By Patrick Manning (auth.)
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Additional info for Big Data in History
Here are the goals for the five years beginning 2013:5 Global Collaboration: collaborative relations to sustain and expand the creation of a world-historical data resource, ▸▸ Crowdsourcing applications: to facilitate data ingest, ▸▸ Col*Fusion: for file merging, ▸▸ CHIA Archive: a distributed archive with datasets held at five levels of integration into the overall CHIA system, ▸▸ Digital Stewardship: following best practices in housing and display of datasets, ▸▸ World-historical gazetteer: a comprehensive (though probably distributed) historical gazetteer, and a spatial search engine to accompany it, ▸▸ Temporal search engine: with extended temporal metadata, ▸▸ Ontology: a developing CHIA ontology, providing topical classification of data, as well as space, time, and the tasks and applications of CHIA, ▸▸ Data: energetic collection of historical data worldwide, ▸▸ Peer review: scholarly review of historical datasets to establish strong academic standards, ▸▸ Theory: engage debate on linkage of social science theories to each other.
W. van Panhuis, D. Bain, Pitt. Global Collaboratory on Labour Relations. U. Bosma and K. Hofmeester, IISH. Migration Data proposal. U. Bosma, IISH. Silver Data. P. Manning, Pitt. African Data. E. Sall, CODESRIA. Continental Populations. P. Manning, Pitt; R. Zijdeman, IISH. Religion Data. R. Woodberry, Singapore. Contemporary global data. A. Karatayev, Moscow State U. Economic history data. Hitotsubashi U. The same priorities for the first five years are summarized again in Chapter 8, but condensed to five categories.
Such documents are available not only for western Europe but for Russia, Japan, Latin American countries, the Ottoman Empire, and for European colonies in all parts of the world. In some cases electronic records have been made of these documents in the form of PDF files, but PDF files do not generally enable searching on individual characters on each page. Scanning through Optical Character Recognition (OCR) can be used to digitize such printed files, though the accuracy of OCR is not yet high enough to provide dependable results on quantitative data.
Big Data in History by Patrick Manning (auth.)