Big Data Opportunities and Challenges

Data retrieval ensures data quality, value addition, and data preservation by reusing existing data to discover new and valuable information. This area is specifically involved in various subfields, including retrieval, management, authentication, archiving, preservation, and representation. The classical approach to structured data management is divided into two parts: one is a schema to store the dataset and the other is a relational database for data retrieval. After data are published, other researchers must be allowed to authenticate and regenerate the data according to their interests and needs to potentially support current results. The reusability of published data must also be guaranteed within scientific communities. In reusability, determining the semantics of the published data is imperative; traditionally this procedure is performed manually. The European Commission supports Open Access to scientific data from publicly funded projects and suggests introductory mechanisms to link publications and data.