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What is it?
What is it?
Crowdsourcing refers to the ability of a library to ask the general public or any community for assistance to identify, tag, inspect, or otherwise create metadata points for a certain resource or collection. Crowdsourcing is exciting to libraries and knowledge institutions because by mobilizing the public to create a data set, quickly, and at little to no cost, the A.I. software in use at the institution can be assisted by the data points to develop a higher accuracy of identifying objects within a collection (Cordell, 2020).
Above: The Library of Congress's crowdsourcing program "By The People".
Case Study: Library of Congress
The Library of Congress and The Smithsonian are both notable examples of institutions that have employed this method of metadata creation in reality (Cordell, 2020). The Library of Congress identified three key categories that the collection resources were required to fit into in order to motivate volunteers of its Humans-in-the-Loop Initiative to assist with the creation of datapoints. These categories were: engaging – to keep the volunteer’s attention, ethical – the subject’s privacy must be respected, and useful – all data created by volunteers must improve discoverability of the item and be useful to library users (Enis, 2022).
References
Cordell, R. (2020, July 14). Machine Learning + Libraries A Report on the State of the Field. LC Labs, Library of Congress.
Enis, M. (2022). News+: Library of congress trains machine learning with crowdsourcing: LC labs reports on humans-in-the-loop initiative. Library Journal, 147(2), 8.
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