IOSACal on the web: quick calibration of radiocarbon dates


The IOSA Radiocarbon Calibration Library (IOSACal) is an open source calibration software. IOSACal is meant to be used from the command line and installation, while straightforward for GNU/Linux users, is certainly not as easy as common desktop apps. To overcome this inconvenience, I dedicated some efforts to develop a version that is immediately usable.

The IOSACal web app is online at https://iosacal.herokuapp.com/.

This is a demo service, so it runs on the free tier of the commercial Heroku platform and it may take some time to load the first time you visit the website. It is updated to run with the latest version of the software (at this time, IOSACal 0.4.1, released in May).

Since it may be interesting to try the app even if you don’t have a radiocarbon date at hand, at the click of a button you can randomly pick one from the open data Mediterranean Radiocarbon dates database, and the form will be filled for you.

The random date picker in action
The random date picker in action

Unfortunately, at this time it is not possible to calibrate or plot multiple dates in the web interface (but the command-line program is perfectly capable of that).

IOSACal Web is made with Flask and the Bootstrap framework, and the app itself is of course open source.

IOSACal is written in the Python programming language and is based on Numpy, Scipy and Matplotlib. This work wouldn’t be possible without the availability of such high quality programming libraries.

IOSACal 0.4

IOSACal is an open source program for calibration of radiocarbon dates.

A few days ago I released version 0.4, that can be installed from PyPI or from source. The documentation and website is at http://c14.iosa.it/ as usual. You will need to have Python 3 already installed.

The main highlight of this release are the new classes for summed probability distributions (SPD) and paleodemography, contributed by Mario Gutiérrez-Roig as part of his work for the PALEODEM project at IPHES.

A bug affecting calibrated date ranges extending to the present was corrected.

On the technical side the most notable changes are the following:

  • requires NumPy 1.14, SciPy 1.1 and Matplotlib 2.2
  • removed dependencies on obsolete functions
  • improved the command line interface

You can cite IOSACal in your work with the DOI https://doi.org/10.5281/zenodo.630455. This helps the author and contributors to get some recognition for creating and maintaining this software free for everyone.