Tech Tool: CloudBooks—and the Semantic Web

By Reuben Tozman

How the CloudBook will change learning.

The Internet has forever changed our world and our relationships with people and organizations. It continues to evolve, with many varied applications and technologies emerging. Although we can’t say for sure what the Internet will look like in the future, there are some trends in which Internet thought leaders agree are here to stay.

One such trend—and perhaps the most comprehensive—is the evolution toward the semantic web (or Web 3.0). Within that trend, it’s important to review the tools that will help us move about in the semantic web, and how they will impact learning and the learning industry. Enter NetBooks and CloudBooks.

(For those of us still trying to resolve Web 2.0 and how to integrate it into learning, hold on tight because the ride is going to speed up faster than you can catch up.)

The basics

First, lets define what is meant by the semantic web. Edd Dumbill, author of O’Reilly’s XML.com (http://www.xml.com/pub/a/2000/11/01/semanticweb/) writes: “The Semantic Web approach instead develops languages for expressing information in a machine processable form." This explanation is perhaps the best way of summing up the semantic web; it’s technologies for enabling machines to make more sense of the web, with the result of making the web more useful for humans.

Please draw your attention to “…enabling machines to make more sense of the web…” for a moment. Some folks may think that machines already make sense of the web by providing us tools like search engines, blogs, wikis, and so forth.

Consider another definition from Wikipedia: “Web 3.0, a phrase coined by John Markoff of the New York Times in 2006, refers to a supposed third generation of Internet-based services that collectively comprise what might be called 'the intelligent web'—such as those using semantic web, microformats, natural language search, datamining, machine learning, recommendation agents, and artificial intelligence technologies, which emphasize machine-facilitated understanding of information in order to provide a more productive and intuitive user experience.”

In this definition, it’s important to focus on the phrase “…machine-facilitated understanding….” Although a search engine can direct us to a website or answer our questions, does it understand? What makes the semantic web different than what we experience now is the presence of context, which enables a machine to understand the information it’s reading—not just point to it based on tags. What exist as links to pages now will be links to the things themselves in so much as they can be represented in digital form.

Making sense of it all

Regardless of the evolution the web has made with its current use of tags and tag clouds, the users of the Internet are always introducing and re-introducing themselves to it each and every time they use it. Think about how you use Google; Every time you search for something, it has no memory of who you are or what you looked for last time. Google is more interested in linking you to the right webpage rather than understanding your context.

Tags and tag clouds help me, the user make sense of the web. The future evolution of the web is that the web will make sense of itself. The web will understand our real life connections: our work environment, our homes, our travel destinations, and so on. And all this will persist with us in the Internet and will provide context for who we are and where we want to go online.

The other aspect to the semantic web is the proliferation of the web as the operating system from which everyone works. Once the Internet can read itself and understand context, the use of the web as a personal operating system becomes less threatening because context will dictate connection to things and people. (This is said without factoring in privacy issues, which is a major hurdle the semantic web will have to overcome). A current example of this trend is the growth of SaaS (software-as-a-service), which allows users to do their desktop computing online through hosted software applications. The benefit to the user is they only pay for what they use. Along with SaaS, comes the notion of CloudBooks and NetBooks.

Enter CloudBooks

Essentially, CloudBooks and NetBooks are storage-diluted compact machines loaded with Internet apps that are designed to work on and from the Internet. These machines have less storage memory but high processing power, making them optimized for use on the net. These machines include our mobile phones, PDA’s, iPods, and so forth. As a friend recently pointed out, the bulk of mobile telephone calls in North America now go through IP switching.

The advent of the CloudBook (herein representing both CloudBooks and NetBooks) is significant in that it supports the notion of using the Internet as an operating system. This also is noteworthy for the learning community not only because it supports the idea of the semantic web, but also because it demonstrates the potential for hardware to change based on an evolved platform. The CloudBook affirms that the evolution of the web is to create more transparency—it enables content and content objects to be transparent to readers in order to create context and meaning. Think iPhone.

