Evolution Towards Web30 Semantic Web 110531013826 Phpapp01

8/6/2019 Evolution Towards Web30 Semantic Web 110531013826 Phpapp01

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Happy to go off track and follow the thread of any interesting questions and discussion

that arise as we go.

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See http://www.w3.org/2009/Talks/0427-web30-tbl/ for Tim Berners-Lees take on

many of these same themes.

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Im not going to dwell on this, because everyone in this class by now surely has a

deeper and more sophisticated understanding of how we got to where we are. But

looking at the steps to this point in the context of a timeline may help us understandthe current Semantic Web landscape.

Two key characteristics of the birth and success of Web 1.0:

1. From the very beginning was founded on democratic principles of no nodes in the

Web being privileged anyone can link to anyone

2. There were (relatively speaking) very few data publishers in the Web initially. Most

users browsed only to consume information.

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The AJAX technology stack allowed developers to create mature Web applications

(approaching parity with fat-client applications) rather than (only) Web pages. It also

began allowing Web content to be repurposed to applications beyond the browser(desktop, embedded devices, mobile devices, ).

Eventually, these Web applications began allowing Web users to contribute to parts of

the Web rather than (only) consume Web pages.

Beginning in 2002, Web thought leaders (esp. Dale Dougherty, Tim OReilly, John

Battelle) began referring to the confluence of user-generated content, Web-as-

platform, social Web, read-write Web, wisdom of crowds, as Web 2.0.

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At the physical level, computers are connected to switches, routers, etc. network

links.

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The Internet directly links machines by abstracting away the network-link boundaries.

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Each computer participating in the Web (Web server) is providing access to many

documents (Web pages). The Web lets us make links between these documents.

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The Web lets us abstract away the computers and the Internet and focus on the linked

documents.

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But people are rarely interested in the documents. Theyre interested in the

informationthe datawithin the documents.

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The Semantic Web abstracts away the documents (the sources of the information), and

leaves us with data linked together. Linked Data, Web of Data, etc. This is the Web

part ofSemantic Web.

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It also gives us the tools to understand the Web of data and bring structure

(understanding) to it. This is the semantics part ofSemantic Web.

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Tim Berners-Lee first used the term Semantic Web to describe a vision for the future of

the Web as early as the first WWW conference in 1994.

Along with Jim Hendler and Ora Lasila, he laid out this vision in a 2001 article in

Scientific American.

In 2007, the birth of the Linking Open Data project saw the first real concerted efforts

to build out the Semantic Web by publishing data sets on the Web that could be

queried and linked to one another.

2008-2010 saw significant uptake in Semantic Web support on the Web and insideenterprises, highlighted by support from Google and Yahoo and data from Best Buy, NY

times, US and UK governments. (Also: Drupal support in Drupal 7 and FaceBook Open

Graph Protocol (2010)).

This is a long time span, and yet many (myself included) would hesitate to say that the

Semantic Web (Web 3.0) is here. When will that day come? How do we tell?

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Whats been happening this whole time? (Between the introduction of the vision and

today.) A lot of technology, standards, tool, and product development. Also, a lot of

advocacy.

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This is the ultimate vision as per the original Scientific American article. Referred to last

week as the top-down approach.

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Many of the people that have been building the technologies, standards, and tools are

doing so with these ends in mind. They have (disruptive, game-changing) problems

today and these technologies provide a way to solve them today.

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Different nuances, but the same actual thing. Still, you can often tell a lot about

someones view ofSemantic Web based on the terms they choose to you to describe it.

Linked Data Web has been relatively speaking successful in gaining traction.

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Ideas?

Incremental value improved efficiency

Link/integrate beyond traditional enterprise sources greater value, more appealing

partner

Shadow data (emails, documents, spreadsheets, presentations, )

Partner data (upstream/downstream supply chain, customers, partners,

channels, )

Needle in haystack (reasoning, inference, rules) greater value

Reach improved efficiency

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On the Web, the advent ofSemantic Web is about moving the paradigm from

document-centric to data-centric. The enterprise has elements of that too, but more

often than not within enterprise IT semantics is about moving from relational database

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Important to the enterprise value proposition: this is overlay technology that does not require an ove


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(This slide best told with animation in the original PowerPoint.)

