The year is 2025, just after Project Catalyst’s thirteenth funding round (fund 13), which, like the preceding ones, marks ethical, well-rounded technological advancements in Cardano. The Web3 horizon is more promising than ever, set to revolutionize how we use technology. Cardano is approaching its super adoption stage with subsequent technocratic developments, and there are steps to addressing the global health data problems, underrepresentation, privacy concerns, and data silos, to mention as examples.
As a standalone domain, data exchange has been on free fall despite the ever-growing amounts produced each year. From the healthcare standpoint, it is imponderable that, relevant to medicine and public health, data produced by individuals, public and private health systems, and health researchers is inaccessible. Locked out, we are left wondering whether healthcare breakthroughs will ever become a reality.
Even with multiple calls to make the data available to the public at a global scope for addressing transnational health challenges, none have been successful. It is possible to quote economic, legal, and political barriers as the primary source of hindrance, whilst the real challenge is a technical obstacle. This trajectory ends here in Cardano, with the sprout of DataWell, a global marketplace to securely and ethically facilitate health data collection.
In this article, we will overview the problems with current health data systems, then move to how blockchain technology is reshaping data exchange. We delve into DataWell, exploring how it works, its developers, the build timeline, and technical development. We close out with DataWell’s ideal value to the Cardano community and broader Web3 ecosystem. In we go…
The Problem with Current Health Data Systems
It is virtually impossible to comprehend Datawell’s role without a solid understanding of the problems at hand. The starting point is to (1) understand the problems with the current health data systems: fragmentation of health data across institutions, the barriers created by regulations, and lack of trust, and (2) its consequences, the likes of slower innovations and inefficiencies. Is this our war? Yes, but what exactly are we up against?
Root Causes: Fragmentation, Barriers, and Mistrust
After scouring the internet, we gather that patients’ medical data is dispersed across systems, databases, and facilities, but this is only well explained by example. Munene, a patient in Kenya, sees a physician for primary healthcare, yet he occasionally visits specialists, labs, and imaging centers to support his treatment. Each institution maintains an independent electronic health record (EHR) system. Not only are these systems dissimilar, but they also store and format data in different ways. In turn, they cannot communicate effectively, which limits their exchangeability.
Essentially, legal barriers are another instrument that restricts data sharing, either due to underlying unwillingness or the fact that it depends on the outcomes of the political process. No matter the geographical location, agencies charged with collecting public health data ought to protect individual and community privacy, as guardians. Besides ownership, copyright is leveraged to restrict sharing, while it should instead be used to expand it.
In the context of privacy, this gets more complicated because a clear distinction between personal identifiers and fully anonymous data is rarely possible, regardless of the legislative bodies that govern collection in the first place. The National Library of Medicine, in an essay on public trust in health information sharing: a measure of system trust, has its principal finding that most of the U.S. public do not trust the organizations that hold health information in many dimensions.
Real-World Impact: From Patient Frustration to Innovation Stalls
The consequences are plenty and devastating. Data fragmentation leads to delayed or inaccurate diagnoses, higher patient costs, poor healthcare coordination, patient frustration, and a stall in the development of better treatment solutions. Additionally, it has created a prioritization problem in selecting innovations, as some groups are well-represented, while others are underrepresented, and still others are overlooked.
What is DataWell?
DataWell, a research and development enterprise that prides itself on fostering diversity and accelerating medical innovations while ensuring robust privacy protection, is a global and secure marketplace where anyone can share health data and receive compensation in cryptocurrency. It connects data providers (individuals and companies) with consumers (institutions that seek medical data to make healthcare breakthroughs).
How DataWell Works
Once the data is collected, it is anonymized and encrypted using blockchain technology to ensure precise data privacy and security, in alignment with the requirements of the providers. Now think of DataWell’s innovation as an algorithm, utilizing machine learning models, that evaluates how valuable the data shared is. Providers are rewarded with cryptocurrency, but how well it appreciates depends on the demand for the extensive dataset, which is an obvious expectation.
The Incentive Model
Digital asset rewards incentivize user contributions, as they will be part of an economically transformative initiative. The ideal here is that, based on the usefulness and rarity of the data shared, the algorithm determines cryptocurrency rewards. Operating on such a model encourages contributions from diverse backgrounds, thereby countering the underrepresentation of groups in datasets. The above paragraphs have so far presented DataWell as a capable platform. Is it feasible?
