EDUCATION A quick guide for using Microsoft OneNote as an electronic laboratory notebook Santiago Guerrero ID1☯*, Andrés López-Cortés1,2☯, Jennyfer M. Garcı́a-Cárdenas ID1☯, Pablo Saa ID3, Alberto Indacochea ID4,5, Isaac Armendáriz-Castillo ID1, Ana Karina Zambrano ID1, Verónica Yumiceba ID1, Andy Pérez-Villa ID1, Patricia Guevara- Ramı́rez ID1, Oswaldo Moscoso-Zea ID3, Joel Paredes ID1,3, Paola E. Leone ID1, César Paz-y- Miño ID1* 1 Centro de Investigación Genética y Genómica, Facultad de Ciencias de la Salud Eugenio Espejo, Universidad UTE, Quito, Ecuador, 2 RNASA-IMEDIR, Computer Sciences Faculty, University of Coruna, Coruna, Spain, 3 Faculty of Engineering Sciences, Universidad UTE, Quito, Ecuador, 4 Gene Regulation, Stem Cells and Cancer Programme, Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain, 5 Oncology and Molecular Pathology Research Group-VHIR- Vall d’ Hebron Institut de Recerca-Vall d’ Hebron Hospital, Barcelona, Spain ☯ These authors contributed equally to this work. * sxguerrero@gmail.com (SG); cesar.pazymino@ute.edu.ec (CPyM) a1111111111 Abstract a1111111111 Scientific data recording and reporting systems are of a great interest for endorsing repro- a1111111111 ducibility and transparency practices among the scientific community. Current research gen- a1111111111 a1111111111 erates large datasets that can no longer be documented using paper lab notebooks (PLNs). In this regard, electronic laboratory notebooks (ELNs) could be a promising solution to replace PLNs and promote scientific reproducibility and transparency. We previously ana- lyzed five ELNs and performed two survey-based studies to implement an ELN in a biomedi- cal research institute. Among the ELNs tested, we found that Microsoft OneNote presents OPEN ACCESS numerous features related to ELN best functionalities. In addition, both surveyed groups Citation: Guerrero S, López-Cortés A, Garcı́a- Cárdenas JM, Saa P, Indacochea A, Armendáriz- preferred OneNote over a scientifically designed ELN (PerkinElmer Elements). However, Castillo I, et al. (2019) A quick guide for using OneNote remains a general note-taking application and has not been designed for scientific Microsoft OneNote as an electronic laboratory purposes. We therefore provide a quick guide to adapt OneNote to an ELN workflow that notebook. PLoS Comput Biol 15(5): e1006918. can also be adjusted to other nonscientific ELNs. https://doi.org/10.1371/journal.pcbi.1006918 Editor: Francis Ouellette, University of Toronto, CANADA Published: May 9, 2019 This is a PLOS Computational Biology Education paper. Copyright: © 2019 Guerrero et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original Introduction author and source are credited. Scientific data recording and reporting systems are of great interest for endorsing reproduc- Funding: The authors received no specific funding ibility and transparency practices among the scientific community [1–3]. Current experimen- for this article. tal [4–6] and bioinformatic research [7] generates large datasets or high-resolution images [8] Competing interests: The authors have declared that can no longer be documented using paper lab notebooks (PLNs). In this regard, electronic that no competing interests exist. laboratory notebooks (ELNs), which are gradually replacing PLNs in academic and PLOS Computational Biology | https://doi.org/10.1371/journal.pcbi.1006918 May 9, 2019 1/9 pharmaceutical research [9–12], could be a promising solution to achieve good documentation practices and promote scientific reproducibility and transparency. ELN development has increased notably during the last few years, from commercial solu- tions to open-source software. Kanza and colleagues [3] identified 72 active ELNs specialized either in specific disciplines or in all-purpose solutions. Compared with PLNs, ELNs could improve data acquisition, archiving, accessibility, sharing, and even data presentation during personal and lab meetings [3,12]. We previously analyzed five ELNs using 42 parameters related to ELN best functionalities [12]. Among the ELNs tested, we found that Microsoft OneNote presents almost all parame- ters evaluated (39/42). We also performed two survey-based studies among 28 scientists and 80 students to evaluate OneNote performance compared with a scientifically designed ELN (PerkinElmer Elements) [12]. Although OneNote is not an ELN per se, both surveyed groups preferred OneNote as an ELN [12]. Indeed, OneNote remains a general note-taking applica- tion and has not been designed for scientific purposes. We therefore provide a quick guide to adapt OneNote to an ELN workflow that can also be adjusted to other nonscientific ELNs. Structure and labeling OneNote provides a hierarchical structure that can be adapted to an ELN