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304 results for “Dutch”
Middle Dutch syllabified words
<p><strong>Specifics of the data:</strong></p> <ul> <li>Text file (<em>syllabified_crm.txt</em>) containing 43,710 syllabified Middle Dutch words, taken from the <em>Corpus Van Reenen-Mulder</em>. This corpus, created by Pieter van Reenen en Maaike Mulder at the Free University Amsterdam, contains about 2,500 Middle Dutch charters. It has about 750,000 tokens. The charters were written in the Netherlands and Flanders between 1300 and 1400.</li> <li>The 43,710 syllabified words in this list is the total amount of unique words from the <em>Corpus Van Reenen-Mulder</em>. Some tokens from this corpus were, however, excluded when assembling the data set due to the fact that they contained diacritic symbols to indicate abbreviations, clitics, or unclear parts in the original charter.</li> <li>A dash-symbol (-) is used as separator.</li> <li>Apart from the entire data set, this DOI also includes: <ul> <li>A pdf-file visualizing the data set</li> <li>The splits used for the automatic syllabification experiment by Haverals, Kestemont & Karsdorp (2018).</li> <li>A gold standard out-of-corpus sample of 1,748 Middle Dutch words, taken at random from the <em>Cd-rom Middelnederlands</em>, also used in the above-mentioned syllabification experiment</li> </ul> </li> </ul>
Inventories of 17th-century Dutch painters and art dealers: the Künstler-Inventare database
<p>Abraham Bredius’ seminal work <em><a href="https://digi.ub.uni-heidelberg.de/diglit/bredius1915ga">Künstler-Inventare</a> </em>contains over 150 inventories of artists’ possessions in the Dutch Republic. However, this rich source has never been fully transformed into datasets, partially because Bredius was selective in his transcriptions of artists’ inventories with a focus on paintings. To fill this gap and to overcome Bredius’ biases, the <a href="https://www.virtualinteriorsproject.nl/">Virtual Interior project</a> assembled and transcribed 46 inventories of artists’ and art dealers’ homes in 17<sup>th</sup>-century Amsterdam. The selection of the inventories was based on three criteria: 1) The artists’ and art dealers’ inventories in my sample were drawn up during an artist’s lifetime or shortly after his death; 2) the inventories listed goods arranged by room; 3) the original documents of the inventories can still be traced in the Amsterdam City Archives. Forty-six inventories were selected and transcribed from the original sources or copied from existing publications. The majority of my samples can be found in the <a href="https://archief.amsterdam/inventarissen/details/5075/keywords/notarissen/withscans/0/start/0/limit/10/flimit/5">notarial archives</a> (Archive nr. 5075) and the rest in the <a href="https://archief.amsterdam/inventarissen/details/5072/withscans/0/findingaid/5072/start/0/limit/10/flimit/5">Archive of the Chamber of Insolvency</a> (<em>Desolate Boedel kamer, </em>Archive nr. 5072), both preserved in the Amsterdam City Archives<em>. </em>Starting with the published inventories, Bart Reuvekamp from our project team traced them back to the original sources in the archive, transcribed centuries-old handwritten pages, and compiled the listed objects in digital form. In this way, our database is able to encompass all belongings present in painters’ workshops, filling in the blanks that Bredius and other authors neglected or chose to leave out – the missing information that once hindered our comprehension of how artists organized their studios.</p> <p>The dataset is organized as follows:</p> <ul> <li><strong>1_Intro_and_data_explanation.xlsx</strong> introduces the dataset and explains the columns in the following files</li> <li><strong>2_Inventory_list.csv</strong> hosts the details of the inventories in this dataset</li> <li><strong>3_Inventory_items.csv</strong> contains the full transcriptions and categorical data of the objects in the inventories</li> <li><strong>4_Inventory_relationships.csv</strong> captures all the people mentioned in the inventories in the pre- or postscript and/or as debtors or creditors</li> <li><strong>5_Inventory_category_reference.csv</strong> provides a reference table for the ‘object_type’ and ‘object_category’ columns in 3_Inventory_items.csv</li> <li><strong>6_Inventory_subjectmatter_reference.csv</strong> offers a reference table for the ‘painting_subject’ and ‘painting_genre’ columns in 3_Inventory_items.csv</li> </ul> <p><strong>NB: This <em>Künstler-Inventare database </em>is a provisional version. The correction and final data process has not been fully finished in Version 1. The transcriptions might contain errors and need to be treated with caution. </strong></p> <p><strong> </strong></p>
Dutch grid map layers for biodiversity surveys
<p>This dataset contains map layers in GeoPackage format with the following grids used in biodiversity surveys in the Netherlands:</p> <table> <tbody> <tr> <td><strong>Layer name</strong></td> <td><strong>Size (m)</strong></td> <td><strong>Description</strong></td> </tr> <tr> <td>IvonGrid Kwartierhok</td> <td>1250x1042 </td> <td>Used between 1902 and 1950 by IVON botanical surveys.</td> </tr> <tr> <td>IvonGrid Uurhok</td> <td>5000x4168 </td> <td>Used between 1902 and 1950 by IVON botanical surveys. Each square contains 16 'kwartierhok' squares with corresponding first four characters in column name.</td> </tr> <tr> <td>RdGrid Kilometerhok</td> <td>1000</td> <td>Used since 1950 in biodiversity surveys. </td> </tr> <tr> <td>RdGrid Uurhok</td> <td>5000</td> <td>Used since 1950 in biodiversity surveys. Each square contains 25 kilometer squares.</td> </tr> </tbody> </table> <p> </p> <p>The RdGrid maps are available in the WGS84 and RD New (EPSG:28992) spatial reference systems, as they are aligned to rounded RD coordinates. IvonGrid is only available in WGS84.