GEMMA Planet
The GEMMA planet refers to all services that use GEMMA Network as a third-party service. GEMMA Network does not impose restrictions on the use of GEMMA Network, and all responsibilities and results for use lie with the tertiary service itself. The GEMMA planet has been classified into WEB 3.0, NFT, PAYMENT, and REWARD according to the type.
WEB 3.0
The GEMMA Network includes a design to support WEB 3.0. It supports high transaction rates, enables metadata management, and provides information security. Therefore, it is possible to flexibly process big data using blockchain, and the WEB 3.0 platform that can be implemented in a more stable decentralized manner.
COLUMBUS
Columbus is a decentralized big data solution applied with the GEMMA Network. Columbus was named to play a pioneering role in the WEB 3.0 market. Columbus is a big data platform that provides blockchain-based user data. This white paper will cover GEMMA NETWORK's WEB 3.0 platform as an application example.
The current data market is exclusively biased toward large companies and is making very high profits from the standpoint of companies through auction-type data billing. On the other hand, users who provide data do not benefit from providing data at all, and the path of providing data is unclear, creating a very unequal market in the relationship of providing and using data. Another problem is that the reliability of the data provided cannot be verified. Data users have to pay high costs without a way to verify the reliability of the data.
Columbus is a decentralized big data platform that solves these problems and creates a transparent relationship between data providers and users. Users can transparently manage their activity data provision. And data users who can access the data can also be checked transparently. When providing data, users can receive rewards directly from data users. On the other hand, data users will be able to receive reliable data that is recorded on the blockchain and cannot be forged. In addition, the cost of using data itself can be lowered.
Columbus' way of working is very similar to Google AD. First of all, COLUMBUS uses LEMMA Uploader to collect data from users. A service provider that provides any APP or WEB service can build LEMMA Uploader into its platform. When users use the service, their data is stored in LEMMA Chain through LEMMA Uploader. Users can check which MY DATA they have collected integrally and transparently through LEMMA Chain. The collected MY DATA is processed into meaningful information in LEMMA Chain and disclosed to users with special access rights such as advertisers through LEMMA Explorer.
GEMMA Blockchain will play three roles. First, it serves to reflect the data of LEMMA Chain in order to secure the reliability of the data of LEMMA Chain. Second, service users and service owners must issue their respective GEMMA wallet addresses. You can use My Data Management or My Service Management of the LEMMA Chain through the issued address. Lastly, it is used for rewards according to data usage. This is because the reward is sent directly to the user or service owner who provided the MyData.
DATA USER (advertiser)
For example, if an advertiser inquires the data of people who have paid for a game at least once in the LEMMA Explorer, they can select trusted advertising targets based on LEMMA Chain. If advertisers send images or video advertisements to these targets, users who experience advertisements will be rewarded as information fees.
COLUMBUS allows advertisers to approach their desired targets with eight data analysis and classification methods.
Affinity: The Affinity section allows advertisers to target customers based on a comprehensive overview of their lifestyles, interests, and behaviors. This section shows a customer base with proven enthusiasm for a given topic, allowing advertisers to target users who are more interested in a product or solution.
Client customization: When advertisers define campaign goals, this section can contribute to targeting customers based on enthusiasm, habits, and the most recent reason for purchasing.
Detailed History: This section will help advertisers target users based on long-term observations of their lifestyles.
Life Event: This section can be used when advertisers plan and conduct various life events for the general public. This is because it is supported to select users to be targeted.
In-Market: Advertisers can approach the user according to the user's recent purchase intention.
Data segmentation: Advertisers can target users who have interacted with their businesses at least once.
Visitors: Advertisers can directly access users who are interested in the service.
Similarity: Advertisers can access customers who are similar to existing customers or users who are interested in services similar to advertisers.
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