As far as I understand, Dolphin BI will be a web-based platform with connection to Ethereum and Waves platforms in order to enable transfers of tokens. Is that correct? I did not fully understand, in your whitepaper, what do you call a set of smart-contracts that Dolphin platform is based on? Are those the Ethereum-based smart-contracts? Or these will be smart-contracts programmed from zero for the Dolphin BI purposes? What is the functional core and principles of these smart contracts from programming point of view?
Thanks for a good question!
We plan to use Ethereum smart-contract as a platfrom core which implement the following functions:
- update Experts’ ratings
- distribute reward among Experts and Authors (in DOBI tokens)
- accept monthly subscription fees (in DOBI tokens) and assign widget access rights for Subscribers (e.g. on pay-per-month basis)
- voting on platform rules updates
This contract will use ERC20 tokens named DOBI. A gateway with Waves Platfrom is planned to be implemented to allow a user to buy and sell DOBI tokens through the Waves Platfrom wallet and DEX.
Frontend is planned to be implemented as a webservice initially and then also a mobile apps will be developed (as descibed in our roadmap). If DApps become widely adopted we will think to implement our Frontend as DApp.
Widgets and Data Providers are to be implemented as Docker containers (we already have this architecture in beta.dolphin.bi). If a decentralized computing becomes widely adopted (Golem, SONM, iExec etc) we will think on moving to a decentralized architecture in this part.
Thank you for your answer! I have couple of other questions: you have already mentioned some resources that you are collecting the data from, like social networks. Could you please name some other sources of the data you are using or want to use for analytics? In your opinion, what would be the most crucial criteria (one or several) in order to identify fraud/suspicious project, and would it be possible to do it based on automated analytics only, without expert involved? Speaking about investment analytics, in which form the final automated investment recommendations/fraud warnings will be given? Will it be some sort of ranking?
Hello Elementique!
Actually, the project itself started from analyzing distribution curves of ICO payments. We have found that for all solid ICOs the distributions after logarithmic transformation looked very similar (bell-shaped, so the underlying distribution could be considered Gaussian or Student's). This allowed us to detect tampering in payments - for example, the project investing big in the start of its own ICO to simulate high demand. However, the main problem here is that this analysis can be only performed after the ICO, so we decided to instead concentrate on something more useful at all stages, like sentiments or ICOface (a database of all people who did an ICO, where you can look them up by their photo).
So what you can surely expect in the future is payment curve and payment distribution analysis, and we also had a cool idea floating around about clustering addresses to find out whether, for example, exchanges were involved. But this is not our focus right now.
As for detecting whether the ICO is fraudulent or not directly, several problems arise - first, the data on fraudulent projects is scarce, not nearly enough to train a decent model; second, people seem to distrust even an amazing model, when the task is formulated as predicting fraud/not fraud. And if you make even a single mistake, you can really upset either investors or the project team that you called fraudsters. After interviewing some investors we found out that they would prefer to see indicators of possible fraudulency themselves and pass judgements on their own.
In the meantime, we will concentrate on some basic widgets like exchange rate curves, number of token holders, token balances distribution and so on.
And perhaps could you please give more insights into the "bug-bounty" program? How it will be implemented, and what would be the main purpose of it?
This is going to be an automated bug hunt after the initial version of Dolphin BI smart-contract will be deployed. The idea is that we set the contract's invariants, and people who manage to break them will automatically be rewarded.
Here's an article where you can learn more:
https://blog.zeppelin.solutions/setting-up-a-bug-bounty-smart-contract-with-openzeppelin-a0e56434ad0e