# Surfacing High Impact Cryptoeconomics Research Topics on Filecoin on 2022

###### tags: `Research`

:::info
Document up to date by October 2022
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*Authors: Danilo Lessa Bernardineli (BlockScience), Jamsheed Shorish (BlockScience), Sean McOwen (BlockScience), David Sisson (BlockScience), Michael Zargham (BlockScience)*

In this document, we propose 10 topics that the ecosystem should treat as high priority. Each topic has a paragraph for:

- **Summary:** A quick overview of the topic
- **Why:** Why the topic is important for the ecosystem
- **Impact:** The value that could be generated from the topic
- **Examples of Artifacts**: Typical deliverables arising from the topic.
- **Examples of Successful use of Artifacts**: Specific positive impacts that depends on the delivery of the artifacts

## :one: Measuring and Forecasting the Success of Cryptoeconomic Mechanisms within the Filecoin ecosystem

*Measuring the impact of Baseline Minting on Miner Rewards based on counterfactual scenarios (source: [Baseline Minting Scenario Calculator](https://medium.com/block-science/a-cadcad-interactive-calculator-to-explore-minting-scenarios-in-filecoin-284009a2e941))*

- **Summary:** To develop accessible historical and expected benchmarks for a diverse set of mechanisms that we have in place (Baseline Minting, FIL+, *et al*.).
- **Why:** Filecoin has a set of mechanisms that support a diverse set of intended outcomes, but which is not always explicit for the community at large. By creating a set of suitable counter-factual historical scenarios and a set of comparison metrics, it is possible to measure how much each mechanism has been successful in delivering the intended design goal.
- **Impact:**
1. Providing an early alert for when to tune / change the individual mechanisms;
2. Make explicit the value being generated by the cryptoeconomic mechanisms;
3. Make explicit the design goals and desiderata behind the cryptoeconomic mechanisms.
- **Examples of Artifacts**: Analysis of what would happened if we didn't had Sector Collaterals since launch, or what would happened if we didn't had FIL+ in place.
- **Examples of Successful use of Artifacts**: Quantifying the total impact of Sector Collaterals on Network Security and Miner Incentives over time. Evaluating the generated network value due to the existance of FIL+.

## :two: Integrating Filecoin into Meta Blockchain Systems

*Diagram showing the relationship of some blockchains connected to the Cosmos universe*

- **Summary:** To describe key leverage and blockage points on integrating Filecoin and Meta Blockchain systems, like Cosmos. To identify the level of effort and economic aspects associated with integration points.
- **Why:** Filecoin is a core Web3 primitive, and as such its value is realized at the fullest when coupled together with more primitives, therefore generating a _grammar_ of Web3 constructs that admits the expression of self-contained technical systems. Recently, the launch of meta-blockchain systems like Cosmos has allowed for the direct integration of different blockchains without compromising on autonomy. By tapping into those, Filecoin can be made readily acessible to a variety of use cases and demands.
- **Impact:** Increased demand and relevance for Filecoin.
- **Examples of Artifacts**: A list of integration opportunities and their value being generated. Guidelines for how the integration implementation should be. Describing examples of applications being unlocked by those integrations.
- **Examples of Successful use of Artifacts**: Opportunities and examples being used as an inceptive points for products on Hackathons and Project initiatives. Use of the guidelines for informing future product roadmaps.

## :three: Modeling Potential Markets for Filecoin based on its Roadmap

*Structure of a semi-endogenous model for Filecoin economics (source: [Filecoin Documentation](https://drive.google.com/drive/u/1/folders/1myzlRSpkWP_iLLDLpkuTIC12PPtT4YWS))*

- **Summary:** Building forecasts / scenarios for the potential demand for use cases & products that are being built on top of Filecoin, segmented by applications (eg. FVM, Project Atlas, Retrieval Pinning, *et al*.).
- **Why:** Currently most of the explicit valuations of the network use the supply as the determining factor. Identifying emerging use-cases and their potential market value can decrease the informational risk associated with developing high impact projects, and allow benchmarks to be made.
- **Impact:** Providing a clear view over the future demand for storage landscape, therefore reducing development risks and incentivizing long-term investments in the network.
- **Examples of Artifacts**: Forecasts of how much additional Filecoin Storage Demand for Deals as measured in FIL and rb-PiB can be generated based on the success of specific projects (Atlas, FVM, etc.) and on multiple scenarios (pessimistic, median, optimistic).
- **Examples of Successful use of Artifacts**: Forecasts being used for attracting further resources (human, creative and financial) on projects. Forecasts being used for long-term planning on projects roadmap.

