social web meets semantic web

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Where the Social Web Meets the Semantic Web:

Where the Social Web Meets the Semantic Web Tom Gruber

Doug Engelbart, 1968:

Doug Engelbart, 1968 "The grand challenge is to boost the collective IQ of organizations and of society. "

Tim Berners-Lee, 2001:

Tim Berners-Lee, 2001 “The Semantic Web is not a separate Web but an extension of the current one, in which information is given well-defined meaning, better enabling computers and people to work in cooperation.” Scientific American, May 2001

Tim O’Reilly, on Web 2.0:

Tim O’Reilly, on Web 2.0 "The central principle behind the success of the giants born in the Web 1.0 era who have survived to lead the Web 2.0 era appears to be this, that they have embraced the power of the web to harness collective intelligence "

Web 2.0 is about The Social Web:

Web 2.0 is about The Social Web diagram source: “Web 2.0 Is Much More About A Change In People and Society Than Technology” 1 billion people connect to the Internet 100 million web sites over a third of adults in US have contributed content to the public Internet. - 18% of adults over 65 source: Pew Internet and American Life Project via -Dion Hinchcliffe, tech blogger

Tim Berners-Lee:

Tim Berners-Lee “The Web isn’t about what you can do with computers. It’s people and, yes, they are connected by computers. But computer science, as the study of what happens in a computer, doesn’t tell you about what happens on the Web.”

But what is “collective intelligence” in the social web sense?:

But what is “collective intelligence” in the social web sense? intelligent collection? collaborative bookmarking, searching “database of intentions” clicking, rating, tagging, buying what we all know but hadn’t got around to saying in public before blogs, wikis, discussion lists “database of intentions” – Tim O’Reilly

the wisdom of clouds?:

the wisdom of clouds?

“Collective Knowledge” Systems:

“Collective Knowledge” Systems The capacity to provide useful information based on human contributions which gets better as more people participate. typically mix of structured, machine-readable data and unstructured data from human input

Collective Knowledge is Real:

Collective Knowledge is Real FAQ-o-Sphere - self service Q&A forums Citizen Journalism – “We the Media” Product reviews for gadgets and hotels Collaborative filtering for books and music Amateur Academia

What about the Semantic Web?:

What about the Semantic Web?

Roles for Technology:

Roles for Technology capturing everything storing everything distributing everything enabling many-to-many communication creating value from the data

Potential Roles for Semantic Net Technology: Two examples:

Potential Roles for Semantic Net Technology: Two examples Composing and integrating user-contributed data across applications example: tagging data Creating aggregate value from a mix of structured and unstructured data example: blogging data

“Ontology is overrated.” -- Clay Shirky:

“Ontology is overrated.” -- Clay Shirky “[tags] are a radical break with previous categorization strategies” hierarchical, centrally controlled, taxonomic categorization has serious limitations e.g., Dewey Decimal System free-form, massively distributed tagging is resilient against several of these limitations


But... ontologies aren’t taxonomies they are for sharing, not finding they enable cross-application aggregation and value-added services

Ontology of Folksonomy:

Ontology of Folksonomy What would it look like to formalize an ontology for tag data? Functional Purpose: applications that use tag data from multiple systems tag search across multiple sites collaboratively filtered search “find things using tags my buddies say match those tags” combine tags with structured query “find all hotels in Spain tagged with “romantic”

Example: formal match, semantic mismatch:

Example: formal match, semantic mismatch System A says a tag is a property of a document. System B says a tag is an assertion by an individual with an identity. Does it mean anything to combine the tag data from these two systems? “Precision without accuracy” “Statistical fantasy”

Engineering the tag ontology:

Engineering the tag ontology Working with tag community, identify core and non core agreements Use the process of ontology engineering to surface issues that need clarification Couple a proposed ontology with reference implementations or hosted APIs

Core concepts:

Core concepts Term – a word or phrase that is recognizable by people and computers Document – a thing to be tagged, identifiable by a URI or a similar naming service Tagger – someone or thing doing the tagging, such as the user of an application Tagged – the assertion by Tagger that Document should be tagged with Term

Issues raised by ontological engineering:

Issues raised by ontological engineering is term identity invariant over case, whitespace, punctuation? are documents one-to-one with URI identities? (are alias URLs possible?) can tagging be asserted without human taggers? negation of tag assertions? tag polarity – “voting” for an assertion tag spaces – is the scope of tagging data a user community, application, namespace, or database?

Volunteers Needed :

Volunteers Needed  Applications that need shared tagging data Tag spaces and sources of tag data Ontology engineers who can run an open source-style project

Role 2: Creating aggregate value from structured data:

Role 2: Creating aggregate value from structured data Problem: In a collective knowledge system, the value of the aggregate content must be more than sum of parts Approach: Create aggregate value by integrating user contributions of unstructured content with structured data.

Example: Collective Knowledge about Travel:

Example: Collective Knowledge about Travel RealTravel attracts people to write about their travels, sharing stories, photos, etc. Travel researchers get the value of all experiences relevant to their target destinations.

Pivot Browsing – surfing unstructured content along structured lines:

Pivot Browsing – surfing unstructured content along structured lines Structured data provides dimensions of a hypercube location author type date quality rating Travel researchers browse along any dimension. The key structured data is the destination hierarchy Contributors place their content into the destination hierarchy, and the other dimensions are automatic.

Destination data is the backbone:

Destination data is the backbone Group stories together by destination Aggregate cities to states to countries, etc Inherit locations down to photos From destinations infer geocoordinates, which drive dynamic route maps Destinations must map to external content sources (travel guides) Destinations must map to targeted advertising

Contextual Tagging:

Contextual Tagging Tags are bottom up labels, words without context. A structured data framework provides context. Combining context and tags creates insightful slices through the aggregate content.

Problems that Semantic Web could have helped:

Problems that Semantic Web could have helped No standard source of structured destination data for the world or way to map among alternative hierarchies Integrating with other destination-based sites is expensive e.g. travel guides No standard collection of travel tags or way to share RealTravel’s folksonomy Integrating with other tagging sites is ad hoc need a matching / translation service

Resources That Did Help:

Resources That Did Help Open source software or free services powerful databases fancy UI libraries search engines usage analytics Open APIs from Google (maps) and Flickr (photos) Commercially available geocoordinate data and services

(Semantic Web) projects that could help collective knowledge systems:

(Semantic Web) projects that could help collective knowledge systems Tag spaces and tag data sharing World destination hierarchy and other geocoordinate databases Portable user identity and reputation Site-independent rating and filtering Alternatives to Google-style search __audience contributions here___

Activities already going:

Activities already going Semantically-Interlinked Online Communities (SIOC) semantic wiki projects __audience contributions here___

Challenges for our Community:

Challenges for our Community How to get knowledge from all those intelligent people on the Internet How to give everyone the benefit of everyone else’s experience How to leverage and contribute to the ecosystem that has created today’s web.

What will the future look like?:

What will the future look like? Social Web Social + Semantic Web