This week ReadWriteWeb will run a series of posts detailing what we think are the five biggest, most cutting-edge Web trends to come out of 2009. We'll be posting one trend analysis per day. Then at the end of the week we'll publish a major update to our standard presentation about web technology trends. The first major Web trend we're looking at is Structured Data . In prior presentations , this has sometimes been referred to under the umbrella term of 'Semantic Web'. However the way 2009 has panned out so far, it's become clear that this trend is much more than the Semantic Web. In this post, we'll analyze the developments in Structured Data this year and provide you with 3 product examples: OpenCalais, Google, Wolfram Alpha. Sponsor Editor's note: This story is part of a series we call Redux, where we'll re-publish some of our best posts of 2009. As we look back at the year - and ahead to what next year holds - we think these are the stories that deserve a second glance. It's not just a best-of list, it's also a collection of posts that examine the fundamental issues that continue to shape the Web. We hope you enjoy reading them again and we look forward to bringing you more Web products and trends analysis in 2010. Happy holidays from Team ReadWriteWeb! Web of Data, Not Documents Tim Berners-Lee said in February this year that we're now in a Web of Data , rather than a Web of Documents. The organization that Berners-Lee heads, the W3C, has heavily promoted two key initiatives that are helping to build this Web of Data: the Semantic Web and more recently Linked Data . However over the past few years, we've seen that there are many other ways to structure data and enable others to build off it. The best current example is surely Twitter , whose API has historically been responsible for around 90% of Twitter's activity - via third party apps. The basic principle of the Web of Data is still the same as what Alex Iskold articulated on ReadWriteWeb back in March 2007: "unstructured information will give way to structured information - paving the road to more intelligent computing." Example 1: OpenCalais Our first example product, OpenCalais , is probably the best current example of Linked Data (which is a type of structured data endorsed by W3C). Thomson Reuters, the international business and financial news giant, launched an API called OpenCalais in Feb '08 . In a nutshell, OpenCalais turns unstructured HTML into semantically marked up data. It orders data into groups such as 'people,' 'places,' 'companies' and more. This way, third party applications and sites can build interesting new things from that data - one of the defining principles of Linked Data. For a full explanation of Linked Data, read Alexander Korth's technical introduction The Web of Data: Creating Machine-Accessible Information from April 2009. I also explained the background and benefits of Linked Data in a May '09 post entitled Linked Data is Blooming: Why You Should Care . Example 2: Google Rich Snippets In May this year, Google added structured data to its core search, in the form of a feature called 'Rich snippets.' Essentially this feature extracts and shows useful information from web pages, by way of structured data open standards such as microformats and RDFa. On launch in May, Google invited publishers to mark up their HTML. While it will take a while for this markup to become widespread, the fact that a huge company like Google implemented it shows the increasing importance of structured data on the Web. Other big companies are also heading in this direction - in particular, Yahoo was an early leader . Example 3: Wolfram Alpha Ever since Wolfram|Alpha 's much hyped launch in May , we've been tracking this innovative product closely. It's a self-described "computational knowledge engine" and while it's not quite the Google killer some predicted, it has many potential uses . Wolfram|Alpha has a search engine-like interface, allowing you to type natural language statements into it. But the main part of the product is the computations you can do on data. The product is premised on using and computing data . If Web 2.0 was about creating data (a.k.a. user generated content), then the next generation of the Web is all about using that data. Conclusion We can see from the above three examples that structured data is rapidly becoming a feature of today's Web. Companies like Thomson Reuters and Google are enabling data to be structured, and new types of products (like Wolfram|Alpha) will make use of structured data in ways we perhaps can't imagine right now. ReadWriteWeb's Top 5 Web Trends of 2009: Structured Data The Real-Time Web Personalization Mobile Web & Augmented Reality Internet of Things Discuss

More here:
Top 5 Web Trends of 2009: Structured Data

In my recent post about the rise of content farms like Demand Media and the current incarnation of AOL, I posited that Google (and search in general) risks becoming less relevant as the Web gets drowned in lesser quality content. This is due to the scale at which these content farms are operating at - Demand Media alone pumps out 4,000 new pieces of content every day . The solution is of course for Google and other search engines to find better ways to surface quality content , whether that be from traditional news media, blogs or even Demand Media ( not all of its content is poor quality ). So how can Google evolve to identify quality content better? Sponsor Quality! Pah, Does Google Need to Bother? Perhaps we should first answer the question: why should Google be worried about the quality issue? After all, it has a virtual monopoly on the search market. The obvious and PR answer is that Google wants to provide the best search results possible for its users. But there is another big reason why Google needs to do something. So-called "quality" content providers are already well advanced in routing around Google, or at least making them less relevant. As I wrote yesterday, Reuters is onto something with its subscription business model. According to Chris Ahearn , President of Media at Thomson Reuters, the company already makes the "vast majority of its revenues" from subscription-based business models targeted to "vertical and niche markets." Reuters also provides services as well as just content. Bloomberg is another leading media company finding success with this strategy. The subscription model is making inroads, because the users themselves are flocking to it. A prime example comes from VC Paul Kedrosky , who became frustrated after doing various Google searches for "dishwasher reviews" and getting unsatisfactory results. He says that this has made him "more willing to pay for things" - in that case a Consumer Reports review of dishwashers. As Kedrosky archly noted, "the opportunity cost of continuing to try to sort through the info-crap in Google results was simply too high." What Google Can Do Google surely knows that quality (or lack thereof) in its index is a problem. As one part of the solution, Google is currently experimenting with real-time search results from social media sites like Twitter, MySpace and even Facebook. The theory is that users are more likely to get timely, relevant results by tapping into their social network. That's all well and good, but real-time search is unlikely to give you better results on the dishwasher search and other topic-focused search queries. So what else can Google do to identify and surface quality material? Some readers in Sunday's post (Tadhg, Charles Coxhead and others) argued that Google's current algorithm accounts for quality well enough, through the link economy. But many others thought that Google must improve its ranking of quality. Here were some of our readers' suggestions: Neutralize the link dilution; A.J. Kohn , who further wrote that "the introduction of SearchWiki, their measurement of short-clicks versus long-clicks, the new domain/brand SERP listing, snippet links, and use of breadcrumbs all point to a gathering movement to help determine quality without such a reliance on an ever diluted link ecosystem." Do a better job ranking authority; for more on this read Clay Shirky's post on "Algorithmic Authority." Introduce a user rating system; Tony Masinelli. Leverage sharing networks to determine where the quality is; Alex Kessinger . Special curation and algorithms on top of that; William Mougayar, whose company Eqentia does precisely that. p2p recommendation (i.e. filtering through your peers); Nick Taylor . Capture engagement data; Mark Littlewood . Give special weightings to categories of content, e.g. content farms, social media bookmarks blogs and Twitter; Aaron Savage . Use anti-spam type software to identify content that makes too much use of keywords; Barry . Track reputation against authors rather than URLs - a 'PageRank for People'; Marshall Clark . These are all great ideas. Google is almost certainly already doing some of these things already - as will other search companies. John Battelle is expecting a "major breakthrough" in search in 2010 and I hope he's right. One thing is for sure, Google will need to do more in 2010 if it's to stay ahead of the content farms and continue to surface quality content for its millions of users. Discuss

Here is the original post:
How Google Can Combat Content Farms