workflow. Based on this organization, a notebook can encompass unlimited projects (Section Groups in OneNote). A project can contain unlimited sections (e.g., protocols); meanwhile, experiments can be arranged using at least three hierarchical layers: sections, pages, and subpages (Fig 1). An experiment or any other analysis should be structured using five essential parts: (1) an intro- duction to the experiment describing, for example, a hypothesis to be tested; (2) a detailed description of the objective(s) of the experiment; (3) a materials and methods section provid- ing all materials or reagents along with their references or lot numbers (specific methods or protocols could be hyperlinked to this part [Insert a link feature or Crtl+K in OneNote]); (4) a results part presenting all main outputs of the experimental approach; and (5) conclusions dis- cussing the main findings and recommendations for further research. To facilitate ELN usage, OneNote allows users to create templates that can contain the aforementioned five elements or specific protocols (e.g., PCRs). Customizable tags can also be used to prioritize or organize experiments or any other entry. For instance, a customizable tag can be applied to easily find and recognize key experiments or protocols important for constructing a manuscript. Nowadays, scientific laboratories accumulate a large amount of data that is of varying qual- ity and usefulness. OneNote’s searching functionality allows users to quickly retrieve impor- tant information through this vast amount of data. Thus, experiments, protocols, or any other entry should be labeled with essential information traceable over time. For example, an experi- ment can be named EX_0001_SG_29/08/2018. RNA extraction of HeLa cells, in which EX = experiment, 0001 = experiment number, SG = researcher’s initials, 29/08/2018 = entry date, and RNA extraction of HeLa cells = title of the experiment. Moreover, experiments, protocols, or bioinformatic analyses could be labeled accordingly: experiments = EX, protocols = PR, and bioinformatics = BI (Fig 1). To improve labeling, you can also check, “Ten simple rules for experiments’ provenance” by Kazic [13]. Data acquisition All data resulting from research experiments, analyses, and observations must be recorded without exception. Details from in silico analyses, bioinformatic pipelines, scripts, or any other computational-related codes or methodologies could be recorded too [14,15]. As previously discussed within PLOS’s Ten Simple Rules collection, Schnell [16] provided a guideline for PLOS Computational Biology | https://doi.org/10.1371/journal.pcbi.1006918 May 9, 2019 2/9 Fig 1. Adaptation of Microsoft OneNote’s hierarchical structure to an ELN workflow. (A) The structure of OneNote (violet) and its adaptation to a scientific setting is presented. (B) A screenshot of a OneNote ELN hierarchical structure is shown. ELN, electronic lab notebook. https://doi.org/10.1371/journal.pcbi.1006918.g001 PLOS Computational Biology | https://doi.org/10.1371/journal.pcbi.1006918 May 9, 2019 3/9 keeping a laboratory notebook in computational biology that can also be applied to ELNs. Rec- ords must also include unintentional errors, as well as negative, unexpected, or conflicting results. Over the past years, a tendency to promote reproducibility and transparency practices has been established among the scientific community [1]. In that respect, most scientific journals demand that researchers provide the raw data generated from their experiments [1,14]. To consolidate this trend, raw data availability should be mandatory in any research facility, regardless of the scientific discipline. OneNote’s data storage feature allows users to optimally collect raw files resulting from any scientific approach. However, storage of large datasets, such as high-quality images or sequencing files, will depend on Microsoft OneDrive or Share- Point storage plans. Alternatively, these datasets can be hyperlinked to internal or external hosting platforms. To avoid hosting-related accessibility issues, a representative file or low- quality image can be uploaded to OneNote along with a detailed description of these hyper- linked datasets. You can also consult the Ten Simple Rules paper by Hart and colleagues. on how to store digital data [17], especially rule 3: keep raw data raw. In addition, protocols should contain detailed information to achieve a successful replica- tion of the results by other researchers; for example, reference or lot number of any material or reagent should be listed. Plasmids, which are indispensable resources among researchers, should be meticulously described. Cloning experiments could therefore contain (1) a cloning strategy (e.g., Gibson cloning) describing