Good data, quality data, data with integrity; it all translates into trust, the trusting of the scientist to whom the data belongs.
Not only does it facilitate trust, but it can result in any paper you might publish being approved and valid. In 2016, 664 articles were retracted (in the biomedical science field). The reasons behind article retractions vary, but can often be linked to the data integrity, or lack thereof. If a paper is retracted, depending on the cause, it could be damaging to one’s reputation, which in turn can decrease trustworthiness.
Graph of the number of papers retracted per fiscal year [Retraction Watch, 2016]
Nobody wants not to be trusted or have their paper retracted. So let’s take a look at data integrity. The definition is the accuracy and consistency of data being stored somewhere. This can be interpreted in three different ways.
Generally, data with integrity is complete and whole, with no gaps or missing lab-books.
Today, so much of what we do is digital, so why not include our data in that? By digitizing your data recording, you can really help improve its integrity, which is beneficial for all.
When using a paper lab notebook, there are many scenarios in which your data integrity might be compromised. Most of these can be prevented or at least limited by digitizing the process from start to finish. Of course, there is always a component of human error present, but hey, scientists are humans, too!
By digitizing your data you can also benefit from the many features of a digital lab notebook. For example, in labfolder, we offer a number of data assessment methods and apps to boost the integrity of your data.
The main managing apps are Mendeley, Figshare and Dropbox, which aid in keeping track of references, storing and importing data and sharing your files, respectively.
Another app that is crucial for your data is Sign And Witness. This app enables the digital signing of your data and its witnessing by a colleague. Once data has been signed, it is locked against editing, improving the integrity. This is known as an active method of ensuring data integrity.
A passive form of ensuring data integrity is the time stamps present at the top of each entry. It tracks when the entry was created and when it was last modified. A full audit trail is then created, where each change to the entry is recorded and has the time and date of alteration, so you’ll never lose track of the steps taken along the data recording.
Research Data Management (RDM) is an overarching process that guides researchers through the many stages of the data lifecycle. In doing so, it enables scientists and stakeholders alike to make the most out of generated research data. Electronic lab notebooks simplify the creation of effective RDM plans and enable researchers to easily put them into action for a better, reproducible, transparent and open science.
To read more about RDM strategies and the role ELNs play, check out our guide on effective Research Data Management.
All of the above features are just a sample of what a digital lab notebook can do to help your data integrity. Remember, data = trust. So don’t wait around, digitize your lab notebook today!
sharing is caring-why data sharing is beneficial for Science