Project Knowledge Template ([[PKT]]) is a structured framework to organize and manage your learning journey. All projects are managed as if the participants are creating a new [[Domain Specific Language]]. It simply provide a [[File]] directory structure that is convenient for taking notes and manage [[LLM]] and rich media assets. It will also facilitate an automated to continuously refine the data content and directory structures of [[PKT]] in general, making data sharing and process pattern sharing more convenient. The [[File]]-oriented approach of [[PKT]] is intended to encourage users of PKT to maximize the utilization of automation without being locked down to one single software application. The template structure is designed to facilitate data replication and version control, so that data content generated and manipulated by a wide range of software tools can all be shared though [[Content Addressable Scheme]]. # PKT's Technical Objective Personal Knowledge Template is an approach to systematically manage data manipulation templates. It should guide users to be viscerally aware of the notion of [[Abstract Syntax Tree]], [[Content Addressable Scheme]], [[Dependent Types]], [[@PurelyFunctionalSoftware2006|The Purely Functional Software Deployment Model]], and the intellectual elegance of [[The Little Series]] can be directly applied to automatically transform and optimize the directory structures of all data assets. As the first chapter art in [[@friedmanLittleTyper2018|The Little Typer]] stated: > **The more things change, the more they stay the same.** ## A Content-centric Programming Language To sum up the technical objective of [[PKT]], one can think of it as a programming language (note that [[Nix]] is a programming language on the file level) that explicitly uses the containment relations represented by the tree-based directory structures to perform data transformation for the file content contained or referenced inside these directories. Note that content updates/version control can be conducted using [[Git]], and public content hashing and addressing scheme can follow: [[IPFS]]. Its implementation should leverage existing software community's functions to automate the practice of data [[Refactoring]]. ### Scalability based on Content Addressable Scheme To ensure that this programming language can scale up for a large number of applications, the notion of [[Content Addressable Scheme]] and [[eBPF]] should be incorporated to reduce the overhead of retrieving networked data content and triggering functions. ### Implementation Details Data is about change, and changes should be managed with a consistent set of representables or symbols. To ensure that [[PKT]] can be dynamically updated with a set of abstract manipulation rules, one may refer to [[Li-yao Xia]]'s [[Interaction Trees]]. A quick look at the Github code base shows that Xia's work is directly related to [[bridgelet]]. The goal is to create an interactive web front end, so that we can visualize the structures of the trees in the runtime environment of [[Automated Theorem Prover]] such as [[Coq]]. ### Directory Structure as Parenthesis in Lisp The directory structure of files is similar to the parenthesis marked structures in [[Lisp]] or [[Backus Naur Form]] code contains explicit computable information whose containment relations can be modeled as [[Lattice]]s. The recursive directory-file containment relations are not only computable, but the structural information is already a form of executable program, and they can be fed into a generic program to perform content quality control tasks. These tasks can be automated based on the data publishing methodology known as [[CICD]] and implemented using [[Permanent/PKM/Tools/GitHub Actions]] or [[Ansible]]/[[Jenkins]]. One should also check out the [[Refactoring]] features of [[Dendron]] to see if these ideas are related. For an interactive way to represent and compute directory structures or parenthesis, see [[Interaction Trees]] by [[Li-yao Xia]]. ### Content Addressable Scheme for Data Intensive Applications Moreover, every [[PKT]]-based directory will become a shared language model that contains a local copy of [[corpus ]] that can be easily replicated and forked by other persons or teams while maintaining some common structures in sharing a common directory structure, so that the engineering efforts in designing a set of data processing and machine learning tools can be shared amongst these communities. In other words, the reuse of data processing patterns across a wide range of content. It will also serve as a rubric to systematically practice [[Personal Knowledge Management]] and [[Data Sovereignty]]. Most importantly, this abstract data structure should follow a common theoretical foundation, such as [[Homotopy Type Theory]], to ensure the generality of how data can be systematically represented and transformed using a set of known rules. # ChatGPT's Answer # Statement of Purpose A Project Knowledge Template (PKT) manages knowledge is designed to provide a comprehensive framework for organizing and managing all the knowledge and assets related to a learning journey. It manages a set of high-level directory structures that are need for both knowledge capture and Machine Learning Operations ([[MLOps]]). Similar to learning a natural language, it contains components and data structures that should increase in size over time. It provides a high-level templated file structure to manage data content over time, and stores notes and hyperlinks in formats that are convenient for document storage, retrieval, and format rendering. # Initial Implementation Strategy To start out, a LogSeq compatible directory structure to leverage the benefits of both Obsidian and LogSeq. For example, [[PKT]] may provide a structured framework to organize and manage your natural language learning journey. Most importantly, it also includes the directory structure to manage other data assets, such as [[Large Language Model]] and Media assets to better organize your technical resources. The PKT consists of the following components: 1. **Data Assets**: The PKT allows you to incorporate various data assets that serve the purpose of your language learning project. The entire data set will be managed under one directory, and managed by [[Git]]. The directory will include data security-related directory, such as password storage file convention with **[[dot gitignore]]**. For a language learning project as an example, It may include spreadsheets to track vocabulary progress, pronunciation recordings, cultural notes, study schedules, or any other data that enhances your learning experience. 