Web 3.0 & the Sem-antic Web

Ready or not, like it or not, Web 3.0 is around the corner. It's coming - so it's best to understand the technologies. Particularly for librarians, we need to understand the intricate technologies behind what the semantic web will look like, how it runs, and what to expect from its much anticipated (although still hyper-theoretical) features.

Ora Lassila and James Hendler, who co-authored along with Tim Berners-Lee, on the article which predicted what the semantic web would look like in 2001, argues in their most recent article, Embracing "Web 3.0" that the technologies that make it possible for the semantic web is slowly but surely maturing. In particular,

As RDF acceptance has grown, the need has become clear for a standard query language to be for RDF what SQL is for relational data. The SPARQL Protocol and RDF Query Language (SPARQL), now under standardization at the W3C, is designed to be that language.

But that doesn't mean that Web 2.0 technologies are obsolete. Rather, they are only a terminal stage of the evolution to Web 3.0. In particular, it is interesting that the authors note

(1) Folksonomies - tagging provides and organic, community-driven means of creating structure and classification vocabularies.

(2) Microformats - the use of HTML markup to decode structured data are a step toward "semantic data." Of course, although not in Semantic Web formats, microformatted data is easy to transform into something like RDF or OWL.

As you can see, we're moving along. Take a look at this: on the surface, Yahoo Food looks just like any Web service; underneath, it is made from SPARQL which really does "sparkle."

Six Kinds of (Social) Searching

Librarians need to be aware of social searching. It's important and it's here to stay. What makes social searching so integral for librarians' information retrieval skills is that it requires knowledge of Web 2.0 (mashups, wisdom of crowds, long tail, etc.) It doesn't mean that "traditional" search skills are obsolete. Far from it. Rather, social searching just adds another layer in the librarian's toolkit. Here are some of my favourites.

1. Social Q&A sites - Cha Cha, Live QnA, Yahoo! Answers, Answer Bag, Wondir

2. Shared bookmarks and web pages - Del.icio.us, Shadows, Yahoo's MyWeb, Furl, Diigo, Connotea

3. Collaborative directories - Open Directory Project, Prefound, Zimbio, Wikipedia

4. Taggregators - Technorati, Bloglines, Wikipedia

5. Personalized verticals - PogoFrog, Eurekster, Rollyo

6. Collaborative harvesters - iRazoo, Digg, Flickr, Youtube, Netscape, Reddit, Tailrank, popurls.com

Top 25 Definitions for Web 2.0

Summer has gone by so quickly. What happened to June? I've been culling readings from all over everywhere, aggregating the best definitions of Web 2.0. Notice there is a lot: twenty-five in all. I tried making sense of everything, even trying to arrange and shuffle for a catchy acronym (think ROY G. BIV). I challenge all librarians and other information professionals interested in Web 2.0 to do the same: find a catchy acronym and share it with us all. I will share my own in one month's time.

(1) Social Networks - The content of a site should comprise user-provided information that attracts members of an ever-expanding network. (example: Facebook)

(2) Wisdom of Crowds - Group judgments are surprisingly accurate, and the aggregation of input is facilitated by the ready availability of social networking sites. (example: Wikipedia)

(3) Loosely Coupled API's - Short for "Application Programming Interface," API provides a set of instructions (messages) that a programmer can use to communicate between applications, thus allowing programmers to incorporate one piece of software to directly manipulate (code) into another. (example: Google Maps)

(4) Mashups - They are combinations of APIs and data that result in new information resources and services. (example: Calgary Mapped)

(5) Permanent Betas - The idea is that no software is ever truly complete so long as the user community is still commenting upon it, and thus, improving it. (example: Google Labs)

(6) Software Gets Better the More People Use It - Because all social networking sites seek to capitalize on user input, the true value of each site is definted by the number of people it can bring together. (example: Windows Live Messenger)

(7) Folksonomies - It's a classification system created in a bottom-up fashion and with no central coordination. Entirely differing from the traditional classification schemes such as the Dewey Decimal or Library of Congress Classifications, folksonomies allow any user to "social tag" whatever phrase they deem necessary for an object. (example: Flickr and Youtube)

(8) Individual Production and User Generated Content - Free social software tools such as blogs and wikis have lowered the barrier to entry, following the same footsteps as the 1980s self-publishing revolution sparked by the advent of the office laser printer and desktop publishing software. In the world of Web 2.0, with a few clicks of the mouse, a user can upload videos or photos from their digital cameras and into their own media space, tag it with keywords and make the content available for everyone in the world.

