Brought to you by the JPI Oceans project MicroplastiX
Authors:
- Robin Lenz¹
- Franziska Fischer¹
- Melinda Arnold¹
- Verónica Fernández-González²
- Carmen María Moscoso Pérez²
- José Manuel Andrade-Garda²
- Soledad Muniategui-Lorenzo²
- Dieter Fischer¹
Affiliations:
- ¹Leibniz Institut für Polymerforschung Dresden, Hohe Straße 6, 01069 Dresden, Germany
- ²University of A Coruña, Campus da Zapateira s/n, 15071, A Coruña, Spain
Citation:
To cite the most recent release of the MPX_specDB code and data please refer to:
Lenz R, Fischer F, Arnold M, Fernández-González V, Moscoso-Pérez CM, Andrade-Garda JM, Muniategui-Lorenzo S, Fischer D, Database of Raman and ATR-FTIR spectra of weathered and biofouled polymers, 2023, https://doi.org/10.5281/zenodo.8314801.
The raw spectra collection can be found on the chemical research data repository Radar4Chem and is citeable as:
Lenz R, Fischer F, Arnold M, Fernández-González V, Moscoso-Pérez CM, Andrade-Garda JM, Muniategui-Lorenzo S, Fischer D, MicroPlastiX SpecDB, https://doi.org/10.22000/1820.
This dataset is a spectroscopic library strucutred as a document database. It contains Raman and ATR-FTIR spectra of weathered and biofouled polymers which can be viewed via an interactive app.
Project MicroPlastiX's Task 4.1 (formerly Task 3.4) examines the biofouling and colonization dynamics of plastic fragments.
In in situ experiments, plastic sheets of 10 different polymers were deployed in the marine environment across five geographical locations. Their immersion in stainless steel cages for different intervals, over four seasons, imitates real-world exposure.
A live version of the app can be found here: https://robna.github.io/MPX_specDB/.
Individual spectra can be be found in the spectra folder, while all available information on the samples is stored in the metadata,json file.
The spectra file names follow the pattern [Region]_[Polymer]_[Biofilm]_[Analysis]_[hash].csv where hash holds the first 8 characters of the sha256 hash of the spectrum data, in order to create unique file names.
You can download or clone the repository to your local machine and use the metadata.json file to search for spectra of interest (for convenice, excel users can also take a look at the metadata.xlsx file, which contains the same information).
You can use the Pipfile to set up a virtual python environment using pipenv or, alternatively the requirements.txt with a virtual env and package manager of your choice.
When using pipenv, open a terminal in the project directory and run pipenv install to install all dependencies.
Then run pipenv run streamlit run app.py to start the app.
Software code in this repository is licensed as specified in the LICENSE file. Spectroscopic data and meta data is licensed under CC BY SA 4.0.