1 / 21

Weaving Your Own Semantic Web

Weaving Your Own Semantic Web. Dennis Quan December 4, 2002. “Information at your fingertips”. Where are we now? How did we get here? Where are we headed? Who has done this before? Why might this not work? What can we do about it? What will “the user” think?. The status quo.

nansen
Download Presentation

Weaving Your Own Semantic Web

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. Weaving Your Own Semantic Web Dennis Quan December 4, 2002

  2. “Information at your fingertips” • Where are we now? • How did we get here? • Where are we headed? • Who has done this before? • Why might this not work? • What can we do about it? • What will “the user” think?

  3. The status quo • The Web is a great place to find all sorts of information: • Weather forecasts • News reports • Stock charts • Phone numbers and addresses • TV program schedules and reviews • Airline reservations • … and much, much more

  4. The origins of the Web • Physicist turned hacker Tim Berners-Lee developed method for linking together network-accessible documents • HTML: easy to read, easy to write, easy to share • HTTP: universal transport for getting at shared documents via Web browsers • Apache, Perl, et al.: easy to hack together scripts for producing Web content en masse • Mosaic, Internet Explorer, Mozilla, etc.

  5. The future of the Web • Today’s Web is great, but… • Users: give them an inch; they want a mile • Vicious (virtuous?) cycle of automation • Right now most Web content is human-readable • “04 05 2002”: part number? birthdate? price? • Possibilities for automation are limited • Screen scraping: pre-interpreting pieces of Web content for use by scripts • Semantic Web: make Web content machine-readable in the first place

  6. Oh, the possibilities! • Once content is directly interpretable, barriers to creative use of such content will be lowered • Appointment scheduling • Price comparison and negotiation • Ontology-based search • Examples: • Find me the cheapest French-speaking city to fly to in March and a hotel others found to be “romantic”. • Schedule the meetings that must occur today for the afternoon and postpone the rest until the next 3 days. • Where can I buy A Tale of Two Cities for the cheapest? I’m willing to buy used if the cost savings is at least 50%.

  7. Lingua franca • Resource Description Framework (RDF): “circle and arrow diagram” method for encoding knowledge Book type A Tale of Two Cities author Charles Dickens price $10.95

  8. Agents • Programs that do things on behalf of humans Honest Joe’s Used Books $4.95 says used price A Tale of Two Cities Good condition says $10.95 price Acme Books

  9. Déjà vu? • Flexible data representation • Knowledge representations, ontologies and descriptive logic systems? • Relational databases? • Number crunching and deduction • Internet price search engines? • Perl scripts? • Multi-agent environments?

  10. Problem #1: information • Information for the Semantic Web must come from somewhere • CyC approach • Spend $25m and 20 years time • Results in highly consistent corpus • Problem: requires $25m and 20 years time • Distributed approach • Piece by piece incrementally • Each user contributes • Problem: requires tools for inputting information

  11. Problem #2: “Grandma” • Grandma doesn’t know about SLAD-DOS: • Scripting • Logic • Agent interaction • Data types • Distributed systems • Ontologies • Schemas • Technology irrelevant if user interface cannot expose it

  12. Problem #3: the web monkey • Web monkeys like: • Simple, easy-to-understand languages (e.g., JavaScript, Perl, HTML) • Granular, hands-on, reusable components (e.g., CGI scripts, Web pages, Java applets) • Ability to cycle through edit-run-debug quickly (e.g., with a Web browser)

  13. Grandma wants to: Tell her friends how great the toaster she bought is Find a romantic comedy on TV tonight Get a doctor’s appointment when Days of Our Lives isn’t on See latest pictures of grandchildren Web monkey will need: Distributed, P2P database with flexible schema Sophisticated Boolean query language Online representation of personal calendars and agent negotiation protocol Content management system The generation gap

  14. RDF to the rescue • Distributed: easily shared between systems and highly granular • Flexible: doesn’t restrict how people think about their information • Plus all the benefits of 50 years of AI and database research RDF

  15. Web monkeys like toys • Standard RDF databases • RDF-enabled scripting language • Distributed agent communication layer • Transports RDF over SOAP, POP3, SMTP, etc. • Drag and drop ontology designers … kind of like httpd, perl, and mysql DB + scripting RDF

  16. Toys that let users play • If users don’t tell their computers things, agents will have nothing to work with • PIM that automagically records calendar, address book, e-mail, to-do list, etc. as RDF • Editors that can take RDF ontologies written by developers and intelligently allow input from users … kind of like Web browsers and e-mail clients UI components DB + scripting RDF

  17. Making use of the toys • Users must be able to ask their computers for their information • Natural language schemas for mapping onto RDF representations • Natural language query engines (e.g. START) • Agents must be made easily accessible • Users maintain their own agents much like they do their bookmark collections … kind of like Google and Priceline.com Agents + search UI components DB + scripting RDF

  18. Sharing your toys • Not all users will understand how to model data • Let those who can share their ontologies • Make the UI capable of finding these ontologies automatically • Must also model “hints” or “templates” that give users suggested defaults • UI components and agents must also be sharable • “Onto-Google”?

  19. Client? Server?What’s the difference? • Both users and developers create content • Both clients and servers store information in RDF • Agents can reside on users’ machines (personal agents) or can be distributed across the Internet (like Web Services) • Truly peer-to-peer

  20. A fantasy?

  21. Exercises for the reader • My home page (http://www.ai.mit.edu/people/dquan/) • Haystack (http://haystack.lcs.mit.edu/) • Semantic Web (http://www.w3.org/2001/sw/) • RDF (http://www.w3.org/RDF/) Thank you for your attention

More Related