Internet the way I see

What is common between Facebook, YouTube, Flickr, LinkedIn and Twitter? Well easy to guess, they all are social networking sites which focus on building online community where people share their interest and activities. In Facebook people create their own profile and share their interests through various online communities, YouTube and Flickr are videos and image management and sharing sites, LinkedIn is a business networking site where people create their profile but unlike Facebook the profile contains mainly details about educational background and their profession and use it for serious business networking. Lastly Twitter is a micro-blogging service. In past few years a trend can be observed that majority of data is user generated i.e. information is “by the people, for the people and of the people”. Compared to the era of 1990’s where there were relatively few information producers and a large number of consumers, the situation has changed now and there is lot more focus on an individual, people try to project themselves either through their profiles in Facebook, LinkedIn or by having their personal Weblogs. Thus now there is a personal space for everyone on web.

Let’s see one more aspect of web. It is a vast ocean of information. Currently most of the information on web is represented using natural language (like English, Russian, Hindi, etc) or using graphics multimedia etc. This information can be processed by humans as they can easily form association between disparate forms of data even if they use different terminologies. However the same task is difficult for machines, it is difficult for them to make sense from say an image, draw analogies or to combine information from heterogeneous sources and make associations among them. There are several tasks which involve tedious work of finding, sharing and combining information on the web; it would be nice if such tasks can be automated i.e. performed by machines (intelligent agents).

For ex: Consider an automatic reservation system. The system should
1. know about my preference
2. build up knowledge using past
3. combine the local knowledge with runtime services
• airline preferences
• dietary requirements
• calendaring
• etc

For making these tasks automated we need a way in which data should be possibly combined, merged on a web scale, there should be some data that describes other data; machines should be able to reason about the data. To make this happen we need a way of defining semantics of the information and services on the web. This concept of making data on web more meaningful is generally referred to as Semantic Web.

To conclude following trends can be seen
1. Greater focus on an individual
2. Semantic web




I did search of "Semantic Web" on Google trends and here is what is shows