The publication covers the following corpora (the DOI links always point at the latest version respectively):</p> <ul> <li><a href="https://doi.org/10.5281/zenodo.7473560">Ludwig van Beethoven - Piano Sonatas</a></li> <li><a href="https://doi.org/10.5281/zenodo.7473566">Frédéric Chopin - Mazurkas</a></li> <li><a href="https://doi.org/10.5281/zenodo.7473568">Claude Debussy - Suite Bergamasque</a></li> <li><a href="https://doi.org/10.5281/zenodo.7473576">Antonín Dvořák - Silhouettes</a></li> <li><a href="https://doi.org/10.5281/zenodo.7473580">Franz Liszt - Années de Pèlerinage</a></li> <li><a href="https://doi.org/10.5281/zenodo.7473528">Nikolai Medtner - Tales</a></li> <li><a href="https://doi.org/10.5281/zenodo.7473582">Robert Schumann - Kinderszenen</a></li> <li><a href="https://doi.org/10.5281/zenodo.7473586">Pyotr Tchaikovsky - The Seasons</a></li> <li><a href="https://doi.org/10.5281/zenodo.7473578">Edvard Grieg - Lyric Pieces</a></li> </ul> <p> </p>
19th Century United States Newspaper images predicted as Photographs with labels for "human", "animal", "human-structure" and "landscape"
<p>The Dataset contains images derived from the Newspaper Navigator (news-navigator.labs.loc.gov/), a dataset of images drawn from the Library of Congress Chronicling America collection (<a href="https://chroniclingamerica.loc.gov/">chroniclingamerica.loc.gov/</a>). </p> <blockquote> <p>[The Newspaper Navigator dataset] consists of extracted visual content for 16,358,041 historic newspaper pages in <em>Chronicling America</em>. The visual content was identified using an object detection model trained on annotations of World War 1-era Chronicling America pages, including annotations made by volunteers as part of the <a href="https://labs.loc.gov/work/experiments/beyond-words/">Beyond Words</a> crowdsourcing project.</p> <p>source:<a href="https://news-navigator.labs.loc.gov/"> https://news-navigator.labs.loc.gov/</a></p> </blockquote> <p>One of these categories is 'photographs'. This dataset contains a sample of these images with additional labels indicating if the photograph has one or more of the following labels: "human", "animal", "human-structure" and "landscape"</p> <p>The data is organised as follows:</p> <ul> <li>The images themselves can be found in `images.zip`</li> <li>`newspaper-navigator-sample-metadata.csv` contains metadata about each image drawn from the Newspaper Navigator Dataset.</li> <li>`multi_label.csv` contains the labels for the images as a CSV file</li> <li>`annotations.csv` conains the labels for the images with additional metadata</li> </ul> <p>This dataset was created for use in an under-review Programming Historian tutorial (<a href="http://programminghistorian.github.io/ph-submissions/lessons/computer-vision-deep-learning-pt2">http://programminghistorian.github.io/ph-submissions/lessons/computer-vision-deep-learning-pt2</a>) The primary aim of the data was to provide a realistic example dataset for teaching computer vision for working with digitised heritage material. The data is shared here since it may be useful for others. <strong>This data documentation is a work in progress and will be updated when the Programming Historian tutorial is released publicly. </strong></p> <p>The metadata CSV file contains the following columns:</p> <p>- filepath<br> - pub_date<br> - page_seq_num<br> - edition_seq_num<br> - batch<br> - lccn<br> - box<br> - score<br> - ocr<br> - place_of_publication<br> - geographic_coverage<br> - name<br> - publisher<br> - url<br> - page_url<br> - month<br> - year<br> - iiif_url</p>
A Dataset of French Trade Directories from the 19th Century (FTD)
