This presentation will focus on discussing a definition of library capacity for big data, based on preliminary findings from the first phase of the IMLS funded project, Library Capacity Assessment and Development for Big Data Curation. The project aims to develop a conceptual framework for assessing libraries’ capacity for big data curation. Understanding the concept of library capacity will assist library staff in understanding their current environments as well as potential impediments to building successful curation programs. As big data increasingly forms the basis of research in many disciplines, academic librarians are now expected to play a role in curating and providing access to big data. Consequently, an increasing number of libraries have been launching data services or extending existing services, but there is a significant level of variation in their services and programs perhaps due to their differing organizational capacities. To successfully and sustainably launch and maintain data services, data curation programs must be tailored to a library’s existing capacity. Eventually, libraries need to build or grow their capacity in appropriate ways to sustain or extend their data curation programs in the long term. Doing so will ensure their effectiveness and help libraries avoid unintended consequences. Particularly, due to the complex and distinctive nature of big data, curation programs require a thorough assessment of sufficient capacity in various dimensions, such as technology infrastructure, policies, values, skills, culture, and leadership.