## :four: A Data-Driven Analysis & Comparative Study of Filecoin and its place in the Storage Economy

*Segmentation of the datasphere create/store trends for the next 5 years*

- **Summary:** To build historical and expected indicators of Filecoin's participation in the Storage Economy, both for the present and also for counterfactual scenarios (e.g. how is Filecoin growth compared to Web2 Cloud Computing growth back in 2010?)
- **Why:** Our comparative knowledge of how Filecoin is faring against its Web2 competitors isn't as real-time and deep as it could be. We don't know how much Filecoin is accomplishing daily or how fast its accomplishments are achieved, compared to its true market potential.
- **Impact:** Generating clear expectations of the potential growth landscape and how much is required in terms of supply and demand in order to saturate it.
- **Examples of Artifacts**: An report on how Filecoin growth compares to Web2 competitors growth. An analysis on how Filecoin fits on existing projections for storage & compute usage over the future. Building live trackers on how Filecoin is achieving compared to its potential on the Datasphere.
- **Examples of Successful use of Artifacts**: Using the comparative studies for doing proper network valuation. Defining product & roadmap priorities as based on the network potential in regards to the datasphere.

## :five: Economics of Compute Over Data

*Example of how individual solutions are integrated together in a compute over data pipeline*

- **Summary:** To describe how the aggregate economics for compute over data (COD) should look for the end-user / consumer at large based on the existing portfolio of solutions on the Filecoin ecossystem, and to provide comparative analysis against the Web2 COD alternatives.
- **Why:** A variety of solutions have been proposed for implementing COD ([bacalhau](https://www.bacalhau.org/), [FILSwan](https://www.filswan.com/), [fluence](https://fluence.network/), *et al*.) while auxiliary solutions are required for replicating typical streaming and ETL workflows ([ceramic](https://ceramic.network/), [kamu](https://www.kamu.dev/), *et al*.). Describing how those primitives are integrated together economically, and how they fit within the demand landscape, will help inform us on continued development of the COD layer on Filecoin.
- **Impact:** Identifying leverage and blockage points for COD adoption on Filecoin, thereby improving user and developer experiences as well as improving sustainability for any composable COD solution.
- **Examples of Artifacts**: A comparative use report on the economic feasibility on Filecoin CoD. An Compute Over Data economic rationality calculator.
- **Examples of Successful use of Artifacts**: Web2 users migrating to the Filecoin ecossystem because of rational concerns. OpEx optimization on the user side because of the availability of comparison tools.

## :six: Describing Design Patterns for Data DAOs

*Slide on Data DAOs and commons on the Filecoin Master Plan Presentation, by Juan Benet.*

- **Summary:** To describe a taxonomy of how Data DAOs can be designed and implemented.
- **Why:** One of the main innovations of Filecoin vs Web2 solutions is the coupling of decentralization and programmability, which allows for concepts like _Perpetual Storage_ to be realized. Mapping out the properties and ways in which the commons can organize around data, and making it visible, can be critical for ideating projects with high innovation content.
- **Impact:**
- A language for describing the diversity of data commons which are possible to Filecoin;
- To increase the innovation content of new products in the ecosystem.
- **Examples of Artifacts**: An written taxonomy of Data DAOs. Guidelines on how to create specific Data DAOs. An mapping between common purposes for building an Data DAO and common patterns on delivering on it.
- **Examples of Successful use of Artifacts**: Increase on the inception of Data DAOs due to reduced uncertainty risks and research efforts. Increased system-wide investment of resouces due to having better cognitive tools to evaluate project quality.

