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The challenge of building a generative art collection on Cardano is significant.
Learning blockchain technology acts as a barrier to entry for existing artists and the current tools are inadequate.
LearnerShape built a proof of concept for open-source, decentralized SkillsGraph in Catalyst F6, is piloting / evolving it in F7 and F8, and will deploy a fully-functional v2 through this project
This is the total amount allocated to LearnerShape SkillsGraph v2.
LearnerShape built a proof of concept for open-source, decentralized SkillsGraph in Catalyst F6, is piloting / evolving it in F7 and F8, and will deploy a fully-functional v2 through this project
LearnerShape is award-winning start-up building open-source, AI/blockchain-based skills infrastructure; 20+ yrs experience on authentication & education tech; funded in F6, F7 & F8 for SkillsGraph projects, with app released; partnering with RootsID, leading wallet provider
Below we first explain the overall background, vision and progress of LearnerShape SkillsGraph, and then describe what we will deliver through this proposal.
LearnerShape SkillsGraph -- Background and Vision
LearnerShape SkillsGraph will be a fully-functional open-source, standards-based Web 3 skills management solution. It is built on three core technical pillars:
The proof-of-concept version of SkillsGraph was developed with Catalyst F6 funding and is available to the public at https://skillsgraph.learnershape.com/. Full documentation is available at https://learnershape.gitbook.io/learnershape-skillsgraph/. The open source code is available at https://github.com/LearnerShape/ls-auth-api and https://github.com/LearnerShape/ls-auth-ui.
SkillsGraph is currently being piloted in two Catalyst-funded projects:
LearnerShape's vision is that SkillsGraph will provide an open-source alternative to existing skills management solutions. For example, the leading current solution is LinkedIn, which is highly functional, but a proprietary walled garden that controls user data. By contrast, SkillsGraph is open source so that any entity that wishes to do so can operate a SkillsGraph instance, and all instances can access standards-based user data (to the extent users wish to make it available) and blockchain proofs of skills authentication.
Separately from SkillsGraph, LearnerShape has developed an open-source AI-based library for recommendation of learning content and jobs using skills (with any skills taxonomy). This library is available at https://github.com/LearnerShape/lsgraph, and descriptions of its capabilities are available on our blog at https://www.learnershape.com/blog. As a key element of the vision set out above, we intend to combine this AI-based recommendation technology with the authentication technology of SkillsGraph.
LearnerShape SkillsGraph v2
LearnerShape will develop and improve various functions of the current proof-of-concept version of SkillsGraph as part of the F7 and F8 pilots described above (which are focused on proving the uses of SkillsGraph and learning how the service should be evolved). However, significant further development work is needed to make larger enhancements to SkillsGraph, and move it towards being a robust solution that is ready for widespread market application. That is the purpose of this proposal.
This proposal will deliver the following enhancements to LearnerShape SkillsGraph:
During the project period, we will also actively promote use of SkillsGraph to projects both inside and (especially) outside the Cardano community. Current opportunities include:
The Dapps, Products and Integrations challenge aims to generate "Dapps, products and integrations for the community to use that increasingly become the better alternatives over current centralized providers". This is precisely the goal of LearnerShape SkillsGraph. We aim for a product (with associated integrations) that offers a better alternative to centralized skills management platforms.
The current leader for centralized skills management is LinkedIn, which provides an excellent service but has serious limitations of being proprietary, limiting access to user data, and having high cost for enhanced services. There are also (i) many other companies that assist companies, other organizations and their employees to manage individual skills (e.g. Degreed, Cornerstone/EdCast), and (ii) providers of skills data for use by third parties (e.g. Burning Glass). But there is no widely-adopted public protocol for management of skills -- which is a glaring hole in a global economy that depends heavily on future skills development.
The following main advantages of SkillsGraph can allow it to become over time a leading open alternative for skills management:
We believe that our project is relatively low-risk from a technical perspective, because the tasks we are undertaking are well-understood (although somewhat complex), and our team has deep technical experience and a strong track record of delivery. The largest risk relates to demand for our services, which is inevitably uncertain.
Risk 1: There is insufficient demand for the services that we are developing.
Explanation and mitigations: This risk is not a direct risk to delivery of the project, but it is an important consideration because we are building in order to provide a widely-used service. As explained in response to the previous question, there are major reasons to believe that we will succeed in doing so.
In addition to the reasons for long-term success noted above, we are mitigating risk by taking an incremental approach that tests features and demand over time. With F6 funding, we delivered a proof-of-concept that is already attracting strong attention through a community pilot funded in F7. With F8 funding, we are running a larger pilot with PeopleCert, a global certification company that has the potential to send high volumes to our service. This F9 proposal, if funded, will further expand our capabilities to satisfy increasingly demanding applications.
In the medium term, we intend for SkillsGraph to generate sufficient demand to be self-funding. Although our code is open-source, we will use it to deliver paying services. For example, we are in initial discussions to use SkillsGraph as part of a skills management platform for the City of London.
Risk 2: Development is more complex than expected, especially the elements requiring integration with third parties.
