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
This is the initial release of the research compendium for the article by Tsirintoulaki, K., Matzig, D.N., Riede, F. (2022) "A 2D geometric morphometric assessment of chrono-cultural trends in osseous barbed points of the European Final Palaeolithic and Early Mesolithic" submitted to Open Archaeology. It contains all data and code, and will generate the results as found in the publication. The files hosted at https://github.com/yesdavid/Osseous_Barbed_Points_2D_GMM are the development versions and may have changed since the publication.
Anonymized responses to the ARIADNEplus questionnaire to gather information for the aggregation of metadata about archaelogical resources to be included in the ARIADNEplus Knowledge Base and portal (https://portal.ariadne-infrastructure.eu/). The csv includes only the plain responses as provided by 31 archaelogical content providers until 18 October 2021. The excel file includes also two additional sheets where the responses about the formats and the aggregation update schedule have been normalised. The responses are discussed in deliverable D12.4 "Final report on data integration" currently under preparation.
The study was undertaken in eleven flashed glass samples, provided by LambertsGlas® consisting of a colorless base glass covered by layers of different colors and thicknesses. This dataset consists of images of the samples; Laser-induced Breakdown Spectrocopy (LIBS) spectra; Laser-induced Fluorescence (LIF) spectra; Optical Microscopy (OM) images; UV-Vis-IR spectra and Field Emission Scanning Electron Microscopy (FESEM) images and the assingment of the Energy-dispersive X-ray (EDS) analysis. This information allows characterizing the composition of both sides of the glasses and determining the chemilcal identification of chromophores responsible for the flashed glass coloration. Images are presented in JPG. All spectra are presented in cvs format, in a single page. Descriptions of the samples and the experimental conditions in which the spectra were taken and the name of the column values are included at the top of each page. For LIBS, 1 file per sample of elemental composition of the flashed glasses are included. Each file is composed of 2 columns (wavelength and intensity). For LIF, 1 file per sample of the analysis of fluorescent species of each flashed glass are included. Each file is composed of 2 columns (wavelength and intensity). For UV-Vis-IR spectroscopy, 1 file per sample of glass chromophores, just for the colored side. Each file is composed of 2 columns (wavelength and intensity). For FESEM-EDS, 2 files per sample. In the first one: "PHOTOS", 1 cross section image per sample is included. In the second group of files: "EDS", 1 file per sample of the assignment of the main elements. Each file is composed of 3 columns (the main elements, the results of the glass base and the colored layer in weight percentage, respectively). -- This dataset is subject to a Creative Commons Attribution 4.0 International (CC BY 4.0) License. There are 5 files which correspond to each technic employed for the analysis of the eleven different samples. The file title "PHOTOS" contains: Fig. 1_Flashedglasses_Photo; Fig. 2_OM_Photo. The file title “LIBS” contains: LIBS_Black-Baseglass; LIBS_Black-Coloredlayer; LIBS_Blue1-Baseglass; LIBS_Blue1-Coloredlayer; LIBS_Blue2-Baseglass; LIBS_Blue2-Coloredlayer; LIBS_Blue3-Baseglass; LIBS_Blue3-Coloredlayer; LIBS_Brown1-Baseglass; LIBS_Brown1-Coloredlayer; LIBS_Brown2-Baseglass; LIBS_Brown2-Coloredlayer; LIBS_Green1-Baseglass; LIBS_Green1-Coloredlayer; LIBS_Green2-Baseglass; LIBS_Green2-Coloredlayer; LIBS_Green3-Baseglass; LIBS_Green3-Coloredlayer; LIBS_Pink1-Baseglass; LIBS_Pink1-Coloredlayer; LIBS_Pink2-Baseglass; LIBS_Pink2-Coloredlayer. The