WP1: Better research in less time

Doing ‘better research in less time’ by following ensuring reproducibility, being open, and using modern collaborative, operational, and project management practices.

Important

More detailed documentation on this particular work package can be found on the webpage here.

Science, while generating cutting-edge knowledge, lags behind most industry settings when it comes to practical, operational aspects that aim to increase efficiency and effectiveness of the research lifecycle. For instance, while much of research done now relies heavily on software and computational work, funding agencies rarely fund software and data engineering projects, nor do many research groups hire these highly skilled technical personnel. So, the aim of Work Package 1 is to establish these skills and needs as a core component of this project and to help do “better research in less time”.

Our basic strategies will be to establish working groups, including a group dedicated to “research operations” to fulfil this core aim, as well as developing and implementing common practices and tools that maximise collaboration and that follow some guiding principles. All groups will include a “tech lead” who has technical knowledge and skills and who will also be part of the research operations group, to help coordinate WP groups with these practices. We aim to onboard and train the tech leads in these practices by embedding them in some work done at SDCA, where these practices have been developing and refining over the last several years. The most relevant practices and skills that this WP1 aims to provide are in software and data engineering, iterative project management, collaborative workflows and tools,

Pertinent to these practices is understanding and assessing risk and challenges. The two biggest challenges we face with this WP1 are:

The need for highly technical personnel who have sufficient fundamental expertise to understand and apply these practices, which we hope to minimise through the training and onboarding of the tech leads.
the IT systems across centers that often don’t work well together, which we hope to reduce the impact of by having a dedicated research operations group.

While this WP1 forms the foundation to all other WPs and in many ways aims to support their success, the activities of WP1 are an increasingly needed aspect of research globally. In this regard, we aim to produce tangible and usable deliverables that are independent and valuable on their own.

Applications

The below content was used for the first and second rounds of applications.

First round

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WP1 answers the increasing need for openness, transparency, and reproducibility in research, will deliver the day-to-day project and operations management of all the WPs and will facilitate close collaboration and joint expertise development across all Steno Centres.

Effective coordination and management of complex projects such as DP-Next requires modern and innovative approaches to project and operational management. We will employ tools developed and tested at SDCA in the past years (1–5) to offer a practical framework for sharing knowledge and technical skills across centres, aiming to deliver “better research done in less time” (6).

Second round

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Science, while pursuing cutting edge knowledge, lags behind industry in standard operational, organisational, and technological practices, tools, and methods. From this, the core visions of WP1 are to do better research in less time (6) and expand the capacity of modern technical engineering-based skills in research groups across Steno and Denmark. By applying modern operational, engineering, and project management practices, we will optimize work done across the WPs. Through formal and informal upskilling sessions, we will develop data engineering and modern collaborative skills and knowledge in researchers from across the Steno Centers.

At SDCA, we have been developing and applying these practices in multiple projects (1–5), which highlight tangible examples of WP1’s activities. The general strategy for WP1 is to: 1) develop and agree on some basic principles for collaboration between centers and WPs that adhere to open scientific practices and modern collaborative methods; 2) investigate potential barriers to effective cross-Steno collaboration; 3) decide on a set of common tools and standards to use across centers for WP. Specific actions and tasks are found in Figure 2 and Figure 4.

Aside from the traditional management group overseeing the project, we will also have a research operations group that will simplify, streamline, and automate the collaboration and coordination of activities and products between WPs and centers as well as provide a space for learning these technical skills. See Figure 3 and the collaboration section below for more details, as well as Figure 1 for the general project timeline.

A major component of WP1 is also upskilling activities, in collaboration with the NNF-funded software and training-based Seedcase Project (4). Training will focus on skills not often taught to researchers, such as data engineering, modern collaborative practices, and iterative project management methods.

More detail on this WP can be found on the DP-Next website (https://steno-aarhus.github.io/dp-next/wp1/), such as the roadmap, potential challenges, and strategy.

