Big data : techniques and technologies in geoinformatics Preface What is big data Due to increased interest in this phenomenon many recent papers and reports have focused on defining and discussing this subject. A review of these publications would point to a consensus about how big data is perceived and explained. It is widely agreed that big data has three specific characteristics: volume in terms of large scale data storage and processing; variety or the availability of data in different types and formats; and velocity which refers to the fast rate of new data acquisition. These characteristics are widely referred to as the three Vs of big data and while projects involving datasets that only feature one of these Vs are considered to be big most datasets from such fields as science engineering and social media feature all three Vs. To better understand the recent spurt of interest in big data I provide here a new and different perspective on it. I argue that the answer to the question of What is big data depends on when the question is asked what application is involved and what computing resources are available. In other words understanding what big data is requires an analysis of time applications and resources. In light of this I categorize the time element into three groups: past (since the introduction of computing several decades ago) near past (within the last few years) and present (now). One way of looking at the time element is that in general big data in the past meant dealing with gigabyte sized datasets in the near past terabyte sized datasets and in the present petabyte sized datasets. I also categorize the application element into three groups: scientific (data used for complex modeling analysis and simulation) business (data used for business analysis and modeling) and general