Big Data

The emergence of big data has cut across research disciplines and applications - from architecture to urban planning; art history to economics. More and more fields that traditionally worked with qualitative (non-numeric) data now have access to relevant and robust big datasets, with big research potential. This book introduces researchers to big data sources, concepts and applications, showing best practices in use and what we can and cannot do with it. It starts by defining the key distinctions between "data" and "big data", practical considerations in moving to real world applications, and considers the methods and ways in which big data is used. It is not a technical book (of which there are many) but an introduction to a new research method, and includes case studies and applications from across disciplines (in the social sciences, arts and humanities). Readers are signposted to more detailed resources they can explore (e.g. software, datasets, tutorials) and how these have been used in research practice with various different formats of big data. The authors take a non-technical approach to introducing big, novel and often complex data for applied research in the social sciences - targeted at those with primarily no background in using big data. It will be essential resource for students, researcher and practitioners.