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1. Collect source data 2. Run data analysis 3. Processed dataset is generated 4. Processed dataset is hashed 5. Hash is combined with the API wa

1. Collect source data 2. Run data analysis 3. Processed dataset is generated 4. Processed dataset is hashed 5. Hash is combined with the API wallet address and rehashed 6. That hash is stored on chain and with a transaction involving their token 7. Data from step 1 changes, repeat It is getting more structured. I like that. The way I read this: - A company created a dataset and updates it from time to time. - For each update, they put a hash of the dataset on a blockchain. Ok. And what is the use case? What would be different if they did not publish the hashes on a blockchain?

mrweiner 3y ago
> A company created a dataset and updates it from time to time. I suppose update frequency doesn’t matter from the perspective of just conveying how it works, but it could be updated frequently. For instance, any time a paper is published, or if the customer provided a data stream, etc. > Ok. And what is the use case? What would be different if they did not publish the hashes on a blockchain? The idea of blockchain is “don’t trust, verify,” right? Imagine you’re a researcher and you’re using this company’s services. Having the hashes on-chain allows you to verify the integrity of the data over time. Having it on-chain removes attack vectors associated with e.g. a standard database. Similarly, all of Vectorspace’s tooling for various services benefit from the same assurances that the data is sound. So like I said initially: data provenance.
- ArtTimeInvestor 3y ago
  "Verify" in which way? What would be the simplest example of "using this company’s services"? Maybe an API call like this? GET /animals/dogs/ears/count And that returns "2"? Now you know that the company claims that dogs have 2 ears. How does the fact that they published a hash on a blockchain allow you to "verify" that statement? At best, you can say "The company claims that dogs have 2 ears and they did so 3 months ago already", right? But the hash does not help you verify the claim on how many ears a dog has.

mrweiner 3y ago

> A company created a dataset and updates it from time to time. I suppose update frequency doesn’t matter from the perspective of just conveying how it works, but it could be updated frequently. For instance, any time a paper is published, or if the customer provided a data stream, etc. > Ok. And what is the use case? What would be different if they did not publish the hashes on a blockchain? The idea of blockchain is “don’t trust, verify,” right? Imagine you’re a researcher and you’re using this company’s services. Having the hashes on-chain allows you to verify the integrity of the data over time. Having it on-chain removes attack vectors associated with e.g. a standard database. Similarly, all of Vectorspace’s tooling for various services benefit from the same assurances that the data is sound. So like I said initially: data provenance.

ArtTimeInvestor 3y ago
"Verify" in which way? What would be the simplest example of "using this company’s services"? Maybe an API call like this? GET /animals/dogs/ears/count And that returns "2"? Now you know that the company claims that dogs have 2 ears. How does the fact that they published a hash on a blockchain allow you to "verify" that statement? At best, you can say "The company claims that dogs have 2 ears and they did so 3 months ago already", right? But the hash does not help you verify the claim on how many ears a dog has.