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Ocean: Ask Me Anything with Developers, Minor Updates

Biweekly update 12th June — 27th June

Felicitations to all members of our community, we are ready to share with you a few updates of Ocean Protocol. As all of us know, Ocean continues to be a small organization and this has led to the low number of updates, especially large-scale ones. Unfortunately, the tech team released only minor updates which can be found below. However, three cool guys, Bruce, Dimi and Aitor, had a meeting with the community. As expected, most of the questions were about POA (Proof of Authority), its development and implementation. Anyway, Ocean released its MainNet in the past month and, in our opinion, we have many more weeks to wait for a great major product update. It is worth remembering that according to ‘Ask Me Anything’ the primary objective is marketing to data scientist communities and developers.

Intro

Even though this is the second report about Ocean Protocol, we feel duty bound to put you in the picture about Ocean:

Ocean Protocol is an ecosystem for the data economy and associated services. It provides a tokenized service layer that exposes data, storage, compute and algorithms for consumption with a set of deterministic proofs on availability and integrity that serve as verifiable service agreements. There is staking on services to signal quality, reputation and ward against Sybil Attacks.

Ocean helps to unlock data, particularly for AI. It is designed for scale and uses blockchain technology that allows data to be shared and sold in a safe, secure and transparent manner.

While vast amounts of data are generated each year, data exchange and analysis have been hampered due largely to concerns over trust and security. Currently, many organizations have data but do not have the trusted and secure means to share it. Without data, AI cannot advance and be applied to solve problems and ultimately improve lives. More pressing is the fact that today, only a handful of companies have both AI and data capacities, and if data remains locked up, these companies could very well govern the development of AI and thereby our future.

Through blockchain technology and tokens, Ocean Protocol connects data providers and consumers, allowing data to be shared while guaranteeing traceability, transparency, and trust for all stakeholders involved. Ocean Protocol is designed to give data owners control over their data assets and prevent them from being locked in to any single marketplace.

By bringing together decentralized blockchain technology, a data sharing framework, and an ecosystem for data and related services, Ocean Protocol is committed to kick-starting a new Data Economy that touches every single person, company and device, giving power back to data owners, enabling people to reap value from data to better our world.

Development

GitHub metrics:

Development is ongoing. Commits on public GitHub appears regularly, several times a day. Furthermore, there is an stable increase in the number of repositories.

Developer activity (from Coinlib.io):

  • Refined who can deploy what components to which networks, using Kubernetes accounts and access control mechanisms.
  • Added more operational tooling for deployed components, e.g. additional monitoring with email sent to admins when something goes wrong.
  • Created tooling to deploy a token bridge, then deployed one between the Ethereum Mainnet and the Pacific Network (which was not public yet). Also created an Ocean-specific theme for it.
  • Deployed several multisig wallets to various networks, to govern things like contract upgrades and Ether management. (In the future, some of those will be replaced by other governance contracts. The future governance contracts are currently in testing and review.)
  • Finished implementing support for local signing.
  • Did lots of testing of the Ocean Protocol components, and fixed issues that were found.
  • Got end-to-end testing working on the Commons Marketplace, using Cypress.
  • Got Elasticsearch working well with Aquarius and made it the default Aquarius backend database (with MongoDB still being an option).
  • Made it easier to determine the versions of connected components and contracts. An example is shown in the screenshot above.

New tutorials:

No updates.

Social encounters

These weeks events:

The community has spoken and Ocean has heard. There are Bruce Pon, Dimitri De Jonghe, and Aitor Argomaniz to answer the community’s questions.

