Evotegra: Extend 100k promo dataset with license plates and faces

[tmanthey]

Name of Project: Extend 100k promo dataset with license plates and faces

Proposal in one sentence

Extend the round 8 promotional 100k traffic dataset with annotations for licence plates and faces to enable the creation and evaluation of automated anonymization algorithms.

Description of the project and what problem is it solving:

In Ocean DAO Round 8 we commited to create a professional traffic image dataset with at least 100.000 images in ~300 categories and an estimated million objects. After the collection and annotation finished this dataset will be published on the Ocean Market with an initial data token price of 1 Ocean. The idea is to create promotional datasets that help to establish Ocean Market as a prime source of high quality data.
We propose to extend this promotional dataset next the promised 300 classes with annotations for faces and license plates. By adding these 2 classes we add significant extra value to the dataset which then can be used to train and evaluate automated anonymization algorithms which is an important requirement to assure compliance with privacy regulation such as GDPR.

Category

Unleash data

Metric

Data Consume Volume

What is the final product?

The final product is an extension of the promotional image dataset proposed in DAO round 8 with 2 additional classes “license plates” and “faces”.

Grant Deliverables:

1. Extend the promotional 100k dataset with face annotations
2. Extend the promotional 100k dataset with license plate annotations
3. Provide additional 5 to 6 digit annotations (data dependant)

R8 Deliverables

Our image collection, annotation, and publishing process follows a waterfall-like structure.
Although we have 50% of the R8 grant carried over, we are realizing the expenses for this batch of data now (Round 8), and amortizing the payment/work over the next 1-2 months.

The following tasks will be carried over from round 8:
[ ] Annotate the images in ~300 classes (~1 month). Annotation can now start since data collection was completed. This will cost 47.5% of the remainder grant amount, and should be delivered by October to November.
[ ] Publish the dataset in a pool for the initial price of 1 Ocean (~1 month). Publishing will take place after annotation is completed. This will cost a final 2.5% of the grant available.

Funding Requested:

20.000 USD

ROI

We see this effort as a starting point to add other promotional datasets. Our goal is to establish Ocean as a prime source for high quality data. The attractive entry price should encourage many first time users to get familiar with wallets, Ocean tokens and the Ocean Market itself.
We expect annotations in the 5 to 6 digits added to the dataset. By enabling new use cases to train and test automated anonymization algorithms this will notably increase the value of the data.

Proposal Wallet Address:

0x61B15998893cC746B46C08FEdEE13a0d1b33bBa9

Team

Web: www.evotegra.de
Email: manthey@evotegra.de
Twitter: @evotegra
Country of Residence: Germany

Previous OceanDAO Grant?

Yes

[realdatawhale]

Hello there!

We believe that your dataset(s) are adding a lot of quality towards the Ocean Market, as there is indeed a lack of quality consumable data at the moment.

However, we’re missing some deliverables tailored towards driving adoption (I.e. consumers) proposal. In the past, one of your proposals included an annotation towards leveraging EvoTegra’s network towards “buying” data on the Ocean Market. Was there any outcome with this? Surely the company has existing clients and it would be great if they could only access the dataset features through Ocean and not directly or through other means, in order to ensure the ROI is positive for network participants.

Since the dataset is funded through Ocean, it should not be available anywhere else (in my opinion).

Let us know your thoughts!

[tmanthey]

Due to the fact that pools had to be funded 70/30 at the time we published EVO/2MP/TRFC/DE/200K we had to split up the dataset into weekly parts to be able to fund the initial liquidity.
While that allowed us to publish a dataset, I think it reduced the value for potential customers. On the other hand we could not give away a dataset we invested a lot of resources in for bargain.
To overcome the dilemma we proposed in round 8 to the DAO to fund their own 100k image dataset that is separated from our data and published in whole for a very low initial price. The idea is here to create promotional datasets that have a very attractive price but still force potential customers to get involved with all tools needed to fully interact with Ocean Markets (Wallet, Tokens…).
To be clear: That dataset has been funded by the DAO and will be exclusively available within the Ocean ecosystem. We are not going to distribute it via other channels without prior consensus with the DAO.

[realdatawhale]

That makes sense! Any activities you’re planning to encourage consumers? Your network would surely add value to the Market overall and I’d really like to see a couple of sales from your existing customer base through Ocean.

[tmanthey]

For sure we are going to push the news through our channels in order to boost sales. But we kindly invite all DAO participants to help to support via their channels and maybe even to create other promotional datasets.
I think it is of strategic value for Ocean to attract professional buyers.

[Gareth]

Good to see this project continuing to expand and grow - great iniative being built here and you have the ongoing support of ResilientML.

Would be good to explore how your data set can link to what is called near miss statistics in insurance for real time auto insurance premiums - would be great to discuss on possibilities here at some stage.

[kaimeinke]

Thumbs up from my side. Let the quality come in and crossing fingers for round 10.