BibTeX
@MISC{Weikum_databaseresearchers:,
author = {Gerhard Weikum},
title = {Database Researchers: Plumbers or Thinkers?},
year = {}
}
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Abstract
DB researchers have traditionally focused on engine-centered issues such as indexing, query processing, and transactions. Data mining has broadened the community’s viewpoint towards algorithmic and statistical issues. However, DB research has always had a tendency to shy away from seemingly elusive long-term challenges with AI flavor. On the other hand, the current explosion of digital content in enterprises and the Internet, is mostly caused by user-created information like text, tags, photos, videos, and not by seeing more well-designed databases of the traditional kind. In this situation, I question the traditional skepticism of DB researchers towards “AI-complete ” problems and the DB community’s reluctance to embark on seemingly non-DB-ish grand challenges. Big questions that I see as great opportunities also for DB research include: 1) automatic extraction of relational facts from naturallanguage
Keyphrases
database researcher db researcher ai flavor elusive long-term challenge digital content user-created information data mining current explosion engine-centered issue relational fact statistical issue db research db community reluctance great opportunity non-db-ish grand challenge well-designed database db research include traditional kind viewpoint towards automatic extraction big question traditional skepticism query processing ai-complete problem
