Top Tips for Going Paperless in the Lab

A key benefit is the positive environmental impact (although this is potentially offset by the increase in digital devices that require power to enable this reduction of paper). The nature of capturing data digitally also paves the way for benefits such as data sharing between colleagues and managers, better retention of data and the potential for easier backup.

However, just because something is “digital” or “paperless”, there is no magical guarantee of quality or improvement. The tools that enable paperless labs can facilitate that, but we need people with the right expertise to help with this, and the tools need to be implemented correctly.

It’s important to distinguish between paperless labs and labs that facilitate better data capture to produce FAIR (Findable, Accessible, Interoperable, Reusable) data, because they are not necessarily the same.

Concerning producing FAIR data, it’s not enough to just buy a set of electronic lab notebook (ELN) licenses. Many people labor under the assumption that much scientific research isn’t reproducible because the important details are locked away in paper lab notebooks, but that’s often not the case. The information scientists require is usually locked away in the original researcher’s head or potentially forgotten with time. We must train our scientists to capture more comprehensive notes with valuable contextual information.

If this [digitization] is done successfully, there are endless potential benefits for labs. But, if done poorly, this is nothing better than the digital equivalent of covering a gaping wound with a small sticky plaster. 

In the short term, yes. Initial outlay costs for hardware and potential improvements to the lab setup may be required. In addition to the obvious software licenses, you will also be paying out staff costs to get things up and running, and will need to use your scientists' time to get them trained on how to use the new tools. There may be additional costs if legacy systems are incompatible with new systems. Further, once these labs are established, you could have higher running costs, e.g., the power to run all these devices, compared to using paper in the lab.

However, the benefits of digitization could save money in other areas if done properly. For example, if good processes are implemented and scientists are accurately capturing scientific data such that others can re-use their work, then you are saving money for each experiment that doesn’t need to be repeated.

I would also advise some general power-saving techniques. The advantage of using cloud-based systems is that they can be accessed from anywhere with any device if there is an internet connection. So, there is no need to keep lab computers constantly powered on. Sensible placement of equipment is also key. While having dedicated lab hardware means not worrying about contamination, you also don’t want to be upending destructive chemicals onto your hardware, as they will need to be replaced, which will cost more money. 

I have seen a significant upsurge in research and development around voice technologies in the lab over the last six years. I remember attending the Lab Innovations Expo before the COVID-19 pandemic and asking many of the ELN and Laboratory Information Management Systems companies if they were investigating the use of voice in their technologies. At that time, it was almost a resounding no.

Fast forward, and several companies are now working on voice in the lab. This could enable a smoother, quicker form of data entry and allow scientists to interact with software when they can’t use their hands.

There is also a push to develop ELN standards and mechanisms to port data between different ELNs. On the academic/open-source side, there is the ELN Consortium, which has worked to develop the ELN File Format. More centered around the large-scale ELNs are the Allotrope Foundation, which is looking at providing a universal file format for scientific data.

Another key emerging technology I have seen is Large Language Models (LLMs), with ELN companies creating LLM assistants to facilitate intelligent and human-friendly searching as opposed to needing to understand complex database queries or application programming interface (API) commands. The combination of this technology with voice commands could prove very powerful.  I have seen it used more to search and query rather than capture, and arguably you would probably be more likely to be near your computer to type things in if you were looking for something versus dictating something during an experiment, but it would make a lot of sense to combine these capabilities.   

It is possible, although it depends on what you define as 100% paperless. All data being captured electronically – absolutely! The entire eradication of paper from the lab – also possible, but potentially somewhat trickier depending on your setup.

Switching over to an ELN requires dedicated hardware that ensures that each researcher has access to a device to capture data and notes.

Additionally, it’s not just enough to have those devices; the lab environment needs to be appropriately set up for them. You need to have good WIFI (assuming the ELN is cloud-based, which many are) or enough Ethernet ports and cables to hardwire the internet connections into devices. There needs to be sufficient power sockets to ensure that desktops can be plugged in, or to have suitable stations for charging. There also needs to be suitable locations to put said hardware. Devices need to either be portable or well-placed for the experimental work that is likely to be undertaken.

Ideally, all notes would be captured in the ELN, but this is a lengthy process for people to adapt to, and it’s always very tempting to scrawl something down quickly if you are trying to remember it. Having a dedicated notes space within your ELN can help to mitigate this. Ultimately, these transitions take time and are complex. I would recommend considering all the things I have mentioned here, and consulting with your scientists to understand their current working practices, what their hardware preferences are and if you have the time/financial capabilities to make these transitions.