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Big Data in Health Care: Applications and Challenges

1 Introduction Big Data, the generic term for data sets of structured and unstructured data that are extremely large and complex so that the traditional software, algorithm, and data repositories are inadequate to collect, process, analyze, and store them ( Asante-Korang & Jacobs, 2016; Kyoungyoung Jee & Gang Hoon Kim, 2013 ; Khoury & Ioannidis, 2014 ; Tan, Gao, & Koch, 2015), has become an intensively studied area in recent years. With the development of the Internet, the mobile Internet, the Internet of things, social media, biology, finance, and digital

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Identifier Services: Modeling and Implementing Distributed Data Management in Cyberinfrastructure

in a dataset’s lifecycle. As long-term custodians of data, existing repository systems fell short of performing this function. Most have poor or no mechanisms to continuously assess identity beyond validating integrity via checksums completed at ingest ( Factor et al., 2009 ). Furthermore, checksum algorithms are of limited use for large data, because they cannot tell what has changed. Finally, repositories have limited mechanisms to link to external related datasets, and current initiatives are more focused on linking data to related publications ( Hoogerwerf et

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