by Graham McGibbon, Manager of Scientific Solutions & Partnerships (ACD/Labs)
I’m going to date myself here, but I remember way back in the day, when I first started out in this industry, taking scrupulous notes on my experiments in small paper notebooks. Eventually, my notebooks would fill up with troves of data, a few useless scribbles and the occasional epiphany before being retired to the microfiche and most likely never seen again.
A lot has changed since then. While many scientists still capture their data in paper notebooks and share them in conversations around the water cooler, we’re also using electronic lab notebooks, iPads, laptops, and numerous other digital devices. No question these devices have made our lives easier; our data now is often more searchable, more easily accessible, and more organized. Yet along with the proliferation of electronic devices, we’ve also seen an explosion in the number of analytical instruments at our disposal, and consequently, a deluge of data.
There is widespread agreement that going digital will help us manage the data better, make us more productive, more innovative and ultimately enable us to make smarter decisions—all the way from the bench to the boardroom. Yet, we remain relatively early in the transition from paper to paperless lab, despite the need for organizations to become more innovative and more competitive.
To realize the digital dream, it’s important to understand what a successful paperless lab would entail and should achieve. It’s also important to understand what a paperless lab is not. To make better decisions, increase productivity, and become more innovative, we simply can’t replace our paper notebooks with electronic laboratory notebooks (ELN) and call it a day.
While ELNs and laboratory information management systems (LIMS) can play an important role in a paperless lab, they were never intended to store, for example, analytical data in a live, homogenized, and structured fashion. To create the ideal paperless lab, we must address the challenges of context, access, and storage.
Perhaps the most crucial and valuable feature of a successful paperless lab is the ability to provide context around all the data we generate. We must be able to take data acquired from a sample, for instance, and associate it with metadata. In other words, we need to be able to understand aspects such as why the experiment was conducted, what was learned about a sample and whether the information is sufficient to explain the questions being asked.
Without context, and information more elusive. With context, data becomes insights and insights lead to intelligence—and smarter decisions. For example, a successful paperless lab would allow us to combine raw or processed data from various techniques and instruments, such as chromatography and spectroscopy, across laboratories into a single environment ready for analysis. That analytical and chemical data can then be combined with a researcher’s interpretations, offering insight across the development cycle.
However, because scientific data comes in various shapes, sizes, and speeds, this remains a challenge for most informatics systems and thus to organizations wanting to go paperless. In a successful paperless lab, data of ALL types must be storable, accessible, and searchable. If scientists cannot readily access a variety of types of data, the data becomes as dead as, well, the microfiche.
Too often, access challenges lead to the ubiquitous PDF becoming the document of choice. This is particularly true the further you move away from the bench and toward the boardroom as access to software, that actually shows data, becomes more difficult. Unfortunately, data distilled into a PDF is inevitably so reduced that it eliminates full insights critical to avoid or resolve problems, and for making smart decisions. ACD/Labs’ solutions on the Spectrus Platform can provide a mechanism for accessing the wide range of data produced both within and across departments and organizations.
We are also generating more data than ever before. Organizations must make fundamental decisions about how much data they want to store. The ability to move large data files around presents yet another challenge in the deployment of a successful paperless lab. Cloud-based systems and software with a variety of intake capabilities are among the ways to address this challenge. Because most organizations have many different technologies and systems, a vendor-neutral platform is critical. Browsers and web-based systems will become increasingly important as well.
We have made great strides in moving from paper-based systems to electronic systems, and science is better for it. But we must look holistically at the critical challenges of context, access, and storage to make a successful paperless lab more than an aspiration.