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gantt
    title Estimated timeline and activities for DP-Next project
    dateFormat  YYYY-MM-DD
    axisFormat %Y
    tickInterval 1year
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    %% (`excludes` accepts specific dates in YYYY-MM-DD format, days of the week ("sunday") or "weekends", but not the word "weekdays".)

    section WP1<br>Management<br>and Collaboration
    T1.1 General project management: t1_1, 2025-01-01, 5y
    T1.2 Optimising collaboration: t1_2, 2025-01-01, 5y

    section WP2<br>Risk Prediction
    T2.1 Separate model development: t2_1, 2025-01-01, 18M
    T2.2 Machine Learning approaches: t2_2, 2026-01-01, 18M
    T2.3 Joint model development: t2_3, 2026-07-01, 18M
    T2.4 Validation: t2_4, 2028-01-01, 18M

    section WP3<br>Heterogeneity
    T3.1 Advanced clustering models: t3_1, 2027-07-01, 18M
    T3.2 Deep phenotyping substudy: t3_2, 2025-07-01, 54M

    section WP4<br>Development<br>and intervention
    T4.1 Investigate barriers and facilitators: t4_1, 2025-01-01, 18M
    T4.2 Develop & co-design: t4_2, after t4_1, 18M
    T4.3 Pilot test in specific populations: t4_3, after t4_2, 1y
    T4.4 Evaluation: t4_4, 2028-07-01, 18M

Figure 1: General Gantt chart for all of DP-Next.

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  title Tasks (T), Milestones (M), and Deliverables (D) for WP1
  dateFormat  YYYY-MM-DD
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  section Ongoing<br>activities
  T4. Iterate and refine collaboration: imp_collab, 2025-01-01, 5y
  T5. Develop project website: imp_proj_web, after collab_agree, 2030-01-01
  T9. Develop research ops website: imp_reops_web, after consensus, 2030-01-01
  T10. Maintain data infrastructure: imp_seedcase, after seedcase, 2030-01-01

  section General<br>setup
  T1. Establish working groups: wg, 2025-01-01, 2M
  T2.  Decide on collaboration approaches: collab_agree, after wg, 10M
  T3. Identify collaboration barriers: barriers, after wg, 10M
  M1. Setup project website: milestone, web_proj, after barriers, 1M
  D1. Collaboration workflow consensus report: milestone, consensus, after web_proj, 1M
  M3. Webpage for research ops: milestone, web_reops, after web_proj, 1M

  section WP2-linked<br>activities
  T6. Setup collaboration workflow: collab_wp2, after web_proj, 6M
  D1. R package infrastructure template: milestone, template_rpkg, 2026-06-01, 1M

  section WP3-linked<br>activities
  T7. Setup data engineering pipeline: de_wp3, after web_proj, 6M
  D2. Data engineering pipeline report: milestone, der_wp3, after de_wp3, 1M
  D3. Data Management Plan template: milestone, template_dmp, 2027-01-01, 1M 
  M4. Setup data infrastructure: milestone, seedcase, 2027-01-01, 1M

  section WP4-linked<br>activities
  M2. Setup knowledge repo: milestone, kr_wp4, after collab_agree, 1M
  T8. Build knowledge dissemination pipeline: kmp_wp4, after kr_wp4, 6M

Figure 2: Gantt chart for Work Package 1

Figure 3: Groups and people working on DP-Next.

References

Johnston LW, Kjærgaard AD, Sandbæk A. Grant Proposal: A framework for an open and scalable infrastructure for health data exemplified by the DD2 initiative. 2022;

Johnston LW, Silverman O, Toft G. Steno Register-based Project: Interplay between diabetes and intergenerational transmission of health determinants over the life course.

Steno Diabetes Center Aarhus. Documentation and R package on working with UK Biobank data at SDCA.

Beicher K, Brødbæk S, Johnston LW. The Seedcase Project: A framework for an open and scalable infrastructure for health data.

Steno Diabetes Center Aarhus. Github Repositories for Research and Knowledge Sharing at Steno Diabetes Center Aarhus.

Lowndes JSS, Best BD, Scarborough C, Afflerbach JC, Frazier MR, O’Hara CC, et al. Our path to better science in less time using open data science tools. Nature Ecology & Evolution. 2017 May;1(6).