Cleaning it up and keeping it clean

Tips for ensuring clean data entry and maintaining data standards

Once you’ve wielded your enviable persuasive powers to charm colleagues into joining your data clean-up odyssey, assess the current data entry environment. What tools do you have available to support the clean-up effort? As everyone on your team works towards improving existing data, consider any options that reduce the risk of creating more messy data.


Consider suppressing the display of any unused fields. These metadata elements can always be reactivated later as required. Fewer onscreen fields translate to less opportunity to create dirty data. Other options for establishing consistent data entry include requiring use of pick lists, setting case-restrictions, and limiting access to specific fields to certain groups of users.


Each Axiell system features field definitions and data entry examples. These may be adjusted by your System Administrator to reflect the styles and practices in use at your organisation. Our default examples and documentation undergo periodic review and we try to make them as informative as possible; however, if you are not sure about the intent of a field, the Axiell Help Desk team is always available to provide advice. Our Axiell business analysis experts are also on hand to provide data clean-up consulting and to collaborate with you to design custom training classes to optimise clean data entry.


Sites with multi-disciplinary collections often have shared fields which require very different terminology depending on what is being catalogued. To assist with managing vocabulary in these scenarios, many of the systems have the ability to configure pick lists to dynamically display terms based on a value entered in related field. For example, System Administrators might decide that Category and Object Name are related. When a user enters a record with a category of VISUAL WORKS, the object name list might include painting, drawing, etching; while a category of DECORATIVE ARTS may have object names of sofa, chair, vase, etc.


Implementing accepted standardised vocabularies serves as an authority for negotiating terminology use among departments. Below are some links to common online resources. We keep a running list of helpful references at Axiell and will update the list below with additional links as accepted best practices evolve:

Links to online external resources may be configured in all of the systems. Enabling access from the applications depends on which system you are using, so please reach out to the Help Desk for additional information.


Maintaining a clean database requires vigilance. To assess the current state of your database, consider running vocabulary lists on key fields on a quarterly basis, auditing a percentage of records at regular intervals, and nominating records for peer review. Putting quality assurance measures in place helps Database Administrators spot any negative trends and reach out to staff for early intervention.


Each of the Axiell systems includes tools that staff can use for data scrubbing. These include Excel uploads, global search and replace functions, vocabulary reports, and online data entry forms such as Sapphire.


Once you’ve got your project up and running, here are some tips to maintaining the momentum in the long term.

Based on feedback to the Dirty Data session of the 2016 Axiell European User Group meeting, we were inspired to design a new Data Bootcamp. Our inaugural session is open to any Axiell system user and will be hosted in our Ottawa office on 7-8 December 2016. We will be reviewing data clean-up tools and strategies and providing moral support for the data lovers amongst us. For pricing and enrolment information or to enquire about scheduling a boot camp in your region, please reach out to us at

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