</p> <p><strong>Grid square codes</strong></p> <p>Kilometerhok (1x1 km) and Uurhok (5x5) grids have corresponding grid square codes. A code consists of three concatenated numbers for map sheat (1-62), 5 km square (11-58) and 1 km square (11-55). E.g. a 5 km square code looks like 4017. In literature and on collection labels this often written as 40.17 or 40-17.</p> <p><strong>Maintanance</strong></p> <p>This dataset is being curated by FLORON Plant Conservation Netherlands since 1988 for use in botanical surveys (previously by Theo Peterbroers, Bart Vreeken and Ruud Beringen).</p> <p><strong>History</strong></p> <p>IVON stands for "Instituut voor Vegetatie-onderzoek Nederland", an NGO founded in 1930 was most active until the 1950's and then succeeded by FLORON in 1988. More information about the repartition of the IVON grid can be found in Atlas van de Nederlandse Flora part 1 (Mennema et al. 1989). The original map was hand drawn on topographical maps by J.W.C. Goethart en W. J. Jongmans (Van Ooststroom 1956) originally following the Bessel 1841 projection (EPSG:7004). The grid cells are equal in size, although not rounded to kilometers. The size was probably chosen to fit maps that were commercially available at that time.</p> <p> </p> <p><strong>References</strong></p> <p>Mennema, J., Quene-Boterenbrood, Plate, C. L., Van der Meijden, R., & Weeda, E. J. (1989). Atlas van de Nederlandse flora. Kosmos, Amsterdam.</p> <p>van Ooststroom, S.J. (1956). Het I.V.O.N. – Werk. Correspondentieblad ten dienste van de floristiek en het vegetatie-onderzoek van Nederland 1: 2–3.</p>
Frequency counts of all adjectives and past participles in the Dutch LassyGroot corpus
<p>This record contains two datasets with the frequency counts of all adjectives and all past participles in the Dutch <a href="https://taalmaterialen.ivdnt.org/download/tstc-lassy-groot-corpus/">LassyGroot</a> corpus. Some of the tokenisation has been cleaned up. For more information, visit the <a href="https://github.com/AntheSevenants/Adjectiveness">GitHub repository</a>.</p>
S110 | DUTCHUSE |Dutch Prioritized Chemical Use Categories
<p>This is the collection associated with list S110 DUTCHUSE Dutch Prioritized Chemical Use Categories on the NORMAN Suspect List Exchange.</p> <p><a href="https://www.norman-network.com/nds/SLE/">https://www.norman-network.com/nds/SLE/</a></p> <p>List of 1700+ compounds with monitoring data and their assigned use categories performed within Dutch prioritization exercise by Ad eco advies and Deltares (NORMAN Working Group 1).<br> The final use category was compiled from several lists, including the <a href="https://watson-cost.eu/outputs/databases/">Watson database</a>, <a href="https://www.riwa-rijn.org/en/">RIWA</a>, <a href="https://rvszoeksysteem.rivm.nl/ZZSlijst/TotaleLijst">Dutch Substances of Very High Concern (SVHC)</a>, Kennisimpuls Waterkwalititeit (KIWK), WFD priority and specific pollutants (NL), <a href="https://www.norman-network.com/nds/SLE/">NORMAN lists</a> and some expert judgement.<br> The 1700 compounds were chosen based on availability of Dutch targeted monitoring data (3 different datasets) in 2022. This list is a translation of the file kindly provided by Anja Derksen, AD eco advies<br> </p>
COALA voice data and transcripts Dutch
<p>This dataset contains audio files and transcripts in Dutch and related to manufacturing. We collected the scripts during the Horizon Europe RIA COALA (GA 957296, <a href="https://cordis.europa.eu/project/id/957296">project reference website</a>) from industrial use cases and hired a service provider to generate the related audio files (BIBA - Bremer Institut für Produktion und Logistik GmbH ordered the service). The service provider checked the audio files for quality.</p> <p>The service provider recruited crowd workers, and gathered their audio records, informed consent (privacy) and agreement that their records become public domain (Creative Commons 0; https://creativecommons.org/share-your-work/public-domain/cc0/). The service provider declared to follow a Crowd Code of Ethics and a Fair Pay policy.</p> <p>The metadata file contains the following information:</p> <ul> <li><strong>file_name</strong>: name of the audio file</li> <li><strong>script</strong>: script the speaker had to speak</li> <li><strong>scriptId</strong>: the numeric identifier of the script</li> <li><strong>participantId</strong>: the numeric identifier of the participant (speaker)</li> <li><strong>gender</strong>: the gender as indicated by the participant (MALE or FEMALE)</li> <li><strong>age</strong>: the age in years as indicated by the participant</li> <li><strong>age_range</strong>: the age range in years (18-30, 31-45, 46+)</li> <li><strong>country</strong>: the birth country indicated by the participant</li> <li><strong>current_country</strong>: the country of residence indicated by the participant</li> <li><strong>primary_language</strong>: the language indicated as primary by the participant</li> <li><strong>ever_worked_factory</strong>: answer to the question: "Have you ever worked in a factory, manufacturing setting?" (Yes/No)</li> <li><strong>years_worked_factory</strong>: answer to the question: "If yes, for how many years?" (1-10, 10+)</li> <li><strong>background_noise_type</strong>: background noise in the audio as indicated by the participant (mild, humming/technical, no noise)</li> <li><strong>gdpr_and_ipr_consent</strong>: answer to the privacy notice and the ipr transfer to CC-0 (Yes)</li> <li><strong>date_signed</strong>: date when the participant signed the consent form (US format, MM.DD.YYYY)</li> </ul>
Recording of a learner of the Dutch language reading a Dutch position paper about Open Science in the Netherlands
