GLAM datasets from government data portals
Current version: v1.0.0
Notebooks and harvested data relating to my attempts to extract information about GLAM (galleries, libraries, archives, and museums) datasets from government data portals. For more information see the GLAM data from government portals section of the GLAM Workbench.
- Harvesting GLAM data from government portals – attempts to harvest the details of GLAM datasets from state and national data portals.
- Harvest GLAM datasets from data.gov.au – quick attempt to harvest datasets published by GLAM institutions using the data.gov.au API.
See the GLAM Workbench for more details.
- GLAM datasets from government data portals – all formats (CSV)
- GLAM datasets from government data portals – CSVs only (CSV)
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).
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
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.
You can use Docker to run a pre-built computing environment on your own computer. It will set up everything you need to run the notebooks in this repository. This is free, but requires more technical knowledge – you'll have to install Docker on your computer, and be able to use the command line.
- Install Docker Desktop.
- Create a new directory for this repository and open it from the command line.
- From the command line, run the following command:
docker run -p 8888:8888 --name ozglam-data -v "$PWD":/home/jovyan/work quay.io/glamworkbench/ozglam-data repo2docker-entrypoint jupyter lab --ip 0.0.0.0 --NotebookApp.token='' --LabApp.default_url='/lab/tree/index.ipynb'
- It will take a while to download and configure the Docker image. Once it's ready you'll see a message saying that Jupyter Notebook is running.
- Point your web browser to
See Using Docker 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.
Assuming you have recent versions of Python and Git installed, the steps might be something like:
- Create a virtual environment, eg:
python -m venv ozglam-data
- Open the new directory"
- Activate the environment
- Clone the repository:
git clone https://github.com/GLAM-Workbench/ozglam-data.git notebooks
- Open the new
- Install the necessary Python packages:
pip install -r requirements.txt
- Run Jupyter:
See Getting started for more details.
See the GLAM Workbench or Zenodo for up-to-date citation details.
This repository is part of the GLAM Workbench.