Many people believe that desktop software will become irrelevant as we enter the age of Web 2.0. This seems to be plausible, at least to those of us who worked in technology. However, if we step back and think from an everyday user’s perspective, a different picture emerges.
Jay Larock, a Senior Product Manager at Corel Corporation, wrote an interesting essay that argues why desktop software is still relevant in the age of Web 2.0. His argument is as the follows.
RDF (Resource Description Framework) is language for describing the semantics of information on the Web. The Semantic Web is a vision of the future Web that will help to increase people’s productivity by enabling machines to understand the Web semantics. While RDF and the Semantic Web is closely related, but it’s a mistake to think that the realization of the Semantic Web and its success will solely depend on RDF technology.
When building Semantic Web applications, developers should keep in mind that the goal is to develop useful technology to help human users — increase their productivity and ease their computing tasks. It’s a mistake to believe that the only way to achieve this goal is by building RDF applications and by developing applications that are solely based on RDF (its syntax, modeling, data stores etc.).
Nova Spivack has some interesting thoughts on the Semantic Web future. His company Radar Network, a software company funded by Paul Allen’s Vulcan Capital, is developing a new semantic platform and online service for group communications and collaboration.
In his essay Minding the Planet: the Meaning and Future of the Semantic Web, Spivack discusses important issues that surround the present Semantic Web development and the future Web.
But what is the Semantic Web, and why does it matter, and how does it enable collective intelligence? And where is this all headed? And what is the long-term fa future going to be like? Is the global mind just science fiction? Will a world that has a global mind be good place to live in, or will it be some kind of technological nightmare?
It’s a sixty-four thousand dollar question — how to create useful Semantic Web applications that will impact the lives of everyday users? Not sure if there is a fixed formula for archiving this objective, but definitely we can define the directions for our future innovation.
After reading John Milan’s blog, I think there are at least two key components that Semantic Web entrepreneurs should pay close attention to: browsers and data.
To geotag blogs is to annotate weblog posts with geographical information. There are at least few reasons why this is a good idea.
Geotagged blogs will enable web search engines to effectively index blogs based on geographical information. This information will help to build more powerful search engines that support spatial queries (e.g., find all blogs on the topic “war” and written by people who are located in “Iraq”). Moreover, geographical information of blog posts will also help us to understand the trends and the ecology of the blogosphere (e.g., what’s the most discussed topic in a particular geographical region, and how opinions differ between people who live in different counties?) At present, these studies are done by collecting IP locations of the bloggers and the written languages of the posts (I think).
There are few different languages and tools for publishing geographical information about blogs, for example, GeoRSS, Microformats, W3C Geo, FOAF, WordPress Geo Plugin (see also [1]).
A question I ask myself today is that “if we already have the languages and tools for geotagging blogs, why geotagged blogs are rare in the blogosphere?”
The term ontology should be no stranger to anyone who studies the Semantic Web. Even if it’s the first time that you’ve heard of this term, you can answer “what’s ontology?” by googling Wikipedia — “an ontology is a data model that represents a domain and is used to reason about the objects in that domain and the relations between them.”
On the Web, what counts as an ontology? This is a question that Tim Finin and Li Ding have explored in their paper “Untangling ontologies on the Semantic Web“.
In their research, they analyzed a collection of over 1.7 million Semantic Web documents (RDF documents) that were crawled by the Swoogle search engine. Based on the statistic data from their analysis, they inferred the characteristics of ontologies in the present Web and used this knowledge to answer the question: what counts as an ontology?
Ontology is a key foundation of the Semantic Web. Without ontology, it will be difficult for applications to share knowledge and reason over information that is published on the Web. However, it is a serious mistake to think that the Semantic Web is simply a collection of ontologies.
Last week I was invited to be on a panel discussion at the Humans and the Semantic Web Workshop. I talked a bit about the Geospatial Semantic Web and its associated research issues. Overall the workshop went very well. You can read about the notes from the workshop here.
The Web has tons of information. The Web also has tons of geospatial information that computer programs don’t really know how to acquire and make use of.
The Web has helped people to be more productive. Geospatial applications such as Google Maps, Google Earth and other “mash-up” applications not only increased people’s productivity but also made their computing experience more enjoyable.
The present Web applications mainly focused on the presentation of information and the enhanced computer-user interactions. While it’s important to continue our innovations in these areas, but also it’s important to tackle new problems that can’t be solved by simply building better UI or more dynamic web pages, e.g., geosptaial semantics.
There are different types of geospatial information on the Web: maps of the Earth surface, digital photos of geographical locations, text documents that describe different world places, events, and people, etc. While information is expressed in ways that are suitable for the humans to understand, but it’s not so for the computer programs. It’s often difficult to develop software programs that can effectively search, discover and reason about the Web’s geospatial information. I called this type of information the hidden geospatial knowledge.