The Semantic Web paradigms allows new and updated data to be brought into the

fold incrementally, without starting over. This makes it particularly amenable to

changing requirements.

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Cray Proprietary 25


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Databases that traditionally manage enterprise data are ITartifacts. Theyre crafted by

IT, for IT: asking scientists or other business domain experts to understand a relational

model with scores of tables, IDs, key/value tables, unused columns, etc. is completely

unrealistic.

The semantic model is a conceptual model. It eschews IDs, keys, etc. in favor of

concepts and relationships expressed/expressible in human language. This is reflected

in software that is built with Semantic Web data. This means that when a researcher is

linking their results spreadsheet, theyre dealing only in concepts that theyre familiar

with (organism, cell line, % inhibition, 4P, IC50, etc.). And that in turn means that this

approach works regardless of whatever spreadsheet layout a particular collaborator is

using: researchers can continue using their current spreadsheets, with no change.

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Were not yet at the point where the Semantic Web is a magic crank. Its not yet:

An automated way for pharmaceutical companies to discover new drugs for their

pipelines

An automated way for oil and gas companies to identify productive drilling locations

The (generic, intelligent) travel butler, or other autonomous Web-based agent

But nevertheless, a lot of people are embracing linked data in a lot of ways, and a lot of

companies are using Semantic Web technologies and a linked data approach

successfully today. What follows are some examples.

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Web 1.0 and Web 2.0(+) are core parts of our lives, from readingCNN.com to buying

things on amazon.com to facebook and twitter and Web-delivered mobile apps for

scanning bar codes, looking up music, etc.

Web 3.0 is not so obvious. The answer to the question is at least occasionally, but you

probably never see it.. Well see some examples of where you might be seeing the

fringes of Web 3.0 in the coming slides, including:

Facebook open graph protocol

Drupal

RDFa in search results with Google and Yahoo!

BBC World Cup site

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Courtesy W3C SWEO group, http://linkeddata.org/docs/eswc2007-poster-linking-open-

data.pdf

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Courtesy of Richard Cyganiak, http://richard.cyganiak.de/2007/10/lod/


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Courtesy ofChris Bizer, http://www4.wiwiss.fu-berlin.de/bizer/pub/lod-datasets_2009-03-05.html


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Linking Open Data cloud diagram, by Richard Cyganiak and Anja Jentzsch. http://lod-cloud.net/


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Possible answers:

Few people are driven by data ownership, data portability

People are drawn to specific sites

People _want_ to segment their online profiles (c.f. Facebook vs. LinkedIn)

Drupalwhich runs 1% of the worlds Web sitesis on the leading edge of adoption of

the Semantic Web for content-driven sites. Drupal 7 exposes the semantics of Drupal

sites natural structures to Google/Yahoo! with RDFa. Also modules for SIOC and

Facebook OGP.

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The key point here is that though FB published this protocol, it relies on open Semantic

Web standards (RDFa) that anyone else can consume. The same semantics allow

people to link the Like button to the type of artifact being liked (movie, here) and also

can allow search engines to give more structure, query engines to find more data, etc.

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Image courtesy of http://bio2rdf.org/ .

Scientific data makes up a significant portion of the current Linked Data Web. This is

information on proteins and genes, pathways, and sequences, chemistry and genetics,

This diagram shows some of the information available and how its linked together.

Nodes are sized according to their quantity of data, and links are sized according to the

quantity of links.

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Google (Rich Snippets) and Yahoo! (originally Search Monkey) consume semantic

markup to enhance search listings.

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http://searchnewscentral.com/20110207129/Technical/rdfa-the-inside-story-from-

best-buy.html

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Many enterprise uses ofSemantic Web / Linked Data are highlighted at:

http://www.w3.org/2001/sw/sweo/public/UseCases/

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Question: Where in this scenario do you think Semantic Web concepts and

technologies are being employed? What would the alternative be?

Answers: integrating data to get as large a universe as possible; rules and reasoning tointelligently filter the data

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Combine manual tagging with ontology-driven reasoning and ontology-driven dynamic

aggregation (700 index pages, more than the rest of the sports site combined) to

produce a dynamic, cross-indexed, cross-linked, usefulsite for the World Cup.