## :seven: A Data-Driven Network Analysis of Filecoin Actors

*Cluster Analysis on Gitcoin Grants Round 8*

- **Summary:** To clearly describe the different compositions of participants in the network and how they relate to each other, based on data-available information.
- **Why:** The cumulative experience with FIPs made explicit that we have a variety of participants with different interests and connections to the ecossystem at large. Understanding the different clusters that knit them together, and describing how they emerged and evolved over time using data-driven approaches, can allow us to better navigate how we approach our prospective research.
- **Impact:** Enabling Cryptoeconomics research to be more directly tailored towards ecosystem desires, therefore reducing governance risk.
- **Examples of Artifacts**: Clearly defining specific clusters of users based on data properties. Describing value and object flows between those clusters.
- **Examples of Successful use of Artifacts**: Usage of the specific clusters for tailoring policy proposals. Quantifying the differential impact of policies on those clusters.

## :eight: Recalibrating / Re-evaluating Baseline Minting

*Simulation of Baseline Minting on counter-factual scenarios*

- **Summary:** To conduct counter-factual studies with different baseline target values and/or different baseline functions.
- **Why:** Baseline Minting is a block reward mechanism that acts as a simple exponential minting for most of the time when the Network Power is above a target, while "slowing down" when it goes below, effectively creating a network-wide 'Savings Account' for when the storage power is higher. The current target was based on growth projections made 3 years ago, when network data was non-existent.
- **Impact:** Tweaking the current minting mechanism has the potential to act as a macroeconomic lever. It also has the potential to enhance or constrain the supply pressure for Network Power. This may be an important tool to deploy in times of economic shocks.
- **Examples of Artifacts**: Proposals for new target functions or parameters. Proposals for different issuance distributions.
- **Examples of Successful use of Artifacts**: Generating FIPs using the artifacts as base documents.

## :nine: Leveraging CATS for FVM Compute Over Data

*Diagram illustrating CA (source: [Compute Over Data Meetup](https://docs.google.com/presentation/d/1gnmgDaQcREvR3BtwuZDcaqhUvt5pZz8lmRjSeUHl-T8/edit#slide=id.p19))*

- **Summary:** There are potentially significant positive synergies between the objectives of the FVM performing & verifying compute operations on data, and CATS providing location-agnostic, verifiable compute transforms. Harnessing these synergies requires an understanding of service provision and incentivization, so that a stable decentralized solution can be supported by the ecosystem.
- **Why:** Technical collaboration is currently underway informally, with BSCI's receiving an invitation to PL's Compute Over Data Working Group. Extending this to _implementation_ is achieved by building an incentive framework that supports decentralized compute over data service provision, so that 1) resource availability is matched to (and perhaps stimulates) demand, and 2) service pricing/returns allow for efficient service supply.
- **Impact:** For PL, utilizing learnings from BSCI's expertise with both CATS and with incentive structures, to provide high value-add over a shorter research horizon when applied to/incorporated into the FVM; for BSCI, access to a high-visiblity / high-impact compute over data channel, benefiting CATS development and dissemination.
- **Examples of Artifacts**: An proof of concept of Content Addressability Pipeline using Filecoin Virtual Machine
- **Examples of Successful use of Artifacts**: Usage of CATs for building reproducible analytic workflows.

## :one: :zero: Stakeholder Objectives and Potential Realignment

*Mapping Concepts and Generative Relationships on Filecoin*

- **Summary:** Changing stakeholder goal landscape requires a mapping between goals and associated metrics of the Filecoin ecosystem that can accommodate underlying dynamic shifts in priorities, horizon, expectations etc.
- **Why:** Stakeholder goals are not constant but change over time. By contrast, existing metrics of the Filecoin ecosystem appear to be "FIL-centric", leading to the possible framing of protocol updates, service introduction etc. as being in service to, among others, supporting FIL pricing. A metric framework that can accommodate updated goals or entirely new service classes (such as the FVM) is less restrictive, allowing different metrics to 'come to the surface' as needed/warranted.
- **Impact:** Pigeonholing novel goals and/or service classes into pre-existing metrics of success is detrimental to stakeholder governance. Rather than rely on governance to change the metrics, defining a _class_ of metric mechanisms allows stakeholders to discuss metrics tailored to current goals/services, rather than restricting to one (e.g. "FIL-centric") perspective.
- **Examples of Artifacts**: An interactive stakeholder map linking actors, concepts and network primitives.
- **Examples of Successful use of Artifacts**: Usage of the map for tailoring policy proposals.