<p>This repo contains a recording I made of me reading the position paper "<a href="https://commons.wikimedia.org/wiki/File:283.002-Erkennen-en-Waarderen-Position-Paper_NL_web.pdf#%7B%7Bint%3Alicense-header%7D%7D">Ruimte voor ieders talent</a>" (<a href="https://commons.wikimedia.org/wiki/File:283.002-Erkennen-en-Waarderen-Position-Paper_EN_web.pdf#%7B%7Bint%3Afiledesc%7D%7D">Room for everyone's talent</a>) upon first contact, albeit after having read the accompanying post "<a href="https://www.scienceguide.nl/2019/11/erkennen-en-waarderen-moet/">Erkennen en waarderen in de wetenschap gaan drastisch veranderen</a>" by Sicco de Knecht, which provides a summary of the position paper and got me interested in knowing more. That post was not openly licensed, so my recording of reading it cannot be shared, but the position paper is available under the <a href="https://en.wikipedia.org/wiki/en:Creative_Commons">Creative Commons</a> <a href="https://creativecommons.org/licenses/by/3.0/nl/deed.en">Attribution 3.0 Netherlands</a> license, which thus also pre-determines the licensing of this recording of me reading it.</p> <p>The reason I am putting this out here is that I am interested in sharing knowledge in general, including the process of how it was acquired, which is usually not very visible, even if all the relevant teaching materials are available, which is getting more popular but still remains rare overall. For the same reasons, by the way, I am running a <a href="https://github.com/Daniel-Mietchen/learning2code">GitHub repo</a> about my progress in learning programming and querying languages.</p> <p>I have no training in Dutch but am a native speaker of German and fluent in English, through which I can understand Dutch texts fairly easily, and I have read a good number of them (including books but more frequently Wikipedia articles) silently over multiple years, which gave me some idea about how the language works.</p> <p>What is usually neglected when reading silently is pronunciation, e.g. while I passively know how numbers and letters are pronounced in Dutch, I normally read them in English or German when reading Dutch texts silently, since that is quicker and less effort for me, and most of the reading I do is to learn about content, not the respective languages.</p> <p>With the bit of extra time afforded by the present holiday period, I can give some more attention to the language part, and since the topic of the position paper (open science and how we need to adapt incentive structures in the research landscape around that) is one that I deeply care about, I could also imagine coming back to the text occasionally to track my progress over time.</p> <p>So if you are interested in the process of language acquisition or in second language acquisition (for me, though, Dutch is far from being second) and especially in open education or open science around these topics, I'd appreciate you getting in touch to learn from each other around how such materials can help me and others learn this language or anything else, and how the workflows around that could be streamlined.</p>
Dutch results from the monitoring of pesticide residues in food
<p>This dataset contains the analytical results of pesticide residues measured in the food products analysed by the national competent authorities. Pesticide residues resulting from the use of plant protection products on crops that are used for food or feed production may pose a risk factor for public health. For this reason, a comprehensive legislative framework has been established in the European Union (EU), which defines rules for the approval of active substances used in plant protection products, the use of plant protection products and for pesticide residues in food. In order to ensure a high level of consumer protection, legal limits, so called “maximum residue levels” or briefly “MRLs”, are established in Regulation (EC) No 396/2005. EU-harmonised MRLs are set for all pesticides covering all types of food products. A default MRL of 0.01 mg/kg is applicable for pesticides not explicitly mentioned in the MRL legislation. Regulation (EC) No 396/2005 imposes on Member States the obligation to carry out controls to ensure that food placed on the market is compliant with the legal limits.</p> <p>A sample is considered <strong>free of quantifiable residues</strong> if the analytes were not present in concentrations at or above the limit of quantification (LOQ). The LOQ is the smallest concentration of an analyte that can be quantified with the analytical method used to analyse the sample. It is commonly defined as the minimum concentration of the analyte in the test sample that can be determined with acceptable precision and accuracy.</p> <p>If a sample <strong>contains quantifiable residues</strong> but within the legally permitted limit (maximum residue level, MRL), it is described as a sample with quantified residue levels within the legal limits (below or at the MRL)</p> <p>A sample is considered <strong>non-compliant</strong> with the legal limit (MRL), if the measured residue concentrations clearly exceed the legal limits, taking into account the measurement uncertainty. It is current practice that the uncertainty of the analytical measurement is taken into account before legal or administrative sanctions are imposed on food business operators for infringement of the MRL legislation.</p> <p> </p> <p><strong>REPORTING AUTHORITIES CONTRIBUTING TO EACH DATA COLLECTION:</strong></p> <p>MOPER_2023 - Netherlands Food and Consumer Product Safety Authority</p> <p>MOPER_2022 - Netherlands Food and Consumer Product Safety Authority</p> <p>MOPER_2021 - Netherlands Food and Consumer Product Safety Authority</p> <p>MOPER_2020 - Netherlands Food and Consumer Product Safety Authority</p> <p>MOPER_2019 - Netherlands Food and Consumer Product Safety Authority</p> <p>MOPER_2018 - Netherlands Food and Consumer Product Safety Authority</p> <p>MOPER_2017 - Netherlands Food and Consumer Product Safety Authority</p> <p>MOPER_2016 - Netherlands Food and Consumer Product Safety Authority</p> <p>MOPER_2015 - Netherlands Food and Consumer Product Safety Authority</p> <p>MOPER_2014 - Netherlands Food and Consumer Product Safety Authority</p> <p>MOPER_2013 - Netherlands Food and Consumer Product Safety Authority</p> <p>MOPER_2012 - Netherlands Food and Consumer Product Safety Authority</p> <p>MOPER_2011 - Netherlands Food and Consumer Product Safety Authority</p> <p> </p> <p><strong>We are seeking feedback on our open data please complete the survey at the link below:<br>https://ec.europa.eu/eusurvey/runner/9344dfa0-f384-cb72-65f6-6c187a6d0f14</strong></p>