Validating the Feasibility
Five imperatives validate the feasibility of bringing this project to life. The first is to conduct pilot studies with selected healthcare organizations to map the efficiency of data collection, anonymization, and encryption techniques. Second, the developmental team is set to engage the community in active feedback loops through early-stage testing to ensure the platform complies with privacy, security, and usability standards.
Compliance and Partnerships
In third place comes collaboration with regulators and key stakeholders to ensure compliance with data protection laws. In second place, following from the last, lies measuring demand by seeking partnerships with healthcare institutions and artificial intelligence (AI) research labs that require diversified datasets. Lastly, Cardano’s blockchain technology is leveraged to ensure transparency, auditability, and trust in the data sharing process. The trick is to use smart contracts for rewards and privacy mechanisms. What are the building steps?
Development Milestones: Technical Build Up
The developmental team has laid out a clear roadmap for building DataWell. Similar to Cardano, and building on it, both speak the same language — creating reliable solutions to solve real-world problems that aren’t limited in scale by global use. This build-up has several key steps: acquisition of pre-seed investment, platform release, first revenue, Series A funding, profitability, and £100 million in revenue — quite a stack of milestones. Here, we break down the individual steps. If you need to refer to the four-milestone chart, you can find it in the original proposal at Project Catalyst.
Milestone 1: Pre-Seed Funding and MVP Development
At level one, we secure pre-seed investment, ensure that initial funding is in place, and begin developing a minimal viable product (MVP). We consider this milestone complete once the raised amount matches the target funding value and we sign formal agreements with investors. We provide bank statements to demonstrate receipt of funding and document signed term sheets and agreements on paper as evidence of completion. At the time of writing, this remains the only completed milestone.
Milestone 2: Platform Release Candidate and Internal QA
Fast forward to the second stage, where the platform release candidate is ready, the Dapp is nearing a near-final version, prepared for testing and initial deployment. To be acceptable, all platform core features must be built and functional, passing final internal tests and quality assurance (QA) checks. A testament to the completion will be detailed release notes, as with any other software, and signed-off internal test reports from the development team.
Milestone 3: Initial Revenue and On-Chain Transactions
Initial revenues, appearing at milestone three, indicate that we can expect initial sales or subscriptions from early adopters. At this point, the stage is considered complete if successful transactions have been completed and recorded on the Cardano blockchain. To support evidence of completion, financial statements must show the first revenue, which is trackable on the Cardano network using blockchain explorers.
Milestone 4: Series A Funding and Business Expansion
Nowhere is the scaling more aptly demonstrated than in the fourth milestone, Series A funding, where the in-market business expands by securing larger investments. Investors will mark the completion of this milestone by providing between £5 million and £10 million in funding and signing equity investment agreements. Similar to the first stage, the team will present signed investment agreements and bank statements showing receipt of funds as evidence of completion.
Milestone 5: Profitability and Operational Efficiency
In the second-to-last milestone, profitability is the primary agenda, as the DataWell platform achieves business operational efficiency at this moment. Simply put, monthly revenue consistently exceeds operational costs for a minimum of three consecutive months. Only by profiling detailed financial reports, including profits and losses, to showcase revenues and expenses, will this milestone be complete.
Milestone 6: £100 Million Revenue Target
The final stage is to achieve a cumulative target of £100 million, as evidenced by financial report audits that show profits and losses, with revenue broken down by source and product lines.
Project Funding
To bring this project to life, the DataWell development team plans to raise £2.5 million in pre-seed funding in February 2025 (so far, they have reimbursed ADA 45,000.00, equivalent to £26,172.66), followed by £8 million in June 2026. They will allocate these funds toward developing a deployment-ready platform and marketing efforts to build the DataWell brand. From a timeline and funding perspective, their priorities focus on development in 2025, with marketing and customer acquisition targeted for 2026 and 2027
The development class encircles outsourced development, in-house crypto teams, cybersecurity and mobile application teams, cloud computing, and database purchases, among other expenses, including application maintenance, upkeep, and support for scalability. Below is a detailed breakdown:
- £280,200 in 2025 + £202,000 in related wages
- £457,971 in 2026 + £857,700 in related wages
- £1,190,667 in 2027 + £1,312,990 in related wages
For brand building and marketing, we are talking market research, the effectiveness of social media strategies and influencer partnerships, advertisements, and affiliate marketing to expand the DataWell brand and reach a broad audience of potential users and customers. Here’s the cost breakdown:
- £4,920,000 in 2027 + £1,719,400 in related wages + £3,000,000 Mr Beast Fund
- £168,000 in 2025 + £243,000 in related wages
- £1,241,000 in 2026 + £703,000 in related wages + £2,000,000 Mr Beast Fund
The Team Behind DataWell
Of the funded projects in Catalyst’s Fund 13, none stands out as DataWell, which has two teams: the active builders and the advisors. The two groups are to work in tandem to bring DataWell to life, so we have listed members below.