all steps of the experimental approach; (2) results containing all positive and negative outcomes, including raw .seq and .ab1 files; and (3) a reconstruction of the final plasmid with its sequence, map, and features. Communications with collaborating researchers (e.g., e-mails or meeting highlights) having an impact on the outcomes of an experiment may also be documented. Data presentation OneNote provides users with several tools to enhance data presentation. These tools are avail- able at the Insert or Draw tabs. For instance, Microsoft Visio (OneNote > Insert > Diagram) is a diagramming application that could be used to sketch a protocol or a bioinformatic pipe- line. Audio or video notes from lab meetings or experiments (e.g., mouse experiments) can also be recorded. OneNote’s optical character recognition (OCR) feature can be used to acquire text from old laboratory documents as well. OCR built-in capability converts the text from a picture, a scanned file, or a handwritten document into a machine-encoded, editable text. OneNote’s compatibility with other Microsoft Office applications, such as PowerPoint or Excel, can give researchers an advantage for figure and table presentation. Graphs and tables constructed in these programs can be easily exported to OneNote. Figures—along with their legends, including graphs, diagrams, or imaging results (e.g., western blot outputs or micro- scopic images)—should be accurately labeled [18]. A legend should contain all information needed to understand and interpret the significance of a figure without reading the whole experiment. Tables must also be well organized with essential information, such as title, col- umn headers, data, and footnotes. A major advantage of ELNs over PLNs is their flexibility to record experiments continu- ously. Data generated from long experiments could be documented on a single page, separat- ing each result by the exact date (OneNote > Insert > Time stamp) on which each part of the experiment was performed. There is no longer any need to create a page for each working day, as it is expected when using a PLN. PLOS Computational Biology | https://doi.org/10.1371/journal.pcbi.1006918 May 9, 2019 4/9 Table 1. Recommendations for data acquisition and presentation using Microsoft OneNote as an ELN. Feature Recommendation Acquisition All data resulting from any experiment, analysis, observation, etc., must be properly recorded without exception. Unintentional errors, as well as negative, unexpected, or conflicting results, should also be documented. All computational-related analyses along with their raw files, such as codes or scripts, should also be recorded. Raw data generated from any experimental approach could be uploaded within the ELN to promote reproducibility and transparency practices. Large datasets, such as high-quality images or sequencing files, can be hyperlinked to internal or external hosting platforms. Protocols and cloning experiments should contain detailed information (e.g., reference and lot number of any material or reagent) to assure reproducibility by other researchers. Important communications with collaborating researchers, such as e-mails or meeting highlights, may also be documented. Presentation Figures and tables should be self-explained with captions and detailed information. Improve data presentation by using OneNote tools available at “Insert” or “Draw” tabs (e.g., Microsoft Visio). Results from long experiments should be documented on a single page; there is no need to create a page for each working day. Use a single note container all along the experiment’s page to avoid unintentional overlapping of text or images. Abbreviation: ELN, electronic lab notebook. https://doi.org/10.1371/journal.pcbi.1006918.t001 OneNote allows users to create multiple note containers (flexible bounding boxes) in one page [19]. Note containers, which can hold text, images, or files, behave as independent entries that can be moved around the page. This can lead to an unintentional overlap of these boxes and, consequently, to a superposition of text or images. To avoid this issue, all data must be included in a single note container. Table 1 summarizes all recommendations for data acquisi- tion and presentation. Sharing Pharmaceutical and academic research is habitually performed within a strong collaborative environment; in this regard, OneNote’s sharing features provide major advantages compared with PLNs. OneNote allows researchers to share their ELN among their team members and collaborators via a cloud-based platform such as Microsoft OneDrive or SharePoint [12]. In this manner, the experimental data are accessible from anywhere at any time, which is essential when an international collaboration has been established. Fig 2 