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Analytical Chemistry

Introduction​

Providing the tools and techniques needed to identify and quantify the chemical constituents of a sample, analytical chemistry is a cornerstone of both academia and industry. It is essential for a wide range of applications, from environmental monitoring to drug discovery.

Despite the diversity of analytical methods, a common denominator is the large amount of data generated by instrumental methods. This data must be processed and interpreted to extract meaningful information. This makes analytical chemistry a challenging field for research data management.

Data Types​

Unlike some other areas of chemistry, most research data in analytical chemistry are generated by instrumental methods. In addition, the size and complexity of the data can vary greatly depending on the method used.

Techniques like mass spectrometry, chromatography, and spectroscopy generate complex data consisting of raw data files, metadata, and processed data. Raw data files are often proprietary and require specialised software to open and interpret. Metadata is crucial for understanding experimental conditions and parameters. Processed data can range from simple peak lists to complex multivariate models.

Some open data formats are available for specific data types, such as mass spectrometry data in the mzML format. The JCAMP-DX format is used for optical spectroscopy data. This format is also suitable for NMR spectroscopy data, but with some major limitations. For chromatography or combined chromatography-mass spectrometry data, the situation is more complex, as many vendors have their own proprietary formats.

ELNs and Other Tools​

For effective data management, tools should be selected at project or group level based on workflows. Because workflows are often method-specific, usage guidelines and metadata templates should be defined and documented in a data management plan (DMP). NFDI4Chem provides an RDMO template tailored to chemistry.

General chemistry ELNs can typically be used for analytical chemistry data and may be well suited to your research topic. However, there are also specialised tools tailored to the needs of analytical chemists. These tools often include features for managing instrument data, processing raw data files, and visualising results. They may also include tools for chemometric analysis.

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Publishing Data​

Data from analytical chemistry can be published on several platforms, depending on the research subject and data type.

If the analytical data have a supporting role in a larger study, it may be appropriate to publish them in a general data repository. If the research focuses on the analytical method itself, a specialised repository may be more appropriate.

General data repositories include RADAR4Chem or Zenodo. For analytical data in context with synthetic chemistry data, Chemotion Repository might also be a suitable option.

For method-specific data, several specialised repositories are available. A few examples include:

  • MassBank EU
    A field-specific ecosystem of databases and tools for mass spectrometry reference spectra.
  • MetaboLights
    A repository for metabolomic studies.
  • nmrXiv
    A repository for NMR data.

This list is not exhaustive, and there may be other repositories that are more suitable for your data.

Challenges​

The biggest challenge in managing analytical chemistry data is the diversity of the field. Different methods generate different types of data, and the data can vary greatly in size and complexity. As mentioned above, the large number of different vendors and proprietary data formats is a major barrier to data sharing and reuse.