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Models for "A data-driven approach to studying changing vocabularies in historical newspaper collections"
<p>NOTE: This is a badly rendered version of the README within the archive.</p> <p><strong>A data-driven approach to studying changing vocabularies in historical newspaper collections</strong></p> <p>Simon Hengchen,* Ruben Ros,** Jani Marjanen,*** Mikko Tolonen***</p> <p>*<a href="https://spraakbanken.gu.se/en/about/staff/simon">Språkbanken Text</a>, University of Gothenburg, Sweden and <a href="https://iguanodon.ai">iguanodon.ai</a>, Belgium: firstname.lastname@gu.se<br> **<a href="https://www.c2dh.uni.lu/people/ruben-ros">Centre for Contemporary and Digital History (C2DH)</a>, University of Luxembourg: firstname.lastname@uni.lu<br> ***<a href="https://www.helsinki.fi/en/researchgroups/computational-history">COMHIS</a>, University of Helsinki: <a href="mailto:firstname.lastname@helsinki.fi">firstname.lastname@helsinki.fi</a>;</p> <p>These are the supplementary materials for the DH2019 paper <em>A data-driven approach to the changing vocabulary of the ‘nation’ in English, Dutch, Swedish and Finnish newspapers, 1750-1950</em>, as well as the 2021 Digital Scholarship in the Humanities publication available in OpenAccess: <a href="https://academic.oup.com/dsh/article/36/Supplement_2/ii109/6421793">https://academic.oup.com/dsh/article/36/Supplement_2/ii109/6421793</a>. If you end up using whole or parts of this resource, please use the following citation(s):</p> <ul> <li>Hengchen, S., Ros, R., and Marjanen, J. (2019). A data-driven approach to the changing vocabulary of the 'nation' in English, Dutch, Swedish and Finnish newspapers, 1750-1950. In <em>Proceedings of the Digital Humanities (DH) conference 2019, Utrecht, The Netherlands</em></li> </ul> <p>and/or:</p> <ul> <li>Hengchen, S., Ros, R., Marjanen, J. and Tolonen, M., 2021. A data-driven approach to studying changing vocabularies in historical newspaper collections. Digital Scholarship in the Humanities, 36(Supplement_2), pp.ii109-ii126.</li> </ul> <p>or alternatively use one of the following <code>bib</code>s:</p> <pre><code>@inproceedings{hengchen2019nation, title="A data-driven approach to the changing vocabulary of the 'nation' in {E}nglish, {D}utch, {S}wedish and {F}innish newspapers, 1750-1950.", author={Hengchen, Simon and Ros, Ruben and Marjanen, Jani}, year={2019}, address = "Utrecht, The Netherlands", booktitle={Proceedings of the Digital Humanities (DH) conference 2019} }</code></pre> <pre><code>@article{hengchen2021data, title={A data-driven approach to studying changing vocabularies in historical newspaper collections}, author={Hengchen, Simon and Ros, Ruben and Marjanen, Jani and Tolonen, Mikko}, journal={Digital Scholarship in the Humanities}, volume={36}, number={Supplement\_2}, pages={ii109--ii126}, year={2021}, publisher={Oxford University Press} }</code></pre> <p> </p> <p>Files</p> <p>This archive contains two folders -- one per diachronic representation method -- as well as this README. The folders each contain four folders, which contain the models for their respective languages. As can be inferred from the small datasize, most of the earlier models are not reliable and should not be used, but are still made available. This work is licensed under a <a href="http://creativecommons.org/licenses/by-sa/4.0/">Creative Commons Attribution-ShareAlike 4.0 International License</a>.</p> <p><strong>Source material</strong></p> <p>Finnish:</p> <p>The models were created with data from the Finnish Sub-corpus of the Newspaper and Periodical Corpus of the National Library of Finland (National Library of Finland, 2011). We used everything in the corpus.