Lessons from the Lab: Real-World Barriers and Breakthroughs in ELN Implementation

https://www.psdi.ac.uk/ Lessons from the Lab: Real-World Barriers and Breakthroughs in ELN Implementation Future Labs, Automation & Technology 2nd December 2025 Dr Samantha Pearman-Kanza About Me Why are we here? Strategic Approaches to Trialling ELNs Barriers to Implementation Drivers of Successful ELN Adoption Post Trial Enhancements & Future Plans Key Learnings Presentation Outline CC BY-ND 4.0 Errant Science - https://errantscience.com/ About Me Principal Enterprise Fellow at University of Southampton Principal Investigator for CaSDaR (Careers & Skills for Data-driven Research) Pathfinder Lead on Process Recording for PSDI (Physical Sciences Data Infrastructure) Deputy Chair of the Faculty Ethics Committee Advisory Boards/Committees: Future Labs Live, London Labs Live, MADICES, Machines Learning Chemistry, RSC-CICAG, STRIX Award, KnowLedger: An Open Digital Research Notebook for Research Data Management, STEP-UP Research Interests: Data Stewardship, FAIR Data, Semantic Web Technologies, IoT, Research Data Management, Digitisation, Lab of the Future, Paperless Labs, Re-use of Technology Why are we here? Exponential Data Growth Research Data is growing exponentially, which could provide great opportunities but also poses significant challenges Fragmented Recording Scientists have a fragmented approach to recording and linking their data, leaving experiments scattered and inconsistent Lost Data & Wasted Opportunities Data is often stored in random places, making access and collaboration very difficult Reproducibility Crisis A vast quantity of scientific research cannot be reproduced, re-used or built upon Community Needs Going forward there is a clear need for central, secure, shareable research records Is this because…scientists still use paper? Not necessarily… “It Was A Normal Day Of Office When A Sweet Voice Break - Computer Vs Paper” – free download from SeekPNG Paper ≠ Bad Paper records aren’t always inherently bad e.g. Darwin’s early Notebooks Electronic ≠ Good Electronic records aren’t always good e.g. spreadsheets with unintelligible column names Tech ≠ Transformation Just because something is in an electronic form, does not mean it adds value! Digital tools should enable CC BY-ND 4.0 Errant Science - https://errantscience.com/ •Idea of using digital methods to capture experiments was born •The term “ELN” started appearing in literature •Some early digital notetaking systems and databases were being used in laboratories •ELN Market exploded with hundreds of ELN offerings •Many ELN offerings moved to cloud-based systems rather than desktop apps •Increased emphasis on FAIR data principles driving adoption •First commercial ELNs were launched •Open Source ELNs also started to emerge •ELN Market starts to grow •ELNs started to evolve past just being a “replacement” •ELNs integrate with SDMS, LIMS, Inventory Systems, Equipment, AI •Many ELNs are modular and API driven 1990-2000 - ELN Foundations 2010-2020 - Cloud ELNs 2000-2010 - ELN Commercialisation 2020-Now - ELN Platforms Evolution of the Lab Notebook Strategic Approaches to Trialing ELNs ELN CHOICE & TRIAL SETUP RUNNING THE TRIAL EVALUATING THE TRIAL FUTURE PLANS ELN Trial Objectives Would the University of Southampton School of Chemistry and Chemical Engineering benefit from an ELN? Does the ELN meet user needs? Is the chosen ELN suitable for the School’s needs? Does the ELN enhance user workflows? ELN Setup & Administration Training ELN BACKEND TRAINING ELN SETUP & DEV TEMPLATES & METADATA PROCURE HARDWARE DEVELOP TRAINING Trial staff were trained in how to administer and develop the ELN, and how to use the ELN (in order to train others in how to use it). Define user roles, create accounts, hierarchies, groups etc. Setup security policy for sharing and collaboration. Implement data exit strategy. Create templates to capture structured data based on pre survey feedback. Added metadata to experiments and notebooks. Defined naming policies. Procured