Big Data in History by Patrick Manning (auth.)

By Patrick Manning (auth.)

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The collaborative dimension of this mission focuses especially on data collection but also on data documentation. The chapter is divided into five sections, each rather different from the other, which combine to create the basic organization and content of the CHIA Archive. First is the issue of identifying the relevant historical data to be included in the archive. Manuscript, print, and digital data have all to be gathered and submitted to CHIA. Second is the ingest of data into the CHIA Level 1 Archive through the crowdsourcing system.

This social scientific world-historical archive will be rather different from the global climate models now in use, but in fact the global climate models provide the closest parallel to the world-historical archive, and we will explore those parallels in detail. Notes 1 Dr. Cao’s position is supported by the Dietrich School of Arts and Sciences at the University of Pittsburgh. In addition, the Office of the Provost at Pitt provided grants of US$ 40,000 to the World-Historical Dataverse during 2011–12 and 2012–13.

Upon ingest, the datasets are reviewed and sorted into various sections of the Level 1 Archive. The result is a large number of parallel datasets, as submitted by their creators, which are sustained by the system of Digital Stewardshop. These Level 1 datasets may be analyzed and visualized by users, for instance through the Spatio-Temporal Bridge. The third section of the chapter focuses on data integration – in effect, the merging of datasets. Col*Fusion is the infrastructure developed at the University of Pittsburgh which permits the integration of datasets through identifying variables that are common to two or more datasets, and then expanding steadily the degree of integration among the linked datasets.

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