Assign a value to each practice (No=0 | Yes=1)
Communication practices
Establish and explain agile communication practices early
Co-create the communication platforms and tools strategy
Define the purpose of the collaboration
Describe, debate, and refine purpose in the first team meeting
Elicit co-creation/participatory design input early and often
Assign roles and clarify responsibilities for all collaboratory members involved in the project lifecycle, including principal investigators and team leads
Outline benchmarks of success (i.e., project milestones and schedule of deliverables)
Introduce collaboration tools and how they relate to the purpose of the project, such as communication platforms and meeting schedules
Provide collaboratory orientation (team introductions, SOP, tool and method training info)
Video conference practices
oDisable mirror cam function during meetings
oDisable cams during presentation of meeting materials
oReduce cam time as much as possible to pull attention to agenda topics and reduce bandwidth issues
oNever ask a participant to turn on their cam if they have chosen to participate off camera
oEnforce the use of the “Raise Hand” function to support uninterrupted speech sans nonverbal cues
Participation best practices
Always ask for clarification when you are uncertain
Offer your own disciplinary input to help refine or expand issues
Respect and encourage a diversity of opinions, backgrounds, and experiences
Avoid jargon when a synonym can be used
When jargon is unavoidable, define terms
Address conflicting ideas or approaches as they arise and employ co-creation techniques in the resolution process
Communicating multidisciplinary concepts
Schedule enough time in the meeting agenda to introduce new terms and concepts
Practice iterative review to raise competency across the entire collaboratory
Issue a project handbook or SOP and add terms and definitions, as necessary
Collaboratory tools
Document work on shared docs that allow multiple users to take notes, edit, and comment in real time.
Allow team members to schedule meetings, set deadlines, assign time-sensitive tasks, and track project milestones on a shared calendar.
Use instant messaging when it is the prescribed method of communication in the SOP (avoid using IM as an ad hoc communication tool to prevent fatigue)
Use data repositories to track version control, multiple threads, and updates.
Practice project archiving to establish a stable record of project assets and to track progress via reflexive practice.
Establish reproducible and executable software configuration practices, commonly referred to as containerization, bundles together software, configuration files, dependent versions, and data so that projects can be reproduced, regardless of future changes in operating systems and software versions.
Preserve data assets with computational notebooks and tutorials that combine code, results, and descriptive text into a computational narrative.
Use scientific discovery platforms to enable collaboration with big data assets.
Data management best practices
Make data as FAIR as possible.
Revisit the data management plan frequently during the project and make changes as necessary.
Consider legal, ethical, and cultural obligations when drafting sharing policies.
Implement a stewardship best practices strategy and reflexive methodology at the project outset.
Code writing practices
oProvide a step-by-step user manual for tools whenever possible
oAlways maintain an up-to-date Readme file where latest updates and requirements are listed
oProvide high-level comments at the beginning of each file and throughout the code as needed
oFollow consistent naming convention across your codes
oAutomate as many of the processes involved in data access, storage, and reformatting as possible.
oKeep separate copies of the original (raw) data and the curated data
oResearch and employ common, successful analysis methods.Do not reinvent the wheel.
oMap your method to the research questions you are trying to answer.Do not try to fit your method to an application.
oMake a tutorial-style document that explains your analytical method in simple language.
oUse visual graphics to communicate results with collaborators.
oUse high quality formats to produce images.
oAutomate data visualization as much as possible.
oAim for users being only a single click away from reproducing everything.
oIf possible and where appropriate, build a Graphical User Interface (GUI) that allows your collaborators to tweak parameters and apply their expertise to parameter evaluation and exploratory analyses.
oWhen appropriate, build add-on packages and libraries, or even lean software tools.
Participatory design practices
Create a flexible-by-design, agile management framework that can accommodate variable scope and unanticipated results.
Specify the distinct contribution that each collaborator has to offer to their field.
Identify inclusive objectives and/or outputs that allow each contributor to advance their own professional goals and research agendas.
Specify how the results of collaborative research, including data science methods, will ultimately be evaluated by disciplinary experts.
Ensure that individual contributions will contribute to the research portfolio of the data science practitioners, and vice versa.
Revise and improve the research plan whenever new collaborators are onboarded.
Roles and responsibilities
Co-create a project management plan with milestones and deadlines that lead to clearly defined project goals by assigning roles and tasks according to the strengths and interests of each team member.
Invest in the personal contribution of individual team members by working one-on-one to design and refine assigned tasks.
Check-in regularly to ensure that each individual is on track with the tools and resources they need to succeed, and adjusting the plan as needed.