mercredi 28 septembre 2016

Personal information management systems and knowledge integration

Personal data is constantly collected, either voluntarily by users in emails, social media interactions, multimedia objects, calendar items, contacts, etc., or passively by various applications such as GPS of mobile devices, transactions, quantified self sensors, etc. The processing of personal data is complicated by the fact that such data is typically stored in silos with different terminologies/ontologies, formats and access protocoles. Users are more and more loosing control over their data; they are sometimes not even aware of the data collected about them and how it is used.
We discuss the new concept of Personal Information Management Systems (PIMS for short) that allows each user to be in a position to manage his/her personal information. Some applications are run directly by the PIMS, so are under direct control of the user. Others are in separate systems, that are willing to share with the PIMS the data they collect about that particular user. In that later case, the PIMS is a system for distributed data management. We argue that the time has come for PIMS even though the approach requires a sharp turn from previous models based on the monetisation of personal data. We consider research issues raised by PIMS, either new or that acquire a new flavor in a PIMS context.
We also present works on the integration of user’s data from different sources (such as email messages, calendar, contacts, and location history) into a PIMS. The PIMS we consider is a Knowledge Base System based on Semantic Web standards, notably RDF and Some of the knowledge is “episodical” (typically related to spatio-temporal events) and some is “semantic” (knowledge that holds irrelative to any such event). Of particular interest is the cross enrichment of these two kinds of knowledge based on the alignment of concepts, e.g., enrichment between a calendar and a geographical map using the location history. The goal is to enable users via the PIMS to query and perform analytics over their personal information within and across different dimensions.

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