Semantics Overview

Organizations need to make quick decisions using all the information that they have

IT should enable this but often can’t deliver quickly enough

Analysis requires us to complete all these steps with our information:

• Create it—works great
• Store it—works great
• Change it—works great
• Find it—not so good
• Integrate it—very complex and difficult
• Analyze it—finally!
• Use it—great if you’re using the app that created it; otherwise a BIG problem

How can we analyze all our information across all platforms,

wherever it sits, quickly?

The Main Difference

The Semantic Web isn't just inevitable.

It is imminent.

http://bit.ly/J2yInC

Semantics???

Semantics!!!

Overview

Problem Statement

DROWNING IN DATA

The Coming

Data Tsunami

Current Approach

• Data from Scarce to Superabundant
• Social Multiplier

Everyone produces Data

• Data Underutilized
• Data is Siloed

* Economist Special Report Attached

Here's how we extract Knowledge

using the Traditional Approach

From "Needle in a Haystack"

To "Needles in a Field of Haystacks"

Traditional BI Shortcomings

Searching instead of Knowing

Employee Hours Wasted per Task

• Still building plumbing
• Yet another SILO
• Can only answer questions that

were conceived ahead of time

• ETL woes - loading, massaging, transform
• Not real-time
• Cannot cope up with the Data Tsunami

• "Dumb" - BI systems cannot infer nor reason

We still have to MANUALLY collate the data

• "Obvious" relationships are not understood by the computer
• Each "fact" has to be explicitly declared
• The system does not "discover" logical facts & relationships
• Certain concepts/relationships cannot be easily expressed
• "Closed World" - the system does not know anything beyond its boundaries

The Semantic Way

The Coming Semantic Wave

A Tidal Wave of Four Internet Growth Stages

(NOW-???)

(The FUTURE)

Web 1.0 - Static Web (1991-2003)

Web 2.0 - Social Networks (2004-2010)

Web 3.0 - Semantic Web (starting NOW)

Web 4.0 - The Ubiquitous Web (future-2020?)

(1991-2003)

(2004-2010)

"Smart Data"

Inference & Reasoning

Semantics 101

Customized tags, like:

XML

<Yorkie>Coco</Yorkie>

+

Relations, in triples, like:

RDF

(Maya) (is_spouse_of) (Joel)

+

(Joel) (is_dogowner_of) (Coco)

Limitations of Conventional

Application Development

Hierarchies of concepts, like:

Ontologies

<rdf:RDF xmlsns="http://natividads.com/metadata/mammal">

+

mammal -> dog -> Yorkie -> Coco

Semantics is not only for Business Intelligence

We can fix the Knowledge Gap at the Source

Inference Rules

If (personA) (is_spouse_of) (personB), then (personA) (is_dogowner_of) (dog)

Conventional

VS

Semantic

Semantics!

=

We infer/discover additional Facts & Relationships

<Yorkie>Coco</Yorkie> INFERS <dog>Coco</dog>, <mammal>Coco</mammal>

(Maya) (Is_spouse_of) (Joel) INFERS (Maya) (is_dogowner_of) (Coco)

• Knowledge is encapsulated in Opaque Software
• Data Schemas reflect limited Knowledge
• Data Organization is tightly coupled with the Schema
• Schemas support limited Data Integrity
• Very hard to Localize Data - gather, collect, and concentrate data from different data sources
• Same source data Localized redundantly by many systems

Be sure to read the Semantic Briefing Portfolio at

From Searching To Knowing - Spectrum of Knowledge Representation and Reasoning Capabilities

Semantics

The Bottom Line

Benefits of Semantic

Application Development

"Smart" Data/Applications

• Knowledge is Baked-in
• New Knowledge can be inferred
• Agility to Adopt to Ever-changing Conditions
• Semi-automatic Data Integration
• Machine Intelligence

PDF password (case-sensitive): "Saraswati"

Conventional

SOA

In Plain English

• Knowledge is represented by an Ontology
• Data Organization is decoupled from the Schema
• Inferencing creates new Knowledge
• Defines the Meaning of Data
• Enables data integration across heteregenous silos
• Utilizes "reasoners" to ensure Data Integrity
• All Semantic data can be web addressable
• SOA "out-of-the-box"
• Ontology can change without altering underlying facts/assertions allowing rapid response to business change

Where most systems are

• Increased Business Agility
• New Business Capabilities & Opportunities
• Dramatically cut back IT expenditures
• While Building, Leveraging & Preserving your current IT investments
• Is INEVITABLE

Knowledge Engineering

Practice

2

kNOW

NOW kNOW

=

Knowledge Engineering

Opportunities

What do the Experts Say?

The Semantic Web can assist the evolution of human knowledge as a whole.

Over the next decade, Web 3.0 will spawn multi-billion dollar technology markets that will drive trillion dollar global economic expansions to transform industries as well as our experience of the internet.

Tim Berners-Lee, "Inventor" of the Internet

Scientific American, 2001

Mills Davis, Semantic Wave Report 2008, Project 10X

This BI industry is estimated to be worth more than $100 billion and growing at almost 10% a year, roughly twice as fast as the software business as a whole.

Today’s business intelligence (BI) and reporting

systems are NOT designed for this on-the-fly creation of meaning. These systems lack the capability to capture and manage the semantics of the business in a more dynamic, scalable way.

Data, Data Everywhere

The Economist, Feb 2010

Semantic Technology Products & Services Opportunities

PWC Tech Forecast, Spring 2009

The real reason why the semantic web is inevitable at this point is because the business potential of a web of data — inside the enterprise and out in the public web — is becoming obvious and immense. Businesses are data-driven.

Systems that are able to “understand” and have far greater contextual awareness will provide a level of proactive assistance that was previously available only from human helpers. For scientists, this will mean deeper scientific insight, richer discovery, and faster breakthroughs.

Scott Brinker, President & CTO,

Ion Interactive, SemTech 2009

June 2009

Craig Mundie, Microsoft Chief Research & Strategy Officer

The Fourth Paradigm, Data-Intensive Scientific Discovery

Microsoft Research 2009

Top 10 Opportunities in the Enterprise

1 Information sharing

2 Semantic search, discovery, & navigation

3 Semantic mashups and composite applications

4 Semantic infrastructure / middleware SSOA, SBPM, SWS, virtualization, policy-based computing

5 Semantic business intelligence

6 Semantic ERP applications CRM, PLM, SCM, HRM

7 Semantic governance, compliance, & risk

8 Semantic web sites, wikis, collaboration, interest networking, & collective knowledge systems

9 Semantic advertising, marketing, personalization, & customization

10 Intelligent systems knowledge-based research, design, engineering, simulation, planning, scheduling, optimization, & decision support.

Mills Davis, Web 3.0 Manifesto, Project 10X, Oct 2008

By 2020, Mills Davis estimates

that the Entire BI Market will be Semantic

Semantic Wave

2010 - Total BI Market estimated at 100 Billion

Semantic Market estimated at 10 Billion

2015 -BI Market Size - 175 Billion

Semantic BI - 52 Billion

Source: Mills Davis, Project 10X

PWC Spring 2009 Tech Forecast

And that is just the Business Intelligence Market,

within the Next Decade, the majority of Information and Communication Technologies (ICT) will have Semantic Capabilities.

It is Inevitable. There is no other way ICT can cope up with

the Data Tsunami.