Where the Social Web Meets the Semantic Web
Description
The Semantic Web is an ecosystem of interaction among computer systems. The social web is an ecosystem of conversation among people. Both are enabled by conventions for layered services and data exchange. Both are driven by human-generated content and made scalable by machine-readable data. Yet there is a popular misconception that the two worlds are alternative, opposing ideologies about how the web ought to be. Folksonomy vs. ontology. Practical vs. formalistic. Humans vs. machines. This is nonsense, and it is time to embrace a unified view. I subscribe to the vision of the Semantic Web as a substrate for collective intelligence. The best shot we have of collective intelligence in our lifetimes is large, distributed human-computer systems. The best way to get there is to harness the "people power" of the Web with the techniques of the Semantic Web. In this presentation I will show several ways that this can be, and is, happening.
| Slides | |
| 0:00 | Where the Social Web Meets the Semantic Web |
| 1:31 | Where the Social Web Meets the Semantic Web |
| 3:20 | Doug Engelbart, 1968 |
| 4:37 | Tim Berners-Lee, 2001 |
| 5:15 | Tim O’Reilly, 2006, on Web 2.0 |
| 6:39 | Web 2.0 is about The Social Web |
| 8:15 | Tim Berners-Lee, 5 days ago |
| 9:10 | But what is “collective intelligence” in the social web sense? |
| 10:13 | the wisdom of clouds? |
| 10:45 | “Collective Knowledge” Systems |
| 11:30 | Collective Knowledge is Real |
| 13:02 | What about the Semantic Web? |
| 13:16 | Roles for Technology |
| 14:01 | Potential Roles for Semantic Net Technology: Two examples |
| 14:50 | “Ontology is overrated.” -- Clay Shirky |
| 15:49 | But... |
| 16:53 | Ontology of Folksonomy |
| 18:48 | Example: formal match, semantic mismatch |
| 19:39 | Engineering the tag ontology |
| 20:29 | Core concepts |
| 20:56 | Issues raised by ontological engineering |
| 23:33 | Volunteers Needed ? |
| 24:55 | Role 2: Creating aggregate value from structured data |
| 26:15 | Role 2: Creating aggregate value from structured data |
| 26:30 | Example: Collective Knowledge about Travel |
| 27:07 | TITLE |
| 27:36 | Pivot Browsing – surfing unstructured content along structured lines |
| 29:40 | Destination data is the backbone |
| 31:29 | TITLE |
| 31:42 | TITLE |
| 31:56 | Contextual Tagging |
| 33:25 | TITLE |
| 33:53 | TITLE |
| 34:38 | Problems that Semantic Web could have helped |
| 37:17 | Resources That Did Help |
| 38:05 | (Semantic Web) projects that could help collective knowledge systems |
| 42:08 | Activities already going |
| 42:28 | What will the future look like? |
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