It is no secret what LeoGlossary is focused upon.

We are intent on building as big a database on Hive as we can. This will incorporate a bunch of different areas, eventually morphing into more areas that end up providing information on a wide range of topics.

So far we have chosen to concentrate on a couple particular areas. With limited resources in terms of personnel, we are still putting up a fair number of pages each day. This allows for more linking, which joins the pages together. This is something that is crucial as the Internet still operates on hyperlinks.

The idea is to get LEO pages expanding, joined together, and keep people (along with the search engine bots) moving from page-to-page.

A database becomes exponential. This is something that we have to keep in mind as we move forward. The slowest path for any of it is in the early stages.

In this article I will go through a few of the key aspects to this and how things are shaping up.

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Enter Once, Use Many

One of the key premises is to enter the information into the database one time but to use it repeatedly.

This is something that Wikipedia does exceptionally well. Not only does it have a huge database of information, with page linking into the billions, it is able to keep reassembling that data, creating even more pages.

It eventually becomes a compounding situation whereby the earlier information is reused.

We are seeing this a bit with LeoGlossary. Here is an example regarding the Academy Awards. This is a shot of the page for Best Picture:

As we scroll down the page, this is what we see:

So far nothing earth-shattering. Create a page, then do the same with a bunch of other pages, then link them.

Where things start to change is when we look at Best Director. Many of the same films won in that category also.

Here is what we see:

Since the pages were made for the other list, a number are easy to fill in. Hence, we have another situation where the same data (page) was used a number of time.

This also provides a couple different links to the individual movie page, drawing the bot to it twice.

Here is a simple example of what happens when the data grows. The ability to generate lists and other uses for the same data enter. It is not a one shot deal in many instances.

What The Internet Truly Is

It we want to get down to the basics, the Internet is nothing more than a series of databases that are accessed by front ends. The user interface is what allows us to see the data that is housed in the particular database.

Of course, these are controlled by the companies that own the data and we are there only with their permission. The fact we were the ones who generated it is not material, at least to the technology companies. You are on their platform, looking at their servers, it is all theirs.

This is how things operate.

Hence, if Web3 wants to be viable, we have to work on building our own databases. We know the likes of Twitter and Facebook are getting particular about sharing theirs. With the advancement of artificial intelligence, especially LLM, it is no surprise.

LeoGlossary is nothing but a database. The idea is to keep building pages of information that are linked together. Then, we can keep repurposing the data for other uses, gaining an exponential benefit.

Music on Leo is following the same mindset. When we look at Spotify or Pandora, what are they really? Nothing but audio databases. We can listen to music (among other things), again with their permission. We access the data using a front end designed to provide the features relevant to the user base.

None of these website would be worth much without the databases they constructed. Why do people on here not believe the same is true. Hive has a glaring hole: the database we set up has little of value in it. This is compounded by the fact that search and locating what we need is a nightmare.

LeoGlossary is changing this. While we are using some very old-fashioned methods, it is proven to be effective. It takes time and effort since there is a lot to input. Of course, it took years for the platforms we use daily to construct the databases they did. Do you remember the early days of Netflix and what their video offering was like.

Let us just say it was rather limited.

Ultimately, when it comes to media, the key is building a library of content. This is something that was given little attention on Hive up to this point. Leo is starting to offer new models that could help in this endeavor.

Nevertheless, there are things in the works to expand the scope of LeoGlossary. We have a couple more areas that we are discussing to start generating a vast amount of content.

That is what Leo truly needs.

And no we are not talking about more blog posts of 250 words meant to scalp a few rewards. What I am referring to is a database that contains data people find useful. It is something that people will return to on many occasions, such as with music. This is how we grow the value of the database.

If you want to rival the big boys, best get working on a database that contains more than just a few breadcrumbs.

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What is Hive

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