作者: Adrian Tear
DOI: 10.1007/978-3-319-09144-0_16
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摘要: Researchers are now accessing millions of Online Social Network (OSN) interactions. These available at no or low cost through Application Programming Interfaces (APIs) data custodians including DataSift and GNIP. Records held in Extensible Markup Language (XML) JavaScript Object Notation (JSON) well structured but often inconveniently formatted for use popular Relational Database Management Systems (RDBMS) Geographic Information (GIS) software. In contrast, emerging NoSQL (Not-only Structured Query Language) technologies specially designed to ‘ingest’ unstructured data. Extract/Transform/Load (ETL) procedures the storage subsequent analysis two OSN datasets SQL/NoSQL databases examined. The fixed model relational approach may prove problematic when loading unpredictable document-based structures arising from extended periods collection. Although far obsolete spatial community seems likely benefit experimentation with new software explicitly handling spatio-temporal Big Data.