Resumen
This article's aim is to advocate for the integration of database systems (DB) and information-retrieval (IR) methods to address applications that are emerging from the ongoing explosion and diversification of digital information. One grand goal of such an endeavor is the automatic building and maintenance of a comprehensive knowledge base of facts from encyclopedic sources and the scientific literature. Facts should be represented in terms of typed entities and relationships and allow expressive queries that return ranked results with precision in an efficient and scalable manner. The article thus explores how DB and IR methods might contribute toward this ambitious goal. Here are DB and IR concepts and methods a developer would find useful: 1. approximate matching and record linkage, 2. too-many-answers ranking, 3. schema relaxation and heterogeneity, 4. information extraction and uncertain data, and 5. entity search and ranking.

Resumen
A group of database researchers, architects, users, and pundits met in May 2008 at the Claremont Resort in Berkeley, CA, to discuss the state of database it search and its effects on practice. This was the seventh meeting of this sort over the past 20 years and was distinguished by a broad consensus that the database community is at a turning point in its history, due to both an explosion of data and usage scenarios and major shifts in computing hardware and platforms. This article explores the conclusions of this self-assessment. The theme of the Claremont meeting was that database research and the data-management industry are at a turning point, with unusually rich opportunities for technical advances, intellectual achievement, entrepreneurship, and benefits for science and society. Given the large number of opportunities, it is important for the database research community to address issues that maximize relevance within the field, across computing, and in external fields as well.