NFT marketplace for science and technology launches

In response to an overwhelming demand for NFT minting and listing by its thousands of members and associated experts, RMDS, a data & AI ecosystem platform, declared that it will start offering NFT services. By late March 2022, RMDS will launch the world’s first NFT marketplace solely for science and technology IPs.

NFT Marketplace for Science and Technology IPs from RMDS

NFTs (Non-fungible Tokens) have been widely adopted for authenticating and exchanging IPs in the fields of art, gaming, and other collectibles. In 2021, NFTs rapidly grew due in part to their ability to capitalize on digital content and digital assets. After the NFT for “Everydays: The First 5000 Days” was sold for $69.35 million in March, worldwide NFT trade grew rapidly. According to Binance, NFT trading increased a whopping 42,988% between 2020 and 2021.

Per Dune Analytics’s collected data from public blockchains, on Jan 2, 2022, OpenSea, the largest NFT marketplace, recorded trade of $243 million on the Ethereum blockchain (far higher than the trade volume of $170 million on Jan 1, 2022) and $124 million on Dec 31, 2021. OpenSea completed a roughly $3.25 billion transaction on the Ethereum blockchain, another record next to the $3.4 billion in August.

Most current NFTs traded on OpenSea and other major marketplaces are art IPs. However, NFTs for science and technology IPs started to merge, including some for Nobel prize-winning research and augmented-reality images of space, even for unpublished scientific research papers. Unfortunately, all of them emerged separately and often got overshadowed by art NFTs, so they have not impacted science and technology developments yet.

RMDS was developed from a known data science community and founded in 2009 by IBM’s Chief Data Scientist, Dr. Alex Liu, promoting scientific innovation via data and AI. Since 2019, RMDS has offered conferences, training, a data project online portal, global data science competitions, and other services to develop scientific IP exchange for more impactful data research. Specifically, RMDS’s many offerings, including an open ecosystem platform, RM4Es-based workflow management, and an RMDS exchange service, demonstrate the company’s accumulation of great resources, communities, and experience for developing and managing science IP marketplace, including that of NFTs.

As the world’s first science & technology IP NFT marketplace, RMDS will solely focus on connecting scientists with investors and linking science & technology IPs with related collectors, investors, and science lovers. Here, RMDS will significantly promote the applications of science & technology IPs to speed up the world’s science & technology innovation. “RMDS’s science & tech NFT marketplace, as the first in the world, will provide new fundraising channels for science & tech projects, will speed up technology transfers, and benefit scientists and the public worldwide. It will also help with taking the NFT business to a completely new level,” said David Zhang, the co-founder of RMDS and founder of Shunya International, a public company.

At the same time, RMDS plans to start its quarterly data science competition for NFTs on January 31, 2022. Contestants will be challenged with collecting datasets to create a dashboard that assesses trends in the development of NFTs and forecast their future trajectory. RMDS’s data science competition is a well-known event to data science communities worldwide. RMDS has partnered with many notable organizations, such as the City of Los Angeles and NASA JPL.“RMDS, as a leading data & AI community and company, has been searching for ways to create wide applications of science and technology. NFT marketplace provides the best solution here. I believe the RMDS Sci & Tech IP NFT marketplace will be loved by scientists worldwide. It will become one of the best places to materialize the value of science & tech projects, to speed up science and technology innovation worldwide,” said Dr. Alex Liu, the founder of RMDS and an advisor for the Harvard Data Science Review.