Summary:

  • Currently the tech team is working on:
  1. delivering the production environment called “Pacific”, a POA network with all components of the ocean stack: smart contracts, access proxies, metadata APIs and secret store as well as all drivers (Javascript, Python, and Java)
  2. Commons marketplace: an Ocean-hosted Dapp allowing to publish and consume data (http://commons.oceanprotocol.com)
  • There are three main groups that the team is aiming for — developers, data scientists, and enterprise.
  • As for other areas of marketing — Ocean will be spending a lot of time in the coming months to reach out to data scientist communities and developers via hackathons, so that Ocean gets grassroots support and building on the protocol. The foundation going to offer prizes and bounties to teams that demonstrate useful applications that can be built.
  • The foundation is working to deploy our POA network, called Pacific. Finalizing the last touches and it looks in good shape. This POA network will be initially hosted quite centrally by BigchainDB and allows for smooth UX compared to Ethereum mainnet (read: low transaction fees and fast confirmation times). The POA network will be connected to the Ethereum mainnet using a token bridge. This means OCEAN holders can transmit tokens back and forth to Pacific POA network and have the full experience of the capabilities of the Ocean Protocol.

Upcoming events:

This meetup features speakers who are working on AI for Good, with the goal to spread the opportunities and benefits of AI to the planet’s billions.

There will be dive deep into understanding how blockchain projects like Ocean Protocol, AI network, Airbloc and Nervos Network have enabled the building of dApps, data sharing and AI training in a larger scale than it ever has been before.

Finance

Source: CoinMarketCap

Explanation of Ocean Finance:

  • Ocean Tokens

Ocean Tokens are the main tokens of the network. The Foundation denote Ocean Tokens as “Ọ​ ” or with ticker symbol OCEAN. They are used in several ways.

First, Ocean Tokens are used as a ​unit of exchange​ for buying and selling data/services. A marketplace would price data/services in Ocean Tokens (OCEAN), or any other currency of the marketplace’s or vendor’s choice, such as USD, EUR, ETH, or DAI. It the latter, the marketplace would use a crypto exchange to convert just-in-time to OCEAN. Therefore, the Ocean network would only see OCEAN. The Foundation explicitly chose a one-token design over two-token design for simplicity, and to help equalize the access to upside opportunities of owning assets.

Second, Ocean Tokens are used for ​staking .​ This includes staking in each given dataset/service, and introduce a long tail of additional tokens called ​drops.​ Drops are derivative tokens of Ocean tokens denoted in “Ḍ​ ”. Each dataset would have its own derivative token. For example, 100 drops of stake in dataset X is “100 Ḍ​ X”. Drops relate to Ocean Tokens via curation markets’ bonding curves, which determine the exchange rates between them for different dataset/services.

Finally, Ocean Tokens are used in dispensing ​network rewards​, according to Ocean’s inflation schedule.

  • Stakeholders

Understanding network stakeholders is a precursor to system design. ​Table below outlines the stakeholder roles participating in the network. There are roles beyond, from developers to auditors.

  • Network Rewards to Incentivize Relevant Data/Services & Make It Available

Here is the ideal allocation approach, i.e. the approach assuming no computational constraints. Rij is the network rewards for actor ​i​ on dataset/service ​j​, ​before b​ eing normalized across all actors and datasets/services. The actual network rewards received are normalized: Rij,no

where,

Sij =​ actor​ i’s​ stake in dataset/service ​j​, measured in ​drops.​

Dj = number of deliveries of dataset/service ​j ​in the block interval

Ri = global ratio for actor ​i s​ erving up vs. accessing a dataset; details are below

T =total Ocean Tokens given during the block interval according to the over all token reward schedule (see Appendix)

The third term, Ri , is to mitigate one particular attack vector ​for data​. (It’s excluded for services.) “Sybil downloading” where actors download files repeatedly to increase their network rewards (more on this later). It uses a tit-for-tat approach like BitTorrent by measuring how much data an actor has served up, versus how much is accessed, as follows:

Ri = {min(B served,i / B downloaded,i, 1.0) if all data assets served; 0.0 otherwise}

where,

Bserved,i = total number of bits that actor ​i​ served (made available) across all data assets they have staked

B downloaded,i = total number of bits that actor ​i​ accessed, from any data assets

  • Circulating Token Supply

The circulating supply will be comprised of Ocean Tokens allotted to Acquirors, the Foundation, the founding teams and the network reward.

