Evaluating Collaboratory Cultures

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

• Optimize productivity by adopting agile techniques and anti-fatigue good practices

• Prioritize inclusivity by normalizing privacy practices, supporting cultural differences, and offsetting nonverbal cues

• Provide secure, stable links to project meetings (including agenda) for asynchronous participation

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

• Good practices for creating sustainable, accessible codes:

• Data curation:

• Data analysis:

• Data visualization practices:

• Build stand-alone 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.