</p> <p>Filesizes:</p> <pre><code>[simon@taito-login3 SGNS]$ du -h fi* 12M fi_1820_SGNS_corpus_file.gensim 89M fi_1840_SGNS_corpus_file.gensim 797M fi_1860_SGNS_corpus_file.gensim 7.0G fi_1880_SGNS_corpus_file.gensim 22G fi_1900_SGNS_corpus_file.gensim</code></pre> <p>Swedish:</p> <p>The models were created with data from the Kubhist 2 corpus (Språkbanken) -- more precisely, the data dumps available at <a href="https://spraakbanken.gu.se/lb/resurser/meningsmangder/">https://spraakbanken.gu.se</a>. After a manual evaluation of Swedish embeddings trained without pre-processing seemed to show that the embeddings were of low quality, we retrained models, only keeping sentences that were at least 10 tokens long and were constituted of at least 50% of lemmas as per the KORP processing pipeline (Borin et al, 2012).</p> <p>Filesizes:</p> <pre><code>[simon@taito-login3 SGNS]$ du -h sv* 1.6M sv_1740_SGNS_corpus_file.gensim 44M sv_1760_SGNS_corpus_file.gensim 124M sv_1780_SGNS_corpus_file.gensim 228M sv_1800_SGNS_corpus_file.gensim 678M sv_1820_SGNS_corpus_file.gensim 1.6G sv_1840_SGNS_corpus_file.gensim 4.5G sv_1860_SGNS_corpus_file.gensim 6.5G sv_1880_SGNS_corpus_file.gensim 113M sv_1900_SGNS_corpus_file.gensim</code></pre> <p>Dutch:</p> <p>The models were created with data from the Delpher newspaper archive (Royal Dutch Library, 2017), through data dumps for newspapers until and including 1876, and through API hits for articles from 1877 to 1899 (included).</p> <ul> <li>For anything pre-1877 we discarded full texts that had, in the metadata, anything else than exclusively <code>nl</code> or <code>NL</code> as a language tag.</li> <li>For the full texts between 1877 and 1899: we queried the API for all items in the “artikel” category that contained the determiner <code>de</code>.</li> </ul> <p>Our assumption was that most articles should contain <code>de</code> at least once, and those that didn't were too short to be deemed interesting. A subsequent study showed that was not exactly the case, but we were reassured by the fact that left-out articles were probably "shipping or financial reports" (thanks go to Melvin Wevers). We also did not include the colonial newspapers for our embeddings. This is motivated by our research questions. A list of removed newspapers is available on request.</p> <p>Filesizes:</p> <pre><code>[simon@taito-login3 SGNS]$ du -h nl* 6.8M nl_1620_SGNS_corpus_file.gensim 7.9M nl_1640_SGNS_corpus_file.gensim 43M nl_1660_SGNS_corpus_file.gensim 78M nl_1680_SGNS_corpus_file.gensim 138M nl_1700_SGNS_corpus_file.gensim 243M nl_1720_SGNS_corpus_file.gensim 287M nl_1740_SGNS_corpus_file.gensim 431M nl_1760_SGNS_corpus_file.gensim 825M nl_1780_SGNS_corpus_file.gensim 1.2G nl_1800_SGNS_corpus_file.gensim 1.8G nl_1820_SGNS_corpus_file.gensim 3.1G nl_1840_SGNS_corpus_file.gensim 5.2G nl_1860_SGNS_corpus_file.gensim 13G nl_1880_SGNS_corpus_file.gensim</code></pre> <p>English:</p> <p>The models were created with data from the British Library Newspapers collection (<a href="https://www.gale.com/intl/primary-sources/british-library-newspapers%5D">link</a>), the Nichols collection (<a href="https://www.gale.com/intl/c/17th-and-18th-century-burney-newspapers-collection">link</a>), and the Burney collection (<a href="https://www.gale.com/intl/c/17th-and-18th-century-nichols-newspapers-collection">link</a>). We used everything in the corpora. For English, only SGNS_ALIGN models are available. We thank Gale Cengage for their help with this project.