Early Acquirors in the Seed and Pre-Launch, and the founding teams have lock-ups ranging from 1.5–5 years.

Token Emissions with a 50 Year Timeframe

In the initial phase, the vast majority of tokens emitted will come from pre-mined tokens for Acquirors, the Foundation and the founding teams. From Q3/2022, the increase in Ocean Token supply will come solely from the network reward.

Token Emissions with a 12 Year Timeframe
  • Network Reward

To implement the network rewards as described above has complexity and high compute cost because, for each network rewards cycle, Ocean Protocol need to compute the amount of stake for each dataset/service made available by each actor, and Ocean Protocol would need a transaction to ​each ​actor to reward their effort.

The Foundation can address these issues by giving keepers the same ​expected ​value of network reward (though higher variance), with less computation using a Bitcoin-style strategy (called “probabilistic micro- payments”​). In Bitcoin, every ten minutes, tokens (Bitcoins) are awarded to a single k​eeper (miner) where the probability of reward is proportional to value added (miner hash rate), compared to the rest of the network’s value added (network hash rate = network difficulty). Network difficulty is updated every two weeks.

Ocean is similar. Rather than rewarding at fixed time intervals, every time a keeper makes a dataset/service available to a consumer, Ocean randomly chooses whether to give network rewards. The amount awarded is based on the value added by the keeper Rij and total network value added.

Rdifficulty is the network difficulty; it gets updated every two weeks (20160 minutes)6, i.e. the difficulty interval. Rrecent is the value added since the last difficulty update.

At network launch, Rdifficulty = 0. At the beginning of each difficulty interval, Rrecent = 0 . Here’s what happens when actor ​i​ makes a dataset/service ​j a​vailable to a consumer.

1. Compute value added:

Rij = log10(Sij ) * log10(Dj ) * Ri 7 2. Update total recent network value added: Rrecent = Rrecent + Rij

3. Compute the probability of getting a network reward, ​P.​ If we wanted one reward on average every two weeks, it would be (1). But let’s have rewards every 1 minute on average. 20160 minutes is two weeks. So, we add in the factor (20160 minutes)/(1 minute). The result is (2).

(1) P = Rij Rdif f iculty

(2) P = Rij *20160/1 Rdifficulty

4. Compute whether actor ​i​ gets the reward:

u ∼ U[0,1], i.e. draw a random real number between 0.0 and 1.0

If u P then actor ​i w​ill get the reward

5. If the actor ​i i​s to get the reward, then compute reward and give it, via a transaction with output to actor i. Since step 3 has a bias to reward more often using the factor (20160/1), here we need to divide the amount awarded by that same factor. We arrive at ​F,​ the fraction of rewards for this action in this difficulty interval. To compute reward , we scale ​F ​by T dif f iculty , where T dif f iculty is the total Ocean Tokens given during the two week difficulty period according to the overall token reward schedule (see Appendix).

F= Rij / ( Rdifficulty *20160/1)

reward = F * Tdifficulty

Once every difficulty interval (two weeks), the difficulty will be updated with ​Rrecent.​ The change is limited to 0.5x to 2.0x of the previous difficulty value.

Rdifficulty = max(0.5 * Rdifficulty, min(2.0 * Rdifficulty), Rrecent)

  • Staking

When users are allowed to invest a currency in a data item, the level of granularity increases dramatically, while also adding an extra incentive: the risk of losing that currency. While most curation mechanics offer a “nothing to lose, nothing to gain” approach, the aspect of stake changes that. This does not necessarily imply a financial dimension. Stake could just as well be reputation points or network credits with a utility value. The items that carry the most stake with them, ought to be of the highest quality.

Curation Markets with Bonding Curves: users can invest in a data asset by buying tokens of that asset, with the hope that their shares will increase. Many variations on curation markets are possible, but deployment can be gas expensive. On-chain is particularly meaningful when dealing with financial incentives.

