May 23 · 21 min read

Biweekly update 9th May — 23rd May

To start with, this is the first biweekly update of Ocean and it happens to be a great company. Ocean has been building non-stop since mid-2017. It has had over 150 events where it reached out to the community. There are now over 8,500 contributors, 250 Ambassadors, 30 Advisors and 50 team members working to build success for Ocean Protocol. Must admit, Ocean developer team released Commons, a marketplace to explore, download, and publish open data sets. By the way, Ocean tried to explain what happened with IEO and, to be honest, they almost got it done very well. Also, we tried to explain tokenomics of Ocean. Ocean Protocol aims to unlock data from silos so it can be used productively. To realize this mission, the Foundation announced that it partnered with Next Billion and Unilever Foundry. There are no other development updates. However, there is plenty of social encounters. We are looking forward to getting more interesting Ocean updates.


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.


GitHub metrics

Development is ongoing. Commits on public GitHub appears regularly, several times a day.

Developer activity (from
  • The Commons Marketplace

Ocean has created Commons, a marketplace to explore, download, and publish open data sets. Commons is built on top of the Ocean Nile beta network, which has just been released. And, to top it all off, we are kicking off the party with more than 1K open datasets for you to play around with!

The primary target audience for our Commons marketplace is enthusiastic & data-hungry data scientists with some crypto experience. It can be used with any Web3-capable browser, like Firefox with MetaMask installed.

All permissions are handled through your wallet account in MetaMask, there’s no login or password or any of that old-school Web 2.0 stuff. You unlock your MetaMask account, and you’re ready to go.

Tutorial is below.

New tutorials:

To publish and download assets, you must point MetaMask towards Ocean’s Nile network. You also need to have some Ether in your account to pay gas costs.

To connect to the Nile network:

  1. select Custom RPC in the network dropdown in MetaMask
  2. under New Network, enter as the custom RPC URL
  3. hit Save, and you’re now connected to Nile:

The Commons marketplace includes a faucet functionality under from where you can easily request some Ether to be added to your account by clicking the Request Ether button:

Social encounters

Generic Guide to Data Curation — pt. I and pt. II

In this guide, Ocean will be exploring all possible permutations of data curation, listed by different aspects of it and starting with the main one: the discovery or signaling function.


User Authentication with flags. Moderators / Curators to check flagged content.

Token Curated Registry (TCR) with challenges for flags and proposals for new entries, both with stake by tokens. Challenges and proposals are decided by voting rounds. There has been a lot of stuff written on TCR’s but very little proof of their efficiency.

TCR by earning tokens. Off-chain: whenever a red flag is removed by curators, user earns a point. Flagging lots of data that does not get removed might give you a penalty.


Star system or similar, with or without authentication.

Deploy a Rating Token that can be used to allocate rating to data. For example: if there is a registry of 100 data items, each user gets 250 Rating Tokens that they can use to give any 0–5 rating to each item. If users within a network are only allowed to hold a limited amount of a certain token within either a certain timespan or category of data, then they can allocate their tokens to the dataset they deem most worthy of their “attention tokens”. This can be improved by deteriorating the value of the token over time or removing tokens from the user’s wallet after a long period.

Penalize users that give too many extreme ratings (0 or 5) to avoid fraud.
Each time you rate an item nets you a fixed amount of score points.
Make game icons customizable with a list (like emoji’s) by user for more fun. The closer your average allocated user rating is towards the mathematical average (e.g. 2,5 or 3), the more points you gain.


Authentication with up- and downvotes. The total vote (up minus down) will determine the ranked position.

Similar, but incentivized by tokens. One way to do this is locking your vote and keeping track of all the votes after yours. For each data item you either up- or downvote, you will get all up and downvotes after yours respectively as tokens. In other words, if you can predict correctly which data will get the most “likes” or “dislikes”, you will gain all the likes or dislikes after. This motivates curators to look for the most promising items with a strong early mover advantage but also attracts “safe betters” to keep bumping items that are already high ranked. Read more here.

Another alternative is Graded Token Curated Registries.

