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ASpecD documentation

Welcome! This is the documentation for ASpecD – a framework for handling spectroscopic data focussing on reproducibility.

In short: Each and every processing step applied to your data will be recorded and can be traced back. Additionally, for each representation of your data (e.g., figures, tables) you can easily follow how the data shown have been processed and where they originate from.

What is even better: Actual data processing and analysis no longer requires programming skills, but is as simple as writing a text file summarising all the steps you want to have been performed on your dataset(s) in an organised way. Curious? Have a look at recipe-driven data analysis – or at the following example:

 2  type: ASpecD recipe
 3  version: '0.2'
 6  - /path/to/first/dataset
 7  - /path/to/second/dataset
10  - kind: processing
11    type: BaselineCorrection
12    properties:
13      parameters:
14        kind: polynomial
15        order: 0
16  - kind: singleplot
17    type: SinglePlotter1D
18    properties:
19      filename:
20        - first-dataset.pdf
21        - second-dataset.pdf

For more general information on the ASpecD framework see its Homepage, and for how to use it, carry on reading. Interested in more real-live examples? Check out the use cases section.


A list of features:

  • Framework for writing applications handling spectroscopic data

  • Consistent handling of numeric data and corresponding metadata

  • History of each processing step, automatically generated, aiming at full reproducibility

  • Undo and redo of processing steps

  • Import and export of data

  • Generic plotting capabilities, easily extendable

  • Report generation using pre-defined templates

  • Recipe-driven data analysis, allowing tasks to be performed fully unattended in the background and without programming skills

And to make it even more convenient for users and future-proof:

  • Open source project written in Python (>= 3.7)

  • Developed fully test-driven

  • Extensive user and API documentation


The ASpecD framework comes with a rather minimal set of requirements:

How to cite

ASpecD is free software. However, if you use ASpecD for your own research, please cite both, the article describing it and the software itself:

  • Jara Popp, Till Biskup. ASpecD: A Modular Framework for the Analysis of Spectroscopic Data Focussing on Reproducibility and Good Scientific Practice. Chemistry–Methods 2:e202100097, 2022. doi:10.1002/cmtd.202100097

  • Till Biskup. ASpecD (2022). doi:10.5281/zenodo.4717937

To make things easier, ASpecD has a DOI provided by Zenodo, and you may click on the badge below to directly access the record associated with it. Note that this DOI refers to the package as such and always forwards to the most current version.

Where to start

Users new to ASpecD should probably start at the beginning, those familiar with its underlying concepts may jump straight to the section explaining how to write applications based on the ASpecD framework.

If you are interested in how working with the ASpecD framework looks like, particularly recipe-driven data analysis, have a look at the use cases section.

The API documentation is the definite source of information for developers, besides having a look at the source code.


To install the ASpecD framework on your computer (sensibly within a Python virtual environment), open a terminal (activate your virtual environment), and type in the following:

pip install aspecd

Have a look at the more detailed installation instructions as well.

Actual use cases

Python packages based on the ASpecD framework have been used already for analysing published data, and for some, the data and recipes have been published as “data publications”. See the list of data publications for further details.


This program is free software: you can redistribute it and/or modify it under the terms of the BSD License. However, if you use ASpecD for your own research, please cite it appropriately. See How to cite for details.