Big Data Applications

Abstract

The sustainability of huge and ever-growing data pools using different formats that cannot be processed with traditional software tools is the next big challenge for web designers, Internet marketers, and software engineers and requires new technologies and practices. One of the approaches to cope with Big Data is to use Semantic Web technologies, especially machine-interpretable metadata and Linked Data. Implementing the Resource Description Framework (RDF) and RDF-based standards ensures that data and its meaning are encapsulated, and concepts and relationships can be managed while connecting diverse data from various data sources. Graph representations, such as Facebook’s Open Graph, add context to and visualize Big Data for data analysis. The Service-Oriented Architecture (SOA) infrastructure over Big Data makes it possible to update Big Data in real time. Data can be automatically classified, relationships associated, and new relationships found, so that data can be collected and integrated without worrying about schemas and data descriptions, yet providing a data description. Big Data applications on the Semantic Web include, but are not limited to, next-generation Search Engine Result Pages, social media graphs, analysis of natural language content, publishing factual data about massive world events, interlinking BBC’s online content, as well as high-performance data storage and processing.