Find research datasets worth reusing

opencc-by-4.0Oct 2022View details →

Diachronic word embeddings from 19th-century newspapers digitised by the British Library (1800-1919)

Word vectors related to the paper Machines in the media: semantic change in the lexicon of mechanization in 19th-century British newspapers by Nilo Pedrazzini and Barbara McGillivray (2022). The embeddings were trained on a 4.2-billion-word corpus of 19th-century British newspapers using Word2Vec and the following parameters: <pre><code>sg = True min_count = 1 window = 3 vector_size = 200 epochs = 5</code></pre> The embeddings are divided into periods of ten years each, with the vectors from each decade aligned to the ones from the most recent decade (1910s) using Orthogonal Procrustes. See related GitHub repository for the full documentation: <a href="https://github.com/Living-with-machines/DiachronicEmb-BigHistData">https://github.com/Living-with-machines/DiachronicEmb-BigHistData</a> Project webpage (Living with Machines): <a href="https://livingwithmachines.ac.uk/">https://livingwithmachines.ac.uk/</a>

opencc-by-4.0May 2023View details →

Decade-level Word2Vec models from automatically transcribed 19th-century newspapers digitised by the British Library (1800-1919)

Word embeddings trained on a 4.2-billion-word corpus of 19th-century British newspapers using Word2Vec and the following parameters: <pre><code>sg = True min_count = 5 window = 5 vector_size = 100 epochs = 5</code></pre> The embeddings are divided into periods of ten years each. Unlike those in <a href="https://doi.org/10.5281/zenodo.7181682">this repository</a>, these were not aligned and OCR errors skimmed from the vocabulary.  See related GitHub repository for the full documentation: <a href="https://github.com/Living-with-machines/DiachronicEmb-BigHistData">https://github.com/Living-with-machines/DiachronicEmb-BigHistData</a> Project website (Living with Machines): <a href="https://livingwithmachines.ac.uk/">https://livingwithmachines.ac.uk/</a>

Images of 3D digitisation of articles of traditional attire

These files are images digitisations of traditional, handcrafted dresses, shoes, handbags, and fabrics. These items are manufactured during the 21st century following traditional manufacturing methods and utilising designs and motifs from Greek antiquities. The 3D models were photogrammetrically captured. These images correspond to the 3D models in <a href="http://doi.org/10.5281/zenodo.8098709">https://doi.org/10.5281/zenodo.8098709</a>

Thumbnails of 3D digitisation of articles of traditional attire

These files are thumbnails of 3D digitisations of traditional, handcrafted dresses, shoes, handbags, and fabrics. These items are manufactured during the 21st century following traditional manufacturing methods and utilising designs and motifs from Greek antiquities. The 3D models were photogrammetrically captured.

opencc-by-4.0Jan 2019View details →

Sri Ksetra (HMA) Digitised Paper Archive (Version 1)

This is the current version of a digitised excavation archive, deriving from archaeological investigations at Sri Ksetra (HMA) in Burma (Myanmar) carried out 2014-16. It comprises: excavation records, artefact illustrations, section drawings, plans, maps, artefact data, sample data, field notes and accompanying indexes.

opencc-by-4.0Mar 2024View details →

Digital Repository of Ireland Member Digitisation Workflows for 2D Image Files: Survey Questions and Dataset

The Digital Repository of Ireland (DRI) issued a survey to its membership, DRI Member Digitisation Workflows for 2D Images, which ran from December 7, 2023–January 31, 2024. The survey was conducted to improve the DRI’s understanding of the technical processes and metadata workflows that our members use to digitise and share images in the Repository, in order to better tailor our support for this work and deliver the most complete information about digital images files available to our users.  The survey informed the actions taken in WorldFAIR Project WP13 deliverable <a href="https://doi.org/10.5281/zenodo.10850009" target="_blank" rel="noopener">13.3 Implementing and Testing the Cultural Heritage Image Sharing Recommendations: DRI Case Study Report</a>. The data will inform ongoing work at DRI aimed at improving the transparency of technical information associated with digital assets accessed through the Repository. Read more about the Cultural Heritage Image Sharing Case Study DRI on our website: <a href="https://dri.ie/the-worldfair-project/">https://dri.ie/the-worldfair-project/</a>.  Summary: DRI is Ireland's national repository for the arts, humanities, and social sciences data, and operates on a membership scheme. There were 20 respondents to the survey, giving us a response rate of about 35% of DRI's membership. Representation from professional fields of work across the cultural heritage sector was captured in the results (note that some institutions gave multiple responses): 17 Archives, 12 Libraries, 5 Museums and 11 Higher Education Institutions.