Monthly births in Dutch Limburg, 1825-1839
<p>Between 1815 and 1839, Belgian Limburg and Dutch Limburg were one province of the United Kingdom of the Netherlands: Limburg. Thus, any provincial statistics published at the time do not distinguish between both. This can create problems when comparing processes over time using aggregated data.</p><p>In this dataset, I have attempted to reconstruct the monthly number of births in Dutch Limburg between 1825 and 1839 by counting the online indexes of <a href="https://aezel.eu/en">AEZEL</a>. This allows researchers to easily analyze the development in the seasonality of births in the province.</p><p> </p><p> </p>
paragraphs of the resolutions of the States General of the Dutch Republic (1576-1796)
<p><strong>Update 2025-03-24:</strong> A new version of the paragraphs has been released, with better date recognition and document segmentation (separately, a new version of the recognied named entties has been released https://doi.org/10.5281/zenodo.15074645). </p> <p>This TSV file contains all the plain text paragraphs of all the resolutions of the States General of the Dutch Republic (1576-1796). These were created as part of the project REPUBLIC (REsolutions PUBLished In a Computational environment) which is funded by NWO grant 175.2017.024</p> <p>There are a total of 1,062,723 paragraphs from 692,156 resolutions, making up a corpus of 129,688,306 words (according to Unix word count). The recognised named entities are available in a separate repository (https://doi.org/10.5281/zenodo.14577243)</p> <p>The file contains six columns:</p> <ul> <li>`session_date`: the date on which the resolution (decision) was reached.</li> <li>`resolution_id`: the identifier of the resolution.</li> <li>`para_id`: the identifier of the paragraph in the resolution.</li> <li>`line_start`: the identifier of the first line in the paragraph. This identifier contains the scan ID and the x,y,w,h coordinates of the line in the scan, so it the resolution text can be traced to where it starts in the scan. </li> <li>`line_end`: the identifier of the last line in the paragraph. This identifier contains the scan ID and the x,y,w,h coordinates of the line in the scan, so it the resolution text can be traced to where it ends in the scan (which is not necessarily the same scan as the first line, as paragraphs can cross scan boundaries). </li> <li>`text`: the text of the paragraph.</li> </ul> <p> </p> <p>For more information on how this was generated, see the following publications:</p> <p>Marijn Koolen, Rik Hoekstra, Joris Oddens, Ronald Sluijter, Rutger van Koert, Ger Brouwer en Hennie Brugman, ‘<a href="https://dl.acm.org/doi/pdf/10.1145/3575864">The Value of Preexisting Structures for Digital Access Modelling the Resolutions of the Dutch States General</a>’, <em>Journal of Computing and Cultural Heritage </em>16:1 (2023). https://dl.acm.org/doi/10.1145/3575864</p> <p>Marijn Koolen en Rik Hoekstra, ‘<a href="https://ceur-ws.org/Vol-3290/long_paper5740.pdf">Detecting Formulaic Language Use in Historical Administrative Corpora</a>’, in: F. Karsdorp, A. Lassche, en K. Nielbo eds., <em>Proceedings of the Computational Humanities Research Conference 2022 </em>(Antwerpen 2022) 127-151. <em>Proceedings http://ceur-ws. org ISSN</em>, <em>1613</em>, 0073. https://ceur-ws.org/Vol-3290/long_paper5740.pdf</p> <p>Koolen, M., Hoekstra, R., Oddens, J., & Sluijter, R. (2023). '<a href="https://ceur-ws.org/Vol-3558/paper9465.pdf">Formulas and decision-making: the case of the states general of the Dutch Republic</a>' in: F. Karsdorp, A. Lassche, en K. Nielbo eds., <em>Proceedings of the Computational Humanities Research Conference 2023 </em>(Paris 2023) 772-798. <em>Proceedings http://ceur-ws. org ISSN</em>, <em>1613</em>, 0073. https://ceur-ws.org/Vol-3558/paper9465.pdf</p> <p>Rutger van Koert, Stefan Klut, Tim Koornstra, Martijn Maas en Luke Peters, ‘<a href="https://link.springer.com/chapter/10.1007/978-3-031-70645-5_6">Loghi: An End-to-End Framework for Making Historical Documents Machine-Readable</a>’,<em> Document Analysis and Recognition – ICDAR 2024 Workshops</em> (Cham: Springer 2024) 73-88. https://link.springer.com/chapter/10.1007/978-3-031-70645-5_6</p>
Foot anomalies in four post-medieval, Dutch populations (17th-19th century)
<p>This dataset was compiled for the master's thesis "Familiar Feet. Kinship analysis using foot anomalies in the cemetery of Middenbeemster (Netherlands, 17th to 19th century)" at Leiden University (Netherlands) by the author. The thesis was submitted on June 15th, 2021 (<a href="https://hdl.handle.net/1887/3204807">https://hdl.handle.net/1887/3204807</a>). The data was collected in the period from January to May 2021 at the Laboratory of Human Osteoarchaeology at Leiden University.