Over the years, there was a lot of discussion regarding the idea of building Wikipedia on Hive. Is this really possible?
In this article, we will look at the possibility of something like that and how it would look.
Before going any further, we have to say that building Wikipedia would be a mammoth undertaking. That project has a couple decades under its belt and a large number of people working on it. To create something like that on Hive would take years.
However, is there a way to duplicate what is going on, even if to a lesser degree? This will be the thrust of our conversation here.
Once again we are going to focus upon Hive as a permissionless, decentralized database.
Hive is an open data storage system with infrastructure already in place. What this means is that, if one wants to build a database, that is available for use.
This is not the case with Wikipedia. It is a true Web 2.0 application. Hive is part of the foundation of Web 3.0. Instead of going out and renting servers, one simply starts building.
Here is a page from the Wikipedia Foundation. It is likely most reading this came across the banners discussing how so few donate to the cause of free and open knowledge. This does not exist on Hive.
The entire business model shifts when entering Web 3.0. Suddenly something like this could be built without the hassle of worrying about infrastructure or the associated costs.
Infrastructure on Hive is provided by block producers who are incentivized in that direction. This comes from the inflation in the base coin, which is distributed for performing this service.
In addition to having a different business model, we have a database that is immutable. Once it is on the blockchain, the information is there. Also, unlike Wikipedia which is likely on a coordinated set of servers, the Hive ledger is mirrored on over 100 uncorrelated nodes. Each is running the software and updating the content every minute throughout the day.
Unlike distributed ledger technology such as Bitcoin, the Hive ledger contains more than just transaction information. Instead, it allows for full text documents to be stored in the dataset.
Finally, once the data is on chain, any front end can read it. This will help a great deal when it comes to search engine ranking.
We often discuss the idea of communities and how powerful they will become. The idea of each being able to spin up its own token and turning itself into an economy is a game changer. That is going to alter the path of society.
There is another point to this. With Hive, each community can also generate its own database if needed. Here is where the idea of "Wikipedia on Hive" comes in.
As opposed to a team trying to build out the project, it develops naturally. After all, the data is housed in the same place regardless of who put it there. Hence, all applications that read the information on Hive will pick it up.
What kind of database would a community build?
This would be anything that has to do with the basics of that community. For example, the photography community could create a database of terms and concepts relating to that field. CineTV could do the same for movies and television shows. If we had a Real Madrid community, they could start a database of the bios on all players, present and past.
The field is actually wide open.
Having an immutable database of information that is on a decentralized storage system is something we have not looked at enough.
While having a database of best gardening techniques might not be the make or break for humanity, there is something to keep information safe.
Let us consider for a second if Wikipedia suddenly was taken down for not paying their bills. What would happen to the accessibility for that information? Naturally, it is in the Internet archives but we know that, rather quickly, the search engines would drop the site from the results.
The same is true for any information source we go to. If companies like AWS decide to turn off the switch, it is effectively gone from the view of most people.
Hive provides a solution to this. With over 100 nodes in operation, each mirroring the content, we are going to see this ongoing. The incentive is there to keep the servers running.
Another benefit is the fact that the information can start to rank in the search engines. We know that projects like Wikipedia and Investopedia turn up on page 1 in many related searches.
Type in anything about finance and the latter will certainly come up as one of the top results in Google. Of course, Wikipedia pops in there also. We will cover why this happens in a bit but the key is that both receive a ton of organic traffic.
Here is where Hive's open database system really can help. Once the data is on chain, all front ends have it. This means that, while the one that originated the information gets the weighting from Google, all will receive some ranking help. Something posted through Leofinance aids that site the most yet both Hive.blog and PeakD still gain.
With a single category of information, this does not equate to much. However, if each community is building out a database of basics concepts, the totality of it will help to thrust Hive onto first page ranking.
The Internet is still made up of hyper-linking to a great degree. This is what makes something like Wikipedia so powerful.
Let us look at the page of American Actor Alan Alda.
We can see there are 24 links in the first paragraph alone. Each of them goes to another Wikipedia page. Can you imagine what does that to the Google spider once it gets into Wikipedia? Internally, it is going to bounce around among billions of links, all related to each other.
Is it any wonder why Google ranks it so high?
Of course, this does not deal with external links. This article has linked to that site a few times already. The site is a treasure trove of information, hence content creators are constantly linking to it. Once again, Google loves that.
Transitioning back to Hive, think of something like Investopedia. Here is their definition of a put. It utilizes the same concept. The page is full of internal links sending people to other Investopedia pages.
This is exactly what could be done on Hive. Different communities could follow the same format, providing linked databases the search engines love.
Of course, others can use the information and reference in their articles. Considering that we write posts, it is easy to see how we can grow this quickly.
Think about these terms and how often they appear on Hive each day:
What would be the impact if each of them was one of the first page of Google for those terms?
One again, how would things look if there were dozens of databases like this on Hive, all pertaining to categories that were applicable to different communities?
Over time, an information base like Wikipedia would form on Hive. Suddenly users, both internal and external could start linking back to the information.
This is how something like Wikipedia could eventually be built on Hive. Remember, that is nothing more than a database on a centralized server system along with a single front end.
With Hive, we simply decentralize it while adding the ability to access it through many front ends.
A glossary of crypto/financial terms can be found here
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