hardware based on the results of the onboarding survey. Dedicated lab hardware has been cited as a key success factor to ELN adoption. Developed specific training for group leaders and users, with guidance and hands on interactive sessions. Trial Launch & Training SHARING EXPLAINED Sharing was explained and group leaders made decisions per group. TRAINING USERS Users were trained in a hands-on session •Separate training for Group Leaders (to understand how to view researchers work and approve experiments) •Specific training for Researchers (to use the ELN as we intended, include relevant metadata and make use of our templates) TRIAL LAUNCH Trial was launched with formal presentation explaining aims, timelines and plans 01 02 03 CC BY-ND 4.0 Errant Science - https://errantscience.com/ Running the Trial 01 02 03 POINTS OF CONTACT Trial leaders were present as points of contact for any issues, so users knew that they had access to support if and when they needed it. GROUP CHECKINS Twice-monthly check-ins were provided for groups to identify teething issues and introduce new features (which were then communicated to the rest of the groups) ELN SURGERIES Surgeries were run monthly for support. They were busy to start with but dropped off as everyone became confident with the ELN and it became part of their everyday process Streamlining Health & Safety ENHANCEMENTS PREVIOUS SETUP NEW TEMPLATES INTEGRATED WORKFLOW Key Findings & Feedback 15% 77% 8% ELN Paper Mixed 82% 18% Supervisors ELN Paper Mixed 25% 75% ELN Paper Mixed 52% 4% 44% Researchers ELN Paper Mixed Preferred lab notebook type pre and post trial Post-trialPost-trialPre-trial Pre-trial USAGE Used across all 12 research groups 120 experiments logged weekly >90% of users want to continue using Signals STRENGTHS Integration with existing tools (ChemDraw) Improved oversight of researchers work (by Group Leaders) Clear Templates and metadata improving FAIRness CHALLENGES Hardware needs (60% of users) add a cost burden Login issues, limited mobile support Complexity of Setup Key Findings & Feedback Barriers to Implementation Integrating ELNs with existing systems and addressing data security concerns creates significant technical barriers. Insufficient lab infrastructure like power outlets and unreliable Wi-Fi hinders effective ELN usage. TECHNICAL INTEGRATION INFRASTRUCTURE CULTURAL RESISTANCE HARDWARE REQUIREMENTS Many researchers prefer traditional paper methods and misunderstand (and mistrust!) digital tools' benefits, causing resistance. Concerns about contaminating personal devices led to the need for dedicated lab hardware solutions. COST TIME Licenses, hardware procurement, and staff costs add financial complexity to implementation. Significant time investment is required for setup, training sessions, and there is always a user learning curve. 01 02 0605 03 04 Drivers of Successful ELN Adoption Stakeholder Alignment Early engagement of leaders and support teams ensures buy-in and resource commitment for ELN implementation. 01 Iterative Development Templates and workflows refined based on feedback provides iterative improvements and maintains user buy-in. 04 Clear Roles & Expectations Defined roles for administrators, trainers, and users establishes clear responsibilities and project timelines. 02 User Adoption Strategies Hands-on training, regular check-ins, and support sessions promotes user engagement and continuous improvement. 03 Post Trial Enhancements & Future Plans DEPARTMENT ROLLOUT LEVERAGING AI WORKFLOW INTEGRATION SCALING & TRAINING Learnings: ELN Implementation Needs PILLARS FOR SUCCESS 01 ENGAGEMENT 02 People, time, and money are essential pillars for effective ELN implementation and transformation. Cultural change and stakeholder engagement are vital to ensure adoption success. STRATEGIC TRIAL DESIGN 03 Design trials with scalability in mind to avoid repeating mistakes during wider rollouts. ALIGNED IMPLEMENTATION 04 Value is created by aligning implementation with organisational goals and iterative learning.