</p> <p>Filesizes:</p> <pre><code>[simon@taito-login3 SGNS]$ du -h en* 4.3M en_1620_SGNS_corpus_file.gensim 11M en_1640_SGNS_corpus_file.gensim 11M en_1660_SGNS_corpus_file.gensim 106M en_1680_SGNS_corpus_file.gensim 409M en_1700_SGNS_corpus_file.gensim 1.7G en_1720_SGNS_corpus_file.gensim 834M en_1740_SGNS_corpus_file.gensim 2.4G en_1760_SGNS_corpus_file.gensim 5.3G en_1780_SGNS_corpus_file.gensim 5.5G en_1800_SGNS_corpus_file.gensim 15G en_1820_SGNS_corpus_file.gensim 42G en_1840_SGNS_corpus_file.gensim 65G en_1860_SGNS_corpus_file.gensim 88G en_1880_SGNS_corpus_file.gensim 26G en_1900_SGNS_corpus_file.gensim 21G en_1920_SGNS_corpus_file.gensim 6.3G en_1940_SGNS_corpus_file.gensim</code></pre> <p><strong>Word embeddings</strong></p> <p>For every language, we train diachronic embeddings as follows. We divide the data in 20-year time bins. We train SGNS_UPDATE and SGNS_ALIGN models. Current research on German (Schlechtweg et al, 2019) and English (Shoemark et al, 2019) indicates you should use the SGNS_ALIGN models. <strong>For EN, FI, NL, no tokens (including punctuation) were removed nor altered, aside from lowercasing</strong>. For SV, see above. Parameters are as follows: SGNS architecture (Mikolov et al 2013), window size of 5, frequency threshold of 100, 5 epochs, 300 dimensions (or 100 for EN).</p> <ul> <li>For SGNS_UPDATE: We first train a model for the first time bin <code>t</code>. To train the model for <code>t+1</code>, we use the <code>t</code> model to initialise the vectors for <code>t+1</code>, set the learning rate to correspond to the end learning rate of <code>t</code>, and continue training. This approach, closely following Kim et al (2014), has the advantage of avoiding the need for post-training vector space alignment.</li> </ul> <p>The Python snippet below, which makes use of gensim (Rehurek and Sojka, 2010), illustrates the approach. Special thanks go to Sara Budts.</p> <pre><code>## dict_files[key] is a dictionary with double decades as keys and a corresponding LineSentence object as value: https://radimrehurek.com/gensim/models/word2vec.html#gensim.models.word2vec.LineSentence count = 0 for key in sorted(list(dict_files.keys())): if count == 0: ## This is the first model. model = gensim.models.Word2Vec(corpus_file=dict_files[key], min_count=100, sg=1 ,size=300, workers=64, seed=1830, iter=5) model.save(os.path.join(data_path_final,"KIM",lang+"_"+str(timebin)+".w2v")) print("Model saved, on to the next\n") count += 1 if count > 0: ## this is for the subsequent models. print("model for double decade starting in",str(key)) model = gensim.models.Word2Vec.load(os.path.join(data_path_final,"KIM",lang+"_"+str(timebin-20)+".w2v")) print("previous model loaded") model.build_vocab(corpus_file=dict_files[key], update=True) model.train(corpus_file=dict_files[key], total_words = model.corpus_count, total_examples = model.corpus_count, start_alpha = model.alpha, end_alpha = model.min_alpha, epochs=model.epochs) model.save(os.path.join(data_path_final,"KIM",lang+"_"+str(timebin)+".w2v")) </code></pre> <ul> <li>For SGNS_ALIGN: We independently train models for all time bins. The models in this repository are <em>NOT</em> aligned, leaving you the choice of how to align them. For example, <a href="https://gist.github.com/quadrismegistus/09a93e219a6ffc4f216fb85235535faf">here</a> is a link to code by Ryan Heuser to do just that. Models were trained with the <code>count == 0</code> scenario in the snippet above.</li> </ul> <p><strong>Acknowledgments</strong></p> <p>This work has been supported by the European Union's Horizon 2020 research and innovation programme under grant 770299 <a href="https://www.newseye.eu/">NewsEye</a>. Specials thanks go to the data providers/collection-holding institutions: the Finnish Language Bank, the Swedish Language Bank, the Royal Dutch Library, and Gale Cengage.</p> <p>The authors would like to thank the following persons and group, listed alphabetically: Antoine Doucet, Antti Kanner, Axel-Jean Caurant, Dominik Schlechtweg, Eetu Mäkelä, Elaine Zosa, Estelle Bunout, Haim Dubossarsky, Joris van Eijnatten, Krister Lindén, Lars Borin, Lidia Pivovarova, Melvin Wevers, Nina Tahmasebi, Sara Budts, Senka Drobac, Tanja Säily, the COMHIS group, and Steven Claeyssens. Computational resources were provided by CSC – IT Center for Science Ltd.