Jump to content


Popular Content

Showing content with the highest reputation since 02/09/2020 in all areas

  1. Thanks so much for all your questions - I’ve enjoyed this conversation!
  2. Thanks everyone for your great questions. I hope you will all be able to successfully navigate collaboration and team science as part of your careers.
  3. Great! I've been fascinated for a long time, since I was a graduate student, in science that bridges disciplines. That, by definition, is team science. I've been at Brown University for nearly 15 years working to bring teams together, help them launch projects, and sustain their science. So, I guess I spend a lot of my time trying to provide that glue that you mention. I agree with you that team science can differ a lot depending on the setting, but that in any situation program management is essential.
  4. There's a tendency in academia (perhaps even in industry!) to think you can do things on the cheap, with existing personnel working on a project. But I think those groups that actually invest in bringing in excellent project managers see huge benefits that justify the additional cost. It can mean more success at bringing in funding AND more efficient usage of resources, as an example.
  5. Hi, I'm Saskia de Vries, and I’m excited to be here today to discuss navigating team science with you. I’m an Asst Investigator at the Allen Institute for Brain Science, where our guiding principles are Big Science, Team Science, and Open Science. Team science and collaboration is the foundation of what we do. But it can look very different from academic collaborations, because we are engaged in large scale projects. We have multidisciplinary teams, with scientist, engineers, mathematicians, technicians, etc, all working closely together. The project I’ve led here, our recent platform paper had over 70 authors! So keep in mind that it is a slightly different scenario than most academic departments or labs. My experience is that there's a lot of organization and communication that is critical to successful collaborations, with strong program management being key. There’s a lot of “glue work” that has to go on to make it possible for all the specialist and experts to do their work and have it all fit together, and that glue work is really important.
  6. It's a really good question. I can't comment on this specific example, but in any situation any participant in a team will have information they are willing to share and information they want to keep private--perhaps with good reason. It can be helpful at the beginning of a collaboration to discuss with all members what information they are expected to share to be a part of the team. They shouldn't be expected to share everything, but it's not unreasonable to expect everyone to share openly information that's relevant to the success of the project.
  7. Collaborations most definitely can fail. Though I think it's more nuanced. There's two kinds of failures. One is a "people" failure -- a group just doesn't gel and it's not a workable team. Sometimes a group can come together because they are excited to work together, but it turns out that the time isn't right for them to pursue a project. A year later, or a decade later, they might come back together and because the science has advanced or new tools are available, a project could succeed. And even if a particular project fails, a collaboration can result in strong ties between the members of the team -- they can continue to learn from each other even if they aren't working on a specific project. A big challenge in science is knowing when to quit. Scientists are persistent, and sometimes projects continue even though the collaboration isn't working. So thinking at the beginning of the project and agreeing on what constitutes a success and a failure, and what criteria you might use to pull the plug, can be useful
  8. I've definitely seen collaborations fail - either the work doesn't pan out or there are conflicts between the members. My sense is often it's more of a petering out, or a disintegration, of the collaboration, but I have known of some situations where it's been contentious. Team science is hard work!
  9. I think that this responsibility falls on the scientific project leaders as well as the program managers. In some cases, program managers might be in a better position to notice things that are slipping through the cracks or getting overlooked, which is why I think they should definitely be involved in this. But I think the scientific project leaders need to be really taking the helm.
  10. I agree that this depends on the setting and the size of the collaboration. I do think that large, or multifaceted, collaborations really need formal project management. But for smaller collaborations (eg. two small academic labs working together), I don't think it's necessary.
  11. Thanks for writing, John Carlo. It's a challenging question about how to manage the balance between collaboration and "doing your own thing." A critical piece in my mind is understanding how you will be evaluated in your position. If you want collaboration to be a central part of your work, I'd make that clear to whoever hires you and who will be reviewing you. If the institution has policies that you don't think are in line with your collaborative work, make sure to clarify how, for instance, collaborative grants or papers would be assessed during a performance review. And you should look closely at how people in your field evaluate each other. If they value collaboration, that presumably would come across in letters of support.
  12. Collaborations across disciplines can be extra challenging, and I think really require extra attention to the differences in the fields and the cultures of those fields. Communication is really important to know that these differences exist and to find plans for how to navigate that space.
  13. Hi, I’m John Davenport, I’m here today to answer your questions about team science – and I’m also excited to learn from my fellow panelist and from you, the audience! Saskia, it’s nice to join you, and I’m curious if you would describe briefly your experience doing team science?
  14. Good question! I don’t know that there’s a single strategy, but I think there are a couple of important pieces. First, being able to very clearly communicate your unique contributions to the team project. Second, having a clear vision for what you will do in your academic lab. I think making sure these two things are well communicated by both the applicant and by their references is critical.
  15. I agree that data sharing is a challenge. This is a case where some "top down" decisions about how a team will operate can be helpful. A democratic discussion might result in every lab continuing to do their own thing -- but setting some ground rules can provide structure-- for instance, that a lab must use a particular format or data sharing platform in order to be part of a larger collaboration. One driver of this is and will continue to be funding agencies who are increasingly dictating data science structures and data sharing as explicit parts of collaborative grants.
