ASpecD – Analysis of Spectroscopic Data
ASpecD is 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 its documentation.
License and citation
ASpecD is free and open source licensed under a BSD 2-clause license. 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 (2024). doi:10.5281/zenodo.4717937
- 2024-01-15: ASpecD v0.9.1 released
- 2024-01-13: ASpecD v0.9.0 released
- 2023-09-08: ASpecD v0.8.3 released
- 2023-08-24: ASpecD v0.8.2 released
- 2023-08-11: ASpecD v0.8.1 released
- 2023-03-26: ASpecD v0.8.0 released
About the Author/Developer: The author of ASpecD is a scientist in the field of physical chemistry and spectroscopy. He has more than fifteen years of practical experience with everyday laboratory work and a penchant for the traceability of data acquisition and processing. In addition, he has developed two relatively extensive and proven evaluation programs for spectroscopic data that form the basis for developing the ASpecD framework. Further information can be found on his homepage.
A note on the logo: The snake (obviously a python, look at how it’s holding the magnifying glass) is well familiar with the scientific method and illustrates the basic idea of the ASpecD framework: reproducible data analysis. The copyright of the logo belongs to J. Popp.