</p> <p><strong>References</strong></p> <p>Borin, L., Forsberg, M., Roxendal, J. (2012). Korp-the corpus infrastructure of Spräkbanken,in: LREC. pp. 474–478.</p> <p>Kim, Y., Chiu, Y.I., Hanaki, K., Hegde, D. and Petrov, S. (2014). Temporal Analysis of Language through Neural Language Models. <em>ACL 2014</em>, p.61.</p> <p>Mikolov, T., Chen, K., Corrado, G. and Dean, J. (2013). Efficient estimation of word representations in vector space. <em>arXiv preprint arXiv:1301.3781</em>.</p> <p>National Library of Finland (2011). <em>The Finnish Sub-corpus of the Newspaper and Periodical Corpus of the National Library of Finland, Kielipankki Version</em> [text corpus]. Kielipankki. Retrieved from <a href="http://urn.fi/urn:nbn:fi:lb-2016050302">http://urn.fi/urn:nbn:fi:lb-2016050302</a>.</p> <p>Rehurek, R. and Sojka, P. (2010). Software framework for topic modelling with large corpora. In <em>Proceedings of the LREC 2010 Workshop on New Challenges for NLP Frameworks</em>.</p> <p>Royal Dutch Library (2017). <em>Delpher open krantenarchief (1.0)</em>. Den Haag, 2017.</p> <p>Schlechtweg D., Hätty A, del Tredici M., and Schulte im Walde S. (2019). A Wind of Change: Detecting and Evaluating Lexical Semantic Change across Times and Domains. In <em>Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)</em>, Florence, Italy. ACL.</p> <p>Shoemark, P., Liza, F.F., Nguyen, D., Hale, S. and McGillivray, B. (2019). Room to Glo: A Systematic Comparison of Semantic Change Detection Approaches with Word Embeddings. In <em>Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP) (pp. 66-76)</em>, Hong Kong.</p> <p>Språkbanken. <em>The Kubhist Corpus</em>. Department of Swedish, University of Gothenburg. <a href="https://spraakbanken.gu.se/korp/?mode=kubhist">https://spraakbanken.gu.se/korp/?mode=kubhist</a>.</p>
EvoBib: A Bibliographic Database and Quote Collection for Historical Linguistics
<p>This databases offers 4564 references dealing with computer-assisted language comparison in a broad sense. In addition, the database offers 8364 distinct quotes collected from 5063 references. The majority of the references in the quote database overlaps with those in the bibliographic database. The quotes are organized by keywords and can browsed with a full text and a keyword search. </p> <p>The data (references and quotes) underlying each new release are provided here, the data can be browsed at <a href="https://evobib.digling.org/">https://evobib.digling.org/</a>.</p> <p>If you use the database, I would appreciate if you could this in your research:</p> <blockquote> <p>List, Johann-Mattis (2024): EvoBib: A bibliographic database and quote collection [Database, Version 1.8.0]. Passau: Chair for Multilingual Computational Linguistics. URL: <a href="https://evobib.digling.org/" rel="nofollow">https://evobib.digling.org/</a></p> </blockquote> <p> </p> <p> </p> <p> </p>
FIG. 10 in Climatic evolution in Western Europe during the Cenozoic: insights from historical collections using leaf physiognomy
FIG. 10. — Evolution of Mean Annual Temperature (MAT), Cold Month Mean Temperature (CMMT), Warm Month Mean Temperature (WMMT) and Mean Annual Precipitation (MAP) in Europe using CLAMP (black dots). For comparison, results obtained with CA are displayed in grey (adapted from Mosbrugger et al. 2005). Abbreviations: MEN, Menat; GEL, Gelinden; SEZ, Sézanne; CEL, Célas; ARM, Armissan; AIX, Aix-en-Provence; SB, Saint-Bauzile. Numerical values are from Table 3. For Gelinden, Sézanne and Armissan, the results from CLAMP analysis using Asia1 calibration are displayed. For all other localities, the results from CLAMP analysis using BR calibration are displayed.
