In order to transform data into information, libraries must adopt new service models. To take advantage of the growing domain of library data analytics, which provides new insights into existing service models, libraries need to improve their technological literacy, especially coding and mark-up. However, acknowledging the importance of proactively calibrating one's professional mission does not imply libraries generate, or manage, big data in the traditional sense. Essentially, it acknowledges that libraries must be aware of being "data savvy" due to the data-intensive world in which they operate. Libraries are not just consumers of data anymore, but also suppliers and to a lesser extent producers. To build a good framework of reference and knowledgebase, patrons rely on good-quality information just as much as new technologies such as artificial intelligence (AI) rely on good-quality data. When determining a reliable data source, data integrity and data ethics are crucial factors to consider. Libraries have always placed a high value on privacy, ethics, and equal access to information, which enables them to serve as new partners for researchers and sources of high-quality data.

___________________________________________________________________________________

Keywords: Data Science, Library Science, Information Science.