• Digital Humanities and Cultural Heritage
• Open Access close
• Research data close
• Research software close
• Other research products close
• ZENODO close

The Visean stage of the Mississippian was a time of rapid tetrapod diversification which marks the earliest appearance of temnospondyls, microsaurs and the limbless aïstopods. Tetrapod finds from this stage are very rare and only a dozen sites are known worldwide. Here we announce the discovery of a new Visean site in Fife, Scotland, of Asbian age, and from it describe a new species of the baphetoid Spathicephalus. These specimens represent the oldest known baphetoid by three million years, yet belong to the most specialized members of the clade. Unlike typical baphetoids with large marginal teeth and palatal fangs characteristic of early tetrapods, spathicephalids had very broad flattened heads with a dentition consisting of a large number of small, uniform teeth. Spathicephalids were probably one of the earliest tetrapod groups to use suction feeding on small, aquatic prey. Palynological and sedimentological analysis indicates that the new fossil bed was deposited in a large, stratified, freshwater lake that became increasingly saline. Smithson et al. A new Mississippian tetrapod Supporting InformationThe file contains a summary of the palynology of the new site. A list of species is given together with two plates of photomicrographs showing each of the spore species recovered.Smithson et al. A new Mississippian tetrapod Sup Info.docx

Final 3D dataset for object 1989.24.71888-71893-71196 in the collections of York Archaeological Trust. 1989.24.71888-71893-71196 comprises three sherds of a North Gaulish White ware 4 mortarium (Tomber and Dore 1998, 75, NOG WH 4; Gillam Type 238 (1970, 25); Monaghan 1997, 939, no. 3407, fig. 374, p.940). Data was captured using a Zeiss Comet L3D 2 5M at 100 FOV to enable the analysis of use-wear on archaeological objects. The model is scaled in millimetres. Final dataset consists of 14,916,975 triangles - additional metadata included in associated spreadsheet. Access to these materials was facilitated by the York Archaeological Trust. Please include the original catalogue reference to the physical object when citing this material. Funding was provided by the University of Missouri System Research Board, Grant no. RB 17-31.

This record contains the datasets and models used and produced for the work reported in the paper "Combining Visual and Textual Features for Semantic Segmentation of Historical Newspapers" (link). Please cite this paper if you are using the models/datasets or find it relevant to your research: @article{barman_combining_2020, title = {{Combining Visual and Textual Features for Semantic Segmentation of Historical Newspapers}}, author = {Raphaël Barman and Maud Ehrmann and Simon Clematide and Sofia Ares Oliveira and Frédéric Kaplan}, journal= {Journal of Data Mining \& Digital Humanities}, volume= {HistoInformatics} DOI = {10.5281/zenodo.4065271}, year = {2021}, url = {https://jdmdh.episciences.org/7097}, } Please note that this record contains data under different licenses. 1. DATA Annotations (json files): JSON files contains image annotations, with one file per newspaper containing region annotations (label and coordinates) in VIA format. The following licenses apply: luxwort.json: those annotations are under a CC0 1.0 license. Please refer to the right statement specified for each image in the file. GDL.json, IMP.json and JDG.json: those annotations are under a CC BY-SA 4.0 license. Image files: The archive images.zip contains the Swiss titles image files (GDL, IMP, JDG) used for the experiments described in the paper. Those images are under copyright (property of the journal Le Temps and of ArcInfo) and can be used for academic research or educational purposes only. Redistribution, publication or commercial use are not permitted. These terms of use are similar to the following right statement: http://rightsstatements.org/vocab/InC-EDU/1.0/ 2. MODELS Some of the best models are released under a CC BY-SA 4.0 license (they are also available as assets of the current Github release). JDG_flair-FT: this model was trained on JDG using french Flair and FastText embeddings. It is able to predict the four classes presented in the paper (Serial, Weather, Death notice and Stocks). Luxwort_obituary_flair-bpemb: this model was trained on Luxwort using multilingual Flair and Byte-pair embeddings. It is able to predict the Death notice class. Luxwort_obituary_flair-FT_indomain: this model was trained on Luxwort using in-domain Flair and FastText embeddings (trained on Luxwort data). It is also able to predict the Death notice class. Those models can be used to predict probabilities on new images using the same code as in the original dhSegment repository. One needs to adjust three parameters to the predict function: 1) embeddings_path (the path to the embeddings list), 2) embeddings_map_path(the path to the compressed embedding map), and 3) embeddings_dim (the size of the embeddings). Please refer to the paper for further information or contact us. 3. CODE: https://github.com/dhlab-epfl/dhSegment-text 4. ACKNOWLEDGEMENTS We warmly thank the journal Le Temps (owner of La Gazette de Lausanne and the Journal de Genève) and the group ArcInfo (owner of L'Impartial) for accepting to share the related datasets for academic purposes. We also thank the National Library of Luxembourg for its support with all steps related to the Luxemburger Wort annotation release. This work was realized in the context of the impresso - Media Monitoring of the Past project and supported by the Swiss National Science Foundation under grant CR- SII5_173719. 5. CONTACT Maud Ehrmann (EPFL-DHLAB) Simon Clematide (UZH)

