A time series data management framework

Abstract

In the real world there are thousands of time series data that coexists with other data. Every day tons of data is collected in the form of time series. Time series is a collection of observations that is recorded or measured over time on a regular or irregular basis generally sequentially. Time series arise in financial, economic, and scientific applications. Typical examples are the recording of different values of stock prices, bank transactions, consumer price index, electricity and telecommunication data, etc. In theory, such data is processed, analyzed, disseminated, and presented. However, many institutions are facing some difficult issues in organizing such a vast amount of data. Therefore, the need for data management tools has become more and more important. This paper addresses this issue by proposing a framework for Time Series Data Management (TSDM). The central abstraction for the proposed domain specific framework is the notion of Business Sections, Group of Time Series, and Time Series itself. The framework integrates minimum specification regarding structural and functional aspects for time series data management.