1 / 5

Overcoming Semantic Heterogeneity in Data Management: Insights from Mike Stonebraker

Explore the challenges of semantic heterogeneity, data integration, and information retrieval in data warehouse and web service projects through the expert perspective of Mike Stonebraker, Adjunct Professor at MIT. Discover solutions to complex currency, salary, and product mapping issues. Learn about Google for structured data and its potential impact on data modeling, query languages, and site integration with a focus on overcoming semantic barriers.

harryl
Download Presentation

Overcoming Semantic Heterogeneity in Data Management: Insights from Mike Stonebraker

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Mike Stonebraker’s Two Bullets Michael Stonebraker Adjunct Professor Massachusetts Institute of Technology (stonebraker@lcs.mit.edu)

  2. Bullet 1: Semantic Heterogeneity • Achilles heel of data warehouse projects • And information integration • And soon of web services • Easy part is euros to/from dollars • Harder is French salary to/from U.S. salary • Hardest is latex gloves to/from rubber hand protectors

  3. Bullet 1: Semantic Heterogeneity • Worked on ever since I have been an adult • With little progress • At some point we need to work on the important stuff…..

  4. Bullet 2: Google for Structured Data • What is the current temperature in Lowell? • Is Flight 214 on time? • Where can I buy pocket protectors?

  5. Bullet 2: Google for Structured Data • Data model • Not likely to be text • Query language • NL doesn’t work (and won’t anytime soon) • Integration of 10** 6 sites • Semantic heterogeneity…… • Site finding --UDDI is a start • Scalability -- 10**6 gateways?

More Related