Assuring Data Trustworthiness - Concepts and Research Challenges

Download Book (4,214 KB) As a courtesy to our readers the eBook is provided DRM-free. However, please note that Springer uses effective methods and state-of-the art technology to detect, stop, and prosecute illegal sharing to safeguard our authors’ interests.
Download Chapter (291 KB)

Abstract

Today, more than ever, there is a critical need to share data within and across organizations so that analysts and decision makers can analyze and mine the data, and make effective decisions. However, in order for analysts and decision makers to produce accurate analysis and make effective decisions and take actions, data must be trustworthy. Therefore, it is critical that data trustworthiness issues, which also include data quality, provenance and lineage, be investigated for organizational data sharing, situation assessment, multi-sensor data integration and numerous other functions to support decision makers and analysts. The problem of providing trustworthy data to users is an inherently difficult problem that requires articulated solutions combining different methods and techniques. In the paper we first elaborate on the data trustworthiness challenge and discuss a framework to address this challenge. We then present an initial approach for assess the trustworthiness of streaming data and discuss open research directions.