3. **App-specific Compatible Directory Structure**: The PKT utilizes LogSeq's directory structure to facilitate seamless integration with LogSeq, enabling you to take advantage of its powerful knowledge graph capabilities. This structure includes folders such as "Daily Notes," "Knowledge Graph," "Tasks," and more. 4. **LLM Assets Directory**: [[LLM]] (Large Language Models) assets are stored in a dedicated directory within the [[PKT]]. This directory can include directories that stores the actual LLM training models, such as [[GGUF]], directories for [[Prompt|prompts]], context-aware translation annotation data. It should also contain [[TDD|Test-Driven Development]] data. To make this idea publishable and replicable by many, follow these steps: 1. **Document the PKT**: Create comprehensive documentation explaining how the PKT is structured and how each component should be utilized. Include examples and guidelines for organizing different types of content within each folder. 2. **Publish on a Public Platform**: Share your PKT documentation on platforms like GitHub or similar platforms where others can access and contribute to it. Consider using Markdown format so that it can be easily viewed and edited by others. 3. **Invite Collaboration**: Encourage others to contribute their own improvements or adaptations to the PKT. Allow users to submit pull requests or propose changes, fostering a collaborative community around the template. 4. **Promote Awareness**: Spread the word about your PKT through language learning forums, social media groups, or relevant communities. Highlight its benefits, such as improved organization, seamless integration with LogSeq, and flexibility to adapt to different language learning projects. 5. **Seek User Feedback**: Actively engage with users who adopt your PKT and incorporate their feedback into future iterations. Consider creating a dedicated channel or forum where users can provide suggestions, ask questions, and share their experiences. By following these steps, you can achieve your goal: 1. Define your goal: Clearly establish what you want to achieve. Be specific and ensure your goal is measurable. 2. Break it down: Divide your goal into smaller, manageable tasks or milestones. This will make it easier to track progress and stay motivated. 3. Create a plan: Develop a detailed plan that outlines the necessary actions required to accomplish each task or milestone. Set deadlines for each step to keep yourself accountable. 4. Gather resources: Identify the tools, information, and support you need to successfully complete each task. This may include research materials, mentors, or specific software. 5. Take action: Start working on your plan by taking the first step towards accomplishing your goal. Begin with small, achievable tasks to build momentum. 6. Track progress: Regularly review your progress against your plan and adjust as needed. Celebrate small victories along the way to stay motivated. 7. Stay focused and motivated: Keep reminding yourself why you set this goal and visualize the end result. Surround yourself with positive influences and seek support from friends or family when needed. 8. Overcome obstacles: Anticipate challenges that may arise during the process and develop strategies to overcome them. Be flexible in adapting your approach if necessary. 9. Learn from setbacks: If you encounter setbacks or failures, view them as learning opportunities rather than reasons to give up. Analyze what went wrong and adjust your plan accordingly. 10. Stay committed: Remain dedicated to achieving your goal even when faced with difficulties or distractions. Remember that persistence is key to success. 11. Celebrate success: Once you reach your goal, take time to celebrate and acknowledge your accomplishment before setting new goals for yourself. Remember, achieving a goal takes time and effort, so be patient with yourself throughout the process! # Bard's Answer ## Project Knowledge Template (PKT) for Language Learning **Description:** This Project Knowledge Template (PKT) provides a structured framework to organize and manage your language learning journey. It combines the strengths of LogSeq's directory structure and LLM assets with additional data assets to create a comprehensive and adaptable learning environment. **Key Features:** - **LogSeq-compatible directory structure:** Organize your learning content hierarchically with folders for topics, flashcards, grammar notes, and more. - **LLM-powered assets:** Leverage the power of large language models (LLMs) to generate personalized study materials, translation aids, and even practice exercises. - **Data asset library:** Store additional resources like images, audio files, and external links, enriching your learning experience. - **Flexible and adaptable:** Tailor the template to your specific language, learning style, and goals. **Structure:** - **LogSeq-compatible directory:** - `/topics/`: Store in-depth content on grammar, vocabulary, and cultural aspects. - `/flashcards/`: Create interactive flashcards for active recall and spaced repetition. - `/notes/`: Capture personal insights, observations, and reflections. - `/resources/`: Organize additional materials like images, videos, and websites. - **LLM asset directory:** - `/prompts/`: Store prompts for LLM-generated study materials and exercises. - `/translations/`: Utilize LLMs for accurate and context-aware translations. - `/practice/`: Generate personalized practice exercises tailored to your needs. - **Additional data asset directory:** - `/media/`: Store audio files, images, and other multimedia content. - `/links/`: Organize external resources like websites, articles, and tutorials. **Making it Publishable and Replicable:** - **Share the PKT as a template:** Upload the PKT file to platforms like Obsidian's Community Templates or other template repositories. - **Provide documentation and tutorials:** Create detailed guides explaining the PKT structure, features, and usage. - **Showcase success stories:** Share your own language learning progress and how the PKT helped you achieve your goals. - **Contribute to open-source projects:** Integrate the PKT with existing language learning tools or contribute to LLM-powered learning platforms. - **Engage with the community:** participate in online forums and discussions to share your experience and receive feedback. By actively promoting and sharing your PKT, you can empower others to replicate your success and make language learning more efficient and enjoyable for everyone. **Remember, this is just a starting point. Feel free to adapt and customize the PKT to fit your unique learning needs and preferences. The key is to create a system that works for you and helps you achieve your language learning goals.** # References ```dataview Table title as Title, authors as Authors where contains(subject, "PKT") ```