shows an ELN-sharing workflow among institutions, laboratories, and lab members. Internally, ELNs could be shared among the members of the same laboratory under the mode “can view” to avoid accidental changes caused by any lab member. Legal documents, pages, or entire sections can be password-protected in order to secure confidential information (OneNote > Review > Password). In addition, we recommend sharing an entire ELN to other laboratories from the same institution to improve reproducible research practices and trans- parency [1]. This ELN could contain specific protocols, a list of sharable resources (e.g., prim- ers, antibodies, cell lines, or chemical compounds), raw data, papers, or bioinformatic codes. All these data could be managed (“can view and edit” mode) by the principal investigator and/ or the lab manager (Fig 2) and organized using OneNote group sections, sections, and pages. Because OneNote does not allow sharing of a specific section or a page [20], an entire ELN PLOS Computational Biology | https://doi.org/10.1371/journal.pcbi.1006918 May 9, 2019 5/9 Fig 2. A schematic diagram presenting a OneNote ELN-sharing workflow. OneNote ELNs can be shared among lab members, laboratories, and institutions using two parameters: “can view” and “can edit and view.” ELN, electronic lab notebook. https://doi.org/10.1371/journal.pcbi.1006918.g002 could be shared when an outside collaboration has been established. This ELN can be orga- nized as described in Fig 1. Make sure to store, secure, and legalize your ELN correctly ELN data storage and security are major concerns among researchers [12]. In this regard, we recommend to establish an on-premise Microsoft SharePoint storage system to prevent data security breaches related to cloud computing [12,21]. We also recommend backing up a full ELN to a OneNote package file (.onepkg); this single file contains the text, embedded files, audio, and video, similar to a .zip file. In addition, this on-premise system, under specific Microsoft SharePoint configurations, is able to provide customizable options to achieve com- pliance with the United States Food and Drug Administration’s Code of Federal Regulations Title 21 Part 11 (FDA 21 CFR Part 11). Part 11 is a US regulation that sets specifications on PLOS Computational Biology | https://doi.org/10.1371/journal.pcbi.1006918 May 9, 2019 6/9 Fig 3. OneNote connectivity. Several external tools can be used to enhance OneNote ELN usage concerning data accessibility, acquisition, and presentation. ELN, electronic lab notebook. https://doi.org/10.1371/journal.pcbi.1006918.g003 electronic records and electronic signatures (ERES). Furthermore, software development com- panies (e.g., Montrium and Paragon Solutions) provide services to reach compliance with EudraLex Volume 4 Annex 11, a European equivalent of the FDA 21 CFR Part 11 [12]. Regarding ERES, OneNote does not provide an option to electronically sign a note; however, completed experiments, protocols, etc., can be exported to .pdf format and be signed electroni- cally. An ELN compliant with Part 11 or Annex 11 is considered as a legally accepted electronic document to protect researchers from legal matters such as fraud accusation or intellectual property theft [12]. Go paperless and get connected Microsoft OneNote is able to interact with several external resources that can be used to improve data accessibility, acquisition, and presentation. Smartphones, tablets, and smart- glasses can be used for audio and video recording, as well as for image capturing (Fig 3). The same devices, along with smartwatches, can also be used for data accessibility. For example, protocols can be displayed during experimentation and therefore minimize paper use and printing costs (Fig 3). In this regard, our survey-based study among 28 researchers using ELNs with tablet-based devices for a 3-month period showed that 67% of researchers think that tab- lets can substitute printed protocols [12]. Moreover, 80% of surveyed researchers think that tablets can improve ELN usage. Wearable technology can also be implemented to improve data accessibility and visualiza- tion during OneNote usage in an experimental setting. For instance, protocols can be con- sulted through smartwatches or smartglasses. This represents a significant advantage when working in laboratory rooms or areas where PLNs are not allowed (e.g., cell culture or PLOS Computational Biology | https://doi.org/10.1371/journal.pcbi.1006918 May 9, 2019 7/9 radioactive rooms). Both devices can also be used as substitutes for some bench equipment, such as chronometers or timers, and could provide researchers with other applications such as calculators, alarms, and reminders [12]. 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