What is the semantic value here?

* Produce an information rich site at many levels of aggregation (player, team,

geography, group, ) without employing a large fleet of editors to curate the sites

_content_. Instead, maintain an ontology and provide a content tagging process.

* Use the ontology to help automate the tagging process (forward-chaining inference

based on taxonomies)

For more details:

http://www.bbc.co.uk/blogs/bbcinternet/2010/07/bbc_world_cup_2010_dynamic_se

m.html

http://www.bbc.co.uk/blogs/bbcinternet/2010/07/the_world_cup_and_a_call_to_ac.h

tml

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Other governments with similar efforts. Australia, Sweden, New Zealand, , various

local governments

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At TED2010, Tim Berners-Lee reported back on one years worth of progress after the

push for raw data began in 2009.

Q: What's special about Semantic Web / Linked Data here? What would be different ifthis were all put out using "Web 2.0" approaches?

* baked into the Web -- _easy to publish and consume via the existing Web

infrastructure, flexible, heterogeneous_

* "semantic" -- _easy for 3rd parties to understand - no screen scraping, "guessing" -

lots you can do with it (layer cake)

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Its not all sunshine, rainbows, and puppies

(This slide better with animation, sorry!)

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Industry: no different from any other investment expect to see ROI, whether in the

form of time-to-market, competitive advantage, greater efficiencies, lessened resource

requirements, etc. Look for disruptive (10x) improvements.

Linked Data Web:

Putting raw data on the Linked Data Web takes work.

Scientific data is funded by government money, with requirements for openness

Commercial data is driven by ROI (cf Best Buys experience)

Government data is trickyat the whims of politics. (cf data.gov.uk with the change

from Gordon Brown to David Cameron)

Maintaining links between data sets is tricky. Is it any trickier than building the

document Web? (Maybe not.)

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Another example NY Times, while embracing Linked Data Web to some extent, is

putting their real content behind a pay wall.

Image copyright Scott Brinker, with attribution tohttp://www.chiefmartec.com/2010/01/7-business-models-for-linked-data.html .

See also http://www.ldodds.com/blog/2010/01/thoughts-on-linked-data-business-

models/ --

Advertising is hard when people arent the consumers and when all data is semantically

identified! (Advertising via Ts&Cs possible)

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A large (Fortune 100) company might have 10,000 database. And some of those

database might be huge 10 TB or bigger.

But large enterprises are also sub-segmentable in ways in which the Web is not. Thereare divisional, departmental, geographic problems that can be solved as if solving the

problems of a much smaller enterprise.

There are social challenges (some of which are covered elsewhere in section of the

talk), but there are also pure technical challenges when working at Web scale:

Distributed query

Cache invalidation

Link rot

Data rot (Linked CT example)

Rules / reasoning across data sets

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(While this is a challenge for being able to fully exploit the Linked Data Web, its also an

opportunity before the Linked Data Web, there was little opportunity to find and

improve these sorts of data quality issues. Linked Data gives us visibility into these data

issues so that source data can be improved. But it is still a challenge to figure out amodel for improving and verifying data quality before individual human interpretation

can be removed from the chain.)

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Possible ideas:

Up-vote/down-vote for data and data sets(wisdom of crowds)

Build agents off of authoritative (1st-party) sources

Certified sources, audited sources, regulated sources

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Potential approaches to trust:

Digital signatures

Social network analysis

Multiple assertions of the same fact (voting, data quality all over again) Provenance (how did we arrive at this data assertion)

Trust the contributions its data quality all over again! (specific facts, sets of facts,

entire data sets)

Related issue: uncertainty

Within an enterprise: accepted sources of authority; default trust state

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Enterprises can derive incremental value via a small number ofSemantic Web vendors

and Semantic Web knowledgeable system integrators (Sis). To gain traction on a Web-

scale, however, requires the world of Web 1.0 & 2.0 (LAMP, JSON, ) developers to

adopt these new (and arguably more complex) technologies.

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Only 9% of Linked Open Data datasets include machine-readable license information.

(http://ivan-herman.name/2011/03/29/ldow2011-workshop/)

Some links for further reading:

http://www.opendefinition.org/guide/data/

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