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Cyclic voltammetry (CV) data becomes FAIR only when the whole chain is managed: acquisition from a potentiostat, transfer out of the instrument computer, connection to the correct sample and experiment, conversion to an interpretable format, complete metadata, digital analysis, and publication in a repository. A 2025 Chemical Science article works through that chain with open-source components, showing how laboratories can make electroanalytical data more findable, accessible, interoperable and reusable without claiming a universal standard or endorsing a particular instrument.
The worked example is valuable because CV files and their context differ between vendors, software packages, electrodes and experimental designs. The workflow can harmonize those inputs, but efficient reuse still depends on agreed measurement procedures, analysis conventions and documentation. The source article was published on 5 February 2025 in Chemical Science; a Chemistry World report followed on 30 April 2025.
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What FAIR means for a cyclic voltammetry experiment
FAIR is a lifecycle, not a file format. Data should be Findable through descriptive metadata and persistent records; Accessible through a defined retrieval path and usable permissions; Interoperable with documented, machine-readable structures; and Reusable because another researcher can understand the measurement, processing and provenance.
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Saving a voltage-current trace on an instrument PC meets none of those goals by itself. A reusable CV record needs the trace, the relationship between repeated scans and the parent experiment, the sample and electrode context, acquisition settings, processing history, and a publication route that preserves both data and metadata. The demonstrated workflow therefore treats every hand-off as part of experimental practice rather than as an archiving task at the end.
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The seven-stage workflow at a glance
| Stage | What happens | Output to protect |
|---|---|---|
| 1. Digital acquisition | The potentiostat software writes raw measurements and associated files. | Original files plus the instrument and software context. |
| 2. Transfer | A routine moves files from the instrument computer to remote storage and then into the documentation system. | An intact copy with transfer provenance. |
| 3. Experiment association | Files are connected to the correct sample, experiment, operator and protocol in an ELN or equivalent environment. | Traceable relationships between data and laboratory context. |
| 4. Format conversion | Vendor or non-standard files are converted into a readable standardized representation such as JCAMP-DX. | A documented, machine-readable data file and a retained original. |
| 5. Metadata completion | Existing fields are extracted, mapped and supplemented with missing experimental details. | Metadata sufficient for interpretation and discovery. |
| 6. Digital analysis | Researchers view, edit and analyze the converted data while preserving provenance. | Results, parameters and processing history linked to the source. |
| 7. Publication | Data and metadata are deposited in a suitable repository for access and reuse. | A citable record with the right files, description and permissions. |
Skipping a stage creates a specific failure: a lost original, an orphaned curve, an unreadable format, an unexplained processing decision or a repository record that cannot be reused.
1. Acquire CV data without losing the source record
A potentiostat is the relevant instrument category for CV. The workflow is intentionally not a hardware comparison: the article names examples from Gamry, Metrohm and PalmSens, but reports no model testing, performance ranking or purchasing recommendation. Treat the instrument as the first data-producing system whose file behavior must be documented.
Record how the instrument writes files
Before automating transfer, establish where the instrument software saves data, which extensions and file groupings it creates, and whether files appear continuously during a run or only when an experiment finishes. CV may contain repeated scans belonging to one experiment, so a folder of similarly named files is not self-explanatory. Preserve the original directory structure or capture an equivalent manifest before conversion.
Keep acquisition context with the raw files
At minimum, retain the instrument identity, software identity, acquisition date and time, operator, sample identifier, electrode information, scan parameters and any run or method identifier supplied by the software. These values may be distributed across files or absent from the export, which is why later metadata work cannot be treated as optional.
2. Transfer files from the instrument computer to the digital record
The example uses ShuttleBuilder as the transfer component. A watcher or scheduled routine accesses data produced by the instrument software, moves it from the instrument computer to remote storage, and then places it in the electronic laboratory notebook (ELN). The same design can be implemented with other transfer services; the important requirement is a verifiable, repeatable hand-off rather than a manual copy that nobody can audit.
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Design the transfer around instrument behavior
- Identify the source location. Document the exact folder, naming pattern and file extensions used by the acquisition software.
