Understanding Text

 
 
By Tony Shaw  |  Posted 2011-04-06
 
 
 

What is Web 3.0? Is it the Web of Data, the Ubiquitous Web, the Mobile Web, the Semantic Web? The answer to all of these questions is “yes.”

Web 3.0 represents the next generation of information infrastructure that will enable an unprecedented level of intelligence in almost all systems and applications. Smarter computing capabilities will perform complex tasks that previously required human capabilities, such as understanding and reasoning—and will accomplish those tasks at enormous scale and efficiency.

These technologies are in use today by organizations ranging from Facebook to the Department of Defense. They’re using the new infrastructure to provide a variety of innovative capabilities, including faster access to and discovery of information through powerfully intelligent decision-making applications. Let’s look at some examples:

Connecting Information: Facebook

The Facebook Open Graph is a great example of Web 3.0’s simple scalability. Open Graph includes a format for marking up Web pages based on the Resource Description Framework (RDF), the Semantic Web data model, so that anyone with a Website can incorporate Facebook’s markup to define what the site is about.

This goes beyond basic metadata because the descriptions enable Web users to find and connect with their friends who have similar interests. The simple manifestation of all this is the Facebook “Like” button: One click can offer an invaluable hub of information that could be used for future communication with friends and to make recommendations and discoveries.

Search Optimization and Web Commerce: Best Buy

One of the most frequently quoted benefits of Web 3.0 is more relevant search results. As applied to Web commerce, this means that businesses can now put additional information into product descriptions and online ads to make them easier for search engines to find.

Best Buy is at the forefront of using this technology to leverage its e-commerce efforts. It is using RDFa (RDF in attributes, which adds a set of XHTML attributes) markup and the Good-Relations vocabulary to produce more targeted search results for shoppers looking for products. So far, some internal company measures suggest that this has increased traffic by 30 percent.

The benefits go further, however, including the ability to examine product attributes more closely and make more granular product comparisons. Best Buy can also take the data from its catalog and integrate it with other data sources, both internally and externally, for data analysis.

The company also marked up blog entries from active store blogs, again with RDFa, to generate more traffic for localized store pages. Their “open-box” project (which includes returned and demo products) brings in customers looking for better deals, producing a revenue windfall on returned items.

Automated Intelligent Decision Making: Amdocs

Amdocs is a $3 billion enterprise that provides “customer experience” on behalf of its clients in service industries such as telecom, health care, utilities and insurance. Creating high-quality, cost-effective customer interaction requires real-time contextual knowledge across all business channels, from internal sources, such as service disruptions and policy management, to external forces, such as social trends and competitive offers.

Only with holistic system awareness can Amdocs provide service representatives with the ability to deliver customer satisfaction and drive the profitability of the business—and do it at a scale of millions of transactions a day.

To address this need, Amdocs created a system that is predictive, personalized and self-learning. Using Web 3.0 semantic technologies, the company combines information from a variety of sources in real time to anticipate the reason for a customer’s call. Appropriate responses to customers can be generated 30 percent faster, which makes for much happier customers and more consistent, productive service operations. It also reduces customer churn and improves up-selling.

New Data Access Flexibility: U.S. Department of Defense

Supporting the business activities of the U.S. Department of Defense accounts for more than half of the DoD’s budget. A long history of piecemeal IT systems and services implementation has produced a level of complexity, redundancy and cost that is simply unsustainable.

The solution to this quagmire might be emerging from the test bed of a new SOA-based business intelligence architecture. The system uses Web 3.0 semantic technologies, from Revelytix, to create an agile, federated query environment.

The concept is relatively simple: By defining pieces of information unambiguously, they become “plug and play.” Information is usable and recombinable quickly and cheaply.

This approach to building information systems is similar to the way electronic systems are created with different combinations of standard components. The goal is to pull data in real time, as needed, from individual systems rather than going through time-consuming and time-delayed ETL (extraction, transformation and loading) processes. The system will be more flexible, lightweight, less invasive and less costly to maintain over time.

