A concept framework for data science in libraries
by Wouter Klapwijk (SIG Convenor), with contributions from SIG Members
Publisher: Big Data SIG
Libraries are challenged to adopt new service models to assist with the transformation of data into information. Libraries need to improve their technological literacy, especially coding and mark-up, to proactively take advantage of the new possibilities presented in the growing domain of library data analytics which provide new insights into existing service models. However, this acknowledgement of being mindful of proactively calibrating one’s professional mission does not in itself imply that libraries generate, or manage, big data as it is usually understood in the traditional sense of the word. It is merely an acknowledgement that the data-intensive world in which libraries function necessitates libraries to have an awareness of being “data savvy”. This is coupled with the responsibility to adapting ones professional skillset to proactively respond to the changing requirements of the user base. A Data Science framework is an outline and description of how to respond to such developments; a position paper rather than a statement of intent to administer big data per se, which is an activity usually associated with the term “data science” as it is traditionally understood.
For a copy of the full framework document, please contact the SIG Convenor.
Last update: 7 July 2019