International Journal of Human-Computer Studies
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Finding relevant and reliable information on the web is a non-trivial task. While internet search engines do find correct web pages with respect to a set of keywords, they often cannot ensure the relevance or reliability of their content. An emerging trend is to harness internet users in the spirit of Web 2.0, to discern and personalize relevant and reliable information. Users collaboratively search or browse for information, either directly by communicating or indirectly by adding meta information (e.g., tags) to web pages. While gaining much popularity, such approaches are bound to specific service providers, or the Web 2.0 sites providing the necessary features, and the knowledge so generated is also confined to, and subject to the whims and censorship of such providers. To overcome these limitations we introduce COBS, a browser-centric knowledge repository which enjoys the inherent openness (similar to Wikipedia) while aiming to provide end-users the freedom of personalization and privacy by adopting an eventually hybrid/p2p back-end. In this paper we first present the COBS front-end, a browser add-on that enables users to tag, rate or comment arbitrary web pages and to socialize with others in both a synchronous and asynchronous manner. We then discuss how a decentralized back-end can be realized. While Distributed Hash Tables (DHTs) are the most natural choice, and despite a decade of research on DHT designs, we encounter several, some small, while others more fundamental shortcomings that need to be surmounted in order to realize an efficient, scalable and reliable decentralized back-end for COBS. To that end, we outline various design alternatives and discuss qualitatively (and quantitatively, when possible) their (dis-)advantages. We believe that the objectives of COBS are ambitious, posing significant challenges for distributed systems, middleware and distributed data-analytics research, even while building on the existing momentum. Based on experiences from our ongoing work on COBS, we outline these systems research issues in this position paper.