dbis.ethz.ch | iMeMex.org

This paper presents HomeViews, a peer-to-peer middleware system for building personal data management applications. HomeViews provides abstractions and services for data organization and distributed data sharing. The key innovation in HomeViews is the integration of three concepts: views and queries from databases, a capability-based protection model from operating systems, and a peer-to-peer distributed architecture. Using HomeViews, applications can (1) create views to organize files into dynamic collections, (2) share these views in a protected way across the Internet through simple exchange of capabilities, and (3) transparently integrate remote views and data into a user’s local organizational structures. HomeViews operates in a purely peer-topeer fashion, without the need for account administration or centralized data and protection management inherent in typical data-sharing systems. We have prototyped HomeViews, deployed it on a small network of Linux machines, and used it to develop two distributed data-sharing applications: a peer-to-peer version of the Gallery photo-sharing application and a simple readonly shared file system. Using measurements, we demonstrate the practicality and performance of our approach.

Our lives are full of memorable and important moments, as well as important items of information. The last few years have seen the proliferation of digital devices intended to support prosthetic memory (PM), to help users recall experiences, conversations and retrieve personal information. We nevertheless have little systematic understanding of when and why people might use such devices, in preference to their own organic memory (OM). Although OM is fallible, it may be more efficient than accessing information from a complex PM device. We report a controlled lab study which investigates when and why people use PM and OM. We found that PM use depended on users ’ evaluation of the quality of their OM, as well as PM device properties. In particular, we found that users trade-off Accuracy and Efficiency, preferring rapid access to potentially inaccurate information over laborious access to accurate information. We discuss the implications of these results for future PM design and theory. Rather than replacing OM, future PM designs need to focus on allowing OM and PM to work in synergy.

The rapidly increasing quantity and diversity of data stored on our PCs made locating information in this environment very difficult. Consequently, recent research has focussed on building semantically enhanced systems for either organizing or searching data on the desktop. Building on previous work, in this paper we present the Beagle ++ toolbox, a set of extendable building blocks for implementing such a system. The corresponding modular desktop search architecture integrates our previously developed metadata generators and ranking components, uses an RDF database to share data between components, and can easily integrate other external components to improve desktop search quality. Additionally, we provide implementation details about all our current components, how they interact with each other, and how to install the complete system on top of a Linux distribution.

In contrast to classical databases and IR systems, real-world information systems have to deal increasingly with very vague and diverse structures for information management and storage that cannot be adequately handled yet. While current object-relational database systems require clear and unified data schemas, IR systems usually ignore the structured information completely. Malleable schemas, as recently introduced, provide a novel way to deal with vagueness, ambiguity and diversity by incorporating imprecise and overlapping definitions of data structures. In this paper, we propose a novel query relaxation scheme that enables users to find best matching information by exploiting malleable schemas to effectively query vaguely structured information. Our scheme utilizes duplicates in differently described data sets to discover the correlations within a malleable schema, and then uses these correlations to appropriately relax the users’ queries. In addition, it ranks results of the relaxed query according to their respective probability of satisfying the original query’s intent. We have implemented the scheme and conducted extensive experiments with real-world data to confirm its performance and practicality.

Abstract. Formal description of concepts so that it may be processed by computers has great promises for people with special needs. By making use of ontologies, improved user interaction with personal information management system is possible for these people. An ontology using semantic web technology is proposed which formally describes the mapping information about user’s impairments, and the available interface characteristics. Effort is made to enhance accessibility at a generic level by making it possible to enrich the ontology for a diverse range of users. Consequently users with all types of special needs are able to get already customized interfaces. Especially, the possible adaptation to our prototype Personal Information Management System SemanticLIFE [1] is the trigger for this investigation. 1

With the explosion in the amount of semi-structured data users access and store in personal information management systems, there is a need for complex search tools to retrieve often very heterogeneous data in a simple and efficient way. Existing tools usually index text content, allowing for some IR-style ranking on the textual part of the query, but only consider structure (e.g., file directory) and metadata (e.g., date, file type) as filtering conditions. We propose a novel multi-dimensional approach to semi-structured data searches in personal information management systems by allowing users to provide fuzzy structure and metadata conditions in addition to keyword conditions. Our techniques provide a complex query interface that is more comprehensive than content-only searches as it considers three query dimensions (content, structure, metadata) in the search. We propose techniques to individually score each dimension, as well as a framework to integrate the three dimension scores into a meaningful unified score. Our work is integrated in Wayfinder, an existing fully-functioning file system. We perform a thorough experimental evaluation of our techniques to show the effect of approximating individual dimensions on the overall scores and ranks of files, as well as on query performance. Our experiments show that our scoring strategy adequately takes into account the approximation in each dimension to efficiently evaluate fuzzy multi-dimensional queries. In addition, fuzzy query conditions in non-content dimensions can significantly improve scoring (and thus ranking) accuracy.

dbis.ethz.ch | iMeMex.org Abstract: We propose a new system that is able to handle the entire Personal Dataspace of a user. A Personal Dataspace includes all data pertaining to a user on all his disks and on remote servers such as network drives, email and web servers. This data is represented by a heterogeneous mix of files, emails, bookmarks, music, pictures, calendar data, personal information streams and so on. State-of-the-art tools such as desktop search engines and desktop operating systems (including the upcoming Vista) are not enough as they neither solve the problem of physical personal information independence (where is my data) nor format and data model independence (how is it stored and which application do I have to use in order to access that data). Our work builds on the visions presented in [DSKB05], which calls for a single system to manage the personal information jungle, and [FHM05], which advocates dataspaces as a new abstraction for information management. In contrast to [FHM05] this paper presents a concrete implementation of a Personal DataSpace Management System (PDSMS) termed iMeMex: integrated memex. We discuss the core architecture of iMeMex and

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Abstract. Semantic Desktop systems appear to be a promising infrastructure for context-aware applications that acquire and make use of user context information in order to provide more efficient interaction between the user and the system. In a systematic analysis, we have analyzed existing Semantic Desktop systems based on a collection of requirements and deduced from it architectural implications for future Semantic Desktop development. 1