Inspiration

My interest in NFTs started with my dad. Although he has never owned an NFT, he is my inspiration for getting into the space because he is a professional comic book deal. Growing up, I would watch my dad place bids on eBay as he sought out the most desirable comics and collectibles from the 1930s, 40s, and 50s. What started as a hobby of his grew into a full profession, where our childhood house is home to more than 17,000 comics and collectibles.

Seeing how he strategically analyzed every collectible purchase, I thought it would be amazing to develop an analytics product that could give buyers insight into NFT collections. Since RMRK is a fairly new, but promising, builder in the NFT ecosystem, we thought it would be a great place to dig deep and show the on-chain data of how collections are being priced over time.

What it does

Our RMRK Time-based NFT Explorer allows users to query NFTs by author, collection, or name. With each collection, you can view data like floor price, number of sales over time, and number of unique owners. When it comes to an individual NFT, users can view the NFT's owner, traits, and current state.

How we built it

We built the RMRK Explorer using a SubQuery backend that leveraged their new Historical Query feature. For the front end, we took some inspiration from https://www.asalytic.app/ and built the UI with React.

Challenges we ran into

The biggest challenge we ran into is that in this last week of the hackathon, our front end developer got Covid, so we only were able to create the backend of our product. We will still complete the front end, but unfortunately won’t be able to do it before the hackathon deadline.

The Historical Query feature on SubQuery is pretty new, so we got slowed down when we realized that we would need a new server to store the historical data. Another issue we ran into was getting the metadata of the NFT return back the image url. It turns out that IPFS is super slow and often times the call to get the metadata 504's. We could index the image URLs, but we would need a gateway that will not 504 inside the SubQuery project. Public gateways are not reliable for this, so it has been a sticking point to really get the best images possible.

Accomplishments that we're proud of

The beautiful interface and intuitive user experience we created for RMRK users

What we learned

We learned that NFTs are all unique in their image hosting characteristics, and so there needs to be a more universal standard of where NFT image data is stored.

What's next for Alphabit

We believe our RMRK Explorer is just the beginning of our NFT analytics journey. The explorer is great for everyday RMRK NFT users, but there are more opportunities to enhance the product to cater to the analytics needs of advanced NFT traders. In the near term, we plan to connect with the top NFT investors in the RMRK ecosystem to see which analytics will help them make more informed decisions about which NFTs and NFT collections to are going to produce the best returns. With this feedback, we'll integrate advanced trading features into our product and then look to users for continuous feedback.

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