Plug-ins for every piece of research tooling known to humankind

Problem Statement:

Researchers utilize a vast array of tools across their workflows, from data acquisition and analysis to visualization and collaboration. However, these tools often operate in isolation, hindering seamless data flow, interoperability, and efficient knowledge management. Using the Eliza framework as the basis for a unified ecosystem of interconnected research tools would significantly accelerate distributed agentic research progress.

While not yet finalized, the possibility of a 2-week prize for "Highest number of useful plugins generated" is a distinct possibility.

Challenge:

Develop plug-ins, extensions, or integrations for any and every research tool imaginable, enhancing their functionality and fostering interoperability within the scientific research ecosystem.

Detailed Description:

• Science on-chain and decentralized Web Integration (Critical):

  • Participants should make every effort to integrating their tooling plugins with decentralized web technologies (e.g., IPFS, Solana, etc) to enhance data provenance, security, and accessibility. Science on-chain is one of the most important goals of this hackathon, it starts with base tooling.

  • Information should be as open as possible and only as closed as necessary. Moving science on-chain with a system default of Open is critical in designing new systems for research. While closing off information is often necessary, it should be a conscious choice made by a researcher which requires extra effort.

• Open Scope:

  • Participants are encouraged to explore and target any research tool, whether widely used or niche.

  • This includes but is not limited to:

    • Email (Gmail, Microsoft Outlook)

    • DeSci Tooling (Molecule IPTs and IPNFTs, AminoChain, ResearchHub, DeSci Nodes, Coordination Network, JOGL, Data Lake, and many many others)

    • Web3 Tooling (EAS, Holonym, Solana, Base, IPFS, Ceramic, GitCoin, drips.network, index network, and many many more)

    • Web2 FAIR Tooling (Nanopublications)

    • Web3 Cloud (Filecoin, Pinata, Gela to, Web3.storage, Prime Intellect, Bacalhau, Olas, Akash, Ceramic, Lit, Ocean, Tableland, etc)

    • Web2 Cloud (Google Cloud, AWS, Microsoft Azure)

    • Manuscript Identifiers (dPIDs, Codex Protocol, ISCCs, dARKs, Archive.ph, Wayback Machine)

    • Data analysis software (e.g., R, Python libraries, MATLAB).

    • Visualization tools (e.g., Tableau, Matplotlib, D3.js).

    • Generic office tooling (Microsoft Suite, Google Suite)

    • Lab notebooks (electronic or physical, Protocols.io)

    • Code repositories (e.g., GitHub, GitLab)

    • Note Taking and Knowledge Management (Notion, Obsidian, Apple Notes)

    • Communication Tools (Microsoft Teams, Telegram, Signal, Gmail, Slack, Loom)

    • General Purpose Data Repositories (e.g., ArXiv, bioArXIV, Zenodo, Figshare, Dataverse, OSF, Software Heritage) - Ensure that Agentic systems are respectful of API limits as many of these systems are non-profit.

    • Domain Specific Data Repositories (Field Specific) - Ensure that Agentic systems are respectful of API limits as many of these systems are non-profit.

    • Agentic Resources (TxGemma, Google Co-Scientist, Elicit, Scite, FutureHouse, Deepmind, PaperQA, Sakana, etc)

    • Cloud Labs (Gingko, many others listed in TechBio)

    • Ontological repositories (Onto portal, BioPortal)

    • Literally, anything.

      • Except JATS integration. We don't want that.

• Plug-in Functionality:

  • Plug-ins can enhance existing tool functionality in various ways, such as:

    • Automating repetitive tasks.

    • Improving data visualization and analysis.

    • Enabling data sharing and collaboration.

    • Integrating with other research tools.

    • Implementing FAIR data principles.

    • Improving Reproducibility.

    • Providing a new method of interacting with a given data type.

• Interoperability Focus:

  • Plug-ins should prioritize interoperability, enabling seamless data flow and communication between tools.

  • Participants are encouraged to use open standards and APIs whenever possible.

• Documentation and Accessibility:

  • Plug-ins should be well-documented and easy to use by researchers with varying levels of technical expertise.

  • Participants are encouraged to provide clear installation instructions and examples.

• Output:

  • Functional plug-ins, extensions, or integrations for targeted research tools.

  • Comprehensive documentation and user guides.

  • Code repositories for the developed plug-ins.

• Potential Technologies:

  • Programming languages relevant to the targeted tools (e.g., Python, JavaScript, R, C++).

  • Web development frameworks (e.g., React, Angular, Vue.js).

  • API development tools.

  • Decentralized web technologies (IPFS, Filecoin, Solid).

• Evaluation Metrics:

  • Does the plugin take every opportunity to log information on-chain?

  • Functionality and usefulness of the plug-ins.

  • Interoperability with other research tools.

  • Ease of use and accessibility.

  • Quality of documentation.

  • Potential impact on research workflows.

Desired Outcomes:

• A diverse ecosystem of plug-ins that enhance the functionality of various research tools.

• Improved interoperability and data flow within the scientific research ecosystem.

• Increased efficiency and productivity for researchers.

• A contribution to open and collaborative research practices.