- Choose a completion signal. If files are written only at experiment completion, trigger on the completed file. If the software writes continuously, transfer a closed copy or use a completion marker so an in-progress file is never mistaken for a finished measurement.
- Preserve grouping. Keep all files belonging to one CV experiment together, including repeated measurements and auxiliary logs.
- Record transfer provenance. Store source path, transfer time, destination and any checksum or integrity result available in the local infrastructure.
- Handle failures explicitly. Queue files when the network is unavailable, report duplicates, and retain the original until the destination copy has been verified.
This stage is where local IT and data-management requirements matter most. A laboratory with restricted instrument computers, intermittent network access or a separate storage policy may need a different implementation while keeping the same evidentiary goals.
3. Put every curve in its experimental context
An ELN is useful here because it can connect a data object to the experiment and sample that produced it. Attach the transferred files to a record that identifies the sample, preparation, operator, date, protocol and instrument session. If several scans or electrodes belong to one experiment, represent that relationship directly instead of publishing each trace as an unrelated object.
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The current-versus-potential values are only one part of a CV record. Context can include electrode material and geometry, cell configuration, electrolyte, concentration, solvent, temperature, scan-rate and potential limits, conditioning steps, replicate information, and deviations from the planned method. Capture the values that your laboratory needs to interpret the result, and mark unknown or not-recorded fields rather than silently filling them.
Use stable identifiers
Give the experiment, sample and data object identifiers that remain meaningful when a file moves from the ELN to analysis software or a repository. A repository record should be able to point back to the ELN entry, while access controls can limit sensitive laboratory notes without breaking the public data relationship.
4. Convert proprietary exports into an interpretable format
Instrument vendors often produce proprietary or non-standard files. The described stack uses Chemotion converter software to convert formats and match metadata, with JCAMP-DX as the standardized output described in the article. Conversion should never overwrite the source: retain the original export, generate the converted file, and record the converter and mapping choices.
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Validate the conversion
- Compare point counts, axis labels, units and numeric ranges between the source and converted files.
- Confirm that repeated scans remain associated with the same experiment and are not reordered or dropped.
- Check that metadata fields such as sample and method identifiers map to the intended destination fields.
- Open the converted file in an independent viewer and inspect the plotted curve for clipping, missing segments or implausible scaling.
- Record conversion warnings and any field that could not be mapped.
JCAMP-DX improves machine readability, but a standardized container does not prove that a measurement was performed consistently or that every field needed by a future analyst is present.
5. Complete metadata instead of merely exporting it
Metadata harmonization combines extraction from the instrument file with information supplied by the researcher. The conversion step can map known fields, but it cannot infer an omitted electrode, an undocumented sample preparation or the reason a scan was discarded. Use the ELN form or an equivalent schema to require critical fields before publication and to distinguish measured values from user-entered descriptions.
A practical metadata checklist
- Identity: experiment, sample, operator, instrument and software identifiers.
- Acquisition: technique, scan direction, potential window, scan rate, sampling or step settings, number of cycles and timestamps.
- Electrochemical setup: working, reference and counter electrodes; cell arrangement; electrolyte and solvent; concentrations; temperature and atmosphere where relevant.
- Sample history: preparation, dilution, conditioning, cleaning and replicate relationships.
- Quality and provenance: calibration or verification notes, deviations, exclusions, conversion software and analysis operations.
- Access and reuse: license, embargo or access restrictions, and links between raw, converted and derived files.
Not every experiment requires every field, but a deliberate “not applicable” or “not recorded” value is more informative than an empty cell.
6. View, edit and analyze while preserving provenance
The article names the ChemSpectra app and ReactSpectra editor for viewing and editing. In a reproducible analysis, visualization is not the same as publication: preserve the converted input, document baseline corrections, smoothing, peak selection, background subtraction or other operations, and save derived outputs with links to the input and parameters.
Make analysis decisions inspectable
- Load the converted file and verify units and axes before changing the data.
- Record the software and version used for each transformation.
- Save processing parameters and, where possible, an untouched intermediate after each major operation.
- Keep excluded scans and the reason for exclusion rather than deleting them.