</p> <p>It includes the data of 380 adult individuals from four different post-medieval, Dutch populations: the rural population of Middenbeemster (MB) (Hakvoort 2013) and the urban populations of Eindhoven (Catharinakerk) (EH) (Arts 2013), Zwolle (Broerenkerk) (ZW) (Clevis and Constandse-Westermann 1992) and Arnhem (Eusebiuskerk) (AR) (Baetsen et al. 2018). For every individual, an estimate of sex and age-at-death was collected. If a DNA analysis was performed, then this result was used instead of an estimation. The sex estimations of the individuals were based on pelvic and cranial morphology (Bainbridge & Genoves Tarazaga, 1956; Bass, 1987; Buikstra & Ubelaker, 1997; Maat & Mastwijk, 2009; McCormick et al., 1991; Phenice, 1969; Stewart, 1979; Steyn & Işcan, 1999; Workshop for European Anthropologists (WEA), 1980) and were supported by archival data. For the Eindhoven collection, the DNA-determined sex estimations took precedence over the estimations by traditional bioarchaeological techniques (Baetsen & Weterings-Korthorst, 2013). The used abbreviations are M = male, PM = probable male, I = indeterminate, PF = probable female, F = female. <br> Age-at-death estimations were made according to traditional bioarchaeological techniques (Brooks & Suchey, 1990; Buckberry & Chamberlain, 2002; İşcan et al., 1984, 1985; Lovejoy et al., 1985; Maat, 2001; Meindle & Lovejoy, 1985; Todd, 1920). The used abbreviations are EYA = early young adult, LYA = late young adult, MA = middle adult, OA = old adult.</p> <p>The foot anomalies included are accessory navicular (AccessNav), brachydactyly D (BrachyD), brachydactyly of the first metatarsal (BrachyMT1), brachydactyly of the fourth metatarsal (BrachyMT4), brachydactyly of the first proximal phalanx (BrachyPP1), calcaneocuboid coalition (CalcCubCoal), calcaneonavicular coalition (CalcNavCoal), coalition between the intermediate and lateral cuneiform (CF2CF3Coal), coalition between the lateral cuneiform and the third metatarsal (CF3MT3Coal), talocalcaneal coalition (TaloCalcCoal), talonavicular coalition (TaloNavCoal) and os intermetatarseum with the medial cuneiform (CF1Intermet), the first metatarsal (MT1Intermet) and/or the second metatarsal (MT2Intermet) involved. The scoring itself was performed without prior knowledge of skeletal data like sex and age to avoid observer bias. The trait could be marked absent (0), present (1), indiscernible if the bone was damaged (6), or missing if the bone was not present (9) for each separate foot (left (L) or right (R) side). Tarsal coalitions were scored if at least one of the two bones could be marked “absent/present”. In the remarks, some of the found lesions are described in more detail.</p> <p>For some of the individuals, there is archival data available. This is indicated with 'Yes' or 'No' in the 'Archive data?' column. For the Middenbeemster population, the location of the individual graves was determined from the grave polygons in the excavation data in QGIS by calculating the centroids of these polygons and resulted in a single pair of (x, y) coordinates.</p> <p>This dataset was used to identify probable genetic relatives within the Middenbeemster skeeltal collection through developmental foot anomalies and to analyse the spatial structure of the Middenbeemster cemetery in the context of intracemetery kinship relations. The Middenbeemster trait frequencies for these anomalies were compared to those of a reference sample of the post-medieval Dutch population (consisting of individuals from the Dutch post-medieval collections of Arnhem, Eindhoven, Zwolle). A hypothetical kinship group could be identified when the trait frequencies of the Middenbeemster sample were considerably higher than those in the reference sample. Other sources had only limited validation value in relation to the hypothesis. Visual examination and spatial statistics of the distribution of the hypothetical kinship group revealed a possible patrilineally structured cemetery, although this is based on a small sample. By putting the observed trait frequencies in a broader context, the data suggested a rather high inter-relatedness of the Middenbeemster community. It also exposed the need for a better understanding of the used traits and perhaps a different approach to kinship analysis (due to necessarily large time investment in contrast to limited results). In conclusion, this study gave an insight into the social structure of post-medieval Dutch communities. Future improvements to kinship analysis may not only be beneficial for bioarchaeology, but also for other fields such as forensic anthropology.<br> For more information on this research, see the thesis (<a href="https://hdl.handle.net/1887/3204807">https://hdl.handle.net/1887/3204807</a>) or the article published in <em>International Journal of Osteoarchaeology</em> (DOI: 10.1002/oa.3100).</p> <p> </p> <p>References:</p> <p>Arts, Nico. 2013. Een knekelveld maakt geschiedenis. Het archeologisch onderzoek van het koor en het grafveld van de middeleeuwse Catharinakerk in Eindhoven, circa 1200-1850. Rapport 22. Utrecht: Uitgeverij Matrijs.</p> <p>Baetsen, Steffen, Willem Baetsen, Martijn Defilet, and Gerben Zielman. 2018. ‘Sint-Jansbeek brengt Oude Kerkhof boven water. Graven bij de Arnhemse Eusebiuskerk’. Archeologie in Nederland 3: 34–43.</p> <p>Baetsen, Steffen, and L. Weterings-Korthorst. 2013. ‘De menselijke overblijfselen’. In Een knekelveld maakt geschiedenis. Het archeologisch onderzoek van het koor en het grafveld van de middeleeuwse Catharinakerk in Eindhoven, circa 1200-1850, edited by Nico Arts and E. Altena, 288. Utrecht: Uitgeverij Matrijs.</p> <p>Bainbridge, D., and S. Genoves Tarazaga. 1956. ‘A Study of Sex Differences in the Scapula’. Journal of the Royal Anthropological Institute of Great Britain and Northern Ireland 86 (2): 109–34. https://doi.org/10.2307/2843994.</p> <p>Bass, W. M. 1987. Human Osteology: A laboratory and Field Manual. Missouri Archaeological Society. Special Publication 2. Columbia (Mo): Missouri Archaeological Society.</p> <p>Brooks, S., and J. M. Suchey. 1990. ‘Skeletal Age Determination Based on the Os Pubis: A Comparison of the Acsadi-Nemeskeri and Suchey-Brooks Methods’. Human Evolution 5 (3): 227–38.</p> <p>Buckberry, J.L., and A.T. Chamberlain. 2002. ‘Age Estimation from the Auricular Surface of the Ilium: A Revised Method’. American Journal of Physical Anthropology 119 (3): 231–39. https://doi.org/10.1002/ajpa.10130.</p> <p>Buikstra, Jane E., and Douglas H. Ubelaker. 1997. Standards for Data Collection from Human Skeletal Remains. 3rd ed. Arkansas Archaeological Survey Research Series 44. Fayetteville, Arkansas: Arkansas Archaeological Survey.