Tokens or points can be used financially, utility or as permissions.
Implement balance checks by penalizing users with only up- or downvotes. Implement anti-skewing mechanics to avoid downvoting to minus infinity.


Authentication with thumbs up (and thumbs down).

Similar. Just like ranking, scarcity can be introduced by tying a token to a like: i.e. “liking” a piece of data costs one token, but you get replenished after burning them all. Other way around: you earn one score token for each like, measuring your curation activity.

Design a formula that distributes tokens or points according to the user’s amount of likes.


Number of downloads, clicks, streams. Can thus be filtered by popularity.

Proofed Curation Markets: the times a certain data set is accessed becomes a component of the reward function formula.

Publishers can be incentivized by earning a share of the popularity, like the number of streams generates revenue for music artists.
Consumers can have a model where they can download the data after X amount of views/streams (like Resonate), which motivates to actively participate.


Allocate a limited amount of credit points per user. Users can stake their points on data assets.

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.

Financial gain by return on investment.
Reputation or points gain by return on investment.


Labeled tags, stored with the data asset metadata.

The usefulness of on-chain tagging is somewhat limited.

Language curation signaling are particularly useful for gamification.


User boards with authentication or comments sections.

Not desirable. It is possible to keep integrity of the reviews by preventing post-editing through storing a hash of the review on-chain.

Contributions by reviews grant permissions.

X-Ray Vision — A Healthcare Use Case

The post describes a healthcare use case, powered by decentralized data science using Ocean Protocol. The goal of this case is to promote discussions on how Ocean Protocol can advance data interoperability and develop industry-specific AI applications.

These weeks events:

“The AI Commons is a new initiative and organization dedicated to problem solving with AI more democratic and accessible; and a framework for the coordination of scaling of AI for Good,” Trent McConaghy at the Rise of AI conference.

Source: Twitter

This is the special Ocean Protocol meetup featuring distinguished industry guests sharing valuable insights into powerful AI/ML workflow tools followed by a lively panel discussion about how Ocean Protocol could be used to orchestrate innovative decentralized AI/ML workflows.

Speakers: “We have a data economy. But it’s a shadow data economy. It’s opaque: Google and the like keep the data to themselves for competitive reasons (data siloes). And, power is concentrated, such as Zuckerberg with his fiefdom of 2 billion people. Companies who know how to utilize the data they have are accruing all the value, while there are companies who have data but do not how to use it. With a new data economy, we hope to enable data sharing in a safe and secure manner with blockchain, while educating on companies how they can utilize new technology to utilize their data and come up with new business models.”

Source: Twitter

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.


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


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}


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

What Happened with the IEO?

  • What happened?

On Friday, May 3, at 1600 GMT, the Ocean Token Contract unlocked. Ocean did this to push through 459 transactions to token holders and allow for deposits into Bittrex accounts. Unfortunately, the process was poorly communicated causing confusion for many wishing to move tokens into Bittrex International. Ocean Team apologizes for this.

In the meantime, people started moving Ocean Tokens to Bilaxy and started trading. Since the token contract is public and accessible, anyone can choose to list Ocean — Bilaxy decided to without communicating with Ocean Protocol. The token price held for a moment above $0.12 but there were more people that wanted to sell than buy. Once the spark was lit, the token price fell quickly to $0.08.

Ocean Token movements into Bilaxy on Friday, May 3
  • How did it happen?

There was no price manipulation or conspiracy to dump. Instead, there was a chain reaction sparked by weak demand that spiralled increasingly downwards as people panic sold until the panic ended.

In the first day, 94m Ocean Tokens went into motion representing 30% of the total token supply. These tokens came from multiple sources including Bittrex International IEO (56.4m), Coinlist ICO (16m), Pre-Launch (93m), Seed (8m), Foundation (47m), Founding Teams (94m) — totalling 314m.

At the maximum period of trading, 79m tokens were on Bittrex International and Bilaxy, and of these no more than 20m on offer at any single moment in time.

Below is a breakdown of the movement of Ocean Tokens on Friday May 3 by group:

Ocean Tokens by Group — along with the Percentage in-motion on Day 1 (Friday, May 3)

Several large movements of tokens did not go to Bittrex International or Bilaxy, but to OTC services which kept tokens out of circulation for trading.