FIG. 2 in Climatic evolution in Western Europe during the Cenozoic: insights from historical collections using leaf physiognomy
FIG. 2. — Gelinden paleoflora (mid- to late Selandian, Paleocene): A, Quercus odontophylla Saporta & Marion (IRSNB, 68151); B, Quercus loozi Saporta & Marion (IRSNB, 68170); C, Dryophyllum curticellense Saporta & Marion (IRSNB, 68384); D, Dryophyllum dewalquei Saporta & Marion (MNHN.F.13628); E, Quercus diplodon Saporta & Marion (MNHN.F.13644); F, Celastrophyllum sp. (Université de Liège, 2625); G, Dewalquea gelindenensis Saporta & Marion (IRSNB, 68142); H, Quercus palaeodrys Saporta & Marion (IRSNB, 68154); I, Cinnamomum ellipsoideum Saporta & Marion (MNHN.F.13677); J, Posidonia perforata Saporta & Marion (IRSNB, 68335); K, Aralia transversinervia Saporta & Marion (IRSNB, 68239); L, Aralia looziana Saporta & Marion (IRSNB, 68242); M, Litsea elatinervis Saporta & Marion (IRSNB, 68033); N, Pasianopsis retinervis Saporta & Marion (IRSNB, 67045); O, Mac-Clintockia heersiennsis Saporta & Marion (IRSNB, 68034); P, Salix longinqua Saporta & Marion (IRSNB, 68227). Scale bars: A, B: 1 cm; C-P, 2 cm.
Figures 10-12 in A new genus and species of armored scale insect (Hemiptera: Diaspididae) from Australia found in the historic Koebele Collection of the California Academy of Sciences John W. Dooley III
Figures 10-12. Diaspididae spp., habitus, detail of venter of L1 lobes, and pygidium ventral (left) and dorsal (right). 10) Dichosoma convexa (after Brimblecombe 1957). 11) Duplaspidiotus claviger (after Ferris 1937). 12) Eulaingia stenophyllae (after Borchsenius and Williams 1963).
Figure 3 in A new genus and species of armored scale insect (Hemiptera: Diaspididae) from Australia found in the historic Koebele Collection of the California Academy of Sciences John W. Dooley III
Figure 3. Protomorgania koebelei adult female (pygidium). A) L1 lobes fused ventrally, appressed dorsally; B) single simple plate between L1 and position of L2 seta; C) anal pore; D) sclerotized arch; E) chitinized and finely stippled cuticle around vulva.
Figure 2 in A new genus and species of armored scale insect (Hemiptera: Diaspididae) from Australia found in the historic Koebele Collection of the California Academy of Sciences John W. Dooley III
Figure 2. Protomorgania koebelei adult female (thorax and Abdomen). A) anterior perispiracular pores; B) dorsal microducts; C) dorsal microducts, magnified; D) roughened cuticle.
Figure 19 in A new genus and species of armored scale insect (Hemiptera: Diaspididae) from Australia found in the historic Koebele Collection of the California Academy of Sciences John W. Dooley III
Figure 19. Pseudotargionia glandulosa, habitus, detail of venter of L1 lobes, and pygidium ventral (left) and dorsal (right) (after Ferris 1937).
Figure 1. Protomorgania koebelei adult female. A in A new genus and species of armored scale insect (Hemiptera: Diaspididae) from Australia found in the historic Koebele Collection of the California Academy of Sciences John W. Dooley III
Figure 1. Protomorgania koebelei adult female. A) habitus; B) tubercle; C) anterior spiracle; D) posterior spiracle; E) pygidial lobes; F) slide mounted female habitus; G) habitus on host; H) close-up of habitus on host
Figures 7-9 in A new genus and species of armored scale insect (Hemiptera: Diaspididae) from Australia found in the historic Koebele Collection of the California Academy of Sciences John W. Dooley III
Figures 7-9. Diaspididae spp., habitus, detail of venter of L1 lobes, and pygidium ventral (left) and dorsal (right) (after Brimblecombe 1957). 7) Diaphoraspis orbata. 8) Diaspidopus distinctus. 9) Diastolaspis novata.
Figures 4-6 in A new genus and species of armored scale insect (Hemiptera: Diaspididae) from Australia found in the historic Koebele Collection of the California Academy of Sciences John W. Dooley III
Figures 4-6. Diaspididae spp., habitus, detail of venter of L1 lobes, and pygidium ventral (left) and dorsal (right) (after Brimblecombe 1957). 4) Achorphora obliqua. 5) Acontonidia triangulari. 6) Aspidonymus woodwardi.
