LISC is a package for collecting and analyzing the scientific literature.

LISC acts as a wrapper and connector between available APIs, allowing users to collect data from and about scientific articles, and perform analyses on this data, such as performing automated meta-analyses.

A curated list of some projects enabled by LISC is available on the projects page.

Supported APIs and data collection approaches include:

• The EUtils API, which provides access to literature data, including the Pubmed database, from which text and meta-data from identified articles can be collected, as well as analyses such as counts and co-occurrences of terms.
• The OpenCitations API, which provides access to citation data, from which citation and reference information can be collected.

In addition to connecting to external APIs, LISC also provides:

• A database structure, and save and load utilities for storing collected data
• Custom data objects for managing and preprocessing collected data
• Functions and utilities to analyze collected data
• Data visualization functions for plotting collected data and analysis outputs

Documentation is available on the documentation site.

This documentation includes:

• Tutorials: with a step-by-step guide through the module and how to use it
• Examples: demonstrating example analyses and use cases, and other functionality
• API list: which lists and describes all the code and functionality available in the module
• Reference: with information for how to reference and report on using the module

For a curated list of projects that use LISC check out the projects page.

LISC is written in Python 3, and requires Python >= 3.6 to run.

Requirements:

• numpy
• requests
• lxml
• beautifulsoup4

Optional dependencies, used for plotting, analyses & testing:

• matplotlib
• seaborn
• scipy
• wordcloud
• pytest

Stable releases of LISC are released on the Github release page, and on PYPI.

Descriptions of updates and changes across versions are available in the changelog.

Stable Release Version

To install the latest stable release, you can install from pip:

$ pip install lisc

LISC can also be installed with conda, from the conda-forge channel:

$ conda install -c conda-forge lisc

Development Version

To get the development version (updates that are not yet published to pip), you can clone this repository.

$ git clone https://github.com/lisc-tools/lisc

To install this cloned copy of LISC, move into the directory you just cloned, and run:

$ pip install .

Editable Version

If you want to install an editable version, for making contributions, download the development version as above, and run:

$ pip install -e .

If you use this code in your project, please cite

Donoghue, T. (2018) LISC: A Python Package for Scientific Literature Collection and Analysis. Journal of Open Source Software, 4(41), 1674. DOI: 10.21105/joss.01674

Direct Link: https://doi.org/10.21105/joss.01674

More information for how to cite this method can be found on the reference page.

This project welcomes and encourages contributions from the community!

To file bug reports and/or ask questions about this project, please use the Github issue tracker.

To see and get involved in discussions about the module, check out:

• the issues board for topics relating to code updates, bugs, and fixes
• the development page for discussion of potential major updates to the module

When interacting with this project, please use the contribution guidelines and follow the code of conduct.