From WWW to GGG: A better Web awaits

I plan to create a new Web separable from the previous Web layer (Web 2.0) that is computable by machines. In just a few shorts years, what we currently understand as the Web will be replaced by Semantic Repositories that enable new applications that can effectively manage our lives and businesses. This Web will have its own way to define and handle terms, concepts, relations, axioms and rules--the structural components of an ontology. Everything else should revolve around it, data population, ontology enrichment, subject indexing, searching, matching, sharing. It will be as different from your current Web experience as your old landline is different from your smart phone. Today’s Web is designed around text and images published as documents to be read and processed by humans. The Concept Web will be designed around concepts published as data in Semantic Repositories that can be read and processed by devices, enabling these machines to find, combine and act on information on the Web from multiple sources.


By publishing content to Semantic Repositories, we remove the silos to create vast storehouses of structured, machine-readable information. These platforms replace or supplement text-based documents with concepts-based data, enabling machines to process knowledge, similar to human reasoning, obtaining more meaningful results. Devices then communicate with one another to perform tasks that currently require multiple searches and force the user to integrate all search results to perform the task.

Today’s Web information is siloed by applications, programs and sites made to automate and monetize specific tasks. Your calendar is an application programmed to schedule meetings. Your work documents use a different application. Your playlist is somewhere else. Soccer team schedules are somewhere else. Then there are the shopping, airline, hotel, community service and multitudes of additional sites, all isolated from one another. I envision a new Web consisting of maybe 35 Web platforms (as the new Web will be one giant database based on my new data model and top maps) covering local knowledge to science.  


The race is on to create mobile software agents (virtual assistants) that can perform tasks, or services for an individual based on user input, location awareness, and the ability to access information from a variety of online sources (such as weather or traffic conditions, news, stock prices, user schedules, retail prices, etc) and to perform ongoing tasks such as schedule management (e.g., sending an alert to a dinner date that a user is running late due to traffic conditions, update schedules for both parties, and change the restaurant reservation time) and personal health management (e.g., monitoring caloric intake, heart rate and exercise regimen, then making recommendations for healthy choices).


However, for all that to happen, we are going to need a new Web that bridges the gap between programming and semantic relations. If you've ever looked at the Google ads that pop up specifically for you, or had a try of Google Now, you will realize that the predictive powers of AI based on computational statistics are extremely limited. They might be able to pick vaguely the topics/products that are very loosely related to you, but they are completely unable to pick topics/products that are both related to you and of interest to you RIGHT NOW. So instead of getting served ads for random stuff you don't want, you get served ads for slightly less random stuff you don't want. 


 There are many pieces to this puzzle for this to work. The first one is extremely deep domain knowledge in machine-readable format. For example, in order for a virtual assistant to find great jeans it has to know everything about jeans. In order to book a flight, it needs many inputs and access to various Web sites or travel agents to do the booking. I'm seeking to help launch this phase of the Web by making blockbuster platforms that are also Semantic Repositories.


The new Web will be mobile first and computable by machines with network awareness which amounts to an engine for processing streams of information, classifying them, learning to spot differences, and using time-based patterns to make predictions about the future. This is the future of advertising. For example, the system may alert the user that there is a high risk of pollen exposure and direct him to a nearby store for allergy medicine products. Much like a stock ticker or a scrolling update, this approach enables proactive information services where the users can be notified of relevant information without the need to be active information seekers. For the old Web stay to relevant, a lot of proprietary systems will need access to each other's APIs and a coherence language, and history has shown large technology companies tend to protect their own patch. So the current Web will largely disintegrate into the lesser Web as as my new Web makes everything more coherent and usability goes way up. 



Once phase one is complete (destruction of the old fragmented Web), I plan to roll out a Web platform that directs science research. The system we’ll be able to merge all references to a concept onto a single topic and you will have access to all the information the systems knows about the concept in one place.  Researchers will be able to integrate their ideas into a greater collection of knowledge and shared across the Web. This will allow a single, coherent visual framework/systematic picture in which users can focus on one or more concepts and immediately see a conceptual summary of their focus. The system will then request scientists, etc to conduct detailed research to discover unknown facts about analyzed knowledge. The system would then put these facts into the database by itself, even without interaction with researchers. 

Many major scientific discoveries and breakthroughs have involved recognizing the connections across domains or integrating insights from several sources. In fact, a recent National Science Foundation report, “Rebuilding the Mosaic”, compiled over 250 white papers from researchers calling for more interdisciplinary research. These are not associations of words; they are deep insights that involve the actual subject matter of these domains. We know that by looking at multiple issues simultaneously, we can expand our knowledge and drastically change how we approach our common problems.

That's the kind of thing that would get science moving forward if done right and lead to revolutio ( where Scientists, professional and amateur would have secure profiles and could publish ideas quickly and be on record as the first to come up with something long before they could get a paper out for peer review. The pressure to publish here would come not from the science greats but from the fringe. If some group of amateurs starts using their collective brains to start mapping out ideas in your area of expertise, you better get all of your work out in the daylight or they will steal your thunder. Any ideas you post to someone else' page are there on record, so your part is known to all. In the past you could have one genius pushing our understanding because a lot wasn't known. Today, progress is a lot more incremental and departmental ... One guy spends 5 years and through trial and error he makes a small discovery. It takes time before other researches integrate his discovery into their thought and put it to use because everything is too fragmented and fucked up. The possibilities are endless here.