file for “LIF” contains: LIF_Black-Baseglass; LIF_Black-Coloredlayer; LIF_Blue1-Baseglass; LIF_Blue1-Coloredlayer; LIF_Blue2-Baseglass; LIF_Blue2-Coloredlayer; LIF_Blue3-Baseglass; LIF_Blue3-Coloredlayer; LIF_Brown1-Baseglass; LIF_Brown1-Coloredlayer; LIF_Brown2-Baseglass; LIF_Brown2-Coloredlayer; LIF_Green1-Baseglass; LIF_Green1-Coloredlayer; LIF_Green2-Baseglass; LIF_Green2-Coloredlayer; LIF_Green3-Baseglass; LIF_Green3-Coloredlayer; LIF_Pink1-Baseglass; LIF_Pink1-Coloredlayer; LIF_Pink2-Baseglass; LIF_Pink2-Coloredlayer. For the “FESEM-EDS” there are two files inside. One title "EDS" which contains the documents: EDS_Black; EDS_Blue1; EDS_Blue2; EDS_Blue3; EDS_Brown1; EDS_Brown2; EDS_Brown2; EDS_Green1; EDS_Green2; EDS_Green3; EDS_Pink1; EDS_Pink2. And the other called "PHOTOS" which contains: FESEM_Black; FESEM_Blue1; FESEM_Blue2; FESEM_Blue3; FESEM_Brown1; FESEM_Brown2; FESEM_Green1; FESEM_Green2; FESEM_Green3; FESEM_Pink1; FESEM_Pink2. This is the experimental dataset used in the paper Appl. Sci., 12(11), 5760 (2022) (https://www.mdpi.com/2076-3417/12/11/5760). Flashed glasses are composed of a base glass and a thin colored layer and have been used since medieval times in stained glass windows. Their study can be challenging because of their complex composition and multilayer structure. In the present work, a set of optical and spectroscopic techniques have been used for the characterization of a representative set of flashed glasses commonly used in the manufacture of stained glass windows. The structural and chemical composition of the pieces were investigated by optical microscopy, field emission scanning electron microscopy-energy dispersive X-ray spectrometry (FESEM-EDS), UV-Vis-IR spectroscopy, laser-induced breakdown spectroscopy (LIBS), and laser-induced fluorescence (LIF). Optical microscopy and FESEM-EDS allowed the determination of the thicknesses of the colored layers, while LIBS, EDS, UV-Vis-IR, and LIF spectroscopies served for elemental, molecular, and chromophores characterization of the base glasses and colored layers. Results obtained using the micro-invasive LIBS technique were compared with those retrieved by the cross-sectional technique FESEM-EDS, which requires sample taking, and showed significant consistency and agreement. In addition, LIBS results revealed the presence of additional elements in the composition of flashed glasses that could not be detected by FESEM-EDS. The combination of UV-Vis-IR and LIF results allowed precise chemical identification of chromophores responsible for the flashed glass coloration. This research has been funded by the Spanish State Research Agency (AEI) through project PID2019-104124RB-I00/AEI/10.13039/501100011033, the Fundación General CSIC (ComFuturo Programme), by project TOP Heritage-CM (S2018/NMT-4372) from Community of Madrid, and by the H2020 European project IPERION HS (Integrated Platform for the European Research Infrastructure ON Heritage Science, GA 871034). Peer reviewed
The project provides the digital edition of the libretti staged for the election of the Council of the Elders in the Republic of Lucca. The celebration, known as funzione delle Tasche, was repeated every three years from 1636 to 1797. The present edition collects the works from 1636 to 1705 in order to analyze changes and recurring motifs throughout the 17th century in a republican context.