Explanation and mitigations: We have a very strong development team, with decades of experience, as explained under Feasibility below, and we are confident that we have the technical ability to deliver the proposed project. However, it is possible that we will encounter technical challenges that this team cannot solve, and if so our approaches will include (i) working with existing collaborators in the Cardano community (including the Atala PRISM team, RootsID, Gimbalabs and ProofSpace), (ii) recruiting other experts via our networks and (iii) modifying the project to reduce technical challenges with minimum feasible impact on functionality.
Risk 3: Sufficient qualified development personnel are not available.
Explanation and mitigations: Our core technical team have busy schedules, and we will likely hire one or two additional people to deliver this project. While there is a great variation in talent of developers and strong ones can be hard to find, we are confident that the Catalyst community and our existing networks provide sufficient resources to address this risk.
Risk 4: The project is not delivered on time, due to complexity, availability of personnel and/or other factors.
Explanation and mitigations: There is a significant chance that complexity will delay delivery of this project. For example, our F6 project was forecast to be delivered in 6 months and ultimately took 7.5 months. Although we believe the project plan detailed under Feasibility below is realistic, it is intentionally designed so that a moderate delay will not impair ultimate delivery -- in particular, there are no significant external dependencies that will be affected by delay. We have sufficient financial resources to handle the impact of delay within the proposed budget.
Risk 5: ADA volatility impairs our ability to pay personnel.
Explanation and mitigations: Like other Catalyst proposers, we are affected by ADA volatility. Because we believe in the long-term strength of ADA, we are reluctant to immediately trade all project funds into fiat. Accordingly, we have adopted a strategy of trading some funds into fiat upon receipt and otherwise trading opportunistically / as needed. To date, this strategy has been effective and has allowed us to deliver past projects.
We plan to deliver this project over a period of approximately 7 months. The main targets for each month are set out below (with key milestones identified), in the following categories of activity: (1) technical design, (2) UI/UX, (3) integrations, (4) general coding and (5) documentation. We will develop more granular project plans as the project proceeds (the LearnerShape team has extensive experience with project management).
September 2022
October 2022
November 2022
December 2022
January 2023
February 2023
March 2023
Our team is also currently working on two other funded proposals related to the SkillsGraph project:
These projects will not interfere with delivery of the current proposal. The F7 project will be completed before this proposal receives funding (if it is successful). The F8 project will be far advanced by that time, and the workload is shared with our partner ProofSpace and the team at PeopleCert.
The budget breakdown below matches the five categories of activity identified in the previous response, plus funding for cloud server capacity. Time costs assume $10,000 per person-month including overhead (which is below cost for top developers), except that amounts for RootsID are agreed fixed amount and server costs are estimated AWS costs.
Technical design: $5000
UI/UX: $4000
Integrations: $18,000
General Coding: $20,000
Documentation: $1500 (0.15 pm)
Cloud server capacity (on AWS): $960 -- assumes $80/month for Elastic Beanstalk (including EC2 instances and load balancing), plus Relational Database Service
Total budget: $49,460
LearnerShape team
RootsID team (for wallet integration)
RootsID are leaders in the Catalyst identity community, and have delivered a series of funded Catalyst projects that are summarized in this F9 proposal (https://cardano.ideascale.com/c/idea/419380). The full RootsID team can be found at https://www.rootsid.com/team. The main RootsID team members who will be involved with this proposal are:
We would likely return to Catalyst for further funding, but we are also aiming for LearnerShape SkillsGraph to become self-supporting, and the current proposal is a major step in that direction.
Project Catalyst has been instrumental to the development of LearnerShape SkillsGraph. As described above, our proof of concept was funded in F6 (and successfully delivered), and two significant pilots are underway with F7 and F8 funding.
The current project will add functions to SkillsGraph to allow it to serve commercial applications which can generate revenue (as do other LearnerShape projects). For example:
We will pursue and expect to develop other significant revenue-generating applications.
In addition, we also expect LearnerShape to raise funding from other external investors in the medium term, which could replace the need for Catalyst funding.
However, it is also likely that we would seek further funding from Catalyst, for example to add additional functions to SkillsGraph or support further pilots. In addition, we attribute great value to our engagement with Project Catalyst, and a significant element of that is being a funded proposer.
This proposal is for a development project, and we will measure progress through delivery of the targets and milestones set out under Feasibility above. Our monthly reports will include progress reports against these milestones -- we are currently using this approach (which exceeds Catalyst requirements) for reporting delivery of our F8 project.
Generally, to track the success of LearnerShape SkillsGraph, we are monitoring the following KPIs (and will continue to monitor then after the project is delivered):
By the end of this project, we aim:
As explained further under Impact, these will be important steps on the path to SkillsGraph becoming a widely-adopted, fully-functional, open-source, standards-based Web 3 skills management solution that significantly improves on existing proprietary solutions.
This proposal is a continuation of the following previous Catalyst projects, as explained above under Impact (and its connection to these projects is explained there):
The main SDGs that are relevant to this project are:
LearnerShape SkillsGraph is fundamentally about education and building skills, so Goal 4 is most relevant. In addition, the ability to map skills of individuals through a widely-available, standardized approach will lead to more inclusive societies, bringing Goal 16 into scope.
LearnerShape is award-winning start-up building open-source, AI/blockchain-based skills infrastructure; 20+ yrs experience on authentication & education tech; funded in F6, F7 & F8 for SkillsGraph projects, with app released; partnering with RootsID, leading wallet provider