This research activity studies linked data and open big data.
Linked Data is a term used to describe a recommended best practice for presenting, sharing, and connecting pieces of data, information, and knowledge on the Semantic Web using URIs and RDF.
Linked data describes a method of publishing structured data so that it can be interlinked and become more useful. It builds upon standard Web technologies such as HTTP and URIs, but rather than using them for web pages for human readers, it extends them to share information in a way that can be read automatically by computers. This enables data from different sources to be connected and queried.
The goal of the Linking Open Data project is to extend the Web with a data commons by publishing various open datasets such as RDF on the Web and by setting RDF links between data items from different data sources.
Big data is a collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications. The challenges include capture, storage, search, sharing, analysis, and visualization. The trend toward larger data sets is due to the additional information derivable from analysis of a single large set of related data, as compared to separate smaller sets with the same total amount of data, allowing correlations to be found to spot business trends, determine quality of research, prevent diseases, link legal citations, combat crime, and determine real-time roadway traffic conditions.