Mineral wealth from the Americas underwrote and undergirded European colonization of the New World; American gold and silver enriched Spain, funded the slave trade, and spurred Spain's northern European competitors to become Atlantic powers. Building upon works that have narrated this global history of American mining in economic and labor terms, Mining Language is the first book-length study of the technical and scientific vocabularies that miners developed in the sixteenth and seventeenth centuries as they engaged with metallic materials. This language-centric focus enables Allison Bigelow to document the crucial intellectual contributions Indigenous and African miners made to the very engine of European colonialism. By carefully parsing the writings of well-known figures such as Cristobal Colon and Gonzalo Fernandez de Oviedo y Valdes and lesser-known writers such Alvaro Alonso Barba, a Spanish priest who spent most of his life in the Andes, Bigelow uncovers the ways in which Indigenous and African metallurgists aided or resisted imperial mining endeavors, shaped critical scientific practices, and offered imaginative visions of metalwork. Her creative linguistic and visual analyses of archival fragments, images, and texts in languages as diverse as Spanish and Quechua also allow her to reconstruct the processes that led to the silencing of these voices in European print culture.

Mining's fascinating and dangerous nature is reflected in the text and over 450 color photographs of specialized tools and artifacts. Thirty categories, from advertising and assay equpment to surveying equipment and tokens, chronicle old mining methods. This is an important and valuable reference for all concerned.

The series, Contemporary Perspectives on Data Mining, is composed of blind refereed scholarly research methods and applications of data mining. This series will be targeted both at the academic community, as well as the business practitioner. Data mining seeks to discover knowledge from vast amounts of data with the use of statistical and mathematical techniques. The knowledge is extracted from this data by examining the patterns of the data, whether they be associations of groups or things, predictions, sequential relationships between time order events or natural groups. Data mining applications are in marketing (customer loyalty, identifying profitable customers, instore promotions, e-commerce populations); in business (teaching data mining, efficiency of the Chinese automobile industry, moderate asset allocation funds); and techniques (veterinary predictive models, data integrity in the cloud, irregular pattern detection in a mobility network and road safety modeling.)

Reprint of the original, first published in 1875.