<p>This dataset is composed of pages and entries extracted from French directories published between 1798 and 1861.</p> <p>The purpose of this dataset is to evaluate the performance of Optical Character Recognition (OCR) and Named Entity Recognition (NER) on 19th century French documents.</p> <p><br> This dataset is divided into two parts:</p> <ol> <li>A <strong>labeled dataset</strong>, which contains 8765 manually corrected entries from 78 pages (18 different directories), and which is designed for supervised training.</li> <li>An <strong>unlabeled dataset</strong>, containing 1058196 raw entries from 6887 pages (13 different directories), and which is designed for self-supervised pre-training.</li> </ol> <p>For the <strong>labeled dataset</strong>, we provide:</p> <ul> <li>Original pages and cropped images</li> <li>Human-corrected positions, transcriptions and entity tagging for each entry</li> <li>OCR prediction from 3 systems (Tesseract v4, PERO OCR v2020 and Kraken)</li> <li>Projected NER reference from clean text to OCR predictions, making it suitable to evaluate the performance of NER systems on real, noisy OCR predictions</li> </ul> <p>For the <strong>unlabeled dataset</strong>, we provide:</p> <ul> <li>Automatically detected positions for each entry (lot of noise)</li> <li>OCR predictions for each entry (PERO OCR engine)</li> </ul> <p> </p> <p><strong>How to cite this dataset</strong><br> Please cite this dataset as:</p> <blockquote> <p>N. Abadie, S. Baciocchi, E. Carlinet, J. Chazalon, P. Cristofoli, B. Duménieu and J. Perret, A Dataset of French Trade Directories from the 19th Century (FTD), version 1.0.0, May 2022, online at https://doi.org/10.5281/zenodo.6394464.</p> </blockquote> <pre><code>@dataset{abadie_dataset_22, author = {Abadie, Nathalie and Bacciochi, St{\'e}phane and Carlinet, Edwin and Chazalon, Joseph and Cristofoli, Pascal and Dum{\'e}nieu, Bertrand and Perret, Julien}, title = {{A} {D}ataset of {F}rench {T}rade {D}irectories from the 19th {C}entury ({FTD})}, month = mar, year = 2022, publisher = {Zenodo}, version = {v1.0.0}, doi = {10.5281/zenodo.6394464}, url = {https://doi.org/10.5281/zenodo.6394464} }</code></pre> <p><br> You may also be interested in <strong>our paper presented at DAS 2022</strong> (15th IAPR International Workshop on Document Analysis Systems), which <strong>compares the performance of OCR and NER</strong> systems <strong>on this dataset</strong>:</p> <blockquote> <p>N. Abadie, E. Carlinet, J. Chazalon and B. Duménieu, A Benchmark of Named Entity Recognition Approaches in Historical Documents — Application to 19th Century French Directories, May 2022, La Rochelle, France, Springer.</p> </blockquote> <pre><code>@inproceedings{abadie_das_22, author = {Abadie, Nathalie and Carlinet, Edwin and Chazalon, Joseph and Dum{\'e}nieu, Bertrand}, title = {{A} {B}enchmark of {N}amed {E}ntity {R}ecognition {A}pproaches in {H}istorical {D}ocuments — {A}pplication to 19th {C}entury {F}rench {D}irectories}, month = may, year = 2022, publisher = {Springer}, place = {La Rochelle, France} }</code></pre> <p><br> <strong>Copyright and License</strong><br> The images were extracted from the original source <a href="https://gallica.bnf.fr">https://gallica.bnf.fr</a>, owned by the <em>Bibliothèque nationale de France</em> (French national library).<br> Original contents from the <em>Bibliothèque nationale de France</em> can be reused non-commercially, provided the mention "Source gallica.bnf.fr / Bibliothèque nationale de France" is kept. <br> <strong>Researchers do not have to pay any fee for reusing the original contents in research publications or academic works. </strong> <br> <em>Original copyright mentions extracted from <a href="https://gallica.bnf.fr/edit/und/conditions-dutilisation-des-contenus-de-gallica">https://gallica.bnf.fr/edit/und/conditions-dutilisation-des-contenus-de-gallica</a> on March 29, 2022.</em></p> <p>The original contents were significantly transformed before being included in this dataset.<br> All derived content is licensed under the permissive <strong>Creative Commons Attribution 4.0 International</strong> license.</p>