opencc-by-4.0Jul 2018View details →

Inventory of criteria for prioritization of digitisation of collections focussed on scientific and societal needs

Anno 2017 the task of mobilizing data from biocollections ahead of us is still enormous (data of 90% of the biocollections still needs to be mobilized). It is imperative for stakeholders, individual keepers of natural science collections, the community at large, and even for funding agencies, not only to tackle this backlog as quickly as possible, but do it in the best possible order. To establish the best possible order for digitizing biocollections a demand driven framework is required based among others on criteria used to digitize biocollections.

opencc-by-4.0Jun 2022View details →

Sri Ksetra (HMA) Digitised Paper Archive (Version 3)

opencc-by-4.0Jul 2021View details →

Multimodal 3D Digitisation of a Simulated Crime Scene

The peer-reviewed publication affiliated to this dataset has been published in Forensic Sci. 2021 an MDPI journal, and can be accessed here: <a href="https://doi.org/10.3390/forensicsci1020008">https://doi.org/10.3390/forensicsci1020008</a>. Please cite this when using the dataset. Usually, crimes and more specifically assassinations take part indoors and at particular locations. Under this scope, we demonstrate a range of  3D scanning modalities in a simulated indoor crime scene. We propose 3D scanning as a complement to traditional photographic documentation of the scene. For better comprehension of the reconstruction quality obtained from each modality and/or further research on the topic, we release the 3D files of the scene to the public. We also provide ground-truth measurements as a comparison to those that could be obtained using the 3D reconstructions. The modalities that were utilized are: <ul> <li> FARO Focus M70 </li> <li> FARO Freestyle 3DX </li> <li> DSLR and Pix4D photogrammetry software </li> <li> RGB-D scanner based on Asus XTION </li> <li> iPhone 12 Pro Max and Trnio 3D Scanner application </li> </ul>

opencc-by-4.0May 2023View details →

Diachronic and diatopic word embeddings from newspapers digitised by the British Library (1830-1889): North and South England

Diachronic word embeddings (decade-level) trained with Word2Vec (via Gensim) on different geographic subcorpora of the Heritage Made Digital British and the Living with Machines historical newspaper collections: - North England (north.zip) - South England (south.zip) At the moment, for each subcorpus, Word2Vec models are available for each decade in the period 1830-1889. More models are on the way for the following: - each decade in the periods 1780-1829 and 1890-1920 for both North and South England. - diachronic models for the following regions: Scotland, Wales, and Midlands. The models were trained using the following parameters: <pre><code>sg = True min_count = 1 window = 5 vector_size = 200 epochs = 5</code></pre> Like the embeddings in <a href="https://doi.org/10.5281/zenodo.7181682">this repository</a>, the model for each decade was aligned to the most recent one with Orthogonal Procrustes. See related GitHub repository for the full documentation: <a href="https://github.com/Living-with-machines/DiachronicEmb-BigHistData">https://github.com/Living-with-machines/DiachronicEmb-BigHistData</a>. Project website (Living with Machines): <a href="https://livingwithmachines.ac.uk/">https://livingwithmachines.ac.uk/</a> Data related to: Nilo Pedrazzini & Barbara McGillivray, Diachronic and diatopic word embeddings from British historical newspapers, presented at AIUCD (Convegno dell’Associazione per l’Informatica Umanistica e la Cultura Digitale) in Siena (Italy), June 2023.

opencc-by-4.0Dec 2022View details →

Local digital elevation model for the Ayeyarwady Delta in Myanmar (AD-DEM) derived from digitised spot and contour heights of topographic maps

