A DTP and SoLiD based Service for Multi-Source Semantically-Heterogeneous Personal Data Management

Abstract

Privacy preservation is drawing growing concern. Due to personal data of massive users is centralizedly owned/managed by service providers at present, it is very easy to lead to privacy disclosure and personal data abuse, therefore many countries and regions put forward privacy protection laws and regulations and researchers also propose some de-centralized personal data management systems. Nevertheless, the implementation of decentralized data management model means a radical change in current service development and service model. For service providers, it is too difficult and costly to realize these personal data management systems, and there are also no additional economic benefits. These personal data management systems are too ideal to popularize from a business model perspective, so the development of decentralized models proceeds slowly. In response to this situation, we propose a new personal data management service which realizes the transition stage between reality and ideal where users’ data can exist both in users’ personal data cloud and service providers. To address the challenges of data collection and data semantic uniformity caused by personal data cloud at this transition stage, we propose a personal data management architecture based on SoLiD (Social Linked Data) and DTP (Data Transfer Project). The proposed architecture could transfer users’ data from service providers to personal data cloud and fuse heterogeneous data through data fusion technology so as to provide users with the ability to manage their own data and a unified view of data. The feasibility and efficiency of the proposed service are practically proved through conducting a case study.