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Asilomar Grand 10-Yr Vision [1998]

Transforming from closed data and info systems to open data agoras for collaborative storage, organization, access, and analysis of human information. Explore the potential of distributed autonomous peers and personalized search experiences. Participate in the emergence of contextualized, socialized, and decentralized environments for information retrieval and exchange.

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Asilomar Grand 10-Yr Vision [1998]

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  1. Asilomar Grand 10-Yr Vision [1998] Far from this: Personal differences Much will remain unorganized, autonomous The Information Utility: Make it easy for everyone to store, organize, access, and analyze the majority of human information online. Much more than access & analysis: collaboration & socialization

  2. Emerging Environments Distributed autonomous peers - access to each others’ data/services thru (transitive) interaction - offering search & other data services for individuals & groups

  3. Search Uncertainty • User may have no knowledge of • System’s actual cost (in work, time, $, …) • Quality of results (wrt freshness, completeness, …) • Origin of results (system’s original or brought in w/) • … • System may have no knowledge of user’s • True needs behind a request • Financial capacity, patience • Quality desires • Risk averseness • Content preferences • …

  4. Emerging Environments Querying/Searching for information should be similar to buying material goods and services in real life

  5. Search/Query Optimization • Multiple criteria • Processing (work, time), result (freshness, completeness, interestingness), money, … • Market research • For data availability, data quality, processing cost, … • Quality Control • Learning of peers’ +’s and –’s • Insurance contracts for quality/cost guarantees • Negotiation • Queries and their results are commodities • Query answers and query operator executions are traded • Deals are struck and contracts are “signed” for specific QoS • Recursive trading possibilities (subcontracting)

  6. Personalization • All aspects of search/querying could be personalized • Systems employ user models & maintain evolving profilesof personalities (preferences, needs) of individuals & groups • Queries (user interfaces, sense of object similarity, …) • Info source (trust of peers, quality parameters, …) • Results (objects of interest, presentation, …) • Profile parts activated at various stages • Query rewriting based on content preferences • Feature-set selection for similarity testing • Choice of information sources or optimization criteria • Socialization, collaboration • Privacy vs. personalization

  7. Contextualization • All aspects of search/querying could depend on the context • Context may include the searcher (personalization), location, time, history, other users present, … • Context modeling, context detection, … Expensive processing Extensive results Quicker answers Shorter result list CFP: VLDB’08 2nd Workshop on “Personalization, Profile-Management, & Context-Dependence in Databases” Deadline: June 1, 2008 http://persdb08.stanford.edu/home.html

  8. Personal Grand 10-Yr Vision [2008] From Closed Data & Info Systems to Open Data & Info Agoras

  9. Open Agoras Agora (ag·o·ra) : A gathering place; especially: the marketplace in ancient Greece • A place where people • congregate and discuss • shop for goods

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