Big Data: Setting Science Free

Big Data: Setting Science Free

Recently I wrote an article for Bio IT World on how our ‘always-on’ digital world has us swimming in oceans of data. IBM’s view that up to 90% of today’s data has been generated in the last two years is astounding. For many, translating Big Data into Big ideas is a Big problem. How can we identify the small data within the Big Data to create the Big ideas?

Successful R&D is all about the creation, use and monetization of information. It requires a constant flow of ideas across a complex ecosystem where globalized, multiparty, multidisciplinary communities connect and collaborate through data.

Enterprise analytics are powerful tools to gain insight and knowledge but there’s another, arguably more powerful, differentiator so simple it’s often missed – underlying data QUALITY.

Harnessing high QUALITY data from the bench to the boardroom means capturing high context data at source, alongside its ontology and provenance. Social interaction is another important data asset, and effective social tools need to capture vital intelligence as researchers interpret and challenge the community data.

High context, connected data stores enable enterprise analytics. We have to look to the quality of fuel we are running our Big Data engines on to get the most from them. Creating this higher quality information optimizes innovation and ultimately, could see Big Data setting science free.