Big data 

Aims and scope

The availability of Big Data is becoming increasingly common in many fields such as business, computer science, government, and the social and behavioral sciences including psychology.

There are four key characteristics that may qualify data as Big Data, namely Volume, Velocity, Variety, and Veracity. High-volume data refers to the size of the dataset. Is it too large that may lead to problems with storage and analysis. High-velocity data means that the data are received at a high rate and/or have to be processed within a short period of time (e.g., real-time and interactive processing). High-variety data are data consisting of many types of structured and unstructured data containing a mixture of text, pictures, videos, and numbers. Another characteristic of Big Data is the veracity, which indicates the importance of the quality (or truthfulness) of the data. Big Data with potential high relevance for psychology include social media data, health/physiological tracker data, geolocation data, dynamic public records, travel route data, and behavioral and genetic data.

The overall aim of the emerging research is to address methods and applications using Big Data in psychology. Future research topics may address, but are not limited to:

• Methodological and statistical issues in collecting, handling, processing, and analyzing Big Data in psychology.
• Applications and illustrations of how Big Data are used to address psychological research questions.
• Psychological interventions making use of Big Data.
• Inference models taking Big Data into account.
• Comparison of Big Data versus ´traditional´ data sources (e.g., self-reports, peer reports, etc.).
• Combining traditional data sources with Big Data.
• Implications of Big Data for research infrastructures in psychology and related areas.