Map of the archaeological sites mentionned in the paper "Abstraction in Archaeological Stratigraphy: a Pyrenean Lineage of Innovation (late 19th–early 21th century)"
<p>Projection: WGS 84. QGIS 3.14.16</p> <p>Sources:</p> <ul> <li>DEM: GEBCO (<a href="https://doi.org/10.5285/A29C5465-B138-234D-E053-6C86ABC040B9">https://doi.org/10.5285/A29C5465-B138-234D-E053-6C86ABC040B9</a>)</li> <li>Borders:<em> Límites municipales, provinciales y autonómicosRecintos municipales y líneas límite (municipales, provinciales y autonómicos)</em>. BDLJE CC-BY 4.0.</li> </ul>
Food riots and food prices in the Eastern Mediterranean (Bilād al-Shām) in the 19th and 20th centuries: a data set
<p>This is an archival release to document the state of the data set for this research project before it got severely derailed by the Covid-19 pandemic and the explosion in Beirut on 4 August 2020. Please consult the readme for a detailed description of the contents and workflows.</p>
A Dataset of French Trade Directories from the 19th Century for Nested NER task
<p>This dataset is composed of pages and entries extracted from French directories published between 1798 and 1861.</p> <p>The purpose of this dataset is to evaluate the performance of Nested Named Entity Recognition approaches on 19th century French documents, regarding both clean and noisy texts (due to the OCR engine).</p> <p><strong>Source dataset</strong></p> <p>This dataset has been built from this source dataset :</p> <pre><code class="language-markdown">N. Abadie, S. Baciocchi, E. Carlinet, J. Chazalon, P. Cristofoli, B. Duménieu and J. Perret, A Dataset of French Trade Directories from the 19th Century (FTD), version 1.0.0, May 2022, online at https://doi.org/10.5281/zenodo.6394464.</code></pre> <p><strong>Our experiments // Paper</strong></p> <p>Details about our experiments on nested NER approaches are given in our paper (<a href="https://hal.science/hal-03994759v2">the pre-print version is available here</a>).</p> <pre><code class="language-markdown">Tual, S., Abadie, N., Chazalon, J., Duménieu, B., & Carlinet, E. (2023). A Benchmark of Nested NER Approaches in Historical Structured Documents. Proceedings of the 17th International Conference on Document Analysis and Recognition, San José, California, USA. 2023. Springer. https://hal.science/hal-03994759v2</code></pre> <p>Our code is available on <a href="https://github.com/soduco/paper-nestedner-icdar23-code">Git-Hub</a>.</p> <p><strong>Dataset overview</strong></p> <p>The following list describes the <strong>keys of the .JSON</strong> file which contain the complete materials of our experiments.</p> <p>- id : Entry unique ID in a given page</p> <p>- box : Bounding box of the entry in the scanned directory page</p> <p>- book : Source directory of the entry (*see more information bellow*)</p> <p>- page : Page ID in a given directory</p> <p>- valid_box : Is the bbox of the entry valid ? (*all bbox are valid here*)</p> <p>- text_ocr_ref` : OCR extracted and manually corrected text of the entry</p> <p>- nested_ner_xml_ref : <em> text_ocr_ref</em> with nested ner entities</p> <p>- text_ocr_pero : OCR extracted text of the entry with PERO-OCR engine (best engine according to Abadie et al. experiment)</p> <p>- has_valid_ner_xml_pero : Is entities mapping between nested-ner entities annotated by hand on the ref text and pero ocr text correct ? (in our experiments, we only use entries with True value)</p> <p>- nested_ner_xml_pero : Annotated noisy entries produced with PERO OCR</p> <p>- text_ocr_tess : OCR extracted text of the entry with Tesseract engine (*not used in our expriments*)</p> <p>- nested_ner_xml_tess : Is entities mapping between nested-ner entities annotated by hand on the ref text and tesseract text correct? (not used in our experiments)</p> <p>- has_valid_ner_xml_tess : Annotated noisy entries produced with Tesseract. (not used in our experiments)</p> <p>Nested entities are annotated using XML tags. Our hierachy of entities is a *Part Of* a two-levels hierarchy. It means that bottom entities are contained in a top level entity.