Collaboration

Collaboration#

Here we are describing a collaboration with the Data Science Platform, so that our collaborators are aware of what they can expect.

We understand our Data Science platform as a collaborative and supportive platform. Our platform:

  • disseminates pipelines and tools

  • helps on statistics and machine learning

  • matches skills between groups to foster collaborations

  • organizes courses and teaches Data Science

  • shares best practices in Research Data management (RDM), metadata collection, and coding

  • serves as domain specific knowledge mediation

  • fosters collaboration with other bioinformaticians of other research groups

Project Life cycle#

We structure a project into different phases:

  1. Initiating

  2. Planning

  3. Executing

  4. Monitoring and controlling

  5. Closing and Retrospective

We are allocating enough time for the two first steps (Inititating and Planning) contacting and organizing the necessary meeting to gain a deep understanding the project, its metadata and the context. You can expect that we gently ask about the project details, the experimental design, the people involved and what is expected from us.

Very often the last step is made in a rush, we are trying to also allocate enough time for a proper project closure and project evaluation of it in our internal meetings or presenting in the BioFoundry forums or in other forums with other bioinformaticians.

Our communication while doing a project is aiming to be open, professional, timely, proactive, transparent, constructive and inclusive. Please contact us to give your feedback if you identify any aspect that we could improve.

Reporting#

Aim#

Here we want to ensure that your work is not only understood, but even more importantly appreciated by your collaborators. Our presentations are tailored to our collaborators understanding of bioinformatics, statistics or machine learning.

Here is our motivation for our reporting meetings: scene of “The Tiger and the snow” by Roberto Benigni (watch here)

Structure#

  1. Introduction or overview of the project as a reminder of the context for everyone attending the meeting. Here we can include experimental design, objectives, data and metadata collection issues to consider, etc…

  2. Methodology and analytical plan (exploratory analyses and group comparisons that are going to be discussed)

  3. Results

    • Clear description of the results, with summarizing tables and plot when applies

    • How to interpret these results

  4. Conclusions aligned to the results seen

  5. Key questions and discussion points for the collaborator