Big data is a term applied to data sets whose size or type is beyond the ability of traditional relational databases to capture, manage, and process the data with low-latency. And it has one or more of the following characteristics – high volume, high velocity, or high variety. Big data comes from sensors, devices, video/audio, networks, log files, transactional applications, web, and social media - much of it generated in real time and in a very large scale.
Qualitative data collects information that seeks to describe a topic more than measure it. Think of impressions, opinions, and views. It seeks to delve deep into the topic at hand to gain information about people’s motivations, thinking, and attitudes. While this brings depth of understanding to your research questions, it also makes the results harder to analyze.
Quantitative data is designed to collect cold, hard facts. Numbers. Quantitative data is structured and statistical. It provides support when you need to draw general conclusions from your research.
Open data is data that anyone can access, use or share. Simple as that. When big companies or governments release non-personal data, it enables small businesses, citizens and medical researchers to develop resources which make crucial improvements to their communities.
A thick discription of a human behavior is one that explains not just the behavior, but its context as well, such that the behavior becomes meaningful to an outsider. Thick data is the recording and addition of these contextual details to big data sets.
Mixed methods research is a methodology for conducting. research that involves collecting, analyzing, and integrating (or mixing) quantitative and qualitative research (and data) in a single study.
Citizen Sensing is a process where people build, use, or act as, sensors – for example, identifying and gathering information (or ‘data’) that will help them to tackle an issue that’s important to them.