How Librarians are Important to the Data Science Movement

The library has always been a repository for knowledge and research tools.  In recent years, with the advent of big data and data science, research has become more powerful and data-driven.  However, despite the increasing treasure trove of data, research indicates that there are not enough people out there who can harness the power of big data.  The consulting group McKinsey estimates that the U.S. currently faces a shortage of nearly 200,000 people who have the technical knowhow to use big data to make effective organizational decisions.  This dearth of big data experts is despite the fact that big data collection itself is increasing worldwide, supported by advances in Internet of Things which enable better real-time data collection.

Librarians have long been shepherds of vast amounts of knowledge.  This is why libraries can stand to benefit by adding data science to their list of offerings.  Big data and data science applications serve to make libraries an even more powerful source of knowledge to bridge the gap and increase big data analytics literacy in society.  Libraries are beginning to offer resources for patrons to learn more about big data and its benefits. It makes sense, practically speaking, for librarians to adopt and support big data practices and resources.  Data science and big data lend themselves readily to research applications in a variety of fields, and can be used in conjunction with machine learning techniques to learn how to cluster, make recommendations, predict outcomes, and so on, based on data.  Librarians can support data science by providing access to training and instructional materials to help improve the knowledge base surrounding big data.  There are several ways libraries can help individuals and organizations adopt data science and big data practices: by providing access to information, organizing educational workshops and courses, and offering services supporting research data management. Read on to discuss the role of data science in the library and how librarians can both support data science and big data, and benefit from these new concepts.