</p> <p> </p> <p><strong>Source documents // Copyright and licence</strong></p> <p><em>This section has been copied from the <a href="https://zenodo.org/record/6394464">original dataset description</a>.</em></p> <p>The images were extracted from the original source https://gallica.bnf.fr, owned by the *Bibliothèque nationale de France* (French national library).</p> <p>Original contents from the <em>Bibliothèque nationale de France</em> can be reused non-commercially, provided the mention "Source gallica.bnf.fr / Bibliothèque nationale de France" is kept. </p> <p>=> <strong>Researchers do not have to pay any fee for reusing the original contents in research publications or academic works.</strong></p> <p>Original copyright mentions extracted from <a href="https://gallica.bnf.fr/edit/und/conditions-dutilisation-des-contenus-de-gallica">https://gallica.bnf.fr/edit/und/conditions-dutilisation-des-contenus-de-gallica</a> on March 29, 2022.</p> <p>The original contents were significantly transformed before being included in this dataset.</p> <p>All derived content is licensed under the permissive *Creative Commons Attribution 4.0 International* license.</p> <p>Links to original contents are given in the window bellow :</p>
Collection of 19th century Spanish-American Novels
<p>This is a text collection prepared for use with the TXM text analysis tool (http://textometrie.ens-lyon.fr/). The collection contains a selection of novels from 1880-1916. There are currently 24 novels with a total of about 1.2 million words. All texts have been tokenised, lemmatised and POS-tagged using TreeTagger. </p>
Figs 50-66 in From the shadows of the past: Moricand senior and junior, two 19th century naturalists from Geneva, with their newly described taxa and molluscan types
Figs 50-66. Unionidae, Etheriidae, and Streptaxidae. (50-53) Unionidae. (50-53) Monocondylaea costulata (J. Moricand, 1858), syntype, MHNG-INVE-91234 (D = 35.0). (54-57) Etheriidae. (54-57) Bartlettia stefanensis (J. Moricand, 1856), syntype, MHNG-INVE-91237 (D = 75.7). (58-66) Streptaxidae. (58-63) Steptartemon comboides (d'Orbigny, 1835), (58-60) syntype of Helix (Cochlodonta) comboides brasiliensis S. Moricand, 1836, MHNG-INVE-68684 (D = 9.01), (61-63) syntype of Helix (Cochlodonta) comboides edentula S. Moricand, 1836, MHNG-INVE-68683 (D = 6.30). (64-66) Streptartemon streptodon (S. Moricand, 1851), syntype, MHNG-INVE-68696 (D = 8.86). ►
Figs 14-31 in From the shadows of the past: Moricand senior and junior, two 19th century naturalists from Geneva, with their newly described taxa and molluscan types
Figs 14-31. Planorbidae, Unionidae, and Helicinidae. (48-53) Planorbidae. (14) Drepanotrema cimex (S. Moricand, 1838), syntype, MHNG-INVE-86802 (D = 6.03). (15-16) Drepanotrema depressissimus (S. Moricand, syntype, MHNG-INVE-86940 (D = 8.99). (17-19) Uncancylus concentricus (d'Orbigny, 1835), syntype of Ancylus barilensis S. Moricand, 1846, MHNG-INVE-87402 (D = 7.49). (20-23) Unionidae. (20-23) Monocondylaea franciscana (S. Moricand, 1838), holotype, MHNG-INVE-91235 (D = 39.5). (24-31) Helicinidae. (24-27) Helicina caracolla (S. Moricand, 1836), syntype, MHNG- INVE-91246 (D = 15.2). (28-31) Helicina haematostoma (S. Moricand, 1838), syntype, MHNG-INVE-91253 (D = 8.75). ►
Figs 4-6 in From the shadows of the past: Moricand senior and junior, two 19th century naturalists from Geneva, with their newly described taxa and molluscan types
Figs 4-6. Inventories of the Moricand collection. (4) Titles of front covers in both books. (5) Part of text dealing with terrestrial mollusc species. (6) First page of 'Coquilles terrestres et fluviatiles', showing progress through time.
