{ "cells": [ { "cell_type": "markdown", "id": "edf41ced", "metadata": {}, "source": [ "# Trove lists and tags\n", "\n", "Current version: [v1.0.0](https://github.com/GLAM-Workbench/trove-lists/releases/tag/v1.0.0)\n", "\n", "Jupyter notebooks to work with data from Trove's public lists and tags. See the [GLAM Workbench](https://glam-workbench.net/trove-lists/) for more details.\n", "\n", "## Notebook topics\n", "\n", "### Lists\n", "\n", "* [**Convert a Trove list into a CSV file**](Convert-a-Trove-list-into-a-CSV-file.ipynb) – extracts list data from the Trove API and saves the results as CSV files (with separate files for newspaper articles and other resources); optionally save OCRd test, PDFs, and images of any listed newspaper articles.\n", "* [**Convert a Trove list into a CollectionBuilder exhibition**](convert-list-to-cb-exhibition.ipynb) – converts Trove lists into a series of files that can be uploaded to a [CollectionBuilder-GH](https://github.com/CollectionBuilder/collectionbuilder-gh) repository to create an instant exhibition.\n", "* [**Harvest summary data from Trove lists**](Harvest-summary-data-from-lists.ipynb) – extract and analyse data from all public lists in Trove\n", "\n", "### Tags\n", "\n", "* [**Harvest public tags from Trove zones**](harvest-tags.ipynb) – assemble a dataset containing all public tags added to Trove\n", "* [**Analyse public tags added to Trove**](analyse_tags.ipynb) – explore ways of analysing and visualising the complete dataset of public tags added to Trove resources" ] }, { "cell_type": "markdown", "id": "1d38d209", "metadata": {}, "source": [ "## Cite as\n", "\n", "See the GLAM Workbench or [Zenodo](https://doi.org/10.5281/zenodo.3521723) for up-to-date citation details.\n", "\n", "----\n", "\n", "This repository is part of the [GLAM Workbench](https://glam-workbench.github.io/). \n", "If you think this project is worthwhile, you might like [to sponsor me on GitHub](https://github.com/sponsors/wragge?o=esb)." ] } ], "metadata": { "jupytext": { "cell_metadata_filter": "-all" }, "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" } }, "nbformat": 4, "nbformat_minor": 5 }