It-Sr-NER tool is a CLARIN compatible NER web service for parallel texts with case study on Italian and Serbian; it can be used for recognizing and classifying named entities in bilingual natural language texts. Input parallel texts should be TMX (Translation Memory eXchange) files, e.g. Sr-It. It-Sr-NER can recognize six NER classes: demonyms (DEMO), works of art (WORK), person names (PERS), places (LOC), events (EVENT) and organisations (ORG). The service can also be used for monolingual text NER annotation for available spaCy NER models. It-Sr-NER uses a CNN architecture within the spaCy tool and Named Entity linking with Wikidata using spaCyOpenTapioca. For further details: API usage is described in: http://ners.jerteh.rs/4api A Postman example is available at https://github.com/rankastankovic/It-Sr-NER/blob/main/static/Postman_call_ners-mono.PNG
ELEXIS-WSD is a parallel sense-annotated corpus in which content words (nouns, adjectives, verbs, and adverbs) have been assigned senses. Version 1.0 contains sentences for 10 languages: Bulgarian, Danish, English, Spanish, Estonian, Hungarian, Italian, Dutch, Portuguese, and Slovene. The corpus was compiled by automatically extracting a set of sentences from WikiMatrix (Schwenk et al., 2019), a large open-access collection of parallel sentences derived from Wikipedia, using an automatic approach based on multilingual sentence embeddings. The sentences were manually validated according to specific formal, lexical and semantic criteria (e.g. by removing incorrect punctuation, morphological errors, notes in square brackets and etymological information typically provided in Wikipedia pages). To obtain a satisfying semantic coverage, we filtered out sentences with less than 5 words and less than 2 polysemous words were filtered out. Subsequently, in order to obtain datasets in the other nine target languages, for each selected sentence in English, the corresponding WikiMatrix translation into each of the other languages was retrieved. If no translation was available, the English sentence was translated manually. The resulting corpus is comprised of 2,024 sentences for each language. The sentences were tokenized, lemmatized, and tagged with POS tags using UDPipe v2.6 (https://lindat.mff.cuni.cz/services/udpipe/). Senses were annotated using LexTag (https://elexis.babelscape.com/): each content word (noun, verb, adjective, and adverb) was assigned a sense from among the available senses from the sense inventory selected for the language (see below) or BabelNet. Sense inventories were also updated with new senses during annotation. List of sense inventories BG: Dictionary of Bulgarian DA: DanNet – The Danish WordNet EN: Open English WordNet ES: Spanish Wiktionary ET: The EKI Combined Dictionary of Estonian HU: The Explanatory Dictionary of the Hungarian Language IT: PSC + Italian WordNet NL: Open Dutch WordNet PT: Portuguese Academy Dictionary (DACL) SL: Digital Dictionary Database of Slovene The corpus is available in a CONLL-like tab-separated format. In order, the columns contain the token ID, its form, its lemma, its UPOS-tag, its whitespace information (whether the token is followed by a whitespace or not), the ID of the sense assigned to the token, and the index of the multiword expression (if the token is part of an annotated multiword expression). Each language has a separate sense inventory containing all the senses (and their definitions) used for annotation in the corpus. Not all the senses from the sense inventory are necessarily included in the corpus annotations: for instance, all occurrences of the English noun "bank" in the corpus might be annotated with the sense of "financial institution", but the sense inventory also contains the sense "edge of a river" as well as all other possible senses to disambiguate between. For more information, please refer to 00README.txt.
MALDI-TOF-MS spectra of extracted collagen from modern reference and archaeological bone samples to develop markers for Zooarchaeology by Mass Spectrometry (ZooMS) to distinguish between Equus species. For each sample digestions were done in both trypsin and chymotrypsin separately. Information about the species of the samples can be found in 'sample metadata.csv' file. Information on the extraction and digestion protocol can be found in the associated manuscript. The sequence data contains alignments of the proteins COL1A1 and COL1A2 for available Equus collagen protein sequences. More information on these files can be found in the corresponding manuscript to this dataset.
Project: EC | Persia and Babylonia (682241), EC | Persia and Babylonia (682241)
SILKNOW Multimodal Cultural Heritage Dataset. Includes text descriptions, images, labels, and predictions made by individual modality classifiers. The data resulted from an export of the SILKNOW Knowledge Graph. See: https://zenodo.org/record/5743090 Repository with code using this dataset available at: https://github.com/silknow/multimodal_cultural_heritage