</p> <p>Clevis, Hemmy, and T. S. Constandse-Westermann. 1992. De doden vertellen: opgraving in de Broerekerk te Zwolle 1987-1988. Kampen: Stichting Archeologie IJssel/Vechtstreek III.</p> <p>Hakvoort, A. 2013. ‘De begravingen bij de Keyserkerk te Middenbeemster’. Hollandia Reeks 464. Hollandia Reeks. Zaandijk: Hollandia Archeologen.</p> <p>İşcan, M. Y., S. R. Loth, and R. K. Wright. 1985. ‘Age Estimation from the Rib by Phase Analysis: White Females’. Journal of Forensic Sciences 30 (3): 853–63.</p> <p>İşcan, M. Yaşar, Susan R. Loth, and Ronald K. Wright. 1984. ‘Metamorphosis at the Sternal Rib End: A New Method to Estimate Age at Death in White Males’. American Journal of Physical Anthropology 65 (2): 147–56. https://doi.org/10.1002/ajpa.1330650206.</p> <p>Lovejoy, C. Owen, Richard S. Meindl, Thomas R. Pryzbeck, and Robert P. Mensforth. 1985. ‘Chronological Metamorphosis of the Auricular Surface of the Ilium: A New Method for the Determination of Adult Skeletal Age at Death’. American Journal of Physical Anthropology 68 (1): 15–28. https://doi.org/10.1002/ajpa.1330680103.</p> <p>Maat, G. J. R., and R. W. Mastwijk. 2009. Manual for the Physical Anthropological Report. 6th ed. Barge’s Anthropologica 6. Leiden: Barge’s Anthropologica.</p> <p>Maat, George J. R. 2001. ‘Diet and Age-At-Death. Determination from Molar Attrition: A Review Related to the Low Countries’. The Journal of Forensic Odonto-Stomatology 19: 18–21.</p> <p>McCormick, W. F., J. H. Stewart, and H. Greene. 1991. ‘Sexing of Human Clavicles Using Length and Circumference Measurements’. The American Journal of Forensic Medicine and Pathology 12 (2): 175–81. https://doi.org/10.1097/00000433-199106000-00017.</p> <p>Meindl, Richard S., and C. Owen Lovejoy. 1985. ‘Ectocranial Suture Closure: A Revised Method for the Determination of Skeletal Age at Death Based on the Lateral-Anterior Sutures’. American Journal of Physical Anthropology 68 (1): 57–66. https://doi.org/10.1002/ajpa.1330680106.</p> <p>Phenice, T. W. 1969. ‘A Newly Developed Visual Method of Sexing the Os Pubis’. American Journal of Physical Anthropology 30 (2): 297–301. https://doi.org/10.1002/ajpa.1330300214.</p> <p>Stewart, T. D. 1979. Essentials of Forensic Anthropology. Springfield (Ill.): C. C. Thomas.</p> <p>Steyn, M., and M. Y. Işcan. 1999. ‘Osteometric Variation in the Humerus: Sexual Dimorphism in South Africans’. Forensic Science International 106 (2): 77–85. https://doi.org/10.1016/s0379-0738(99)00141-3.</p> <p>Todd, T. 1920. ‘Age Changes in the Pubic Bones, I: The White Male Pubis’. American Journal of Physical Anthropology 3: 285–334.</p> <p>Workshop for European Anthropologists (WEA). 1980. ‘Recommendations for Age and Sex Diagnoses of the Skeleton’. Journal of Human Evolution 9: 517–49. https://doi.org/10.1016/j.jchb.2005.07.002.</p> <p> </p>
Topological Network of the Dutch Fairway Information System
<p>Topological fairway network derived from the <a href="https://www.vaarweginformatie.nl/">Dutch Fairway Information System</a>. The data is processed to be topological connected and usable for transport network analysis. </p> <p>Files</p> <p><code>network_digital_twin_v0.3.json</code> This is the json (for web) file for the Rhine corridor extending from Rotterdam (NLD) to Basel (Switzerland).</p> <p><code>network_digital_twin_v0.3.pickle</code> This is the pickled (for performance) file for the Rhine corridor extending from Rotterdam (NLD) to Basel (Switzerland).</p> <p><code>network_digital_twin_v0.3.zip</code> This is the shapefile (for gis) file for the Rhine corridor extending from Rotterdam (NLD) to Basel (Switzerland).</p> <p>Methodological information</p> <p>For details about the creation of the network see <a href="https://github.com/Deltares/digitaltwin-waterway/blob/master/notebooks/Build_FIS_network.ipynb">Build_FIS_network.ipynb</a>.</p> <p>Updates in version 0.3.0:</p> <p>- Added information on discharge dependent <a href="https://github.com/Deltares/digitaltwin-waterway/blob/feature/sailing/notebooks/velocities/read-velocities.ipynb">velocities</a> and <a href="https://github.com/Deltares/digitaltwin-waterway/blob/feature/sailing/notebooks/waterlevels/read_waterlevels.ipynb">waterlevels</a> in <code>river_waterlevel.geojson</code> and <code>river_velocity.geojson</code></p> <p>- Moved information on <a href="https://github.com/Deltares/digitaltwin-waterway/blob/feature/sailing/notebooks/fis-network/generate_bathymetry.ipynb">bathymetry</a> to separate file<code>edges_0.3_with_bathy.geojson</code></p> <p>- More structures added (fix in source dataset)</p> <p>- Edge and node id's are now always strings</p> <p>- Removed yaml file. It was not efficient enough and reading functionality is removed from networkx</p> <p> </p> <p>Updates in version 0.2.0:</p> <p>- added bathymetry info: mean, standard deviation , percentiles [0 (min), 5, 10, 50 (median), 90, 95, 100 (max)]</p> <p>- added new output formats: added shapely compatible geometry type</p> <p>Source data for the network is available at <a href="https://www.vaarweginformatie.nl/">https://www.vaarweginformatie.nl/</a>.</p> <p>Sharing and Access information</p> <p>CC BY-SA 4.0 license applies: <a href="https://creativecommons.org/licenses/by-sa/4.0/">https://creativecommons.org/licenses/by-sa/4.0/</a>.</p>
Polifonia Corpus - Encyclopedic Module Metadata - Dutch Language
<p>We make available the Metadata related to the Wikipedia pages that constitute the Encyclopedic Module of the Polifonia Textual Corpus. Metadata for this module includes, per each Wikipedia page, its Wikipedia ID, BabelNet ID, gloss, resource type (that can be named entity or concept), Lemmata, Sensekey, WikiData ID.</p> <p>Full description at <a href="http://github.com/polifonia-project/Polifonia-Corpus">https://github.com/polifonia-project/Polifonia-Corpus</a></p>
Open Access levels of Dutch universities 2010-2017
