Dotmatics
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    AI-powered data management and workflow automation for multimodal scientific discovery

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    Adaptive Workflows

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  • Platform

    Scientific Intelligence Platform

    AI-powered data management and workflow automation for multimodal scientific discovery

    Learn More

    Capabilities

    Adaptive Workflows

    Customize, automate, and scale your lab workflows

    Artificial Intelligence

    Leverage AI and ML to accurately predict scientific outcomes

    Material & Ontology Management

    Classify materials and manage entities with full traceability

    Luma Products

    BioGlyph Luma

    Next-gen protein design for complex biologics – integrating molecular modeling, registration, and production with seamless data traceability and precision.

    Geneious Luma

    Accelerated antibody discovery for sequence analysis, construct design, and lab execution—integrating the power of Geneious Prime and Geneious Biologics with Luma’s adaptive workflows.

    Lab Connect

    Automated lab data ingestion and modeling—connect instruments, structure scientific data, and streamline lab operations with seamless integration.

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    The State of Chemicals & Materials

    Uncover key trends shaping the chemicals and materials industry

    Read More

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The Risks of Using OneNote as an ELN Workaround

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Some researchers looking to digitize their lab notebooks have turned to Microsoft OneNote as a cheap and easy solution, but there are risks which should be considered when using the product as a research and development electronic laboratory notebook (ELN).

What is OneNote?

OneNote is a basic, universal note-taking program that’s part of the Microsoft Office suite. It lets users sketch free-form notes and add on multimedia materials, such as screen grabs, audio or video clips, and limited-size files. Think home-design projects with sketches, photos, budgets, and shopping lists. Think of virtual school notebooks with different subject tabs and linked references and media files. OneNote also has basic indexing and search functionality, and it allows sharing and simultaneous editing.

Does OneNote work for scientific research?

OneNote was not built for capturing scientific research data, but scientists with budget limitations use OneNote as a short-term band aid solution for tracking experiments and associated data.

The Risks of Using OneNote as a Research Notebook

Let's look at a high-level overview of how some scientists use OneNote as an ELN and the risks that come with those use cases.

Experiment Setup Workarounds

Essential to a OneNote ELN workaround is leveraging its core hierarchical structuring scheme, which organizes content into notebooks > sections (and section groups) > and pages (and subpages). So, researchers might consider each notebook a project; each section is a protocol; each page and its subpages are an experiment and results.

With this workaround, researchers can use OneNote to build templates that organize their experiments and protocols. In doing such, they need to create and stick to detailed naming conventions, as well as add and flag notes about the materials and reagents used in an experiment. The onus lies with the users to be sure all data is labeled and recorded correctly. There are no built-in checks and balances; it is simply a note-taking system. All users must strictly adhere to the defined conventions or else the experiment and results may be rendered disconnected and unsearchable. Oftentimes, this means a principal investigator (PI) or laboratory manager needs to frequently review all team members’ work to ensure compliance of data entry.

Messy and Incomplete Data Input

OneNote is based around the idea of endless notebook pages. There are no boundaries like in a word processing document. Users can manually input data, upload datasets, import Excel and PowerPoint files, and even capture and upload images, videos, and audio files from tablets or mobile devices. However, once again, flexibility in OneNote comes at a cost. Users must ensure proper naming conventions are followed upon upload, otherwise data may be inaccessible and unlinked via search.

While users can dump all sorts of data into OneNote, it is not always clear where data are stored. One reason for this is because OneNote lacks the capacity to store large volumes of data. Instead, data is often stored on OneDrive or SharePoint. Users cannot directly include large datasets or high-quality images; they must instead include detailed written descriptions or low-quality images that hyperlink to the real data in storage.

Other caveats users note when recording data in OneNote include:

  • Frequent reliance on custom coding, scripts, or plug-ins to make things work

    • Interference of automatic spell-check in “code” mode

    • Risk of using plug-ins that might not be supported in future Microsoft updates

  • Cumbersome import of large datasets

    • Obfuscation of where data are stored

    • Need to hyperlink to large datasets and high-resolution image files

    • Poor rendering, handling, and resizing of large images

  • Difficulty with drawing tools

    • Preference to import work done by hand or in another program, such as PowerPoint

  • Fragility of notebook pages

    • Risk of accidently breaking pages with OneNote’s drag-and-drop functionality

    • Possibility of pages being rendered illegible after version updates

Complicated Data Output

Just as it’s not always easy to know where data are stored in OneNote, it is also not always easy to get data out. Issues abound—whether users are trying to browse, search, or export data. Some specific caveats users have noted when attempting to export data out of OneNote include:

  • Painfully inefficient browsing

    • Slow page scrolling seems less effective than just flipping through physical notebooks

    • Difficulty accessing data contained deep on the periphery of “infinite” or “boundless” pages

  • Lackluster search capabilities

    • Single-parameter text search only with no support for multi-parameter searching, such as needed with complicated experiments

    • Reliance on error-free tagging of input data so that it is searchable

    • No text searching in scientific files

  • Troublesome PDF export

    • Frequent export errors due to limitless pages

    • Awkward and mid-image page breaks

    • Illegibility due to poor rendering

Vulnerable Data Sharing and Security

Researchers within an organization can collaborate with colleagues in other labs by sharing entire OneNote notebooks. However, it’s not possible to share specific pages or content blocks. In terms of permissions, OneNote offers basic control over how data are shared, allowing password-protection by section or page, and the option to classify content as view-and-edit or view-only. Single user-level permissions aren’t an option.

When it comes to legal and compliance issues, OneNote hits some major roadblocks. It requires customization to comply with regulations surrounding electronic record keeping. Additionally, it lacks built-in signature, only offering a workaround that involves exporting PDFs to sign electronically (but remember, exported PDFs are often poorly rendered).

The Better Way to Meet Research Goals

OneNote may seem like the perfect stopgap solution to the immediate need for an online notebook, but it’s a stopgap at best. It is crucial to find a solution that enables digitization and also contributes to more informed decision making based on a secure, unified, and collaborative system.

Enter the Dotmatics electronic lab notebook.

The Dotmatics ELN was built for scientists, by scientists who understand the challenges of maintaining large amounts of sensitive data. Specifically, the ELN addresses some major and fundamental needs for an effective system.

A Single Source of Linked Truth

A solution built with researchers and lab managers in mind enhances their capabilities throughout the research processes. For example, Dotmatics' advanced ELN includes sharing capabilities so multiple parties can work within the same system and work with the same experiment.

Maintaining Data Security

For critical intellectual property protection, researchers can define the receptors and trace the history of the constituent subdomains directly in Dotmatics, while also tracking relationships between full length proteins as you make changes to your science and technology inventions.

Seamless Workflow Integration

Scientists can optimize the cycle of innovation with a cohesive notebook workflow, where data flows securely between the ELN and experiment registration, screening, and decision support.

See Dotmatics in Action

Get a demo of Dotmatics' modern ELN to see how you can use the unified system built for researchers to uncover breakthroughs quickly and securely.

Additional resources

View All Resources
eln adoptionBlog

Electronic Lab Notebook Adoption: Carrot or the Stick?

scientific-rd-data-liquidityBlog

Scientific R&D Data Liquidity: What It Is and Why It Matters

lab errorsBlog

Maximize Efficiencies by Avoiding These 9 Critical Lab Errors

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