Pivot Points is a monthly column by EuroScientist writer David Bradley.
The Web in the 1990’s, Web 1.0 you might call it, was all about content as everyone from shopkeepers to spectroscopists scrabbled to get online. The major scientific journals began their slow but steady adoption of the new access tools and community sites like ChemWeb and BioMedNet sprang up, endlessly mashing together capitalised prefixes and suffixes.
In the 2000’s, Web 2.0 emerged to add personal connections to that content through social bookmarking, social networking, and social media where users created or shared content. For science, this new information connectivity held all the promise of open collaborations, high-speed networking, and rapid access to the scientific literature.
Despite its antagonists, the Web 2.0 era sites, which include Mendeley, ResearchGate, Nature Networks, ResearchBlogging.org, ScienceBlogging.org and many others have grown rapidly and continue to expand membership and activity. The vast array of sites that purport to be a “Facebook for Scientists”, “MySpace for Researchers”, or an “iTunes for scientific journals” are still missing a key ingredient, however. Memberships are in the tens of thousands, compared to the hundreds of thousands enjoyed by the likes of BioMedNet in the 1990 and the hundreds of millions claimed by Facebook today.
Scientists are just as likely to be gossiping around the Facebook and Twitter water coolers as anywhere else. Certainly without reaching a critical mass the idea that any of the dozens of social networking sites for scientists will emerge as the main contender remains something of a pipe dream. Nevertheless, the semantic web will add machine-readable context to content and connections to give us web 3.0 and this could be the key ingredient that those sites need to find to allow them to adapt and survive.
We are, however, a long way from a realisation of the original vision of Tim Berners-Lee, inventor of the Web. He suggested that a semantic web would be as readable (and understandable) to a person as to a computer so that any digital object, whether that is a simple web page, an image, a video clip, journal article, or any other accessible file, would have embedded within it latent data, meta data, that would provide context to the content and allow software to extract meaning from the file.
Such a semantic vision would change search immensely because the computer would understand what you were searching for and return only entirely pertinent materials rather than page after page of irrelevancies. Moreover, semantics implies inference, which means that a computer could derive a logical conclusion given a set of facts.
There are a lot of scientists using social media to chat among themselves, particularly on FriendFeed and even with the general public via Twitter. Many have Facebook pages, some are on LinkedIn, others attend conferences such as ScienceOnline to discuss the very issues surrounding how best to do science in a web world. The majority of those involved are advocates of various approaches to social media and related communication tools. However, they are still but a small sample of the research sphere. The vast majority of scientists are not yet hooked up on these networks. Before the semantic web emerges with its many obviously, after the fact, advantages, should we persuade scientists to join in with Web 2.1 and what might that involve that would convince them of the benefits?
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