A tool for personal data extraction

• Published in: 2014 IEEE 30th International Conference on Data Engineering Workshops pp. 80 - 83
• Main Authors: Vianna, Daniela, Yong, Alicia-Michelle, Chaolun Xia, Marian, Amelie, Nguyen, Thu
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.03.2014
• Subjects: Data mining; Data models; Electronic mail; Facebook; Google; Knowledge discovery
• DOI: 10.1109/ICDEW.2014.6818307

Digital storage now acts as an archive of the memories of users worldwide, keeping record of data as well as the context in which the data was acquired. The massive amount of data available and the fact that it is fragmented across many services (e.g., Facebook) and devices (e.g., laptop) make it very difficult for users to find specific pieces of information that they remember having stored or accessed. Unifying this fragmented data into a single data set that includes contextual information would allow for much better indexing and searching of personal information. Thus, we have developed a personal data extraction tool as a first step toward this vision. In this paper, we present this extraction tool, along with some preliminary statistics about personal data gathered by the tool for several users. The goal of the data analysis is to give a glimpse of what the digital life of a person may look like, and how it is currently partitioned across many different services; moreover, it reinforces the fact that it is not possible for users to manually retrieve, store and access their extensive digital data without the support of a personalized information management tool.