Researchers need to be sure of the questions that they wish to ask and the knowledge that they are trying to gain, before even bringing in the data. Too often people jump into looking at the technology required to analyse big data in all its complexity, bypassing the critical first step of putting the data into context. It’s not even necessary to download the entire dataset in order to discover what you need to know.
So: where to start?
Well, it’s all about getting into the hong kong rcs data appropriate mindset for approaching big data. In essence, a big data mindset forms around examining the data approach, posing and answering such questions as what counts as big data? What data should be used? How do I know what is relevant?
Key principles include:
Sharing – taking a proactive stance on access to, and the exploration of, shareable data through appropriate, flexible and task-specific technologies, approaches and policies that enable widespread data sharing, discoverability, management, curation and reuse;
Accessibility – a commitment to making data accessible for re-use. ‘Open’ data is of little use if it is inaccessible or unintelligible because of technical or institutional constraints; (this is a bit confusing – if it’s open – it’s accessible if not – it wouldn’t be called open)
Security – Protecting privacy and intellectual property.