between 6 and 8 million individuals. They are the most extensive serial records for the history of Africans in the Atlantic World and also include valuable information on the indigenous, European, and Asian populations who lived alongside them. The involvement of librarians and archivists plays an important part in digital humanities projects because of the recent expansion of their role so that it now covers digital curation, which is critical in the preservation, promotion, and access to digital collections, as well as the application of scholarly orientation to digital humanities projects. A specific example involves the case of initiatives where archivists help scholars and academics build their projects through their experience in evaluating, implementing, and customizing metadata schemas for library collections. The initiatives at the National Autonomous University of Mexico is another example of a digital humanities project. These include the digitization of 17th-century manuscripts, an electronic corpus of Mexican history from the 16th to 19th century, and the visualization of pre-Hispanic archaeological sites in 3-D. Cultural analytics "Cultural analytics" refers to the use of computational method for exploration and analysis of large visual collections and also contemporary digital media. The concept was developed in 2005 by Lev Manovich who then established the Cultural Analytics Lab in 2007 at Qualcomm Institute at California Institute for Telecommunication and Information (Calit2). The lab has been using methods from the field of computer science called Computer Vision many types of both historical and contemporary visual media—for example, all covers of Time magazine published between 1923 and 2009, 20,000 historical art photographs from the collection in Museum of Modern Art (MoMA) in New York, one million pages from Manga books, and 16 million images shared on Instagram in 17 global cities. Cultural analytics also includes using methods from media design and data visualization to create interactive visual interfaces for exploration of large visual collections e.g., Selfiecity and On Broadway. Cultural analytics research is also addressing a number of theoretical questions. How can we "observe" giant cultural universes of both user-generated and professional media content created today, without reducing them to averages, outliers, or pre-existing categories? How can work with large cultural data help us question our stereotypes and assumptions about cultures? What new theoretical cultural concepts and models are required for studying global digital culture with its new mega-scale, speed, and connectivity? The term "cultural analytics" (or "culture analytics") is now used by many