Big Data Museums need Human Curators

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Most analysts define "Big Data" subjectively as information datasets whose size is beyond the ability of mature software tools to capture, store, manage and analyze it. As people and business go on about their lives, they generate huge data exhaust as a by-product of social media, smartphones, computing and embedded devices. Since it is very hard for machines to pull operational insights out of big data, there is a rise in the need for data scientists often referred to as data "curators." Much like a museum curator collects, catalogues, interprets and preserves artwork or historic items, a data curator works to improve the quality of data-driven information within their operational processes. This also involves active lifecycle management that attempts to connect the sciences, social sciences and humanities. Even though there are programs that can poll APIs for AWS or GitHub and pull out somewhat structured data, it cannot be fully interpreted without human intervention. This is good news because with our newfound tools, people will transform the study social sciences to more digital humanities where insightful connections are made to economics, law, medicine, education and communication.

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