<p>This small dataset contains csv data on the number of articles+reviews published by authors affiliated to Dutch Universities, 2010-2017, according to the Web of Science database, measured on 20171220. It also indicates the number of open access articles+reviews among those and the resulting percentages.</p> <p> </p>
Video of Using LOD to crowdsource Dutch WW2 underground newspapers on Wikipedia, SWIB2016, Bonn, 29-11-2016
<p><strong> </strong> Video registration of presentation about <a title="File:Using LOD to crowdsource Dutch WW2 underground newspapers on Wikipedia, SWIB2016, 29-11-2016.pdf" href="https://commons.wikimedia.org/wiki/File:Using_LOD_to_crowdsource_Dutch_WW2_underground_newspapers_on_Wikipedia,_SWIB2016,_29-11-2016.pdf">Using Linked Open Data to crowdsource Dutch WW2 underground newspapers on Wikipedia</a>, <a href="https://swib.org/swib16/programme.html" rel="nofollow">SWIB2016</a>, 29-11-2016 in Bonn.</p> <p>The video describes a project <a title="nl:Wikipedia:Wikiproject/Verzetskranten" href="https://nl.wikipedia.org/wiki/Wikipedia:Wikiproject/Verzetskranten">to systematically describe and interlink 1,300 Dutch underground newspapers from World War 2</a> on Wikipedia using linked open data.</p> <p>The project extracts contextual information about the newspapers from a book, converts it to structured data, and generates Wikipedia stubs linked to metadata, full texts, and each other.</p> <p>Volunteers are expanding the stubs into full articles, improving access to information about this historical period.</p> <div> <h2>Abstract</h2> </div> <p>During the second World War some 1.300 illegal newspapers were issued by the Dutch resistance. Right after the war as many of these newspapers as possible were physically preserved by Dutch memory institutions. They were described in formal library catalogues that were digitized and brought online in the 1990s. In 2010 the national collection of underground newspapers - some 200.000 pages - was full-text digitized in Delpher, the national aggregator for historical full-texts. Having created online metadata and full-texts for these publications, the third pillar <em>context</em> was still missing, making it hard for people to understand the historic background of the newspapers. We are currently running a project to tackle this contextual problem. We started by extracting contextual entries from a hard-copy standard work on Dutch illegal press and combined these with data from the library catalogue and Delpher into a central LOD triple store. We then created links between historically related newspapers and used Named Entity Recognition to find persons, organisations and places related to the newspapers. We further semantically enriched the data using DBPedia. Next, using an article template to ensure uniformity and consistency, we generated 1.300 Wikipedia article stubs from the database. Finally, we sought collaboration with the Dutch Wikipedia volunteer community to extend these stubs into full encyclopedic articles. In this way we can give every newspaper its own Wikipedia article, making these WW2 materials much more visible to the Dutch public, over 80% of whom uses Wikipedia. At the same time the triple store can serve as a source for alternative applications, like data visualizations. This will enable us to visualize connections and networks between underground newspapers, as they developed over time between 1940 and 1945.</p> <div> <h2>Presentation slides</h2> </div> <ul> <li><a title="File:Using LOD to crowdsource Dutch WW2 underground newspapers on Wikipedia, SWIB2016, 29-11-2016.pdf" href="https://commons.wikimedia.org/wiki/File:Using_LOD_to_crowdsource_Dutch_WW2_underground_newspapers_on_Wikipedia,_SWIB2016,_29-11-2016.pdf">Using LOD to crowdsource Dutch WW2 underground newspapers on Wikipedia</a></li> <li><a href="https://swib.org/swib16/slides/janssen_using_lod.pdf" rel="nofollow">https://swib.org/swib16/slides/janssen_using_lod.pdf</a></li> <li><a href="https://doi.org/10.5281/zenodo.13132987" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.13132987</a></li> </ul>
Dataset of Middle Dutch lexical stress patterns and syllabifications
<p>This dataset consists of <strong>48.219 Middle Dutch words</strong> taken from in total 205 rhymed texts of the <em>Cd-rom Middelnederlands </em>(1998). All of these words have been <strong>assigned a syllabification and lexical stress pattern</strong>.</p> <p>E.g.: <em>proevede</em> is syllabified as <em>proe-ve-de</em> and has a stress index set at -3, which means that – counting from the rightmost syllable – the third syllable receives stress.</p> <p>This upload contains the following files:</p> <ul> <li>The <strong>JSON-file</strong> (compressed), which was used as input data for a machine learning algorithm trained for the automatic syllabification and stress assignment of Middle Dutch polysyllabic words (for the code of this experiment, see <a href="https://github.com/WHaverals/stresser">GitHub</a>)</li> <li>An <strong>Excel-file</strong>, containing the same data as the JSON (for more convenient reference)</li> <li>A <strong>split file </strong>(compressed), used in the training proces of the above-mentioned experiment</li> <li>A pdf-file with some <strong>insightful illustrations</strong> about the contents of the dataset</li> </ul> <p>This dataset is part of the research of <a href="https://www.uantwerpen.be/en/staff/wouter-haverals/research/">Wouter Haverals</a> (FWO, University of Antwerp), carried out under the supervision of prof. Mike Kestemont and em. prof. Frank Willaert.</p>
Fig. 1 in Diversity of carabids (Coleoptera: Carabidae) within two Dutch cereal fields and their boundaries
Fig. 1. Positions of sampling locations (squares) within two fields of winter wheat, Droevendaal farm, Wageningen. A – field 1; B – field 2. dd – dry ditch; gr – 2 m high grassy ridge; gs – grassy strip; h – hedge; r – tarred road; t – paved track; tr – tree row; wd – water ditch; ws – weedy strip.
