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This code demonstrates generic public examples of a Simple IIIF Discovery system, based on tools used within the National Gallery to provide access to images from multiple institutions and present them together in IIIF compatible viewers. The system is based on a website requesting the details of IIIF images from a Simple IIIF Discovery end-point, based on a simple keyword search. The website does not need to understand the complexities of any underlying APIs, just the simple structure of the results returned by the end-point. The website then just needs to be able to reformat the IIIF results and feed them into a IIIF based viewer of choice. This version includes a number of updates to the original demonstrator related to improving the user interface, including adding a toggle option to jump between IIIF viewers, and updating the administration process of creating new end-points and related web-pages, this is all achieved via a simple JSON config files now. A working demo of this system can be seen at: https://research.ng-london.org.uk/ss-iiif

This is a simple set of processes for creating a standard set of webpages based on a simple set of json files. This project is intended to work along side other projects to provide a simple way of creating a set of consistent webpages, which can be delivered as part of your own GitHub project using GitHub pages. It has been extended to allow more complex features such as presenting IIIIF (https://iiif.io) viewers, Timelines, and ordered Lists & Galleries. Various updates to the related JavaScript libraries have been added along with an option to use the whole system to create dynamic as well as static websites. For more detail and the most current version of the code see: https://github.com/jpadfield/simple-site

This is an interactive live modelling system which can automatically convert simple tab separated triples or JSON-LD into graphical models using the mermaid library. General updates and improvements have been carried out, with the addition of the Mermaid SubGraph functionality to aid the organisation of more complex models. Instructions: Full details and instructions relating to how this system works is still being developed, however several examples are included in the interactive web site: dynamic modelling, with all of the related code presented in GitHub.

This repository contains all the code supplementing the article by Vanessa Joosen, Research in Action: Constructing Age for Young Readers. In: International Research in Children’s Literature 14.3 (2021): 252–268. More specifically, the files are the following: - IRCL_parser.ipynb --> Jupyter Notebook, containing code for linguistic parsing - IRCL_speech_distribution.ipynb --> Jupyter Notebook, containing code for investigating speech distribution - IRCL_speech_scatterplot.ipynb --> Jupyter Notebook, containing code for building a Scatterplot (based on the wonderful Scattertext implementation by Jason S. Kessler; arxiv.org/abs/1703.00565). - norm_age.py --> Python script for extracting labeled information from the corpus according to specific age categorization methods {"references": ["Vanessa Joosen,\u00a0Research in Action: Constructing Age for Young Readers. In:\u00a0International Research in Children's Literature\u00a014.3 (2021): 252\u2013268."]}

optimalcores is an R software project to analyse the temperature and isotope time series in an isotope-enabled climate model simulation; specifically, the ECHAM5/MPI-OM-wiso past1000 climate model run can be analysed, but also any other suited model run. The software is especially intended to determine optimal spatial sampling configurations for Antarctic ice cores which maximize the correlation with a target site temperature time series. Version 1.0.0 of the software is released along with the publication Münch, Werner and Laepple: How precipitation intermittency sets an optimal sampling distance for temperature reconstructions from Antarctic ice cores, Clim. Past, 17, 1587–1605, 2021.

This repository contains several items supplementing the article Constructing Age in Children’s Literature: A Digital Approach to Guus Kuijer’s Oeuvre [The Lion and the Unicorn, forthcoming] stylometry_kuijer.ipynb -- a Jupyter Notebook, containing the code to (re)run the stylometric analyses. Given that the original texts are copyrighted, they are not part of this repository. meta.xlsx -- a spreadsheet containing meta-information about the works of fiction authored by Guus Kuijer. scatterplot_kuijer.html -- an interactive scatterplot, comparing children and adolescent speech on the one hand, and adult and old adult speech on the other (made with the scattertext tool, developed by Jason Kessler).

This is an interactive live modelling system which can automatically convert simple tab separated triples or JSON-LD into graphical models using the mermaid library. Instructions: Full details and instructions relating to how this system works is still being developed, however several examples are included in the interactive web site: dynamic modelling, with all of the related code presented in GitHub.

Added new options to improve stability of external links - aliases can now be used to ensure old links will still work when webpage names need to be updated, also to minimise the need for changing page names a displayName option has been added in to allow the names of pages in menus and links to be different from the actual html page name. Additional updates have been added to improve the display of page code, when needed.

WHOSe Heritage: Classification of UNESCO World Heritage "Outstanding Universal Value" Documents with Smoothed Labels This repository provides the supplemental materials for reproducing the results of the above-mentioned paper as submitted to arXiv preprint server, including both models and results.

Description This package is a helpful wrapper around functions from mainly the Momocs (Bonhomme et al. 2014), EBImage (Pau et al. 2010), and imager (Barthelme et al. 2020) packages. It is designed for the fast and easy extraction of single outline shapes of, for example, stone tools from images containing multiple thereof, such as the ones present in archaeological publications. This release is provided with a testing dataset, using the Morar Quartz Industry image (Credit: Wellcome Collection, https://wellcomecollection.org/works/th7egtfj, distributed under CC BY 4.0). A brief explanation of the workflow and the package functions can be found on github.com/yesdavid/outlineR. References Barthelme et al. 2020: Barthelme, S., Tschumperle, D., Wijffels, J., Assemlal, H. E., & Ochi, S. (2020). imager: Image Processing Library Based on “CImg” (0.42.3) [Computer software]. https://CRAN.R-project.org/package=imager Bonhomme et al. 2014: Bonhomme, V., Picq, S., Gaucherel, C., & Claude, J. (2014). Momocs: Outline Analysis Using R. Journal of Statistical Software, 56(13). https://doi.org/10.18637/jss.v056.i13 Pau et al. 2010: Pau, G., Fuchs, F., Sklyar, O., Boutros, M., & Huber, W. (2010). EBImage—An R package for image processing with applications to cellular phenotypes. Bioinformatics, 26(7), 979–981. https://doi.org/10.1093/bioinformatics/btq046