Map the record from worklist to reported result
A common flow begins with a worklist or sample set, produces a plate and reader file, runs a versioned analysis, records the review decision, and returns structured results with a report identifier. Name the system that is the official source at every stage.
Do not use file names as the only identifier. Assign stable identifiers to the run, plate, sample, method, analysis, result, and report, and carry the original identifiers through every transfer.
Keep the scientific result separate from review status
A structured result can include the analyte or endpoint, value, unit, model, parameters, uncertainty where applicable, criteria outcomes, exclusions, fingerprints for the source data file and analysis configuration, and software version. Review or release status is a separate human or workflow decision.
Give the data format a version. A receiving system should flag unsupported versions instead of silently ignoring new fields. Record time zones and use an agreed list of statuses.
Plan for transfers that fail partway through
After a network timeout, the sender may not know whether the receiving system saved the result. Use a unique request identifier, a reliable queue, delivery confirmation, limited retries, a place for failed deliveries, monitoring, and reconciliation so a retry cannot create a duplicate result.
Store the exact result sent and the confirmation received. Reconciliation should identify missing, duplicate, mismatched, and superseded records without relying on manual memory.
Secure and test the connection
Use authenticated service identities, only the permissions required, encrypted transport, protected credentials, logging, and controlled endpoints. Define which data is sent and how long it is retained.
Test normal and failure paths with representative data: invalid identifiers, duplicate messages, data-format or unit mismatches, timeouts, partial outages, repeated delivery, corrected results, and unavailable reports. Control changes to the connection and data format.
Prove the data contract with a documented CSV or JSON export
A structured export with stable identifiers, source references, settings versions, results, and exclusions lets the analysis and LIMS teams agree on field meaning before delivery is automated.
Then test secure transport, duplicate prevention, retries, acknowledgements, monitoring, reconciliation, corrections, and change handling in the systems and operating environment where the connection will run.
Frequently asked questions
Should the LIMS receive every fitted parameter?
Send the fields required for downstream use and retain a link to the complete analysis. Avoid placing an undocumented block of JSON inside a single result field.
Why use a job queue for analysis or delivery?
A reliable queue can preserve work through temporary failures and long-running analyses. It still needs unique request identifiers, visible status, monitoring, and checks for missing or duplicate results.
Can CSV be validated?
Yes, but define the encoding, delimiter, fields, identifiers, units, format version, error handling, and transfer controls. JSON or an API is not automatically safer without equally clear rules.