Package: aspecd
ASpecD is aframework for handling spectroscopic datafocussing onreproducibility. In short: Each and every processing step applied to your data will be recorded and can be traced back, and 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 analysisno 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? Here is an example:format:
  type: ASpecD recipe
  version: '0.2'

datasets:
  - /path/to/first/dataset
  - /path/to/second/dataset

tasks:
  - kind: processing
    type: BaselineCorrection
    properties:
      parameters:
        kind: polynomial
        order: 0
  - kind: singleplot
    type: SinglePlotter1D
    properties:
      filename:
        - first-dataset.pdf
        - second-dataset.pdfFor more general information on the ASpecD framework see itshomepage, and for how to use it, itsdocumentation.FeaturesA list of features:Framework for writing applications handling spectroscopic dataConsistent handling of numeric data and corresponding metadataHistory of each processing step, automatically generated, aiming at full reproducibilityUndo and redo of processing stepsImport and export of dataGeneric plotting capabilities, easily extendableReport generation using pre-defined templatesRecipe-driven data analysis, allowing tasks to be performed fully unattended in the background and without programming skillsAnd to make it even more convenient for users and future-proof:Open source project written in Python (>= 3.7)Developed fully test-drivenExtensive user and API documentationTarget audienceThe ASpecD framework addresses every scientist working with data (both, measured and calculated) on a daily base and concerned withreproducibility. The ASpecD framework ensures reproducibility and—as much as possible—replicability of data processing, starting from recording data and ending with their final (graphical) representation, e.g., in a peer-reviewed publication. This is achieved by automatically creating a gap-less record of each operation performed on your data. If you do care about reproducibility and are looking for a system that helps you to achieve this goal, ASpecD may well be interesting for you.How to citeASpecD 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–Methods2:e202100097, 2022.doi:10.1002/cmtd.202100097Till Biskup. ASpecD (2022).doi:10.5281/zenodo.4717937To make things easier, ASpecD has aDOIprovided byZenodo, 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.Related projectsThere is a number of related packages that are based on the ASpecD framework and each focus on one particular type of spectroscopy. The most mature packages available to date are:treprPackage for processing and analysing time-resolved electron paramagnetic resonance (TREPR) data, developed by J. Popp, currently developed and maintained by M. Schröder and T. Biskup.cweprPackage for processing and analysing continuous-wave electron paramagnetic resonance (cw-EPR) data, originally developed by P. Kirchner, currently developed and maintained by M. Schröder and T. Biskup.FitPyFramework for the advanced fitting of models to spectroscopic data focussing on reproducibility, developed by T. Biskup.You may as well be interested in theLabInform projectfocussing on the necessary more global infrastructure in a laboratory/scientific workgroup interested in morereproducible research. In short, LabInform is “The Open-Source Laboratory Information System”.Finally, don’t forget to check out the website onreproducible researchcovering in more general terms aspects of reproducible research and good scientific practice.LicenseThis program is free software: you can redistribute it and/or modify it under the terms of theBSD License.