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Trove National eDeposit (NED)

Current version: v1.0.0

Tools to use and explore publications submitted to Trove through the National eDeposit service.

See below for information on running these notebooks in a live computing environment. Or just take them for a spin using Binder.

ARDC Binder Binder

Notebooks

Create a searchable database from issues of a NED periodical

Trove contains thousands of publications submitted through the National eDeposit Service (NED). When I last checked, this included 8,572 periodicals comprising a total of 179,510 issues! Amongst the periodicals are many local and community newsletters that provide a valuable record of everyday life – often filling the gap left by the demise of local newspapers. Some of these periodicals have access constraints, but most can be viewed online in Trove. However, unlike Trove's own digitised periodicals or newspapers, the contents of these publications don't appear in Trove search results. This notebook provides a workflow through which you can extract text from all the issues of a NED publication and build a fulltext-search-enabled database for exploration of its contents.

Harvest details of periodicals submitted to Trove through the National edeposit scheme (NED)

This notebook harvests details of periodicals submitted to Trove through the National edeposit scheme (NED). It creates two datasets, one containing details of the periodical titles, and the other listing all the available issues.

Datasets

Searchable database of content from The Triangle

Examples of SQLite databases created by extracting and indexing the text content of NED periodicals. Includes custom metadata files for Datasette configuration.

Details of periodicals submitted to Trove through the National edeposit scheme (NED)

This dataset contains details of periodical titles and issues submitted to the Trove through the NLA's National edeposit scheme. It includes CSV-formatted lists of titles and issues, and an SQLite database created for use with Datasette-Lite.

Run these notebooks

There are a number of different ways to use these notebooks. Binder is quickest and easiest, but it doesn't save your data. I've listed the options below from easiest to most complicated (requiring more technical knowledge).

Using ARDC Binder

Launch on ARDC Binder

Click on the button above to launch the notebooks in this repository using the ARDC Binder service. This is a free service available to researchers in Australian universities. You'll be asked to log in with your university credentials. Note that sessions will close if you stop using the notebooks, and no data will be preserved. Make sure you download any changed notebooks or harvested data that you want to save.

See Using ARDC Binder for more details.

Using Binder

Launch on Binder

Click on the button above to launch the notebooks in this repository using the Binder service (it might take a little while to load). This is a free service, but note that sessions will close if you stop using the notebooks, and no data will be saved. Make sure you download any changed notebooks or harvested data that you want to save.

See Using Binder for more details.

Using Reclaim Cloud

Launch on Reclaim Cloud

Reclaim Cloud is a paid hosting service, aimed particularly at supported digital scholarship in hte humanities. Unlike Binder, the environments you create on Reclaim Cloud will save your data – even if you switch them off! To run this repository on Reclaim Cloud for the first time:

  • Create a Reclaim Cloud account and log in.
  • Click on the button above to start the installation process.
  • A dialogue box will ask you to set a password, this is used to limit access to your Jupyter installation.
  • Sit back and wait for the installation to complete!
  • Once the installation is finished click on the 'Open in Browser' button of your newly created environment (note that you might need to wait a few minutes before everything is ready).

See Using Reclaim Cloud for more details.

Running in a container on your own computer

GLAM Workbench repositories are stored as pre-built container images on quay.io. You can run these containers on your own computer to set up a virtual machine with everything you need to use the notebooks. This is free, but requires more technical knowledge – you'll have to install Podman on your computer, and be able to use the command line.

  • Install Podman.
  • In a terminal, run the following command:
    podman run --rm -p 8888:8888 quay.io/glamworkbench/trove-ned jupyter lab --ip=0.0.0.0 --port=8888 --ServerApp.token="" --LabApp.default_url="/lab/tree/index.ipynb"
  • It will take a while to download and configure the container image. Once it's ready you'll see a message saying that Jupyter Notebook is running.
  • Point your web browser to http://127.0.0.1:8888
  • When you've finished, download any files or data you want to keep from Jupyter Lab, and enter Ctrl+C int the terminal.

See Running in a container on your own computer for more details.

Setting up on your own computer

If you know your way around the command line and are comfortable installing software, you might want to set up your own computer to run these notebooks. You'll need to have recent versions of Python and Git installed. I use pyenv, pyenv-virtualenv, and pip-tools to create and manage Python versions and environments.

In a terminal:

  • Create a Python virtual environment (Python >= 3.10 should be ok): pyenv virtualenv 3.10.12 trove-ned
  • Activate the virtual environment: pyenv local trove-ned
  • Use git clone to create a local version of the GLAM Workbench repository: git clone https://github.com/GLAM-Workbench/trove-ned.git
  • Use cd to move into the newly-cloned folder: cd trove-ned
  • Run pip install pip-tools to install pip-tools.
  • Run pip-sync requirements.txt dev-requirements.txt to install the required Python packages.
  • Start Jupyter with jupyter lab – a browser window should open automatically. If not, copy and paste the url from the command line to your web browser.
  • To shut down your Jupyter Lab session enter Ctrl+C in the terminal.

See Using Python on your own computer for more details.

Contributors

Cite as

Sherratt, Tim. (2025). GLAM-Workbench/trove-ned (version v1.0.0). Zenodo. https://doi.org/10.5281/zenodo.14887116