Healthcare data standards are being extended to include 3D structures for cancer data. The free-to-use canSAR research database “now holds the 3D structures of almost 3 million cavities on the surface of nearly 110,000 molecules”. This is a timely and significant example of what people mean when they talk about adding big data features to existing standards. Sometimes it's a stretch for people to understand why standards for big data objects are important – is this just the standards guys looking for something to do?
Well, I can tell you that people involved with standards tend to be conservative (with a small c) and are looking to make as few changes as necessary to serve their users. At the same time, they are responsible for making sure the community's standards evolve to meet changing needs. Big data has been subject to the hype cycle, like every technology. This means the real value of big data is sometimes obscured by the rhetoric and the sales messages.
If you're trying to cure cancer, it sure helps to be able to explore complex cellular structures and share those explorations across the global research community. Likewise, if you're involved in insurance you will soon have a deep interest in being able to collect, analyze, and share data streams from embedded devices, wearables, and autonomous vehicles. Big data is adding new depth to multiple activities. Standards for big data items are just as important as standards for more traditional data items. As the months and years roll by, the distinction will fade.
Data analysts sometimes characterize data as “something of interest to the business”. It doesn't matter if that thing is big or small, simple or complex. If it's of interest to the business, then it must be understood, managed, and used. With the growing interdependencies among organizations and the central role of data in all activities, defining data is increasingly a matter for the community rather than individual players. We call it “industry standards”. Health IT
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