  • Bonding Curves

A ​bonding curve​ relates a token’s drops “Ḍ​ ” to Ocean Tokens “Ọ​ ” for a given dataset/service. ​Figure below​ shows a bonding curve for dataset X. It relates the ​price in Ọ​ to buy more drops of X​ (y-axis) as a function of the ​current supply of drops ​(x-axis). As people stake more interest in X, its ḌX supply goes up according to the bonding curve.

Bonding curves can take whatever shape the creator wishes. But to reward early adopters, a bonding curve typically makes it more expensive to buy ḌX as more people stake in it; this is the positive slope in the curve.

Bonding curve for Ḍ​X

A new curation market is initialized each time a new dataset or service is made available. With this, the actor has already staked Ọ​ to have the dataset or service vetted. A later section describes vetting. Once vetted, this stake goes into the curation market, in return for drops as to a measure stake. ​Figure below​ illustrates. We’re at the far left of the bonding curve because 0 ḌX have been generated. There, each ḌX costs 0.1 Ọ. If the initial user staked 50 ​Ọ, she would gain 50 Ọ​ / 0.1 ​Ọ/ḌX = 500 ḌX. The supply for ḌX increases from 0 to 500.

increasing supply to 500 ​ḌX

From here on, anyone can stake further in X. Let’s say a user wants to purchase 500 ḌX by staking more Ọ​ tokens. This would make the supply go from 500 ḌX to 1000 ḌX. In that range, the price is (0.1 + 0.2 ​Ọ/ḌX)/2 = 0.15 Ọ/ḌX. The user would get 500 ḌX for a total cost of 500 ḌX * 0.15 ḌX/Ọ = 75 ​Ọ.

increasing supply to 1000 Ḍ​X

Roadmap

  • Seed November 2017

Ocean Token seed distribution

Technical Primer

Marketplace Framework

  • Whitepapers February 2018

Released Technical Whitepaper & Business Whitepaper

  • Pre-Launch March 2018

Ocean Token pre-launch distribution with 3500 Contributors in 100 countries

Activated community & built up the team

Announced partnership with IBM Watson AI XPRIZE

Advisor Program launched with 40 advisors in 20 cities

Bounty Program launched with 15 bounties and 88,000 PROCN tokens offered

  • Plankton August 2018

Spree test network created

Ocean Enhancement Proposals introduced

Pleuston, a proof-of-concept data marketplace

  • V1 Alpha (Trilobite) December 2018

Spree test network updated

Development and documentation of Ocean network components

Building global community: 130+ events, 35+ advisors, 120+ ambassadors in 40 countries, 15+ bounties

Partnerships & collaborations: MOBI Grand Challenge, Fitchain

  • V1 Beta (Tethys) April 2019

Nile beta network deployed, with Service Execution Agreements, Access control, Metadata store

Commons marketplace

Project Manta Ray, a data science workflow powered by Ocean Protocol

More collaborations announced

  • V1 2019 *

Production-ready Ocean network

Case specific marketplaces

Web 2.0 integration (for compute and storage services)

Improved Service Execution Agreements: staking conditions; slashing conditions; bounty rewards; competition rewards

  • V2 2019 or 2020 *

Proof of Authority network

Initial PoA network governance enabling contract update prioritization and upgrades, and network optimization

Token migration from ETH Mainnet to Ocean PoA

  • V3 TBD *

Verification and Validation of conditions and service (cryptographic proofs)

Incentives / network rewards for different actors (including verifiers)

Web 3.0 integration (for example: with other decentralized projects)

  • V4 TBD *

Bounties on-chain (DASH style model)

Clan governance (enable marketplace specific governance, group governance, etc.)

  • V5 TBD *

Fully permission-less Ocean Protocol

Balanced governance: transparent process for updating protocol that balances stakeholder needs (keepers, service providers, curators, validators)

Partnerships and team members

No updates

Social media metrics

Social media activity:

Considering that Ocean Protocol is not an old project and its IEO was conducted only on 2nd May 2019, Ocean has a great community.

Social media dynamics:

The graph above shows the dynamics of changes in the number of Ocean Reddit subscribers and Twitter followers. The information is taken from Coingecko.com.

This is not financial advice.

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