Data governance provides you with a method for the proper care and feeding of data and information.
When applied correctly, it provides the appropriate checks and balances to ensure those who need access to the data can do so.
The policies deny connection to the data by those people, internal or external, friend or foe, who do not need to know anything related to the data.
What kinds of policies do we mean? Any kind of policy, actually.
The policies might prevent access to research data by staff and outside persons who do not need to see it, much less alter it.
Rules might protect privacy, as with the upcoming General Data Protection Regulations (GDPR). Or, the enforced policies might preserve cultural heritage and research data into the indefinite future.
When research data is protected and stored properly, it allows future scientists to study past research to note changes in the environment, climate, or simply in peoples’ attitudes and actions.
When data is preserved, it provides a window into the past. More importantly, it means that research is repeatable, which is one of the basic criteria for any applied research method.
The drawbacks to data governance are that when it is applied improperly, it becomes a bottleneck that impedes work or research.
People then work around it, and the policies become paper rules and regulations, that are not enforced within a culture or within machine code.
While this may aid in pushing day-to-day work forward, over the long term, it leaves companies and organizations open to litigation and/or expensive fines.
With regards to cultural heritage or research data, once the data is lost, damaged, or altered in some way, most cannot be recovered.
What is the Best Method for the Proper Care and Feeding of Data and Information?
The best course of action with any data governance policy is to balance the needs of employees and researchers to get their work done, against rules and regulations.
Large fines for GDPR violations could wipe out any gains by employees “cheating” to bypass data restrictions. The loss of research and cultural heritage data has no price.
When applying data governance to your enterprise, research project, or organization, the best course of action is to be brutally pragmatic.
Figure out which polices you must enforce, which ones you should enforce, and which ones would be nice to enforce. Then proceed to set up your systems and processes accordingly.
If you would like to work with us on a data governance project, please see our services page.