In the NNLM Big Data in Healthcare: Exploring Emerging Roles course, we asked participants, as they progressed through the course to consider the following questions: Do you think health sciences librarians should get involved with big data in healthcare? Where should librarians get involved, if you think they should? If you think they should not, explain why. You may also combine a “should/should not” approach if you would like to argue both sides. NNLM will feature responses from different participants over the coming weeks.
Written by by Emily B. Kean, MSLS, Research and Education Librarian, Donald C. Harrison Health Sciences Library, University of Cincinnati Libraries.
I believe that health sciences librarians can positively contribute to big data in healthcare, to an extent. After completing this course, I certainly have a much better understanding of what big data is, and I can also see some overlap between traditional functions of librarianship and several of the concepts of big data. In my opinion, the areas where librarians could most significantly contribute are in areas such as creating and developing taxonomies for machine learning. From some of the readings in the class, it seems like some of the positions which were described as data managers are roles that librarians could easily fill; however, as was also demonstrated in the literature, non-librarian professionals are rarely identifying librarians as capable of filling these roles. I feel that if librarians are striving to fill the role of data managers or data scientists, based on some of the readings from this class and some of the discussion that has taken place, a serious effort would have to be made to educate colleagues and peers about the role that librarians can play.
Overall, I find that after completing this course it seems to me that the approach described by Dr. Patti Brennan regarding nursing in the field of data science is also incredibly applicable to the field of librarianship and data science. I think Dr. Brennan’s approach that nurses have an understanding and appreciation for what data science can do for their profession but also the idea that not all nurses will become data scientists is a very healthy approach and it’s one that is also applicable to the field of librarianship. I can easily see a future where librarians could potentially participate on teams that might involve healthcare professionals and data scientists, but I don’t know that it’s realistic that all librarians will develop the skills of a true data scientist. Along the mindset presented in Dr. Brennan’s lecture, I don’t think it’s desirable that all librarians should become data scientists. As Dr. Brennan describes, there will still be a need for nurses to fill traditional nursing roles and there will still be a need for librarians to fill traditional librarian roles, with a small percentage from each profession adopting the role of data scientist.
Just as the traditional approach to schooling for librarians has evolved to encompass the ideas of information science, I do see a future where a Masters in Library Science program would encompass the ideas of data science as well. One of the areas that was touched upon by this course but we didn’t really get into in great detail are all of the different programming languages used by data scientists. I don’t know that it’s entirely feasible to re-train the majority of current working health sciences librarians, but I do believe that exposing library science students to data science concepts as part of their masters-level education will better prepare future librarians – in the health sciences and other areas – to be perceived as experts in this field and be approached as team members for interdisciplinary collaborations.