The future of learning?

Although predicting the future of the Internet is out of scope for this article, it is valuable to capture some key trends that characterize changes with introduction of the CloudBook to see how learning will fundamentally change:

·         Machines are enabled to derive context.

·         Machines are enabled to draw meaning from context.

·         Content can be transparent to machines.

·         Hardware can use the Internet as its operating system.

However, before we move onto how learning will change, let’s take a brief moment to capture how learning has already changed. For clarity, most agree that our physiological processes for learning have fundamentally remained the same, but the ways in which we package learning to appeal to those physiological processes has changed. Therefore, we’re really concerned with how workplace learning and performance professionals have repackaged learning content over the years. Specifically, one of the real advances in learning has been the ability to distribute learning to greater numbers and yet allow it to be even more targeted to the individual. This is accomplished through modularization of content and packaging formats such as SCORM. In essence, we’ve changed distribution models from pushing content through a central brain to facilitating pulling content through a distributed network of brains (similar to the evolution of robotics).

If access to content is a growing trend, then as learning practitioners we should really focus our attention on how to facilitate access. To some degree the SCORM standard has identified access to content as something that requires attention through inclusion of learning object metadata as part of the standard. Metadata allows content creators to package content with an assortment of information describing it to assist the people accessing it decide whether the content is appropriate for their needs. SCORM itself was meant to deal with interoperability issues, however, it was always conscious of the “what if” factor when content repositories grew to extremely large scales. How would consumers of content find what they were looking for in large libraries? How could learning content repositories avoid the “Google” effect.

Now we are at a point in which learners can access large libraries of content, search for relevant content objects, find what they are looking for, and make their way through that content at their own pace and at their own discretion—at least in theory. Learners also can find relevant networks of people with expertise or similar interests as their own and pull content from those networks. This happens in both controlled environments such as the corporate LMS and uncontrolled environments such as blogs and other social networks. In either case (controlled or uncontrolled), the link between learner and content is manual. There are instances in controlled environments in which learning paths are pre-programmed based on learner criteria, and thus provide a pre-programmed link between learner and content. However this link is native to the system that the learner operates in and is not persistent outside of that environment.

Can and will CloudBooks change this scenario? First and foremost, CloudBooks function based on the premise that the Internet, to be known as the ‘cloud’ will be an intelligent, networked operating system from which the CloudBook will negotiate context and process information in real time based on that context. (Think of your cell phone knowing when you are in the United States versus Canada versus Europe.) In essence, there are no predetermined links to pages, but rather networked context that a CloudBook will need to read, understand, and process in real time to deliver to the information the user requires.

What is the implication for learning? The future of the web is to provide a learning environment where learners and content are linked through context and that is persistent regardless of where the learner is operating. This is due in part to the notion of the Internet as an operating system, but also is a result of semantic technologies. There are several hurdles that we need to overcome to make the semantic web a reality, not the least of which is agreement on the language to use for creating context. For example, consider the Dewey Decimal System. What makes the Dewey Decimal System so potent is not the technology used in conjunction with it, but the adoption of it as the standard for cataloguing literary references by libraries across the globe. Once the standard is in place, better and faster tools can be created to facilitate its use. The creation of a Dewey Decimal System for the semantic web will be a long arduous process more so because the initial step is the deconstruction of all information on the web.

Learning on the semantic web also will require the creation of semantics so that its context can be properly negotiated by CloudBooks. If the learning community can come together and create a globally accepted semantic structure, then both software and hardware can adopt the standard and make use of it. If CloudBooks reaffirm that hardware adaptations are made based on the implementation of standards or software, then they will be able to provide us with the Holy Grail of learning—true just-in-time learning. Learning applications can be built to facilitate this notion and loaded onto our CloudBooks (or mobile phone or PDA).

As learning professionals we need to understand and embrace this evolution. Nothing has ever come close to delivering just-in-time learning like the semantic web promises to do. If learning professionals can rally behind the concept, then the work of creating our Dewey Decimal System for learning content can be achieved.