Active Builders: Core Team
Industry Experience
- Prof. Martin De Heaver — A top developer of artificial systems and a collaborator in many United Kingdom (UK) universities. He brings 30 years of experience in the design and build of major IT systems. Besides being a crypto miner, user, and advocate, Martin is a co-founder of several companies, including Computer Vision, GEOMii (focused on smart cities), and Merger Antitrust Review (specializing in financial information), while currently serving as the CEO of the Oxford University spin-out company ORBIT.
- Dr Roman Bauer — A professor at the University of Surrey in computational neural science. He is a researcher in computational modelling and analysis of brain biological dynamics. With a keen research focus, Roman concentrates on modern computing techniques, machine learning, and artificial intelligence, as well as other IT projects. He is also a spokesman for the international Computational Biology collaboration BioDynaMo, and a cofounder of the biotech company Oxford Cryotechnology.
Student Talent
- Fakhri Abbasov — A third-year computer scientist at the University of Nottingham, who demonstrates leadership qualities through university group projects. He leads as the school captain, runs the mathematics club, and has organized multiple charity events. Regarding industry experience, Fakhri brings expertise in software development and machine learning, including optimizing mechanistic calculations of fluid and gas properties in oil pipes and implementing the prototype of the data valorization algorithm for DataWell.
- Aditya Bhagavatula — A computer scientist in the third year at the University of Nottingham. He has led a 10-month software engineering project, iteratively refined the DataWell brief, and developed an innovative data valuation machine learning model. In the quest to hone his technical skills, Aditya has actively participated in crypto and robotics hackathons, notably recognized for his mobile robot gesture recognition system. He has also served as a first aider at Premier League games, gaining a relevant medical background as a contributor to DataWell.
Passive Builders: Advisors
- Professor João Pedro Magalhães — A graduate in microbiology from the Escola Superior de Biotecnologia of Porto, Portugal, and a PHD holder from the University of Namur in Belgium. At the moment of writing, Pedro leads the Genomics of Ageing and Rejuvenation Lab as the chair of Molecular Biogerontology at the University of Birmingham. His laboratory investigates the aging process to develop strategies to counteract age-related diseases and enhance human health.
- Professor Marina Jirotka — A professor of human-centered computing at the University of Oxford. He leads a research team that combines social and computer sciences in the design of technology. As the director of the newly established Responsible Technology Institute, Marina works on a broad range of ICT areas, including robotics, AI, and the digital economy. His recent projects have centered around trust in algorithms, social media, data, and digital economies.
- Dr Ehsan Toreini — A research engineer with a specialty in physical security (electric hardware and non-electric components), web security, and ethical machine learning. His work has been a breakthrough in designing real-world attacks and cost-effective mitigations. Ehsan has over 35 peer-reviewed publications in transaction privacy and cybersecurity. Additionally, Ehsan has won two U.S. patents for the authentication of physical objects and has received national and international grants for utilizing blockchain in e-voting.
There is no doubt that the DataWell task force is more than capable of changing how we utilize healthcare data. Once completed, we can expect other industries with data lock-up to follow suit.
The Future Outlook: Value for Cardano
In the Web3 community, DataWell propagates a positive impact by driving the adoption and utility of the Cardano blockchain and its native currency, ADA. It is by creating a secure, decentralized marketplace for healthcare data that DataWell presents Cardano infrastructure in a real-world usage, leveraging its transparency, security, and scalability. The project incentivizes participation worldwide through a shared cryptocurrency, increasing the usage and demand for the Cardano network. Cutting across decentralized finance and ethical data sharing, this initiative positions Cardano as a leader in technology that empowers transformative, real-world applications.
The DataWell project, built on Cardano, leverages smart contracts, scalability, and low transaction costs. By creating an ever-growing dataset for the healthcare industry, DataWell will drive greater adoption of Cardano, consequently increasing demand for ADA while simultaneously fostering more widespread use of the network. Over time, the returns on investment are likely significant, driving value to the Cardano ecosystem in terms of growth, network activity, and blockchain adoption.
You can learn more about DataWell by reading their official proposal on Project Catalyst and visiting their official website.