Video: Creating LOD for Dutch public libraries - WikidataCon, Berlin, 25-26 October 2019
<p><span><strong>English: </strong></span> Directly inspired by a <a href="https://meta.wikimedia.org/w/index.php?title=GLAMTLV2018/Submissions/Don%27t_forget_the_libraries_-_increasing_the_coverage_in_Wikidata&oldid=18551326">lightning talk from GLAM-Wiki 2018</a> I started a project to improve the coverage and visibility of public libraries in the Netherlands on Wikidata.</p> <p>Although there are a number of websites listing all these plusminus 1300 library branches, I was quite surprised to find that none of them provide both structured and openly licensed, let alone linked data, while openness should be at the the core of every library's mission.</p> <p>I decided to solve this problem by adding address and geo data of every public library to Wikidata, hence for the very first time creating a (5-star) linked open data set for this type of library. See <a href="https://www.wikidata.org/wiki/Wikidata:WikiProject_Netherlands_Public_Libraries">https://www.wikidata.org/wiki/Wikidata:WikiProject_Netherlands_Public_Libraries</a></p> <p>This enables innovative uses, such as overviews and visualisations of the Dutch public library landscape on organisational, municipal, regional, provincial and national levels.</p> <p>This is of interest not only to Wikipedia and LOD enthousiasts, but also to e.g. policy makers, municipalities, scientists and journalists.</p> <p>In addition, to enable SPARQL generated library image galleries, I have started '1Lib1Photo' (inspired by 1Lib1Ref), an initiatieve to add an openly licensed image of every Dutch public library to Wikimedia Commons.</p> <p><strong>Takeaways</strong></p> <p>As a beginning Wikidatian myself, I hope to show that this type of project is suitable for beginners; adding address and geo infomation to Wikidata is a simple task that any one can do and a great way to learn SPARQL. Despite the simple nature of the inputs, the outputs (maps, image galleries, tables) are very relevant, not only for adding overviews of libraries to Wikipedia, but also for parties outside the Wiki sphere.</p> <p>As this project was directly inspired by work done in Wales by Simon Cobb (<a title="User:Sic19" href="https://commons.wikimedia.org/wiki/User:Sic19">User:Sic19</a>), I in my turn hope to inspire others to start similar projects in other countries.</p> <div> <h2><span></span>Context & presentation</h2> </div> <p><a href="https://www.wikidata.org/w/index.php?title=Wikidata:WikidataCon_2019/Program/Sessions/Libraries_panel&oldid=1039089450">https://www.wikidata.org/w/index.php?title=Wikidata:WikidataCon_2019/Program/Sessions/Libraries_panel&oldid=1039089450</a></p> <p>The recorded presentation was part of a <a title="d:Wikidata:WikidataCon 2019/Program/Sessions/Libraries panel" href="https://www.wikidata.org/wiki/Wikidata:WikidataCon_2019/Program/Sessions/Libraries_panel">panel about Wikidata in libraries</a></p> <p>This presentation (PDF) is also available on <a title="File:Creating LOD for Dutch public libraries - WikidataCon Berlin 25-26 October 2019 Olaf Janssen.pdf" href="https://commons.wikimedia.org/wiki/File:Creating_LOD_for_Dutch_public_libraries_-_WikidataCon_Berlin_25-26_October_2019_Olaf_Janssen.pdf">Wikimedia Commons</a> and on <a href="../records/12568513" rel="nofollow">Zenodo</a>.</p>
Fig. 5. A in Whale lice (Isocyamus deltobranchium & Isocyamus delphinii; Cyamidae) prevalence in odontocetes off the German and Dutch coasts - morphological and molecular characterization and health implications
Fig. 5. A: Ulcerative lesion with whale lice in harbour porpoise (Phocoena phocoena); B: rake marks with whale lice on pilot whale (Globicephala melas).
Fig. 4 in Whale lice (Isocyamus deltobranchium & Isocyamus delphinii; Cyamidae) prevalence in odontocetes off the German and Dutch coasts - morphological and molecular characterization and health implications
Fig. 4. Maximum likelihood phylogeny tree produced with MEGA (version X), sequences in red box from this study. Bootstrap values (n = 1000 replicates) above 50% are shown above the branches.
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.