Презентация на тему What a long, strange trip it’s been

Презентация на тему Презентация на тему What a long, strange trip it’s been, предмет презентации: Образование. Этот материал содержит 45 слайдов. Красочные слайды и илюстрации помогут Вам заинтересовать свою аудиторию. Для просмотра воспользуйтесь проигрывателем, если материал оказался полезным для Вас - поделитесь им с друзьями с помощью социальных кнопок и добавьте наш сайт презентаций ThePresentation.ru в закладки!

Слайды и текст этой презентации

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What a long, strange trip it’s been



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Outline of talk

The context
How did we end up where we are

What it is, status of adoption
Schema.org principles, how does it work

Looking ahead
Next Generation Applications


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About 18 years ago, …

People started thinking about structured data on the web
A few people from Netscape, Microsoft and W3C got together @MIT

Trying to make sense of a flurry of activity/proposals
XML, MCF, CDF, Sitemaps, …

There were a number of problems
PICS, Meta data, sitemaps, …

But one unifying idea


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Context: The Web for humans



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Goal: Web for Machines & Humans


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What does that mean?

Notable points
- Graph Data Model
- Common Vocabulary


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How do we get there?

How does the author give us the graph
Data Model: Graph vs tree vs …
Identifiers for objects

Why should the author give us the graph?


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Going depth first

Many heated battles
Lot of proposals, standards, companies, …

Data model
Trees vs DLGs vs Vertical specific vs who needs one?

XML vs RDF vs json vs …

Model theory anyone
We need one vs who cares vs what’s that?


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Timeline of ‘standards’

‘96: Meta Content Framework (MCF) (Apple)
’97: MCF using XML (Netscape) → RDF, CDF
’99 -- : RDF, RDFS
’03: Microformats
And many many many more … SPARQL, Turtle, N3, GRDDL, R2RML, FOAF, SIOC, SKOS, …

Lots of bells & whistles: model theory, inference, type systems, …


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But something was missing …

Fewer than 1000 sites were using these standards

Something was clearly missing and it wasn’t more language features

We had forgotten the ‘Why’ part of the problem

The RSS story


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’07 - :Rise of the consumers

Yahoo! Search Monkey, Google Rich Snippets, Facebook Open Graph

Offer webmasters a simple value proposition

Search engines to webmasters:
You give us data … we make your results nicer

Usage begins to take off
1000x increase in markup’ed up pages in 3 years


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Yahoo Search Monkey

Give websites control over snippet presentation
Moderate adoption
Targeted at high end developers
Too many choices


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Google Rich Snippets: Reviews


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Google Rich Snippets: Events


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Google Rich Snippets

Adhoc vocabulary for each vertical
Very clear carrot
Lots of experimentation on UI
Moderately successful: 10ks of sites
Scaling issues with vocabulary


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Situation in 2010

Too many choices/decisions for webmasters
Divergence in vocabularies
Too much fragmentation
N versions of person, address, …

A lot of bad/wrong markup
~25% for micro-formats, ~40% with RDFA
Some spam, mostly unintended mistakes

Absolute adoption numbers still rather low
Less than 100k sites


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Work started in August 2010
Google, Yahoo!, Microsoft & then Yandex

One vocabulary understood by all the search engines
Make it very easy for the webmaster

It is A vocabulary. Not The vocabulary.
Webmasters can use it together other vocabs
We might not understand the other vocabs. Others might


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Schema.org: Major sites

News: Nytimes, guardian.com, bbc.co.uk,
Movies: imdb, rottentomatoes, movies.com
Jobs / careers: careerjet.com, monster.com, indeed.com
People: linkedin.com,
Products: ebay.com, alibaba.com, sears.com, cafepress.com, sulit.com, fotolia.com
Videos: youtube, dailymotion, frequency.com, vinebox.com
Medical: cvs.com, drugs.com
Local: yelp.com, allmenus.com, urbanspoon.com
Events: wherevent.com, meetup.com, zillow.com, eventful
Music: last.fm, myspace.com, soundcloud.com


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Schema.org principles: Simplicity

Simple things should be simple
For webmasters, not necessarily for consumers of markup
Webmasters shouldn’t have to deal with N namespaces

Complex things should be possible
Advanced webmasters should be able to mix and match vocabularies

Microdata, usability studies
RDFa, json-ld, …


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Schema.org principles: Simplicity

Can’t expect webmasters to understand Knowledge Representation, Semantic Web Query Languages, etc.

