Analysis and Implementation of an Electronic Laboratory Notebook in a Biomedical Research Institute

Electronic laboratory notebooks (ELNs) will probably replace paper laboratory notebooks (PLNs) in academic research due to their advantages in data recording, sharing and security. Despite several reports describing technical characteristics of ELNs and their advantages over PLNs, no study has directly tested ELN performance among researchers. In addition, the usage of tablet-based devices or wearable technology as ELN complements has never been explored in the field. To implement an ELN in our biomedical research institute, here we first present a technical comparison of six ELNs using 42 parameters. Based on this, we chose two ELNs, which were tested by 28 scientists for a 3-month period and by 80 students via hands-on practical exercises. Second, we provide two survey-based studies aimed to compare these two ELNs (PerkinElmer Elements and Microsoft OneNote) and to analyze the use of tablet-based devices. We finally explore the advantages of using wearable technology as ELNs tools. Among the ELNs tested, we found that OneNote presents almost all parameters evaluated (39/42) and both surveyed groups preferred OneNote as an ELN solution. In addition, 80% of the surveyed scientists reported that tablet-based devices improved the use of ELNs in different respects. We also describe the advantages of using OneNote application for Apple Watch as an ELN wearable complement. This work defines essential features of ELNs that could be used to improve ELN implementation and software development.This work was supported by the Spanish Ministry of Economy and Competitiveness and the Catalan Government through the Economy and Knowledge Department and the Health Department. This work was also supported by doctoral fellowships from the Spanish Ministry of Economy and Competitiveness and “La Caixa” to MIF and HPN, respectively. SG was supported by a post-doctoral fellowship from “Fundació la Marató de TV3”. GD has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 661051