  16. This is a big challenge - both for collaborations and for open science. I do think moving towards more standardized file formats is valuable here, but even when it’s not completely possible, we can move in that direction. When I was in graduate school working on my solitary project, every experiment data file was structured slightly differently from the others. It was mayhem. So at a minimum, consistency within a project is a required, and robust meta-data and documentation is extremely important for other collaborators to be able to use the data. Communicating and planning how this will be done needs to happen up front. But, big picture, I think this is something that needs to be addressed by the larger field as we move toward more and more data sharing, even outside of collaborations. We need better infrastructure and standards that enable data to be shared and re-used meaningfully.
  17. I agree that it's the responsibility of the project leaders as well as project managers, to instill good practices in rigor and reproducibility. Project managers are in a good position to identify data or experimental practices that don't meet good standards -- but they may not feel comfortable or have the authority to confront a member of the team. I've mentioned this in a couple of replies and I'll mention again -- teams should also look for institutional training and resources that can help with this very important component to science. Your efforts will have more traction if your team guidelines are in line with your institutional guidelines, or, for instance, guidelines of important journals.
  18. Agreed. I think a tentative plan can be discussed at the outset, but this needs to be revisited during the collaboration. Projects change and shift, and authorships needs to reflect the work that’s been done rather than the plan when it began.
  19. It can be difficult to define authorship strictly ahead of time, but I'd recommend setting ground rules for how decisions are made. For instance, will everyone on the team be an author on every paper? Or will you only be an author on those where you had a substantial contribution?
  20. That's a great question--the international component can add an additional layer of complexity. I know at our University we have offices that help with navigating institutional agreements, including those outside the US. And we have experts in materials transfer and data agreements. I don't have a specific answer to your question, but I will say, scientists shouldn't try to address all these issues on their own. Bringing in experts who handle different aspects of international agreements can really be helpful, save you a lot of time, and help you avoid taking on liability that you don't need to. Use your institutional processes and protocols to your advantage. Yes, sometimes it can seem like just adding bureaucracy. But if you find the right people, they can be great allies and great members of your team.
  21. I wouldn't necessarily say bias -- but I definitely think people on hiring committees struggle with assessing collaboration vs. individual success. Hopefully, a group is honest with itself and with the candidates about what kind of person and approach fits best with that institutions -- do they want the isolated superstar or a team player? The reality is that many places want both -- someone who has the recognizable individual success but also contributes to community and can work as part of a team. Another element of this is that any given community -- say an academic department or institute, or a division at company -- will be made up of individuals who are more collaborative and those who are more solitary. Both can contribute to a vibrant and successful community.
  22. Thanks for your response. Its right some times different perspectives are challenging!! I like to add another question..In a collaborative team between countries, how do you prevent the breaks in the confidentiality?.
  23. Do you think that it is also the task of the program manager to oversee training of all individuals of the team in Rigor, Reproducibility and Responsible Conduct of Research? Or what are your thoughts on making sure everyone is fully trained and on the same page?
  24. I agree. Different disciplines speak their own languages, and often times the same term has drastically different meanings to different scientific communities. So it's important that everyone be willing to listen and learn from each other and take time to understand how someone from a different perspective sees things. On a more practical level, how scientists publish can vary from one community to another (for instance, does the senior author typically appear first or last on an author list; are conference abstracts "counted" as publications)? Understand that others on the team may need to check different boxes to make sure their careers progress. Overall, remember that the assumptions you have about the way science is done may be totally foreign to someone in a different field.
  25. Great question! I think this is a big challenge. We need better ways of communicating contribution than the order of a person’s name in the list of authors. Clearer, more easily digested author contribution statements are part of it. I like the idea of author contribution table, that digests the authors contribution statement into a visualization. But that still has limitations. Ultimately, individuals, and the team, have to be able to communicate outside of the paper what each person did. A letter of recommendation where this gets spelled out very concretely can be part of it. Being able to point to specific code someone wrote on GitHub, or protocols that they developed, that otherwise get lost in the swamp of the paper, can be really useful for this - but it means we in the field need to be paying attention to these other pieces as well as the big papers.
  26. Great question! There are certainly some formal training programs that provide structured training in project management. I think it depends somewhat on where you are working. Industry settings may require or desire these more formal certifications. In my experience in academia, training is usual on the job (for better or for worse). Because of that, successful individual are those who already have outstanding organizational skills and a knack for managing projects. Again, speaking about academia, teams often don't think about the need for project management (but I think this is changing). So many times jobs come about because a member of the team recognizes the team for organization and coordination and takes on that role. And that can involve into a formal project management position.
  27. Hi, My name is Hugo... How do you work with the concept of immeasurability between some areas or approaches?
  28. Good Day Professors DeVries and Davenport. My name is John Carlo J. Combista, a member of the SfN Community Leaders. I am currently doing my MSc graduate studies at Tel Aviv University and I'm liking how Israeli PIs value collaborations and open science environment wherein all of our lab members as well as the PI are equally passionate and supportive with each other. But can you further elaborate when is the time to do collaborations and when is the time to just focus on your own as a PI as there are pros and cons in doing collaborations. If you can give us scenario to understand further. Thank you very much. All the best.
  29. Hi John and Saskia. This is Lique Coolen: Thank you so much for organizing this live chat to answer our questions and lead a discussion on this very important topic. Saskia: with so many authors, how can everyone get the credit they deserve and will a paper like that even "count" for everyone's CV?
  • Create New...