On emerging use cases and techniques in large networked data in biomedical and social media domain

Over the last two decades the tremendous growth of the Internet has resulted in large-scale generation of digital content. This has excited analysts and researchers to further the technological capabilities to store, represent, and analyze this voluminous data. To illustrate the magnitude of data explosion, specifically in last four years, consider the figures reported in gantz2010digital. The article suggests that we generated around 5 exabytes of data from the time data was earliest recorded to year 2003, while we now produce the same amount in a matter of just 2 days! Apart from social media and related domains, advances inbiological, medical, and healthcare technologies, along withdevelopment in high-throughput biomedical technologies such as -omic (e.g., genomic, metabolomics, proteomics, and next generation sequencing), imaging (e.g., behaviormonitoring), wearable and portable medical sensors, yield vast amounts of highly complex biomedical data on a daily basis. Thus, paucity of data is no longer a bottleneck for data analysis. On the contrary, this rate and size of generated data not only compels us to think of effective ways for data management and content presentation for conveying good quality information to the end users but also of effective and efficient techniques in data analyses and pattern extraction.