Planning and Configuration Management: Elastra

Elastra is using Web 3.0 technologies to support the automated planning of its cloud-based computing services. This functionality exploits one of the key Web 3.0 “smart” capabilities: the ability to reason, or automatically make intelligent decisions about the optimal course of action.

Consider Elastra’s high-end, large-scale service offerings, which require complex configuration-management processes to deploy multitier applications—possibly across a hybrid public/private cloud, and potentially with hundreds or thousands of security, policy, network and services options.

Elastra’s approach is to use an automated hierarchical planning tool in combination with the industry-standard Pellet reasoning engine (both from Clark & Parsia). Ordinarily, this could be accomplished with standard rules-based system approaches, but the reasoning tools allow the company to manage thousands of potential configuration possibilities within seconds, without having to specifically program every rule. This allows Elastra to keep the system updated for new options with relatively modest maintenance effort.

Understanding Text: Millward Brown

Web 3.0 is ideally suited to the management and analysis of documents and content because it enables computers to quickly sift through large amounts of text and extract the meaning. One example is “sentiment analysis,” which involves measuring how customers feel about an organization, as expressed through surveys, blogs, online forums and social networks.

The global research agency Millward Brown, which works with Fortune 500 companies on their branding strategies, uses Web 3.0 technologies from OpenAmplify to identify the strategically insightful information derived from customer feedback. This information can then be used to drive marketing messages, public relations efforts, pricing strategies and service responses.

Content and Media Management: BBC

The British Broadcasting Corp. 2010 FIFA World Cup site was built on a Web 3.0 platform. The site contains more than 700 dynamically linked pages, covering teams, players and results. The BBC’s Web 3.0 publishing framework automatically generates relevant Web pages by aggregating content, linking to related stories and producing topic hubs on the fly—all with minimal journalistic intervention.

The secret to the speed and flexibility of the site is that the framework publishes semantic data about the content—its metadata—rather than attempting to create original content directly. This metadata describes the various concepts and content of the World Cup, and provides the basis for connecting it to other content.

When a user clicks on a topic of interest, the content management system quickly assembles the pieces to construct the Web page. The system reduces the cost of development and provides users with a more customized experience because it can produce many more customized pages than could be anticipated by Web developers creating specialized pages manually.

Mobile, Linked Data: Amsterdam Fire Department

The need for speedy, accurate information access is paramount in an emergency response. As a fire team races to save lives, the questions start with, “How do we get there?” and moves on to “What’s inside this building we are entering?”

In the city of Amsterdam, The Netherlands, fire teams are using Web 3.0 Linked Data technologies to improve overall response times by collecting as much relevant information as possible, as quickly as possible, and presenting it in a time-sensitive display to the people who need it the most—the firefighters.

The key component is the rapid compilation of data from a variety of sources using the Linked Open Data standard. This data format provides lightweight, fast and cheap data integration that is quickly adaptable to the situation—for example, by linking in real time to OpenStreetMap to optimize navigation.

Similarly, data from other emergency responder systems and services can be linked into one information stream. The next step, coming soon, will be to incorporate building floor plans and structural details via the Open Floor Plan Display/Exchange Project. So, once on the scene, firefighters will know more about the building they are about to enter.

Web 3.0 is a combination of technologies that enable organizations to increase productivity by automating many of the processes involved in information collection and analysis that are currently done manually—or are not done at all because of the size and complexity of the information requirements.

As such, Web 3.0 brings us to the edge of a new era in computing applications. No doubt, it will take some time for the full potential to be realized, but nobody should make the mistake of taking a wait-and-see attitude. The Web 3.0 era has already begun, and, as we’ve shown above, many innovative organizations are already leveraging these technologies.

Tony Shaw is founder of Wilshire Conferences and Dataversity, and is educational chairman of the SemTech semantic conference. Shaw has broad expertise in the assessment of emerging technologies and facilitates the TTI/Vanguard strategy forum for CTOs.