Setting Yourself Up for Success: 3 Best Practices for Using Standard Nomenclature

A standard nomenclature is incredibly valuable for teams using LabKey Server SDMS to do collaborative biomedical research and becomes increasingly more important as they grow in size and data volume. Defining how data fields should be named is essential to the efficiency of teams, as it aids both those generating and/or capturing data as well as those conducting data analysis.

As you get started using LabKey Server SDMS, keep in mind the best practices below for defining and maintaining a standard nomenclature in your lab:

Define Nomenclature Up Front

Standardizing nomenclature may seem like an unnecessary up-front investment, but ultimately your team will experience less confusion and more efficiency as they progress with their work. Empower your team by allowing them to have a voice as you define which terms will be used in your research. By including team members in the process, they will feel more invested and be more likely to adhere to standard naming conventions.

Use LabKey QC Features to Ensure Consistency

In an ideal world, all team members will consistently use the nomenclature agreed upon by the team when adding data to your Server SDMS. But in practical application, it is more likely that from time to time a team member will mistakenly enter “H20” instead of the lab standard name “Water” into their ingredient list, potentially breaking standard reports, grid views, etc.

Using LabKey quality control features like lookups, aliases, and validators in key fields can help combat this scenario. A LabKey lookup will allow you to to map several common variations of a term to a desired standard field value. For example, an administrator could configure a lookup so that “H20” and “Tap Water,” common deviations from the standard, would both map to “Water.” These types of lookups allow teams to maintain the integrity of their data, in spite of inevitable human error.

Administrators can also use to regex or range validators on new data being entered to ensure that users are entering valid data into the system. By placing these restrictions, teams can improve data entry and help analyses down the pipeline.

Evaluate and Adjust

It’s easy to enforce the use of standard nomenclature when your team is small and your research is in its early stages. But over time, as teams grow and become further removed from when nomenclature guidelines were established, they can develop a “laboratory shift” in how things are named. In order to stay on top of your terminology and keep your data clean, plan to regularly review and assess your standard nomenclature. Are there additional terms that need to be defined? Have any standard terms become outdated? Are certain terms consistently being used incorrectly? Making small adjustments as your research needs evolve will help maintain the integrity of your data.

LabKey helps enforce nomenclature standards, leading to cleaner data and more efficient research. Sign-up for a demo to see these and other core Server SDMS features in action. 

 

Related Documentation

• Lookup Columns 
• Field Level Validation
• Data Quality Control