It has to fit in with existing workflows
A posteriori ‘markup tools’ don’t work

Avoid KR system driven artifacts
Multiple domain / range for attributes
No classes like ‘Agent’
Categories and attributes should be concrete


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Schema.org principles: Simplicity

Copy and edit as the default mode for authors
It is not a linear spec, but a tree of examples

Authors only need to have local view
But schema.org tries to have a single global coherent vocabulary


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Schema.org principles: Incremental

Started simple
~ 100 categories at launch

Applies to every area
Add complexity after adoption
now ~1200 vocab items
Go back and fill in the blanks

Move fast, accept mistakes, iterate fast


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Schema.org Principles: URIs

~1000s of terms like Actor, birthdate
~10s for most sites
Common across sites

~10ks of terms like USA
External enumerations

~1b-100b terms like Chuck Norris and Ryan, Oklahama
Cannot expect agreement on these
Reference by description
Consumers can reconcile entity references


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Schema.org Principles: Collaborations

Most discussions on public W3C lists

Work closely with interest communities

Work with others to incorporate their vocabularies
We give them attribution on schema.org
Webmasters should not have to worry about where each piece of the vocabulary came from
Webmasters can mix and match vocabs


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Schema.org Principles: Collaborations

IPTC /NYTimes / Getty with rNews
Martin Hepp with Good Relations
US Veterans, Whitehouse, Indeed.com with Job Posting
Creative Commons with LRMI
NIH National Library of Medicine for Medical vocab.
Bibextend, Highwire Press for Bibliographic vocabulary
Benetech for Accessibility
BBC, European Broadcasting Union for TV & Radio schema
Stackexchange, SKOS group for message board
Lots and lots and lots of individuals


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Schema.org Principles: Partners

Partner with Authoring platforms
Drupal, Wordpress, Blogger, YouTube

Drupal 8
Schema.org markup for many types
News articles, comments, users, events, …
More schema.org types can be created by site author
Markup in HTML5 & RDFa Lite
Will come out early 2015


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Recent Additions

From Nouns to Verbs: Actions
Object → potential actions
Constraints on actions
E.g., ThorMovie → Stream, Buy, …

Introducing time: Roles
E.g., Joe Montana played for the SF 49ers from 1979 to 1992 in the position QuarterBack


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Recent Additions

Scholarly work, Comics, Serials, …
Communications: TV, Radio, Q&A, …
Commerce: Reservations
Buyer/Seller, etc.

The ontology is growing …
~800 properties
~600 classes


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Looking forward

Schema.org is doing better than we expected
Thanks to millions of webmasters!

But this is not the final goal
Just the means to the next generation of applications

First generation of applications
Rich presentation of search results

Many new applications
Related to search and beyond


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Newer Applications: Knowledge Graph


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Newer Applications: Knowledge Graph


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Non search applications: Google Now

User profile
structured data feeds


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Pinterest: Schema.org for Rich Pins


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Reservations ➔ Personal Assistant

Open Table website → confirmation email → Android Reminder


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Vertical Search

Structured data in search
Web search: annotate search results
Filtering based on structured data
Only in specialized corpus
Ecommerce, real estate, etc.

How about filtering based on structured data across the web?


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Google Rich Snippets: Recipe View


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Web scale vertical search

Searching for Veteran friendly jobs


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Web Scale custom vertical search

Build your own custom vertical search engine
Google does the heavy lifting: crawling, indexing, etc.
You specify the schema.org restricts
APIs to help build your own UI

Searches over all pages on the web with a certain schema.org markup



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Scientific Data Publishing

US Govt alone spends over $60B/yr on scientific research

Primary output of most of this research is data
Most of the data is thrown away
All that is published are papers

We would like the data published in a easily reusable form


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Case study: Clinical Trials

Clinical trials
4000+ clinical trials at any time in the US alone
Almost all the data ‘thrown away’
All that gets published is a textual ‘abstract’

Many of the trials are redundant
Earlier trials have the data
Assumptions, etc. cannot be re-examined
Longitudinal studies extremely hard, but super important

Having all the clinical trial data on the web, in a common schema will make this much easier!


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Case study: SkyServer

Huge amount of astronomy data

Jim Gray, NASA and others brought it all together, normalized it and made it available on the web

Has changed the way astronomy research takes place
Students in Africa getting PhDs without leaving Africa!
Radio/Ultra-violet/Visible light data easily brought together

SQL biased, not distributed, not scalable
All normalization done by hand, once
Small number of data sources
But shows that it can be done …


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First steps for scientific data publication

OPTC directive for data from federally funded research to be freely available

Formation of new ‘Data Science’ institute inside NIH

Seeing traction in scientific data on the web
Lot of interest in creating schemas
Public repositories for scientific data starting


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Structured data on the web is now ‘web scale’

Schema.org has got traction and is evolving

The most interesting applications are yet to come


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