Figures 16-18 in A new genus and species of armored scale insect (Hemiptera: Diaspididae) from Australia found in the historic Koebele Collection of the California Academy of Sciences John W. Dooley III
Figures 16-18. Diaspididae spp., habitus, detail of venter of L1 lobes, and pygidium ventral (left) and dorsal (right). 16) Neoleonardia extensa (after Ferris 1938). 17) Neomorgania eucalypti (after Ferris 1937). 18) Pseudaonidia duplex (after Ferris 1937).
Fig. 29 in Diversity and taxonomy of the Late Triassic sauropodomorphs (Saurischia, Sauropodomorpha) stored in the Palaeontological Collection of Tübingen, Germany, historically referred to Plateosaurus
Fig. 29. Skeletal elements of specimen GPIT-PV-30788 on display in the diorama. A. Both pubes with some gastric ribs. B. Probably nine dorsal vertebrae, two sacral vertebrae. C. Twelve caudal vertebrae. D. A partial left ilium, conjoined ischia. E. Left femur. F. Left tibia, left fibula, left astragalus. G. Two distal tarsals, five metatarsals, partial digits.
Fig. 27 in Diversity and taxonomy of the Late Triassic sauropodomorphs (Saurischia, Sauropodomorpha) stored in the Palaeontological Collection of Tübingen, Germany, historically referred to Plateosaurus
Fig. 27. Specimen GPIT-PV-30786 on display nowadays in the diorama (as it was originally mounted, Fig. 13E), comprising a complete right hindlimb, the left pes, partial pubes and conjoined ischia, and a series of around 50 caudal vertebrae. The specimen is embedded in a cast matrix.
Fig. 25 in Diversity and taxonomy of the Late Triassic sauropodomorphs (Saurischia, Sauropodomorpha) stored in the Palaeontological Collection of Tübingen, Germany, historically referred to Plateosaurus
Fig. 25. Illustration of specimen "GPIT Skelett I" by von Huene (new catalogue number: GPIT-PV-117990). The translation of the text is as follows: "Skeleton 1. Plateosaurus Quenstedti Huene in a bent down position. An in natural context found individual from the lower bone layer. 1. Skull (the original skull on skeleton I is under the glass top), on the mounted skeleton is the plaster cast of another individual. 2. Cervical vertebrae. 3. Dorsal vertebrae. 4. Sacral Vertebrae. 5. Caudal vertebrae. 6. Scapula (shoulder blade). 7. Coracoid, attached to which are rudiments of the clavicles (collar bones). 8. Humerus (upper arm). 9. Radius and ulna (forearm). 10. Hand. 11. Ilium. 12. Pubis. 13. Ischium. 14. Femur (thigh). 15. Tibia and fibula (lower leg). 16. Foot. 17. Abdominal ribs. These numbers denote the same skeletal parts on the other explanations." [Fig. 13].
Fig. 23 in Diversity and taxonomy of the Late Triassic sauropodomorphs (Saurischia, Sauropodomorpha) stored in the Palaeontological Collection of Tübingen, Germany, historically referred to Plateosaurus
Fig. 23. The holotype of 'Pachysaurus giganteus' von Huene, 1932 (comprises three metatarsal bones, poorly preserved and heavily reconstructed as it was mounted in a now dismounted display. A. Drawing of the dismounted corner, details in Fig. 22. B. Drawing of specimen "GPIT E". C. GPIT-PV-60234, metatarsal II. D. GPIT-PV-60235, metatarsal III. E. GPIT-PV-60236, metatarsal IV.
Fig. 22 in Diversity and taxonomy of the Late Triassic sauropodomorphs (Saurischia, Sauropodomorpha) stored in the Palaeontological Collection of Tübingen, Germany, historically referred to Plateosaurus
Fig. 22. Most of this "Lying Skeleton Parts" corner was removed in the 60s and comprised three historical specimens: "skeleton IV", referred to as Plateosaurus 'plieningeri', most of it now the holotype of Tuebingosaurus maierfritzorum Regalado Fernández & Werneburg, 2022, the gastralia blocks of specimen GPIT-PV-30784 ("GPIT I"), and three metatarsals that make up the holotype of 'Pachysaurus giganteus' von Huene, 1932 (Fig. 23), or historical number "GPIT E". Explanation of the numbers: 1. = cranial material; 4. = sacral vertebrae; 5. = caudal vertebrae; 9. = radius and ulna (forearm); 10. = manus; 11. = ilium; 12. = pubis; 13. = ischium; 14. = femur (thigh); 15. = tibia and fibula (lower leg); 16. = pes; 17. = abdominal ribs (gastralia).