(9) Harness the Power of the Crowd - Harnessing not the "intellectual" power, but the power of the "wisdom of the crowds," "crowd-sourcing" and "folksonomies."

(10) Data on an Epic Scale - Google has a total database measured in hundreds of petabytes (a million, billion bytes) which is swelled each day by terabytes of new information. Much of this is collected indirectly from users and aggregated as a side effect of the ordinary use of major Internet services and applications such as Google, Amazon, and EBay. In a sense these services are 'learning' every time they are used by mining and sifting data for better services.

(11) Architecture of Participation - Through the use of the application or service, the service itself gets better. Simply argued, the more you use it - and the more other people use - the better it gets. Web 2.0 technologies are designed to take the user interactions and utilize them to improve itself. (e.g. Google search).

(12) Network Effects - It is general economic term often used to describe the increase in vaue to the existing users of a service in which there is some form of interaction with others, as more and more people to start to use it. As the Internet is, at heart, a telecommunications network, it is therefore subject to the network effect. In Web 2.0, new software services are being made available which, due to their social nature, rely a great deal on the network effect for their adoption. eBay is one example of how the application of this concept works so successfully.

(13) Openness - Web 2.0 places an emphasis on making use of the information in vast databases that the services help to populate. This means Web 2. 0 is about working with open standards, using open source software, making use of free data, re-using data and working in a spirit of open innovation.

(14) The Read/Write Web - A term given to describe the main differences between Old Media (newspaper, radio, and TV) and New Media (e.g. blogs, wikis, RSS feeds), the new Web is dynamic in that it allows consumers of the web to alter and add to the pages they visit - information flows in all directions.

(15) The Web as a Platform - Better known as "perpetual beta," the idea behind Web 2.0 services is that they need to be constantly updated. Thus, this includes experimenting with new features in a live environment to see how customers react.

(16) The Long Tail - The new Web lowers the barriers for publishing anything (including media) related to a specific interest because it empowers writers to connect directly with international audiences interested in extremely narrow topics, whereas originally it was difficult to publish a book related to a very specific interest because its audience would be too limited to justify the publisher's investment.

(17) Harnessing Collective Intelligence - Google, Amazon, and Wikipedia are good examples of how successful Web 2.0-centric companies use the collective intelligence of users in order to continually improve services based on user contributions. Google's PageRank examines how many links points to a page, and from what sites those links come in order to determine its relevancy instead of the evaluating the relevance of websites based solely on their content.

(18) Science of Networks - To truly understand Web 2.0, one must not only understand web networks, but also human and scientific networks. Ever heard of six degrees of separation and the small world phenomenon? Knowing how to open up a Facebook account isn't good enough; we must know what goes on behind the scene in the interconnectedness of networks - socially and scientifically.

(19) Core Datasets from User Contributions - Web 2.0 companies use to collect unique datasets is through user contributions. However, collecting is only half the picture; using the datasets is the key. These contributions are then organized into databases and analyzed to extract the collective intelligence hidden in the data. This extracted information is then used to extract collective knowledge that can be applied to the direct improvement of the website or web service.

(20) Lightweight Programming Models - The move toward database driven web services has been accompanied by new software development models that often lead to greater flexibility. In sharing and processing datasets between partners, this enables mashups and remixes of data. Google Maps is a common example as it allows people to combine its data and application with other geographic datasets and applications.

(21) The Wisdom of the Crowds - Not only has it blurred the boundary between amateur and professional status, in a connected world, ordinary people often have access to better information than officials do. As an example, the collective intelligence of the evacuees of the towers saved numerous lives in the face of disobeying authority which told them to stay put.

(22) Digital Natives - Because a generation (mostly the under 25's) have grown up surrounded by developing technologies, those fully at home in a digital environment aren't worried about information overload; rather, they crave it.

(23) Internet Economics - Small is the new big. Unlike the past when publishing was controlled by publishers, Web 2.0's read/write web has opened up markets to a far bigger range of supply and demand. The amateur who writes one book has access to the same shelf space as the professional author.

(24) "Wirelessness" - Digital natives are less attached to computers and are more interested in accessing information through mobile devices, when and where they need it. Hence, traditional client applications designed to run on a specific platform, will struggle if not disappear in the long run.

(25) Who Will Rule? - This will be the ultimate question (and prize). As Sharon Richardson argues, whoever rules "may not even exist yet."

