Understanding How Librarians can Support Data Science and Big Data

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 Cathryn Miller, Social Sciences Librarian, Duquesne University, Pittsburgh, PA Supporting data science and big data means supporting a new form of research.  Researchers engaging in data science often find or collect big data (large volumes of data), wrangle (prepare) the data, analyze it, and create reports (Federer, 2018).  A common technique used in data science is machine learning in which machines (computers) learn how to cluster, make recommendations, predict outcomes etc based on what the machines learn from the data.  In a healthcare setting, big data and data science can transform the clinical decision-making process. How can librarians support researchers engaging in data science?  By no means do I think that librarians must learn advanced statistics or computer programming to support data science and big data.  We can support data science and big data by extending our strengths in providing access to ...
Source: NN/LM Middle Atlantic Region Blog - Category: Databases & Libraries Authors: Tags: Data Science Source Type: news