Title: Local digital elevation model for the Ayeyarwady Delta in Myanmar (AD-DEM) derived from digitised spot and contour heights of topographic maps Citation: Seeger, K.; Minderhoud, P. S. J., Peffeköver, A., Vogel, A., Brückner, H., Kraas, F., Nay Win Oo, Brill, D. (2023): Local digital elevation model for the Ayeyarwady Delta in Myanmar (AD-DEM) derived from digitised spot and contour heights of topographic maps. Zenodo, <a href="https://doi.org/10.5281/zenodo.7875965">https://doi.org/10.5281/zenodo.7875965</a>. Supplement to: Seeger, K., Minderhoud, P. S. J., Peffeköver, A., Vogel, A., Brückner, H., Kraas, F., Nay Win Oo, and Brill, D. (2023): Assessing land elevation in the Ayeyarwady Delta (Myanmar) and its relevance for studying sea level rise and delta flooding. EGUsphere [preprint], <a href="https://doi.org/10.5194/egusphere-2022-1425">https://doi.org/10.5194/egusphere-2022-1425</a>. Abstract: The local digital elevation model (DEM) of the Ayeyarwady Delta, referred to as AD-DEM, was generated based on elevation data of topographic maps at scale of 1:50,000 published in 2014 while source data was compiled between 2000 and 2004. Empirical Bayesian Kriging with empirical data transformation and exponential modelling was applied to interpolate ~5100 elevation points (spot heights) and ~13600 elevation points extracted from contour data of the topographic maps. Elevation values higher than 10 m were excluded from interpolation and the SRTM water body mask created in 2000 was applied to the processed AD-DEM. The AD-DEM was transformed from its original vertical reference of local mean sea level at Kyaikkhami tide gauge to continuous mean sea level based on the mean dynamic topography data (CNES-CLS18 dataset of Mulet et al. (2021; <a href="https://doi.org/10.5194/os-17-789-2021">https://doi.org/10.5194/os-17-789-2021</a>) that we transposed to EGM96) in order to account for sea level variations along the Myanmar coast. The AD-DEM contains itself some uncertainty due to the lack of evenly distributed spot heights in areas of the upper delta, for which a separate shapefile is provided. However, we highlight to consider the AD-DEM as being the currently best available model against the background of the lacking possibility of ground truthing and being independent from satellite-based measurements. For further information on data processing, including DEM interpolation, determination of local mean sea level and vertical datum conversions, as well as DEM performance, see the corresponding paper and supplementary material. File name: ADDEM_Con250m_lesseq10_MDT_AD_MMR2000_masked_maskedSRTM.tif File format: GEOTIFF file Spatial reference: MMR2000_46N Vertical reference: local continuous mean sea level, i.e., mean dynamic topography (CNES-CLS18 dataset of Mulet et al. (2021; <a href="https://doi.org/10.5194/os-17-789-2021">https://doi.org/10.5194/os-17-789-2021</a>) transposed to EGM96 Cell size: 750 × 750 m File name: DataPoorAreas_MMR2000.shp File format: ESRI Shapefile Spatial reference: MMR2000_46N

Images and 3D digitisations of articles of traditional attire

These files are 3D digitisations and images of those of traditional, handcrafted dresses, shoes, handbags, and fabrics. These items are manufactured during the 21st century following traditional manufacturing methods and utilising designs and motifs from Greek antiquities. The 3D models were photogrammetrically captured.

3D digitisation of articles of traditional attire

These files are 3D digitisations of traditional, handcrafted dresses, shoes, handbags, and fabrics. These items are manufactured during the 21st century following traditional manufacturing methods and utilising designs and motifs from Greek antiquities. The 3D models were photogrammetrically captured.