The largest movement of tokens came from the Pre-Launch cohort where 24% (22m) of tokens shifted, which added to the existing 56.4m already in the Bittrex International platform. A smaller portion of ICO and Seed tokens also moved but not in meaningful quantities.

Ocean wrote that there had been no dumping and no selling from the Foundation.

  • How will the ICO/ IEO funds be used?

The Foundation is working on a transparency report to show the community how funds have been used and to give quarterly updates on progress. This will be coming out soon.

To give a quick preview, the Foundation has the role to activate a Data Economy with the funds raised and token treasury. Funds raised are issued to service providers for software, business development, legal, security and community efforts. Both BigchainDB and NewtonCircus (DEX) have signed agreements to deliver certain components in exchange for a transfer of funds. Ocean also have service providers such as Dentons, KPMG, Holland & Knight, Trail of Bits, CertiK, Bittrex International, Coinlist and many others that provide a host of legal, audit, and compliance services.

  • What future activities are planned?

The developer team will continue to build the protocol and network so that the community and enterprises will adopt it. Also it will continue to focus on creating value for its users and will give regular updates via Meetups, AMAs and in Telegram.

Coming up, Ocean Protocol will:

  1. Work towards releasing a production network
  2. Release a reference marketplace for commons data and with simple pricing
  3. Integrations with data science tools
  4. Initiatives to attract developers and enterprise.


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)

Note: Software is sometimes hard to predict, so there might be delays. Ocean will update projected dates once it is closer to a milestone’s completion.

Partnerships and team members

  • Unilever and Next Billion team up with Ocean Protocol

Ocean Protocol aims to unlock data from silos so it can be used productively. To realize this mission, the Foundation announced that it partnered with Next Billion and Unilever Foundry.

NextBillion creates data platforms to gather customer insights, offering fair value for data, while giving flexible, cost-competitive insights to companies. These insights help companies to expand effectively in emerging markets by respecting local customs, norms and preferences. With these types of Win-Win partnerships, the livelihoods for people are improved.

Unilever Foundry supports NextBillion by being an anchor customer and using their data and AI services that are built on Ocean Protocol technology.

To improve sanitation in schools in Vietnam, Unilever is working with NextBillion to garner insights from on data collected across hundreds of schools. This work is based off of an earlier pilot project with the Government of Thailand, Ministry of Health that reduced illnesses, improved maintenance and operations and supported education campaigns.

Barbara Guerpillon, Director of the Unilever Foundry SEAA and New Business Growth, explains “We are working in a world where AI and algorithms are all around us and used to solve problems. We all know AI needs data. I’m very happy to see companies like Ocean Protocol who are actually supporting and helping companies to access their own data and access any other type of data.”

“The NextBillion platform and service bridges an important gap between data and solutions,” says Oliver Gilbert, Managing Director of Next Billion. “Our collaborations with Ocean Protocol and Unilever is the perfect combination that allows us to solve problems that enterprises care about, while giving people a fair deal for helping us to collect data.”

“I’m so excited that we can move forward with a world-class partner in Unilever, to solve an important problem using data and AI,” Daryl Arnold, Founder of Ocean Protocol. “ When more data is collected and unlocked, good things happen. Ocean Protocol is pleased to provide the blockchain technology that supports data sharing use cases that bring value to everyone — enterprises, startups and people”


No updates.

Social media metrics

Social media activity:

There are no social activity dynamics published yet, because this is the first overview of Ocean Protocol. But considering that Ocean Protocol is not an old project and its IEO was conducted only on 2nd May 2019, Ocean has a great community.

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

This is not financial advice.

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Paradigm is a family office fund investing in crypto space since 2013. We are a group of industry experts & crypto enthusiasts consisting of PhDs and graduates from the top universities with experience in creating startups, trading on traditional financial markets and blockchain


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In chaos lies the truth

Paradigm fund

Paradigm is a family office fund investing in crypto space since 2013. We are a group of industry experts & crypto enthusiasts consisting of PhDs and graduates from the top universities with experience in creating startups, trading on traditional financial markets and blockchain

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