Librarian 3.0

I was recently asked in a job interview how Web 3.0 would work for a law firm. It's made me think on the fly: how would the Web of the future work in such a scenario? We're barely even half-way into Web 2.0...I had to think back to an article that Michael V. Copeland of Business 2.0 Magazine had written entitled, What's next for the Internet to envision a glimpse of the "future."

The semantic Web in the Berners-Lee vision acts more like a series of connected databases, where all information resides in a structured form. Within that structure is a layer of description that adds meaning that the computer can understand.

Since we're on the topic of visions and dreams, here would be my answer: Imagine the lawyer, Mr. X, flipping open his laptop (which by then would be priced similarly to a cell phone), and typing in "2 o'clock meeting with Angela at Starbucks." All of a sudden, his online calendar would pop open and a series of clients names would appear, and the correct "Angela Smith" would be sent an email with details of the meeting agenda sent to the printer. Starbucks would receive an electronic notification with the usual order of Venti Chai Latte (two cups) and a newspaper -- the Globe and Mail (his favourite) to boot. Because Mr. X's car is in the shop because of a recent accident and a replacement car isn't ready yet, a taxi has been order automatically for Mr. X and will be ready for him upon arrival for 1:30 at the entrance. The ride is estimated for 15 minutes to his destination, but his preference has always been for early arrival.

Finally, it's the library's turn now. Mr. X. sends an email to the librarian, (after all, she is the one responsible for the library's more intricate databases), simply with the message "Wang V. Granville LLP" (both pseudonyms of course), and immediately, the librarian works her magic and types in the necessary key terms. All of the acts, statutes, regulations, as well as updated case files relating to the case are electronically retrieved and stored onto a file which is automatically sent to the lawyer's dossier. (The librarian's job is behind the scene - she is the one who carefully collates the materials and gives them tags which the semantic databases will translate into its own readable language).

The lawyer walks out of the firm nonchalantly and begins his afternoon with everything he needs, but taking only one-tenth of the time and effort he would need back in the days of Web 2.0. That, in my hypothetical world based on user history and preferences and interlocking databases, is how the future of Web 3.0 might look like.

The Paradox of Choice

As information professionals, we face a plethora of choice each and everyday of our working lives, from what brand of coffee to buy in the morning to the database we want to conduct for a search. So many choices, so little time to choose. Barry Schwartz, Professor of Social Theory and Social Action, reveals in The Paradox of Choice strategies that can refine our decision-making processes to more effective results. His book is worth a read. Here are some major points:

(1) Choose When to Choose - If choice makes you feel worse about what you've chosen, you really haven't gained anything from the opportunity to choose. By restricting our options, we will be able to choose less and feel better.

(2) Be a Chooser, Not a Picker - Choosers make the time to modify their goals; pickers do not. Good decisions take time and attention, and the only way we can find the needed time and attention is by choosing our spots.

(3) Satisfice More and Maximize Less - Maximizers suffer most in a culture that provides too many choices. Learn to accept "good enough" since it will simplify decision making and increase satisfaction. Results are subjective sometimes; yet, satisficers will almost always feel better about their decisions.

(4) Think About the Opportunity of Opportunity Costs - The more we think about opportunity costs, the less satisfaction we'll derive from whatever we choose.

(5) Make Your Decisions Nonreversible - The very option of being allowed to change our minds seems to increase the chances that we will change our minds. When we can change our minds about decisions, we are less satisfied with them.

(6) Practice and "Attitude of Gratitude" - Our evaluation of our choices is profoundly affected by what we compare them with, including comparisons with alternatives that exist only in our imaginations. The experience can be either disappointing or delightful. We can improve our subjective experience by consciously striving to be grateful more often for what is good about a choice and to be disappointed less by what is bad about it.

(7) Regret Less - The sting of regret (actual or potential) colours many decisions, and influences us to avoid making decision at all sometimes. Although it is often appropriate and instructive, when it becomes so pronounced that it poisons or even prevents decisions, we should make an effort to minimize it.

(8) Anticipate Adaptation - Learning to be satisfied as pleasures turn into mere comforts will reduce disappointment with adaption when it occurs.

(9) Control Expectations - The easiest route to increasing satisfaction with the results of decisions it to remove excessively high expectations about them.

(10) Curtail Social Comparison - We evaluate the quality of our experiences by comparing ourselves to others, so by comparing ourselves to others less, we will be satisfied more.

(11) Learn to Love Constraints - As the number of choices we face increases, freedom of choice eventually becomes a tyranny of choice. Choice within constraints, freedom within limits, is what enables us marvelous possibilities.