Fig. 20 in Diversity and taxonomy of the Late Triassic sauropodomorphs (Saurischia, Sauropodomorpha) stored in the Palaeontological Collection of Tübingen, Germany, historically referred to Plateosaurus
Fig. 20. Material collected in Hechingen, an outcrop of the Knollenmergel, known as the historical collection number "GPIT 18375". A. GPIT-PV-60357, middle caudal in left lateral view. B. GPIT- PV-60360, middle caudal in left lateral view. C. GPIT-PV-60359, middle caudal in left lateral view. D. GPIT-PV-60358, middle caudal in left ventrolateral view. E. GPIT-PV-60356, middle caudal in right lateral view. F. GPIT-PV-60361, anterior caudal in right lateral view. G. GPIT-PV-60362, anterior caudal in left lateral view. H. GPIT-PV-60355, chevron in left lateral view. I. GPIT-PV-60353, chevron in left lateral view. J. GPIT-PV-60352, chevron in left lateral view. K. GPIT-PV-60354, chevron in left lateral view. L. GPIT-PV-60351, chevron in left lateral view. M. GPIT-PV-60348, chevron in left lateral view. N. GPIT-PV-60347, chevron in left lateral view. O. GPIT-PV-60350, distal part of the scapular blade. P. GPIT-PV-60349, manual ungual. Q. GPIT-PV-60346, presumed manual ungual.
Fig. 18 in Diversity and taxonomy of the Late Triassic sauropodomorphs (Saurischia, Sauropodomorpha) stored in the Palaeontological Collection of Tübingen, Germany, historically referred to Plateosaurus
Fig. 18. Holotype of "Teratosaurus" trossingensis von Huene, 1907 (historical number "GPIT 18064") from Rottweil. A. GPIT-PV-60447, astragalus, in ventral view. B. Outline of the metatarsals in proximal view. C–Q. GPIT-PV-60448, partial right pes. C. Metatarsal V in anterior view. D. Metatarsal IV in anterior view. E. Pedal phalanx IV.1 in anterior view. F. Pedal phalanx IV.2 in anterior view. G. Pedal phalanx IV.3 in anterior view. H. Pedal phalanx IV.4 in anterior view. I. pedal ungual IV.5. J. Metatarsal III in anterior view. K. Pedal phalanx III.1 in anterior view. L. Pedal phalanx III.2 in anterior view. M. Pedal phalanx III.3 in anterior view (most of the element is reconstructed). N. Metatarsal II (shaft is probably a negative cast). O. Pedal phalanx II.1 (half of the element is probably a negative cast). P. Mmetatarsal I in anterior view (shaft is probably a negative cast). Q. Pedal phalanx I.1 in anterior view.
Fig. 17. Unidentified material from Aixheim, collected from the Stubensandstein. A in Diversity and taxonomy of the Late Triassic sauropodomorphs (Saurischia, Sauropodomorpha) stored in the Palaeontological Collection of Tübingen, Germany, historically referred to Plateosaurus
Fig. 17. Unidentified material from Aixheim, collected from the Stubensandstein. A. GPIT-PV-60390, fragment of a scapular blade in lateral view. B. GPIT-PV-60400, serrated conical tooth. C. GPIT-PV-60401, fragment of a vertebra. D. GPIT-PV-60402, indeterminate bone fragment. E. GPIT-PV-60403, rib fragment. F. GPIT-PV-60404, indeterminate bone fragment. G. GPIT-PV-60405, rib fragment. H. GPIT- PV-60406, bone fragment. I. GPIT-PV-60407, rib fragment. J. GPIT-PV-60408, zygapophysis. K. GPIT- PV-60409, rib shaft fragment. L. GPIT-PV-60410, zygapophysis. M. GPIT-PV-60411, rib fragment. N. GPIT-PV-60412, zygapophysis. O. GPIT-PV-60413, ventral margin of centrum. P. GPIT-PV-60414, fragment of a phalanx. Q. GPIT-PV-60415, fragment of a phalanx. R. GPIT-PV-60416, partial phalanx.
ScienceDex guides
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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.