A thumbnail of 3D digitisation of traditional shoes

This file is a thumbnail of 3D digitisations of traditional, handcrafted dresses, shoes, handbags, and fabrics. These items are manufactured during the 21st century following traditional manufacturing methods and utilising designs and motifs from Greek antiquities. The 3D models were photogrammetrically captured.

opencc-by-4.0Apr 2020View details →

Fig. 6.1. Shell digitised with different methods. The photogrammetry model was captured with a 100 in Handbook of best practice and standards for 2D+ and 3D imaging of natural history collections

Fig. 6.1. Shell digitised with different methods. The photogrammetry model was captured with a 100 mm Macro lens and processed with Agisoft Photoscan. The visual comparison of the mollusc shows a similar level of detail between photogrammetry and MechScan for the external surfaces, with still a bit more detail for the MechScan. The HDI Advance has a much lower resolution.

opencc-by-4.0Apr 2020View details →

Digitised weekly Murrumbidgee river heights southeastern Australia 1874 to 2017 (updated JJA to 31/08/2018)

The aim is to make available online to research institutions, government agencies and the public in general, weekly Murrumbidgee river heights at Hay from November 1873 to June 2017 and now updated for JJA to August 2018. Such a data repository would be a very convenient acquisition that would enhance knowledge of historical stream flow allowing annual and seasonal analysis for climate change in addition to the effect of catchment development on streamflow.

opencc-by-4.0Nov 2022View details →

Data set: Europeana Metadata to Analyse The EU's Policy Effectiveness in Digitising European Heritage

This dataset was produced as a part of a research MSc thesis project, “Using Europeana Metadata to Analyse The EU’s Policy Effectiveness in Digitising European Heritage” published by the KU Leuven in joint cooperation with Europeana. The dataset contains the data from the Europeana API call, graphs created form the data and the code needed to collect the CH metadata from Europeana digital collections which was used to evaluate the policy aims used in the study. Within this repository one will find the code scripts used to make the API calls, three Raw data files and two cleaned data spreadsheets with graphs used in the published revised research thesis Links to the research produced with this dataset and the Original Thesis published by the KU Leuven can be found below. Research Report: Morgenstern, Paul Simon. (2022). Using Europeana Metadata to Analyse The EU's Policy Effectiveness in Digitising European Heritage. Zenodo. https://doi.org/10.5281/zenodo.7278645   Thesis: Morgenstern, P., Truyen, F., & Nyi Nyi Htun, ’. (2022). Using Europeana Metadata to Analyse The EU’s Policy Effectiveness in Digitising European Heritage. KU Leuven. Faculteit Wetenschappen.

opencc-zeroJan 2023View details →

Files digitised by the National Archives of Australia, 25 February 2021 to 24 December 2022

This dataset contains details of 731,079 files digitised by the National Archives of Australia in 2021 and 2022. The National Archives of Australia's online database, RecordSearch, includes a list of recently digitised files, but the list only includes files digitised in the last month. This dataset was created by combining regular harvests of this list to create a continuous record of files digitised from 2021 and 2022. It was created and shared to help document long-term changes in access to files held by the NAA. The <a href="https://github.com/GLAM-Workbench/recordsearch/blob/master/data/recently-digitised-20210327">first harvest</a> was run on 27 March 2021 and captured details back to 25 February. Since then I have automatically run weekly harvests and saved them in <a href="https://github.com/wragge/naa-recently-digitised">this repository</a>. At the end of 2022, changes to RecordSearch broke the harvesting script, so I ran an extra harvest of the previous month on 20 January 2023 to make sure nothing was missed. I combined all the harvests into a single dataset, filtered it to include only 2022, and removed any duplicates. I also added series titles. The harvesting method is documented in <a href="https://glam-workbench.net/recordsearch/#harvest-recently-digitised-files-from-recordsearch">this notebook</a>. The dataset is saved in CSV format and includes the following columns: <ul> <li><code>title – </code>the title of this file</li> <li><code>item_id – </code>the identifier of this file</li> <li><code>series – </code>the identifier of the series that contains this item</li> <li><code>control_symbol – </code>the control symbol of this file</li> <li><code>date_range – </code>the date range of the item's contents</li> <li><code>date_digitised – </code>the date the file was digitised</li> <li><code>series_title – </code>title of the series that contains this item</li> </ul> You can construct a url to a digitised file using the <code>item_id</code>. For example: <code>http://recordsearch.naa.gov.au/scripts/AutoSearch.asp?O=I&Number=[item_id]</code> For more information on harvesting data from RecordSearch, see the <a href="https://glam-workbench.net/recordsearch/">GLAM Workbench</a>.