Role and Importance of Semantic Search in Big Data Governance

Abstract

Big Data promise to funnel masses of data into our information ecosystems where they let flourish a yet unseen variety of information, providing us with insights yet undreamed of. However, only if we are able to organize and arrange this deluge of variety according into something meaningful to us, we can expect new insights and thus benefit from Big Data. This chapter demonstrates that text analysis is essential for Big Data governance. However, it must reach beyond keyword analysis. We need a design of semantic search for Big Data. This design has to include the individual nature of discovery and a strong focus on the information consumer. In short, it has to address self-directed information discovery. There are too many information discovery requests that cannot be addressed by mainstream Big Data technologies. Many requests often address less spectacular questions on a global scale but essentially important ones for individual information consumers. We present an open discovery language (ODL) that can completely be controlled by information consumers. ODL is a Big Data technology that embraces the agile design of discovery from the information consumer’s perspective. We want users to experiment with discovery and to adapt it to their individual needs.