Spatiotemporal Applications of Big Data

Abstract

Big data has emerged as a field of study and gained huge importance these days for both industry and researcher's point of view. Initially database management systems (DBMS) developed to solve data management and relevant queries. Relational DBMS (RDBM) gave another innovation to the database field. Through the passage of time, it observed that some issues remained unsolved and required some more dimensions be added to the data. One of those was time and the other was location. Spatiotemporal aspects of data gained importance and scientists thought of incorporating these in the upcoming databases. This paper covers the inclusion of these dimensions in a database and its applications in today's world. It also compares some of the tools used these days and suggests a combination for better results in an efficient and cost-effective way.