- Export figures and tables as derivatives linked to the data object, not as replacements for the underlying values.
The workflow does not prescribe a single CV analysis method. It makes the analysis history discoverable so another researcher can assess whether a result is comparable or needs reprocessing.
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7. Publish data and metadata in a repository
Publication is the final lifecycle stage, not a link pasted into a paper after the fact. The examples use the Chemotion repository, RADAR4Chem and Zenodo. Chemotion and RADAR4Chem are described as integrated with the ELN in the demonstrated workflow; a repository without direct integration can also be used when its submission process preserves the same links and metadata.
Choose a repository by workflow fit
| Need | Selection question |
|---|---|
| ELN integration | Can the repository receive records or identifiers from your ELN without manual re-entry? |
| Data representation | Will it accept raw vendor files, JCAMP-DX, derived data and the metadata fields your study requires? |
| Access control | Does it support the public, embargoed or restricted access appropriate to the project? |
| Persistent citation | Does the deposited object receive a durable identifier and a clear version history? |
| Community fit | Can likely reusers find the record through discipline or institutional discovery services? |
No repository is universally best. Select one that can carry the raw and standardized representations, explain the experiment, and expose the relationships among source, converted and derived files.
Prepare the submission
- Include the original instrument export and the standardized file when licensing and policy permit.
- Attach a human-readable description of the experiment and a machine-readable metadata record.
- State software, versions, conversion mappings and analysis provenance.
- Define the reuse license and any embargo or access condition.
- Verify that identifiers resolve and that a user without ELN access can still understand the public record.
What this example proves—and what it does not
The authors show that one open-source stack can harmonize CV data generated by devices from different vendors in the reported setup. That is evidence of an adaptable implementation, not a community-wide standard. Local instrument configuration, infrastructure, security policy and data-management obligations will change the details.
Standardization remains an open prerequisite. Nicole Jung told Chemistry World that “some key prerequisites for the efficient use of Fair data are still missing – most importantly, the standardisation of measurement procedures, data analysis and documentation.” Her related explanation was that “By utilising this infrastructure, researchers no longer need to invest effort in generating Fair data, as the harmonisation functionality is already integrated into the software.” Those statements describe reduced friction inside a configured system, not automatic FAIR status for every dataset.
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Leah McEwan, a Cornell University chemistry librarian and advisor to the work, said the open-source materials let other institutions explore adaptations to their local infrastructure and data-management requirements. Tanja Junkers of Monash University separately called for a “rethinking of the workflows we use today, and creation of generally accepted data standards.” Together, these comments identify the practical boundary: software can support harmonization, while communities still need shared methods and documentation conventions.
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Common failure modes and recovery actions
The transfer captured an incomplete file
Check whether the instrument writes continuously. Change the trigger to a completion marker, closed-file event or delayed queue, then re-transfer the verified source while retaining the failed copy and its error record.
Several scans lost their experiment relationship
Reconstruct grouping from the instrument run identifier, timestamps and original folder structure. Attach the scans to one parent experiment and document any uncertainty instead of publishing them as independent measurements.
Conversion dropped fields or changed units
Compare source and converted headers and numeric ranges, inspect the curve in a second viewer, and correct the mapping or annotate the missing field. Keep both versions and record the converter configuration.
A repository record is technically public but not reusable
Add the missing sample, electrode, method and processing metadata; include a readable description and persistent links among raw, standardized and derived files. If a field cannot be recovered, mark it explicitly as unavailable.
The local infrastructure cannot use the named components
Preserve the seven functional stages with different software. The names in the article are implementation references from its 2025 configuration, not requirements for every laboratory or current-release guidance.
How to adapt the pattern beyond CV
Other measurement types can follow the same lifecycle: capture source data, transfer it with provenance, associate it with an experiment, convert it to a documented representation, complete metadata, analyze reproducibly and publish both data and context. Adaptation still requires a technique-specific schema, validation against the instrument’s output, and agreement on what a future user must know. A workflow that works for CV should therefore be treated as a design pattern to test locally, not as evidence that every technique can be converted without additional method development.
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