citationnet 1.0.0

Visualize citation and reference networks in 3D.

A Flask app to generate and display reference and citation traces of a single publication using Dimensions Analytics.

Documentation is available on ReadTheDocs.

Installation

tl;dr Use pip

pip install citationnet

Consider using a clean virtual environment to keep your main packages separated. Create a new virtual environment and install the package

python3 -m venv env
source env/bin/activate
pip install citationnet

Run the app

To run the app activate the virtual environment, export the app name and run Flask

source env/bin/activate
export FLASK_APP=citationnet
flask run

Now open the adress http://127.0.0.1:5000 in your browser and start exploring.

To close the app, press CTRL C in the terminal and close it (on Linux).

Using the interface

The button Usage toggles an explanation of the visual representation of the citation network.

First query

Before running the first query, you will need to provide an access token for Dimensions Analytics by selecting Enter Dimensions Analytics token in the interface. If you previously have used the Dimensions Analytics query language dimcli and setup a personal credential file, you can leave this field empty.

To run a query, enter a DOI and press the submit button. For very highly cited papers, the query time is to long. By default there is therefore a limit on the number of citations for the source publication and all other citations (100 citations). The default value can be changed to at most 500 citations.

The end of data generation is signaled by a success message stating the filename and runtime.

Repeated querying

The token is saved in the session cookie and re-used for the next queries. After closing the browser you will need to re-enter the token.

Query results are saved as JSON files in the media folder of the installed Flask package and can be accessed using the search input field at the navigation bar.

Visual representation

The inital graph is viewed from the side with the requested publication placed in the center of the screen, shown in red. Time ranges from bottom to top, such that newer publications are above the center and older ones below. If viewed from above nodes, farer away from the center have more citations.

Hover over a node to show DOI, year of publishing, fields of research and the number of citations according to Dimensions. Click a node to open the publication using it's DOI.

Click and drag inside the window to rotate the graph. Right-click and drag inside the window to move. Scroll inside the window to zoom in or out.

The menu button right next to the sidebar opens and closes the sidebar, which allows controlling the perspective (side or top), node and edge options as well as some basic layout options (cylinder radius, citation value of outer radius, and spacing around input node).

Testing

Tests can be run by installing the dev requirements and running tox.

pip install citationnet[dev]
tox

Building documentation

The documentation is build using sphinx. Install with the dev option and run

pip install citationnet[dev]
tox -e docs

Funding information

The development is part of the research project ModelSEN

Socio-epistemic networks: Modelling Historical Knowledge Processes,

in Department I of the Max Planck Institute for the History of Science and funded by the Federal Ministry of Education and Research, Germany (Grant No. 01 UG2131).