Figs 1-3 in From the shadows of the past: Moricand senior and junior, two 19th century naturalists from Geneva, with their newly described taxa and molluscan types
Figs 1-3. Portraits. (1) S. Moricand, at unknown but probably young age (coll. MHNG). (2) J.S. Blanchet (after García Polo, 2015). (3) A. Brot (modified from Campos, 2013: 255).
Figs 7-13 in From the shadows of the past: Moricand senior and junior, two 19th century naturalists from Geneva, with their newly described taxa and molluscan types
Figs 7-13. Thiaridae and Pleuroceridae. (7-9) Thiaridae. (7-9) Aylacostoma crenocarina (S. Moricand, 1841), (7) syntype of Melanopsis crenocarina melanostoma S. Moricand, 1841, MHNG-INVE-91242 (H = 38.8), (8) syntype of Melanopsis crenocarina bilineata S. Moricand, 1841, MHNG-INVE-91240 (H = 36.2), (9) syntype of Melanopsis crenocarina leucostoma S. Moricand, 1841, MHNG-INVE-91241 (H = 42.9). (10-13) Pleuroceridae. (10) Doryssa ventricosa (J. Moricand, 1856), syntype, MHNG-INVE-91243 (H = 37.6). (11) Doryssa brasiliensis (S. Moricand, 1838), syntype, MHNG-INVE-91238 (H = 41.1). (12) Doryssa macapa (J. Moricand, 1856), syntype, MHNG-INVE-91239 (H = 37.1). (13) Doryssa cingulata (J. Moricand, 1860), syntype, MHNG-INVE-91245 (H = 33.5). ►
Figs 80-88 in From the shadows of the past: Moricand senior and junior, two 19th century naturalists from Geneva, with their newly described taxa and molluscan types
Figs 80-88. Streptaxidae, Euconulidae, and Charopidae. (80-82) Streptaxidae. (80-82) Streptartemon cryptodon (S. Moricand, 1851), syntype, MHNG-INVE-68687 (D = 3.68). (83-85) Euconulidae. (83-85) Pseudoguppya semenlini (S. Moricand, 1846), syntype, MHNG-INVE-70933 (D = 2.26). (86-88) Charopidae. (86-88) Lilloiconcha pleurophora (S. Moricand, 1846), syntype, MHNG-INVE-69077 (D = 2.15).
Figs 32-49 in From the shadows of the past: Moricand senior and junior, two 19th century naturalists from Geneva, with their newly described taxa and molluscan types
Figs 32-49. Ampullariidae, Planorbidae, Unionidae, Polygyridae, and Megalomastomidae. (32-33) Ampullariidae. (32-33) Pomacea decussata (S. Moricand, 1836), syntype, MHNG-INVE-33485 (H = 29.4). (34-36) Planorbidae. (34-36) Biomphalaria glabrata (Say, 1818), syntype of Planorbis dentifer J. Moricand, 1853, MHNG-INVE-86932 (D = 12.7). (37-40) Unionidae. (37-40) Monocondylaea reticulata (J. Moricand, 1858), syntype, MHNG-INVE-91236 (D = 41.8). (41-46) Polygyridae. (41-43) Practicolella (Practicolella) berlandieriana (S. Moricand, 1834), syntype, MHNG-INVE-37027 (H = 8.98). (44-46) Polygyra (Linisia) texasiana texasiana (S. Moricand, 1833), syntype, MHNG-INVE-72781 (D = 10.4). (47-49) Megalomastomidae. (47-49) Aperostoma blanchetiana (S. Moricand, 1836), syntype, MHNG-INVE-91233 (D = 30.3). ►
ScienceDex guides
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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.