These files contain the calculations of phonological proximity and validations with users carried out on a subset of the Costa Rican Sign Language (LESCO, for its acronym in Spanish). The signs corresponding to the alphabet have been used.

Figure 4 - Impressions from a poster session organized during the 1st European Conference on Echinoderms, held 1979 in Brussels. (A) Jan J. S. Broertjes, Haruo Kanatani, Peter A. Voogt. (B) Guy Coppois, Chantal De Ridder, Edith Bricourt, Lucie Jangoux, Robert Fenaux, Lucienne Fenaux. (C) Mrs. Monteiro Marques, Vasco M. A. Monteiro Marques, Gustave Cherbonnier, Lucie Jangoux, Solveig Sjögren. (D) Alfred Goldschmid (background), Tim Bowmer, Claude Massin, Jean-Pierre Féral, John Costelloe, Brendan O'Connor. (E) Richard M. Pagett, Iain C. Wilkie, Alan M. Raymond, Roland H. Emson. (F) Raimundo Pidal, Ricard Martínez, Enrico Tortonese, F. Jensenius Madsen, Bent Hansen.

After a theoretical introduction on the concepts of reproducible science and the Web of Data, we will present the methodology of scientific notebooks (e.g. Jupyter Notebooks). In this context, we will present a step-by-step approach to the creation of a scientific notebook in history: we will load a dataset from the Open Data of the institute and then apply filters and calculations on the data. A presentation and analysis layer with graphics will complete our research product with enrichments from external data and vocabularies from the Semantic Web. This will make our output reproducible and documented with text enriched with semantic schemas (schema.org) and disambiguation authorities (GND, dpPedia, Wikidata...), data sources and computer code. The presentation does not require advanced technical knowledge. It is aimed at beginners. The technical demonstration, in the second part, is deliberately simple in content and will be commented on as it goes along.

Anonymised version of the survey results on alternative aggregation mechanisms. The online survey was conducted through Google Forms and was available from April 20 to May 8, 2020 as part of a master’s thesis in Information Science. The main objective of this survey was to gauge the awareness, interest, and use of technologies other than OAI-PMH for (meta)data aggregation. The main target audiences of the survey were the data providers and the aggregators of the Europeana network, albeit it should be noted that it was also open to other organisations and individuals working in the cultural heritage field. Another goal of the survey was to identify possible pilot experiments that Europeana could conduct with interested organisations.

Contributing metadata to the Ethnic and Migrant Minorities' (EMM) Survey Registry as a professional polling/survey company A training video targeting professional polling/survey companies to entice them to document their surveys on the EMM Survey Registry Target Audience for the video: Professional polling/survey companies producing quantitative surveys on ethnic and migrant minorities’ integration and/or inclusion